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[ { "role": "user", "content": "Given a short query with keyphrases about a research idea in 2019 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.\n\nQuery: We propose a graph-based model to transfer knowledge from previously seen classes to novel\n\nKeyphrases: generalized few-shot learning\n\nDataset description:\nTHEODORE: Recent work about synthetic indoor datasets from perspective views has shown significant improvements of object detection results with Convolutional Neural Networks(CNNs). In this paper, we introduce THEODORE: a novel, large-scale indoor dataset containing 100,000 high- resolution diversified fisheye images with 14 classes.\nImageNet: The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.\nKdConv: KdConv is a Chinese multi-domain Knowledge-driven Conversation dataset, grounding the topics in multi-turn conversations to knowledge graphs. KdConv contains 4.5K conversations from three domains (film, music, and travel), and 86K utterances with an average turn number of 19.0.\nAIDS: AIDS is a graph dataset. It consists of 2000 graphs representing molecular compounds which are constructed from the AIDS Antiviral Screen Database of Active Compounds.\n\nOptions:- A: THEODORE B: ImageNet C: KdConv D: AIDS" }, { "role": "assistant", "content": "ImageNet" } ]

[ { "role": "user", "content": "You will be shown biomedical passages and your task is to the answer the provided question. Provide a concise and accurate response and do not include any additional text in the response other than the answer.\n\nQuestion: What protein is recruited by Crumbs to regulate tracheal development?\n\nContext: We propose that early endocytosis maintains normal steady-state levels of Crumbs, which recruits apical phosphorylated (active) Moe, which in turn regulates seamless tube shape\nThere, Crb, acting in parallel with the epidermal growth factor receptor (Egfr) pathway, is required for tracheal cell apical constriction and for organising an actomyosin complex, which we propose is mediated by Crb recruitment of moesin (Moe)." }, { "role": "assistant", "content": "moesin (Moe)" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: Even younger people may experience a similar pattern of severe disease as older people\n\nAbstract:\nThe rapid global spread of SARS-CoV-2 and resultant mortality and social disruption have highlighted the need to better understand coronavirus immunity to expedite vaccine development efforts.\nMultiple candidate vaccines, designed to elicit protective neutralising antibodies targeting the viral spike glycoprotein, are rapidly advancing to clinical trial.\nHowever, the immunogenic properties of the spike protein in humans are unresolved.\nTo address this, we undertook an in-depth characterisation of humoral and cellular immunity against SARS-CoV-2 spike in humans following mild to moderate SARS-CoV-2 infection.\nWe find serological antibody responses against spike are routinely elicited by infection and correlate with plasma neutralising activity and capacity to block ACE2/RBD interaction.\nExpanded populations of spike-specific memory B cells and circulating T follicular helper cells (cTFH) were detected within convalescent donors, while responses to the receptor binding domain (RBD) constitute a minor fraction.\nUsing regression analysis, we find high plasma neutralisation activity was associated with increased spike-specific antibody, but notably also with the relative distribution of spike-specific cTFH subsets.\nThus both qualitative and quantitative features of B and T cell immunity to spike constitute informative biomarkers of the protective potential of novel SARS-CoV-2 vaccines." }, { "role": "assistant", "content": "{\"verdict\": \"NEI\", \"evidence\": []}" } ]

[ { "role": "user", "content": "You will be presented a sentence from biomedical research text. Extract all terms that correspond to chemical entities of biological interest (ChEBI).\nReturn your identified terms in a JSON array, formatted like this: [\"Entity1\", \"Entity2\", ...].\nIf no such entities are detected, respond by providing an empty JSON array [].\n\nBiomedical context:\nInmales,GFP,RFP,FFPandAIwereincreasedby29.0%,51.2%,42.9%and30.0%,respectively." }, { "role": "assistant", "content": "[]" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: Blood clotting a significant cause of death in patients with COVID-19\n\nAbstract:\nThe ongoing outbreak of COVID-19 has been expanding worldwide.\nAs of 17 April 2020, the death toll stands at a sobering 147,027 and over two million cases, this has been straining the health care systems all over.\nRespiratory failure has been cited as the major cause of death but here we present a case about a patient who instead succumbed to severe metabolic acidosis with multiple organ failure." }, { "role": "assistant", "content": "{\"verdict\": \"CONTRADICT\", \"evidence\": [\"Respiratory failure has been cited as the major cause of death but here we present a case about a patient who instead succumbed to severe metabolic acidosis with multiple organ failure.\"]}" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:\n\n- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.\n- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.\n- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.\n\nPlease format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.\n\nAs an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:\n\n[[\"artesunate\", \"artemether\", \"COMB\"], [\"Nifedipine\", \"Labetalol\", \"Prazosin\", \"POS\"]]\n\nThe paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.\n\nIn your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.\n\nparagraph: The clinical and economic benefits of capecitabine and tegafur with uracil in metastatic colorectal cancer. Two oral fluoropyrimidine therapies have been introduced for metastatic colorectal cancer. One is a 5-fluorouracil pro-drug, capecitabine; the other is a combination of tegafur and uracil administered together with leucovorin. The purpose of this study was to compare the clinical effectiveness and cost-effectiveness of these oral therapies against standard intravenous 5-fluorouracil regimens. A systematic literature review was conducted to assess the clinical effectiveness of the therapies and costs were calculated from the UK National Health Service perspective for drug acquisition, drug administration, and the treatment of adverse events. A cost-minimisation analysis was used; this assumes that the treatments are of equal efficacy, although direct randomised controlled trial (RCT) comparisons of the oral therapies with infusional 5-fluorouracil schedules were not available. The cost-minimisation analysis showed that treatment costs for a 12-week course of capecitabine ( Pounds 2132 ) and tegafur with uracil ( Pounds 3385 ) were lower than costs for the intravenous Mayo regimen ( Pounds 3593 ) and infusional regimens on the de Gramont ( Pounds 6255 ) and Modified de Gramont ( Pounds 3485 ) schedules over the same treatment period . Oral therapies result in lower costs to the health service than intravenous therapies. Further research is needed to determine the relative clinical effectiveness of oral therapies vs infusional regimens.\n\nsentence: The cost-minimisation analysis showed that treatment costs for a 12-week course of capecitabine ( Pounds 2132 ) and tegafur with uracil ( Pounds 3385 ) were lower than costs for the intravenous Mayo regimen ( Pounds 3593 ) and infusional regimens on the de Gramont ( Pounds 6255 ) and Modified de Gramont ( Pounds 3485 ) schedules over the same treatment period ." }, { "role": "assistant", "content": "[[\"capecitabine\", \"tegafur\", \"uracil\", \"COMB\"]]" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: smokers are at greater risk of complications from COVID-19 than non-smokers. \n\nAbstract:\nABSTRACT Introduction: Recent studies show cigarette smokers are markedly under-represented among patients hospitalized for COVID-19 in over a dozen countries.\nIt is unclear if this may be related to confounding factors such as age distribution, access to care, and inaccurate records.\nWe hypothesized that these concerns could be avoided by studying smoking prevalence in relation to COVID-19 mortality.\nSince climate has been identified as a factor in COVID-19, we studied groups of countries with relatively comparable temperatures.\nMethods: The 20 hottest and 20 coldest countries in the Johns Hopkins Mortality Analysis database with a minimum mortality rate of .3 deaths/100,000 were selected on the basis of the average temperatures of their largest city.\nMortality rates were determined as of May 1, 2020 and correlated with national smoking rate adjusting for sex ratio, obesity, temperature, and elderly population.\nResults: A highly significant inverse correlation between current daily smoking prevalence and COVID-19 mortality rate was noted for the group of hot countries (R=-.718, p = .0002), cold countries (R=-.567, p=.0046), and the combined group (R=-.324, p=.0207).\nHowever, after adjustments only the regression for hot countries and the combined group remained significant.\nIn hot countries, for each percentage point increase in smoking rate mortality decreased by .147 per 100,000 population (95% CI .102- 192, p=.0066).\nThis resulted in mortality rates several-fold elevated in the countries with the lowest smoking rates relative to the highest smoking rates.\nIn the combined group, mortality decreased by .257 per 100,000 population (95% CI .175-.339, p=.0034).\nDiscussion: These findings add support to the finding of an inverse relationship between current smoking and seriously symptomatic COVID-19.\nHowever, we conclude that the difference in mortality between the highest and lowest smoking countries appears too large to be due primarily to the effects of smoking per se.\nA potentially beneficial effect of smoking is surprising, but compatible with a number of hypothetical mechanisms which deserve exploration: 1) Studies show smoking alters ACE2 expression which may affect COVID-19 infection or its progression to serious lung pathology.\n2) Nicotine has anti-inflammatory activity and also appears to alter ACE2 expression.\n3) Nitric oxide in cigarette smoke is known to be effective in treating pulmonary hypertension and has shown in vitro antiviral effects including against SARS-CoV-2.\n4) Smoking has complicated effects on the immune system involving both up and down regulation, any of which might alone or in concert antagonize progression of COVID-19.\n5) Smokers are exposed to hot vapors which may stimulate immunity in the respiratory tract by various heat-related mechanisms (e.g. heat shock proteins).\nStudies of steam and sauna treatments have shown efficacy in other viral respiratory conditions.\nAt this time there is no clear evidence that smoking is protective against COVID-19, so the established recommendations to avoid smoking should be emphasized.\nThe interaction of smoking and COVID-19 will only be reliably determined by carefully designed prospective study, and there is reason to believe that there are unknown confounds that may be spuriously suggesting a protective effect of smoking.\nHowever, the magnitude of the apparent inverse association of COVID-19 and smoking and its myriad clinical implications suggest the importance of further investigation." }, { "role": "assistant", "content": "{\"verdict\": \"SUPPORT\", \"evidence\": [\"4) Smoking has complicated effects on the immune system involving both up and down regulation, any of which might alone or in concert antagonize progression of COVID-19.\", \"At this time there is no clear evidence that smoking is protective against COVID-19, so the established recommendations to avoid smoking should be emphasized.\"]}" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: If you continue to smoke, you also have a greater risk for respiratory infections like colds, flu and also covid-19.\n\nAbstract:\nObjectives: To investigate whether there is a causal effect of cardiometabolic traits on risk of sepsis and severe covid-19.\nDesign: Mendelian randomisation analysis.\nSetting: UK Biobank and HUNT study population-based cohorts for risk of sepsis, and genome-wide association study summary data for risk of severe covid-19 with respiratory failure.\nParticipants: 12,455 sepsis cases (519,885 controls) and 1,610 severe covid-19 with respiratory failure cases (2,205 controls).\nExposure: Genetic variants that proxy body mass index (BMI), lipid traits, systolic blood pressure, lifetime smoking score, and type 2 diabetes liability - derived from studies considering between 188,577 to 898,130 participants.\nMain outcome measures: Risk of sepsis and severe covid-19 with respiratory failure.\nResults: Higher genetically proxied BMI and lifetime smoking score were associated with increased risk of sepsis in both UK Biobank (BMI: odds ratio 1.38 per standard deviation increase, 95% confidence interval [CI] 1.27 to 1.51; smoking: odds ratio 2.81 per standard deviation increase, 95% CI 2.09-3.79) and HUNT (BMI: 1.41, 95% CI 1.18 to 1.69; smoking: 1.93, 95% CI 1.02-3.64).\nHigher genetically proxied BMI and lifetime smoking score were also associated with increased risk of severe covid-19, although with wider confidence intervals (BMI: 1.75, 95% CI 1.20 to 2.57; smoking: 3.94, 95% CI 1.13 to 13.75).\nThere was limited evidence to support associations of genetically proxied lipid traits, systolic blood pressure or type 2 diabetes liability with risk of sepsis or severe covid-19.\nSimilar findings were generally obtained when using Mendelian randomization methods that are more robust to the inclusion of pleiotropic variants, although the precision of estimates was reduced.\nConclusions: Our findings support a causal effect of elevated BMI and smoking on risk of sepsis and severe covid-19.\nClinical and public health interventions targeting obesity and smoking are likely to reduce sepsis and covid-19 related morbidity, along with the plethora of other health-related outcomes that these traits adversely affect." }, { "role": "assistant", "content": "{\"verdict\": \"SUPPORT\", \"evidence\": [\"Results: Higher genetically proxied BMI and lifetime smoking score were associated with increased risk of sepsis in both UK Biobank (BMI: odds ratio 1.38 per standard deviation increase, 95% confidence interval [CI] 1.27 to 1.51; smoking: odds ratio 2.81 per standard deviation increase, 95% CI 2.09-3.79) and HUNT (BMI: 1.41, 95% CI 1.18 to 1.69; smoking: 1.93, 95% CI 1.02-3.64).\", \"Conclusions: Our findings support a causal effect of elevated BMI and smoking on risk of sepsis and severe covid-19.\"]}" } ]

[ { "role": "user", "content": "You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.\n\nLiterature Review Title: Geometric Algebra in Signal and Image Processing: A Survey \nChapter Title: II. RELATED WORK A. THE BASIC OF GEOMETRIC ALGEBRA \n1. Abstract of Cited Paper (BIB001): Most conventional methods of feature extraction for pattern recognition do not pay sufficient attention to inherent geometric properties of data, even in the case where the data have spatial features. This paper introduces geometric algebra to extract invariant geometric features from spatial data given in a vector space. Geometric algebra is a multidimensional generalization of complex numbers and of quaternions, and it ables to accurately describe oriented spatial objects and relations between them. This paper proposes to combine several geometric features using Gaussian mixture models. It applies the proposed method to the classification of hand-written digits. \n2. Abstract of Cited Paper (BIB002): We survey the development of Clifford's geometric algebra and some of its engineering applications during the last 15 years. Several recently developed applications and their merits are discussed in some detail. We thus hope to clearly demonstrate the benefit of developing problem solutions in a unified framework for algebra and geometry with the widest possible scope: from quantum computing and electromagnetism to satellite navigation, from neural computing to camera geometry, image processing, robotics and beyond. \n3. Abstract of Cited Paper (BIB003): Medical imaging involves important computational geometric problems, such as image segmentation and analysis, shape approximation, three-dimensional (3D) modeling, and registration of volumetric data. In the last few years, Conformal Geometric Algebra (CGA), based on five-dimensional (5D) Clifford Algebra, is emerging as a new paradigm that offers simple and universal operators for the representation and solution of complex geometric problems. However, the widespread use of CGA has been so far hindered by its high dimensionality and computational complexity. This paper proposes a simplified formulation of the conformal geometric operations (reflections, rotations, translations, and uniform scaling) aimed at a parallel hardware implementation. A specialized coprocessing architecture (ConformalALU) that offers direct hardware support to the new CGA operators, is also presented. The ConformalALU has been prototyped as a complete System-on-Programmable-Chip (SoPC) on the Xilinx ML507 FPGA board, containing a Virtex-5 FPGA device. Experimental results show average speedups of one order of magnitude for CGA rotations, translations, and dilations with respect to the geometric algebra software library Gaigen running on the general-purpose PowerPC processor embedded in the target FPGA device. A suite of medical imaging applications, including segmentation, 3D modeling and registration of medical data, has been used as testbench to evaluate the coprocessor effectiveness. \n4. Abstract of Cited Paper (BIB004): We address the \\(\\ell _1 \\)-norm minimization problem, which plays an important role in the compressed sensing (CS) theory. While most previous approaches are designed for signals of low dimensions, we present in this paper an algorithm using geometric algebra (GA) for solving the problem of \\(\\ell _1 \\)-norm minimization for multi-dimensional signals with and without noise contamination by converting it to second-order cone programming. The algorithm represents the multi-dimensional signal as a multivector in the GA form to process it in a holistic way without losing the correlation among different dimensions of the multi-dimensional signal. Numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm and its robustness to noise. The proposed algorithm can also be used to guide perfect recovery of multi-dimensional signals, and may find potential applications when CS theory meets the multi-dimensional signal processing.\n\nLiterature Review:" }, { "role": "assistant", "content": "Geometric algebra (GA) BIB001 , BIB005 is created by W.K. Clifford, also called Clifford algebra. GA provides a mathematical framework, which is ideal to constitute an extension of real, complex and quaternion algebras to complete associative algebras of subspaces of vector spaces in the general framework of vector. Geometric relationships and algorithms can be described by GA, compactly and geometrically. Thus, GA can completely make use of the information associated with different geometric data and improve the computational efficiency. In recent years, GA has become one of the research hotspots in the area of information science owing to the advantages mentioned above, it has been widely and successfully applied to object detection and face recognition, image processing and analysis BIB004 - BIB002 . Mathematically, suppose G n is denoted as a 2 n -dimensional vector space, the basis of G n is denoted as e A = e a 1 · · · e a r |A = (a 1 , . . . a r ) ∈ B BIB003 where G n can be denoted as G p,q , and n = p + q. In general, GA is non-commutative, the multiplication of GA will follow the next rules.      e 2 a i = 1, a i = 1, . . . , p e 2 a i = −1, a i = p + 1, . . . , p + q e a i e a j = −e a j e a i , a i = a j BIB001 The power set of {1, · · · , n} can turn the basis into an ordered one with the index set B. For example, the basis in 2 3 vector space can be described as e ∅ , e 1 , e 2 , e 3 , e 12 , e 13 , e 23 , e 123 BIB004 For convenience, in the rest of the paper, A = a 1 · · · a r will be denoted as A = a 1···r , and e ∅ = 1. The set G t n is denoted as following, representing t-vector part of G n . An arbitrary element of GA is given as where x A ∈ R. For example, an element in 2 3 vector space can be represented as The addition of GA can be defined as The geometric product of GA can be written in the following form. where x ·y and x ∧y represent inner product and outer product, respectively. For performing more complex multivectors operations, several rules are defined as following. a: The reversion of GA is b: The conjugation of GA is c: The module of GA is" } ]

[ { "role": "user", "content": "Given an abstract from a research paper, your task is to identify and label relationships between chemical compounds and genes mentioned in the abstract.\n\nThe relationship type must be one of ['DOWNREGULATOR', 'SUBSTRATE', 'INDIRECT-REGULATOR', 'PART-OF', 'MODULATOR-ACTIVATOR', 'REGULATOR', 'INHIBITOR', 'COFACTOR', 'UPREGULATOR', 'ACTIVATOR', 'ANTAGONIST', 'NOT', 'INDIRECT-DOWNREGULATOR', 'SUBSTRATE_PRODUCT-OF', 'INDIRECT-UPREGULATOR', 'AGONIST', 'PRODUCT-OF', 'MODULATOR', 'DIRECT-REGULATOR', 'UNDEFINED', 'AGONIST-INHIBITOR', 'AGONIST-ACTIVATOR', 'MODULATOR-INHIBITOR'].\n\nPlease format your output as a JSON array. Each entry in the array should express a single relation, formatted as [\"<Entity_A>\", \"<RELATION_A_B>\", \"<Entity_B>\"]. If no relations can be found, please output an empty JSON array [].\n\nAbstract:\n\nRole of organic cation/carnitine transporter 1 in uptake of phenformin and inhibitory effect on complex I respiration in mitochondria. Phenformin causes lactic acidosis in clinical situations due to inhibition of mitochondrial respiratory chain complex I. It is reportedly taken up by hepatocytes and exhibits mitochondrial toxicity in the liver. In this study, uptake of phenformin and [ (14) C]tetraethylammonium (TEA) and complex I inhibition by phenformin were examined in isolated liver and heart mitochondria. Uptake of phenformin into isolated rat liver mitochondria was higher than that into heart mitochondria. It was inhibited by several cat ionic compounds, which suggests the involvement of multispecific transport system (s). Similar characteristics were also observed for uptake of TEA; however, uptake of phenformin into mitochondria of organic cation/carnitine transporter 1 (OCTN1) knockout mice was lower than that in wild-type mice, whereas uptake of TEA was comparable between the two strains, suggesting the involvement of distinct transport mechanisms for these two cations in mitochondria. Inhibition by phenformin of oxygen consumption via complex I respiration in isolated rat liver mitochondria was greater than that in heart mitochondria, whereas inhibitory effect of phenformin on complex I respiration was similar in inside-out structured submitochondrial particles prepared from rat livers and hearts. Lactic acidosis provoked by iv infusion of phenformin was weaker in octn1 (-/-) mice than that in wild-type mice. These observations suggest that uptake of phenformin into liver mitochondria is at least partly mediated by OCTN1 and functionally relevant to its inhibition potential of complex I respiration. This study was, thus, the first to demonstrate OCTN1-mediated mitochondrial transport and toxicity of biguanide in vivo in rodents." }, { "role": "assistant", "content": "[[\"phenformin\", \"INHIBITOR\", \"complex I\"], [\"phenformin\", \"SUBSTRATE\", \"OCTN1\"], [\"phenformin\", \"SUBSTRATE\", \"organic cation/carnitine transporter 1\"]]" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nCoronavirus disease 2019 (COVID-19) is a pandemic infection. Similar to other respiratory viruses, severe acute respiratory syndrome coronavirus (SARS-COV-2) may enter the brain via the hematogenous or neuronal route; however, only a few reports are available on the neurological complications of COVID-19. Encephalopathy is a significant neurological complication of COVID-19. We herein present an update on the virology, neurological pathogenesis, and neuroinvasive potential of coronaviruses and briefly discuss the latest findings on SARS-CoV-2 neuroinfection. The reports thus far indicate that the access of SARS-CoV into host cells is bolstered chiefly by a cellular receptor, angiotensin-converting enzyme 2, and that SARS-CoV-2 may induce some neurological manifestations via direct or indirect mechanisms. Further research is required to shed sufficient light on the impact on the central nervous system and altered mental status in patients with COVID-19. Indeed, a better understanding of the pathways of SARS-CoV-2 neuroinvasion would further clarify the neurological pathogenesis and manifestations of coronaviruses and enhance the management and treatment of this group of patients. In the current epidemic era of COVID-19, health care staff should strongly become aware of SARS-CoV-2 infection as an essential diagnosis to get away misdiagnosis and prevention of transmission." }, { "role": "assistant", "content": "[\"Treatment\", \"Diagnosis\", \"Mechanism\"]" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: When infected with the SARS-CoV-2 coronavirus, many people experience mild and moderate symptoms, but for some people infection can be severe or fatal. \n\nAbstract:\nCoronaviruses are a genetically highly variable family of viruses that infect vertebrates and have succeeded in infecting humans many times by overcoming the species barrier.\nThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which initially appeared in China at the end of 2019, exhibits a high infectivity and pathogenicity compared to other coronaviruses.\nAs the viral coat and other viral components are recognized as being foreign by the immune system, this can lead to initial symptoms, which are induced by the very efficiently working immune defense system via the respiratory epithelium.\nDuring severe courses a systemically expressed proinflammatory cytokine storm and subsequent changes in the coagulation and complement systems can occur.\nVirus-specific antibodies, the long-term expression of which is ensured by the formation of B memory cell clones, generate a specific immune response that is also detectable in blood (seroconversion).\nSpecifically effective cytotoxic CD8+ T­cell populations are also formed, which recognize viral epitopes as pathogen-specific patterns in combination with MHC presentation on the cell surface of virus-infected cells and destroy these cells.\nAt the current point in time it is unclear how regular, robust and durable this immune status is constructed.\nExperiences with other coronavirus infections (SARS and Middle East respiratory syndrome, MERS) indicate that the immunity could persist for several years.\nBased on animal experiments, already acquired data on other coronavirus types and plausibility assumptions, it can be assumed that seroconverted patients have an immunity of limited duration and only a very low risk of reinfection.\nKnowledge of the molecular mechanisms of viral cycles and immunity is an important prerequisite for the development of vaccination strategies and development of effective drugs." }, { "role": "assistant", "content": "{\"verdict\": \"NEI\", \"evidence\": []}" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nObjective: To analyze the clinical characteristics of 2019 novel coronavirus (2019-nCoV) pneumonia and to investigate the correlation between serum inflammatory cytokines and severity of the disease. Methods: 29 patients with 2019-ncov admitted to the isolation ward of Tongji hospital affiliated to Tongji medical college of Huazhong University of Science and Technology in January 2020 were selected as the study subjects. Clinical data were collected and the general information, clinical symptoms, blood test and CT imaging characteristics were analyzed. According to the relevant diagnostic criteria, the patients were divided into three groups: mild (15 cases), severe (9 cases) and critical (5 cases). The expression levels of inflammatory cytokines and other markers in the serum of each group were detected, and the changes of these indicators of the three groups were compared and analyzed, as well as their relationship with the clinical classification of the disease. Results: (1) The main symptoms of 2019-nCoV pneumonia was fever (28/29) with or without respiratory and other systemic symptoms. Two patients died with underlying disease and co-bacterial infection, respectively. (2) The blood test of the patients showed normal or decreased white blood cell count (23/29), decreased lymphocyte count (20/29), increased hypersensitive C reactive protein (hs-CRP) (27/29), and normal procalcitonin. In most patients, serum lactate dehydrogenase (LDH) was significantly increased (20/29), while albumin was decreased (15/29). Alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (Tbil), serum creatinine (Scr) and other items showed no significant changes. (3) CT findings of typical cases were single or multiple patchy ground glass shadows accompanied by septal thickening. When the disease progresses, the lesion increases and the scope expands, and the ground glass shadow coexists with the solid shadow or the stripe shadow. (4) There were statistically significant differences in the expression levels of interleukin-2 receptor (IL-2R) and IL-6 in the serum of the three groups (P<0.05), among which the critical group was higher than the severe group and the severe group was higher than the mild group. However, there were no statistically significant differences in serum levels of tumor necrosis factor-alpha (TNF-alpha), IL-1, IL-8, IL-10, hs-CRP, lymphocyte count and LDH among the three groups (P>0.05). Conclusion: The clinical characteristics of 2019-nCoV pneumonia are similar to those of common viral pneumonia. High resolution CT is of great value in the differential diagnosis of this disease. The increased expression of IL-2R and IL-6 in serum is expected to predict the severity of the 2019-nCoV pneumonia and the prognosis of patients." }, { "role": "assistant", "content": "[\"Treatment\", \"Mechanism\", \"Diagnosis\"]" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nThe novel coronavirus disease 2019 (COVID-19), detected in Wuhan City, Hubei Province, China in late December 2019, is rapidly spreading and affecting all countries in the world. Real-time reverse transcription-polymerase chain reaction (RT-PCR) test has been described by the World Health Organization (WHO) as the standard test method for the diagnosis of the disease. However, considering that the results of this test are obtained between a few hours and two days, it is very important to apply another diagnostic method as an alternative to this test. The fact that RT-PCR test kits are limited in number, the test results are obtained in a long time, and the high probability of healthcare personnel becoming infected with the disease during the test, necessitates the use of other diagnostic methods as an alternative to these test kits. In this study, a hybrid model consisting of two-dimensional (2D) curvelet transformation, chaotic salp swarm algorithm (CSSA) and deep learning technique is developed in order to determine the patient infected with coronavirus pneumonia from X-ray images. In the proposed model, 2D Curvelet transformation is applied to the images obtained from the patient's chest X-ray radiographs and a feature matrix is formed using the obtained coefficients. The coefficients in the feature matrix are optimized with the help of the CSSA and COVID-19 disease is diagnosed by the EfficientNet-B0 model, which is one of the deep learning methods. Experimental results show that the proposed hybrid model can diagnose COVID-19 disease with high accuracy from chest X-ray images." }, { "role": "assistant", "content": "[\"Diagnosis\"]" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: drinking water every 15 minutes will save a person from getting infected by the coronavirus or that the stomach acid will kill the virus.\n\nAbstract:\nAccess to safe Water, Sanitation and Hygiene (WASH) services have been recognized as a highly precautionary measure essential to protecting human health during this COVID-19 outbreak.\nHowever, it is currently unknown whether poor or non- availability of these services are also closely related to COVID-19 fatalities.\nWe analysed the latest data on COVID-19 fatality rates in Sub Saharan Africa with indicators of safe water and sanitation governance to test this hypothesis.\nWe found a strong correlation between a higher case fatality rate and poorer access to safe drinking water as well as safe sanitation.\nThe Pearson correlation is stronger for access to safe sanitation ( -0.30) compared to access to safe drinking water (-0.20).\nThe Chad, Niger and Sierra Leone were amongst the countries with the highest fatality rates (>6.0) and also had particularly poor access to safe drinking water (<34%) and safe sanitation (<22%).\nThe hypothesis of an association between COVID-19 fatalities and poor access to water and sanitation was confirmed by this study.\nHowever, our analysis does not establish causality.\nGiven the increase spread of COVID-19 and related deaths, this analysis serves as an important reminder that safe water and sanitation services are key for public health interventions and highlights the need to prioritise this sector in all economies." }, { "role": "assistant", "content": "{\"verdict\": \"CONTRADICT\", \"evidence\": [\"Access to safe Water, Sanitation and Hygiene (WASH) services have been recognized as a highly precautionary measure essential to protecting human health during this COVID-19 outbreak.\"]}" } ]

[ { "role": "user", "content": "You have to answer a biomedical question in binary format, i.e. only yes and no are the only acceptable answer formats. A list of paragraphs is provided as context to help you answer the question.\n\nQuestion: Is there an association between bruxism and reflux\n\nContext: Rhythmic masticatory muscle activity, including sleep bruxism (SB), can be induced in healthy individuals by experimental esophageal acidification, which plays an important role in the pathogenesis of gastroesophageal reflux disease (GERD). However, no robust evidence supports the association between SB and GERD.\nSleep bruxism is prevalent in GERD patients, and GERD is highly associated with SB.\nOur large-scale cross-sectional study found that problem behaviors in adolescents were associated with sleep problems, including sleep bruxism, as well as lifestyle and food habits and GERD symptoms.\nThe frequencies of EMG bursts, rhythmic masticatory muscle activity (RMMA) episodes, grinding noise, and the RMMA/microarousal ratio were significantly higher in the 20-minute period after acidic infusion than after saline infusion. RMMA episodes including SB were induced by esophageal acidification.\nDirect restorative treatment of dental erosion caused by gastroesophageal reflux disease associated with bruxism:\nThis article presents a case report of a 27-year-old male smoker with tooth wear and dentin sensitivity caused by GERD associated with bruxism\nDental wear caused by association between bruxism and gastroesophageal reflux disease:\nThis paper presents a case report in which bruxism associated with acid feeding, smoking habit and episodes of gastric reflow caused severe tooth wear and great muscular discomfort with daily headache episodes.\nmost jaw muscle activities, ie, RMMA, single short-burst, and clenching episodes, occur in relation to gastroesophageal reflux mainly in the supine position.\nAssociation between nocturnal bruxism and gastroesophageal reflux.\nNocturnal bruxism may be secondary to nocturnal gastroesophageal reflux, occurring via sleep arousal and often together with swallowing." }, { "role": "assistant", "content": "yes" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: Pixatimod is active in lab studies against SARS-CoV-2\n\nAbstract:\nSARS-CoV-2 rapidly spread around the globe after its emergence in Wuhan in December 2019.\nWith no specific therapeutic and prophylactic options available, the virus was able to infect millions of people.\nTo date, close to half a million patients succumbed to the viral disease, COVID-19.\nThe high need for treatment options, together with the lack of small animal models of infection has led to clinical trials with repurposed drugs before any preclinical in vivo evidence attesting their efficacy was available.\nWe used Syrian hamsters to establish a model to evaluate antiviral activity of small molecules in both an infection and a transmission setting.\nUpon intranasal infection, the animals developed high titers of SARS-CoV-2 in the lungs and pathology similar to that observed in mild COVID-19 patients.\nTreatment of SARS-CoV-2-infected hamsters with favipiravir or hydroxychloroquine (with and without azithromycin) resulted in respectively a mild or no reduction in viral RNA and infectious virus.\nMicro-CT scan analysis of the lungs showed no improvement compared to non-treated animals, which was confirmed by histopathology.\nIn addition, both compounds did not prevent virus transmission through direct contact and thus failed as prophylactic treatments.\nBy modelling the PK profile of hydroxychloroquine based on the trough plasma concentrations, we show that the total lung exposure to the drug was not the limiting factor.\nIn conclusion, we here characterized a hamster infection and transmission model to be a robust model for studying in vivo efficacy of antiviral compounds.\nThe information acquired using hydroxychloroquine and favipiravir in this model is of critical value to those designing (current and) future clinical trials.\nAt this point, the data here presented on hydroxychloroquine either alone or combined with azithromycin (together with previously reported in vivo data in macaques and ferrets) provide no scientific basis for further use of the drug in humans." }, { "role": "assistant", "content": "{\"verdict\": \"NEI\", \"evidence\": []}" } ]

[ { "role": "user", "content": "Given an abstract from a research paper, your task is to identify and label relationships between chemical compounds and genes mentioned in the abstract.\n\nThe relationship type must be one of ['DOWNREGULATOR', 'SUBSTRATE', 'INDIRECT-REGULATOR', 'PART-OF', 'MODULATOR-ACTIVATOR', 'REGULATOR', 'INHIBITOR', 'COFACTOR', 'UPREGULATOR', 'ACTIVATOR', 'ANTAGONIST', 'NOT', 'INDIRECT-DOWNREGULATOR', 'SUBSTRATE_PRODUCT-OF', 'INDIRECT-UPREGULATOR', 'AGONIST', 'PRODUCT-OF', 'MODULATOR', 'DIRECT-REGULATOR', 'UNDEFINED', 'AGONIST-INHIBITOR', 'AGONIST-ACTIVATOR', 'MODULATOR-INHIBITOR'].\n\nPlease format your output as a JSON array. Each entry in the array should express a single relation, formatted as [\"<Entity_A>\", \"<RELATION_A_B>\", \"<Entity_B>\"]. If no relations can be found, please output an empty JSON array [].\n\nAbstract:\n\nFetal PGC-1α overexpression programs adult pancreatic β-cell dysfunction. Adult β-cell dysfunction, a hallmark of type 2 diabetes, can be programmed by adverse fetal environment. We have shown that fetal glucocorticoids (GCs) participate in this programming through inhibition of β-cell development. Here we have investigated the molecular mechanisms underlying this regulation. We showed that GCs stimulate the expression of peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α), a coregulator of the GCs receptor (GR), and that the overexpression of PGC-1α represses genes important for β-cell development and function. More precisely, PGC-1α inhibited the expression of the key β-cell transcription factor pancreatic duodenal homeobox 1 (Pdx1). This repression required the GR and was mediated through binding of a GR/PGC-1α complex to the Pdx1 promoter. To explore PGC-1α function, we generated mice with inducible β-cell PGC-1α overexpression. Mice overexpressing PGC-1α exhibited at adult age impaired glucose tolerance associated with reduced insulin secretion, decreased β-cell mass, and β-cell hypotrophy. Interestingly, PGC-1α expression in fetal life only was sufficient to impair adult β-cell function whereas β-cell PGC-1α overexpression from adult age had no consequence on β-cell function. Altogether, our results demonstrate that the GR and PGC-1α participate in the fetal programming of adult β-cell function through inhibition of Pdx1 expression." }, { "role": "assistant", "content": "[]" } ]

[ { "role": "user", "content": "You will be shown sections from a scientific research paper, together with a question about the paper. Your task is to answer the question based on the contents of the paper. Your response should be a `json` object with two fields:\n\n\"answer\": An array of strings extracted directly from the paper which, collectively, answer the question.\n\"evidence\": An array of strings. Each should be an excerpt from the paper, in which one or more of the extracted answers can be found.\n\nFor instance, for the question \"What baselines did the authors compare against?\", a sample response might be:\n\n{\n \"answer\": [\"BERT\", \"RoBERTa\"],\n \"evidence\": [\"In our experiments, we compare the performance of our model against BERT and RoBERTa.\"]\n}\n\nDo not include any text in your response other than the json.\n\nIf the question is unanswerable given the provided excerpts, respond with the single word \"null\".\n\nPaper: Analysing Coreference in Transformer Outputs\n\nWe analyse coreference phenomena in three neural machine translation systems trained with different data settings with or without access to explicit intra- and cross-sentential anaphoric information. We compare system performance on two different genres: news and TED talks. To do this, we manually annotate (the possibly incorrect) coreference chains in the MT outputs and evaluate the coreference chain translations. We define an error typology that aims to go further than pronoun translation adequacy and includes types such as incorrect word selection or missing words. The features of coreference chains in automatic translations are also compared to those of the source texts and human translations. The analysis shows stronger potential translationese effects in machine translated outputs than in human translations.\n\nBackground and Related Work ::: Translation studies\nDifferences between languages and genres in the linguistic means expressing reference are important for translation, as the choice of an appropriate referring expression in the target language poses challenges for both human and machine translation. In translation studies, there is a number of corpus-based works analysing these differences in translation. However, most of them are restricted to individual phenomena within coreference. For instance, BIBREF20 analyse abstract anaphors in English-German translations. To our knowledge, they do not consider chains. BIBREF21 in their contrastive analysis of potential coreference chain members in English-German translations, describe transformation patterns that contain different types of referring expressions. However, the authors rely on automatic tagging and parsing procedures and do not include chains into their analysis. The data used by BIBREF4 and BIBREF22 contain manual chain annotations. The authors focus on different categories of anaphoric pronouns in English-Czech translations, though not paying attention to chain features (e.g. their number or size).\nChain features are considered in a contrastive analysis by BIBREF6. Their study concerns different phenomena in a variety of genres in English and German comparable texts. Using contrastive interpretations, they suggest preferred translation strategies from English into German, i.e. translators should use demonstrative pronouns instead of personal pronouns (e.g. dies/das instead of es/it) when translating from English into German and vice versa. However, corpus-based studies show that translators do not necessarily apply such strategies. Instead, they often preserve the source language anaphor's categories BIBREF20 which results in the shining through effects BIBREF23. Moreover, due to the tendency of translators to explicitly realise meanings in translations that were implicit in the source texts BIBREF24, translations are believed to contain more (explicit) referring expressions, and subsequently, more (and longer) coreference chains.\nTherefore, in our analysis, we focus on the chain features related to the phenomena of shining through and explicitation. These features include number of mentions, number of chains, average chain length and the longest chain size. Machine-translated texts are compared to their sources and the corresponding human translations in terms of these features. We expect to find shining through and explicitation effects in automatic translations.\n\nSystems, Methods and Resources ::: State-of-the-art NMT ::: S1\nis trained with the concatenation of Common Crawl, Europarl, a cleaned version of Rapid and the News Commentary corpus. We oversample the latter in order to have a significant representation of data close to the news genre in the final corpus.\n\nSystems, Methods and Resources ::: Test data under analysis\nAs one of our aims is to compare coreference chain properties in automatic translation with those of the source texts and human reference, we derive data from ParCorFull, an English-German corpus annotated with full coreference chains BIBREF46. The corpus contains ca. 160.7 thousand tokens manually annotated with about 14.9 thousand mentions and 4.7 thousand coreference chains. For our analysis, we select a portion of English news texts and TED talks from ParCorFull and translate them with the three NMT systems described in SECREF4 above. As texts considerably differ in their length, we select 17 news texts (494 sentences) and four TED talks (518 sentences). The size (in tokens) of the total data set under analysis – source (src) and human translations (ref) from ParCorFull and the automatic translations produced within this study (S1, S2 and S3) are presented in Table TABREF20.\nNotably, automatic translations of TED talks contain more words than the corresponding reference translation, which means that machine-translated texts of this type have also more potential tokens to enter in a coreference relation, and potentially indicating a shining through effect. The same does not happen with the news test set.\n\nSystems, Methods and Resources ::: Manual annotation process\nThe English sources and their corresponding human translations into German were already manually annotated for coreference chains. We follow the same scheme as BIBREF47 to annotate the MT outputs with coreference chains. This scheme allows the annotator to define each markable as a certain mention type (pronoun, NP, VP or clause). The mentions can be defined further in terms of their cohesive function (antecedent, anaphoric, cataphoric, comparative, substitution, ellipsis, apposition). Antecedents can either be marked as simple or split or as entity or event. The annotation scheme also includes pronoun type (personal, possessive, demonstrative, reflexive, relative) and modifier types of NPs (possessive, demonstrative, definite article, or none for proper names), see BIBREF46 for details. The mentions referring to the same discourse item are linked between each other. We use the annotation tool MMAX2 BIBREF48 which was also used for the annotation of ParCorFull.\nIn the next step, chain members are annotated for their correctness. For the incorrect translations of mentions, we include the following error categories: gender, number, case, ambiguous and other. The latter category is open, which means that the annotators can add their own error types during the annotation process. With this, the final typology of errors also considered wrong named entity, wrong word, missing word, wrong syntactic structure, spelling error and addressee reference.\nThe annotation of machine-translated texts was integrated into a university course on discourse phenomena. Our annotators, well-trained students of linguistics, worked in small groups on the assigned annotation tasks (4-5 texts, i.e. 12-15 translations per group). At the beginning of the annotation process, the categories under analysis were discussed within the small groups and also in the class. The final versions of the annotation were then corrected by the instructor.\n\nResults and Analyses ::: Chain features\nFirst, we compare the distribution of several chain features in the three MT outputs, their source texts and the corresponding human translations.\nTable TABREF20 shows that, overall, all machine translations contain a greater number of annotated mentions in both news texts and TED talks than in the annotated source (src and src$_{\\rm CoreNLP}$) and reference (ref) texts. Notice that src$_{\\rm CoreNLP}$ —where coreferences are not manually but automatically annotated with CoreNLP— counts also the tokens that the mentions add to the sentences, but not the tags. The larger number of mentions may indicate a strong explicitation effect observed in machine-translated texts. Interestingly, CoreNLP detects a similar number of mentions in both genres, while human annotators clearly marked more chains for TED than for news. Both genres are in fact quite different in nature; whereas only $37\\%$ of the mentions are pronominal in news texts (343 out of 915), the number grows to $58\\%$ for TED (577 out of 989), and this could be an indicator of the difficulty of the genres for NMT systems. There is also a variation in terms of chain number between translations of TED talks and news. While automatic translations of news texts contain more chains than the corresponding human annotated sources and references, machine-translated TED talks contain less chains than the sources and human translations. However, there is not much variation between the chain features of the three MT outputs. The chains are also longer in machine-translated output than in reference translations as can be seen by the number of mentions per chain and the length of the longest chain.\n\nResults and Analyses ::: Error analysis\nThe total distribution for the 10 categories of errors defined in Section SECREF23 can be seen in Figure FIGREF29. Globally, the proportion of errors due to our closed categories (gender, number, case and ambiguous) is larger for TED talks than for news (see analysis in Section SECREF28). Gender is an issue with all systems and genres which does not get solved by the addition of more data. Additionally, news struggle with wrong words and named entities; for this genre the additional error types (see analysis in Section SECREF30) represent around 60% of the errors of S1/S3 to be compared to the 40% of TED talks.\n\nResults and Analyses ::: Error analysis ::: Types of erroneous mentions\nFinally, we also analyse the types of the mentions marked as errors. They include either nominal phrases or pronouns. Table TABREF32 shows that there is a variation between the news texts and TED talks in terms of these features. News contain more erroneous nominal phrases, whereas TED talks contain more pronoun-related errors. Whereas both the news and the TED talks have more errors in translating anaphors, there is a higher proportion of erroneous antecedents in the news than in the TED talks.\nIt is also interesting to see that S3 reduces the percentage of errors in anaphors for TED, but has a similar performance to S2 on news.\n\nAcknowledgments\nThe annotation work was performed at Saarland University. We thank Anna Felsing, Francesco Fernicola, Viktoria Henn, Johanna Irsch, Kira Janine Jebing, Alicia Lauer, Friederike Lessau and Christina Pollkläsener for performing the manual annotation of the NMT outputs. The project on which this paper is based was partially funded by the German Federal Ministry of Education and Research under the funding code 01IW17001 (Deeplee) and by the German Research Foundation (DFG) as part of SFB 1102 Information Density and Linguistic Encoding. Responsibility for the content of this publication is with the authors.\n\nTable 1: Number of lines of the corpora used for training the NMT systems under study. The 2nd and 3rd columns show the amount of oversampling used.\n\nTable 2: Statistics on coreference features for news and TED texts considered.\n\nFigure 1: Number of errors per system (S1, S2, S3) and genre (news, TED). Notice that the total number of errors differs for each plot, total numbers are reported in Table 3. Labels in Figure (b)–S3 apply to all the chart pies that use the same order and color scale for the different error types defined in Section 4.3.\n\nTable 4: Percentage of erroneous mentions: antencedent vs. anaphor, and noun phrase vs. pronominal.\n\nQuestion: What languages are seen in the news and TED datasets?" }, { "role": "assistant", "content": "{\"answer\": [\"English\", \"German\"], \"evidence\": [\"As one of our aims is to compare coreference chain properties in automatic translation with those of the source texts and human reference, we derive data from ParCorFull, an English-German corpus annotated with full coreference chains BIBREF46. The corpus contains ca. 160.7 thousand tokens manually annotated with about 14.9 thousand mentions and 4.7 thousand coreference chains. For our analysis, we select a portion of English news texts and TED talks from ParCorFull and translate them with the three NMT systems described in SECREF4 above. As texts considerably differ in their length, we select 17 news texts (494 sentences) and four TED talks (518 sentences). The size (in tokens) of the total data set under analysis \\u2013 source (src) and human translations (ref) from ParCorFull and the automatic translations produced within this study (S1, S2 and S3) are presented in Table TABREF20.\"]}" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:\n\n- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.\n- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.\n- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.\n\nPlease format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.\n\nAs an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:\n\n[[\"artesunate\", \"artemether\", \"COMB\"], [\"Nifedipine\", \"Labetalol\", \"Prazosin\", \"POS\"]]\n\nThe paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.\n\nIn your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.\n\nparagraph: Role of acetylcholine transmission in nucleus accumbens and ventral tegmental area in heroin-seeking induced by conditioned cues. The involvement of cholinergic transmission in heroin self-administration and the reinstatement of heroin-seeking was examined in rats trained to nose-poke for i.v. heroin. Systemic treatment with physostigmine , an inhibitor of acetylcholinesterase , modestly reduced the acquisition and rate of heroin self-administration , and this suppression of heroin intake was reversed by pretreatment with scopolamine but not by mecamylamine . Following 10-14 days of self-administration, rats were left in the home environment for 14 days. Subsequently, rats were evaluated for extinction of nose-pokes during the first hour after being returned to the self-administration apparatus. One hour later a conditioned stimulus (house light, light in the nose-poke hole, sound of the infusion pump) was presented to initiate cue-induced reinstatement. Physostigmine produced a dose-dependent inhibition of cue-induced reinstatement, but only the dose of 0.5 mg/kg significantly decreased nose-poke responding in the extinction test. Chronic treatment with physostigmine (0.1 mg/kg) did not impair performance during acquisition of heroin self-administration. However, during a subsequent reinstatement test conducted in the absence of physostigmine pretreatment, heroin seeking was significantly below that of rats chronically pretreated with saline. To evaluate brain regions mediating the effects of systemic drug treatment on reinstatement, physostigmine was microinjected into the nucleus accumbens (NAc) or ventral tegmental area (VTA). Microinjection of physostigmine into the NAc prior to presenting conditioned cues inhibited the reinstatement of heroin-seeking, without affecting extinction responding. In contrast, microinjection of physostigmine into the VTA augmented the reinstatement induced by conditioned cues and extinction responding. Inactivation of either NAc or VTA by microinjecting tetrodotoxin blocked both extinction responding and cue-induced reinstatement. These data demonstrate that cholinergic transmission influences heroin self-administration and reinstatement. Moreover, cue-induced reinstatement was inhibited by physostigmine in the NAc and potentiated by cholinergic stimulation in the VTA.\n\nsentence: Systemic treatment with physostigmine , an inhibitor of acetylcholinesterase , modestly reduced the acquisition and rate of heroin self-administration , and this suppression of heroin intake was reversed by pretreatment with scopolamine but not by mecamylamine ." }, { "role": "assistant", "content": "[]" } ]

[ { "role": "user", "content": "You will be shown biomedical passages and your task is to the answer the provided question. Provide a concise and accurate response and do not include any additional text in the response other than the answer.\n\nQuestion: Which is the target of the drug Denosumab?\n\nContext: Denosumab is a human monoclonal antibody which specifically blocks receptor activator of nuclear factor κB ligand and is a very potent antiresorptive drug.\ndenosumab, a monoclonal antibody against RANKL\nDenosumab is a human monoclonal antibody indicated for the treatment of osteoporosis in postmenopausal women with a high risk of fractures.\nDenosumab (Dmab) is a fully human monoclonal antibody against the receptor activator of nuclear factor-κB ligand (RANKL), which, through the prevention of the RANKL/RANK interaction, inhibits osteoclast-mediated bone resorption and significantly reduces the risk of vertebral, nonvertebral, and hip fractures." }, { "role": "assistant", "content": "receptor activator of nuclear factor-κB ligand, or RANKL" } ]

[ { "role": "user", "content": "You will be shown a question, followed by excerpts from biomedical research papers. Please answer the question based on the provided context. Do not include any text in your response other than the answer.\n\nQuestion: What is the function of GFRAL?\n\nContext: GFRAL is the receptor for GDF15 and the ligand promotes weight loss in mice and nonhuman primates.\nWe further found that GFRAL expression was limited to hindbrain neurons and not present in peripheral tissues, which suggests that GDF15-GFRAL-mediated regulation of food intake is by a central mechanism.\nHere we report that GDNF-family receptor α-like (GFRAL), an orphan member of the GFR-α family, is a high-affinity receptor for GDF15.\nHere we identify glial cell-derived neurotrophic factor (GDNF) receptor alpha-like (GFRAL) as a brainstem-restricted receptor for growth and differentiation factor 15 (GDF15).\nFour laboratories have recently identified GFRAL, an orphan receptor of the glial-derived neurotrophic factor (GDNF) receptor α family, as the receptor for MIC-1/GDF15, signaling though the coreceptor Ret." }, { "role": "assistant", "content": "GFRAL (orphan receptor of the glial-derived neurotrophic factor (GDNF) receptor α family) is a high-affinity receptor for GDF15.\nGFRAL expression is limited to hindbrain neurons and not present in peripheral tissues, which suggests that GDF15-GFRAL-mediated regulation of food intake is by a central mechanism." } ]

[ { "role": "user", "content": "You will be presented with a citation segment from the section of a research paper. Classify the intent behind this citation by choosing from one of the following categories:\n\n- Method: Cites the paper for its methodology or procedure.\n- Background: Cites the paper to provide background information.\n- Result: Cites the paper for its findings or results.\n\nYour answer should be a single word from the following list of options: [\"Method\", \"Background\", \"Result\"]. Do not include any other text in your response.\n\nCitation sentence:\n\nThere are several key mechanisms in tumorigenesis that may involve Hh/GLI signaling [11,13]; first, inactivating mutations in the negative regulators PTCH or SUFU, or activating mutations in the positive regulator SMO cause pathway activation in a cellautonomous and Hh ligand independent manner [5,26–28]; secondly, ligand-dependent autocrine mechanisms in which cancer cells both secrete and respond to Hh ligands causing cellautonomous pathway activation [29,30]; thirdly, paracrine mechanisms in which stromal cells are induced by Hh producing cancer cells [31–34]." }, { "role": "assistant", "content": "Background" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: Face masks might reduce coronavirus spread\n\nAbstract:\nThe COVID‐19 pandemic caused by the novel coronavirus SARS‐CoV‐2 has claimed many lives worldwide.\nWearing medical masks or N95 masks (namely N95 respirators) can slow the virus spread and reduce the infection risk.\nReuse of these masks can minimize waste, protect the environment, and help to solve the current imminent shortage of masks.\nDisinfection of used masks is needed for reuse of them with safety, but improper decontamination can damage the blocking structure of masks.\nIn this study, we demonstrated, using avian coronavirus of infectious bronchitis virus to mimic SARS‐CoV‐2, that medical masks and N95 masks remained their blocking efficacy after being steamed on boiling water even for 2 hours.\nWe also demonstrated that three brands of medical masks blocked over 99% viruses in aerosols.\nThe avian coronavirus was completely inactivated after being steamed for 5 minutes.\nTogether, this study suggested that medical masks are adequate for use on most social occasions, and both medical masks and N95 masks can be reused for a few days with steam decontamination between use.\nThis article is protected by copyright.\nAll rights reserved." }, { "role": "assistant", "content": "{\"verdict\": \"SUPPORT\", \"evidence\": [\"Wearing medical masks or N95 masks (namely N95 respirators) can slow the virus spread and reduce the infection risk.\", \"We also demonstrated that three brands of medical masks blocked over 99% viruses in aerosols.\", \"The avian coronavirus was completely inactivated after being steamed for 5 minutes.\", \"Together, this study suggested that medical masks are adequate for use on most social occasions, and both medical masks and N95 masks can be reused for a few days with steam decontamination between use.\"]}" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nThe welfare of health care professionals working in hazardous environments is a concerning issue. Personal protective equipment such as face masks, disposable gowns, hair covers, gloves, and shoe covers is often used to prevent contamination from patient contact and droplets. This is especially relevant during an epidemic, when health care professionals are at elevated risk of infection. Failure to provide adequate protection to health care workers during epidemics has medical, ethical, and legal ramifications." }, { "role": "assistant", "content": "[\"Prevention\"]" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: As the world races for a COVID-19 vaccine, it has never been more important for clinical trials to reflect the population at large.\n\nAbstract:\nBackground and objective: Despite medical advances, we are facing the unprecedented disaster of the coronavirus disease 2019 (COVID-19) pandemic without available treatments and effective vaccines.\nAs the COVID-19 pandemic has approached its culmination, desperate efforts have been made to seek proper treatments and response strategies, and the number of clinical trials has been rapidly increasing.\nIn this time of the pandemic, it is believed that learning lessons from it would be meaningful in preparing for future pandemics.\nThus, this study aims at providing a comprehensive landscape of COVID-19 related clinical trials based on the ClinicalTrials.gov database.\nMaterials and methods: Up to 30 March 2020, we identified a total of 147 eligible clinical trials and reviewed the overview of the studies.\nResults: Until then, the most clinical trials were set up in China.\nTreatment approaches are the most frequent purpose of the registered studies.\nChloroquine, interferon, and antiviral agents such as remdesivir, lopinavir, and ritonavir are agents under investigation in these trials.\nConclusions: In this study, we introduced the promising therapeutic options that many researchers and clinicians are interested in, and to address the hidden issues behind clinical trials in this COVID-19 pandemic." }, { "role": "assistant", "content": "{\"verdict\": \"NEI\", \"evidence\": []}" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nBackground and objectives: Public health interventions have reduced coronavirus disease 2019 (COVID-19) transmission in several countries, but their impacts on COVID-19 epidemics in the USA are unclear. We examined associations of stay-at-home order (SAHO) and face-masking recommendation with COVID-19 epidemics in the USA. Methods: In this quasi-experimental interrupted time-series study, we modeled temporal trends in daily new cases and deaths of laboratory-confirmed COVID-19 cases, and COVID-19 time-varying reproduction numbers in the USA between March 1 and April 20, 2020. In addition, we conducted simulation analyses. Results: The number of residents under SAHO increased since March 19 and plateaued at 290,829,980 (88.6% of the U.S. population) on April 7. Trends in COVID-19 time-varying reproduction numbers peaked on March 23, further reduced on April 3, and fell below/around 1.0 on April 13. Early-implementation and early-lift of SAHO would reduce and increase COVID-19 epidemics, respectively. Multivariable piecewise log-linear regression revealed the states' neighboring relationship with New York was linked to COVID-19 daily new cases and deaths. There were two turning points in daily new-case trend, being March 28 (slope-changes = -0.09) and April 3 (slope-changes = -0.09), which appeared to be associated with implementation of SAHO on March 28 (affecting 48.5% of the US population in 22 states and District of Columbia), and face-masking recommendation on April 3, respectively. There were also two turning points in daily new-death trend, being April 9 (slope-changes = -0.06) and April 19 (slope-changes = -0.90). Conclusions: We identified two turning points of COVID-19 daily new cases or deaths in the USA, which seem to be linked to implementation of SAHO and the Center for Disease Control's face-masking recommendation." }, { "role": "assistant", "content": "[\"Prevention\"]" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research paper, followed by a question about the paper. Please extract text from the paragraph to answer the question. Do not include any text in your repsonse other than the answer.\n\nParagraph: Inhibitory Effect and Possible Mechanism of Action of Patchouli Alcohol against Influenza A (H2N2) Virus\n\nhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6264369/\n\nSHA: f2d842780b9928cc70f38a4458553f2431877603\n\nAuthors: Wu, Huaxing; Li, Beili; Wang, Xue; Jin, Mingyuan; Wang, Guonian\nDate: 2011-08-03\nDOI: 10.3390/molecules16086489\nLicense: cc-by\n\nAbstract: In the present study, the anti-influenza A (H2N2) virus activity of patchouli alcohol was studied in vitro, in vivo and in silico. The CC(50) of patchouli alcohol was above 20 µM. Patchouli alcohol could inhibit influenza virus with an IC(50) of 4.03 ± 0.23 µM. MTT assay showed that the inhibition by patchouli alcohol appears strongly after penetration of the virus into the cell. In the influenza mouse model, patchouli alcohol showed obvious protection against the viral infection at a dose of 5 mg/kg/day. Flexible docking and molecular dynamic simulations indicated that patchouli alcohol was bound to the neuraminidase protein of influenza virus, with an interaction energy of –40.38 kcal mol(–1). The invariant key active-site residues Asp151, Arg152, Glu119, Glu276 and Tyr406 played important roles during the binding process. Based on spatial and energetic criteria, patchouli alcohol interfered with the NA functions. Results presented here suggest that patchouli alcohol possesses anti-influenza A (H2N2) virus properties, and therefore is a potential source of anti-influenza agents for the pharmaceutical industry. Text: The influenza virus, which is one of the main causes of acute respiratory infections in humans, can lead to annual epidemics and infrequent pandemics. The two influenza pandemics of the 20 th century, \"Asian Influenza (1957/H2N2)\" and \"Hong Kong Influenza (1968/H3N2)\" resulted in the deaths of an estimated 2-3 million people globally [1, 2] . Today, their descendants continue to cause the majority of influenza infections in humans [3] . So far as it is learned that the most effective antiviral drug is the neuraminidase (NA) inhibitor, which target the NA glycoproteins of influenza A and B virus [4, 5] . The release of new virions from the infected cell is a key step in the influenza life cycle and need neuraminidase (NA) to cleave the α-ketosidic linkage between terminal sialic acid and an adjacent sugar residue [6] . The NA inhibitors were designed to prevent the key step by blocking the active site of enzyme and thus allow sufficient time for the host immune systems to remove infected viruses [7] . Consistent efforts have been devoted to the development of NA inhibitors, using the crystal structure of the N2 sub-type NA protein [8] [9] [10] [11] [12] [13] [14] [15] . Indeed, oseltamivir (Tamiflu) is the representative NA inhibitor that has proven to be uniquely applicable oral drug in clinical practice for the treatment of influenza infection [4, 8, 9] . However, with an increase in medical use, the oseltamivir-resistant strains have been found and probably lead to a large scale outbreak of novel pandemic flu [16, 17] . Patchouli alcohol ( Figure 1 ) has been well known for over a century. It is a major constituent of the pungent oil from the East Indian shrub Pogostemon cablin (Blanco) Benth, and widely used in fragrances. Patchouli oil is an important essential oil in the perfume industry, used to give a base and lasting character to a fragrance [16, 17] . The essential oil is very appreciated for its characteristic pleasant and long lasting woody, earthy, and camphoraceous odor, as well as for its fixative properties, being suitable for use in soaps and cosmetic products [16, 17] . The aerial part of Pogostemon cablin has wildly been used for the treatment of the common cold and as an antifungal agent in China [16, 17] . Moreover, the plant is widely used in Traditional Chinese Medicine as it presents various types of pharmacological activity according to the composition of the oil [16, 17] . Patchouli alcohol, as the major volatile constituent of patchouli oil, has been found to strongly inhibit H1N1 replication and weakly inhibit B/Ibaraki/2/85 replication [18] . To the best of our knowledge, the anti-influenza virus (H2N2) activities of patchouli alcohol have not been evaluated yet. Therefore, the aim of the present study was to evaluate the anti-influenza A virus (H2N2) activity of patchouli alcohol by MTT assay and mouse influenza model. On such basis, explicitly solvated docking and molecular dynamic (MD) methods were applied to investigative the binding mode involving patchouli alcohol with influenza virus NA protein. We anticipate that the insight into the understanding of inhibiting mechanism will be of value in the rational design of novel anti-influenza drugs. First the efficacy of patchouli alcohol on influenza A (H2N2) virus replication and cell viability were examined. CC 50 was used to express the cytotoxicity of patchouli alcohol on MDCK. The CC 50 of patchouli alcohol was above 20 mM, which indicated that patchouli alcohol did not affect the growth of MDCK (Table 1) . Thus, it seems that the antiviral effects of patchouli alcohol were not due to the cytotoxicity. Moreover, patchouli alcohol was found to inhibit influenza A (H2N2) virus with an IC 50 of 4.03 ± 0.23 µM. Based on the IC 50 and CC 50 values, the selectivity index (SI) was calculated as >4.96. It is reported that a SI of 4 or more is appropriate for an antiviral agent [18] , suggesting that patchouli alcohol can be judged to have anti-influenza A (H2N2) virus activity. Until now, it has been found that patchouli alcohol showed dose-dependent anti-influenza virus (A/PR/8/34, H1N1) activity, with an IC 50 value of 2.635 µM. Furthermore, it showed weak activity against B/Ibaraki/2/85 (IC 50 = 40.82 µM) [19] . With the addition of the above H2N2 inhibitory activity, we have a comprehensively view of the anti-influenza activity of patchouli alcohol. Cells were pretreated with patchouli alcohol prior to virus infection (pretreatment cells), viruses were pretreated prior to infection (pretreatment virus), and patchouli alcohol was added during the adsorption period (adsorption) or after penetration of the viruses into cells (replication). Experiments were repeated independently three times and data presented are the average of three experiments. The symbols * indicated very significant difference p < 0.01 with respect to other mode (pretreatment virus, adsorption and pretreatment cell). As shown in Figure 2 , patchouli alcohol showed anti-influenza A (H2N2) virus activity in a timedependent manner. It showed best antiviral activity when added at a concentration of 8 µM during the replication period with inhibition of the viral replication of 97.68% ± 2.09% for influenza A (H2N2) at 72 h. However, no significant effect was detected when patchouli alcohol was used for pretreatment of cells or viruses or when patchouli alcohol was only added during the adsorption phase. These results suggested that the inhibition of influenza A (H2N2) virus by patchouli alcohol appears to occur much more strongly after penetration of the virus into the cell. Besides, biochemical studies have indicated that the bioactivity of NA protein is essential determinant after the replication of influenza A (H2N2) virus [20] [21] [22] . Hence, we conclude that the function of NA protein may be suppressed by patchouli alcohol. To evaluate the toxicity of patchouli alcohol, the mean value of body weight of mice in each group was statistically analyzed. The mean weights of mice administered at the 2 mg/kg/dose oseltamivir, 2 mg/kg/dose patchouli alcohol and 10 mg/kg/dose of patchouli alcohol one time daily for 7 days were not significantly different compared with the normal control mice, showing no toxicity of patchouli alcohol and oseltamivir within the testing concentration (P > 0.05). Physiological status was observed in virus infection mice. Three days after viral infection, some mice, especially mice in the H2N2 infected control group showed changes in behavior, such as a tendency to huddle, diminished vitality, and ruffled fur, etc. In the mouse influenza model, viral infection leads to loss of body weight and high mortality. Therefore, the efficacy of patchouli alcohol and oseltamivir were evaluated on the basis of survival rate measured for 15 days post-infection, for treated infected animals relative to untreated infected (control) animals. A comparison of efficacy of patchouli alcohol and oseltamivir in vivo mouse influenza model (oral treatment) showed that at a dose of 5 mg/kg/day, patchouli alcohol showed obvious protection against the influenza virus, as the mean day to death was detected as 11.8 ± 1.1 (Table 2) . When the dose was lowered to 1 mg/kg/day, patchouli alcohol showed weaker protection (measured by Survivors/total) than that of 5 mg/kg/day, the mean day to death was 7.5 ± 1.8. Whereas oseltamivir at this dose level (1 mg/kg/day) showed 50% protection (measured by survivors/total) against the influenza virus. In the H2N2 infected control group, there were no survivors. In view of both in vitro and in vivo data, we conclude that patchouli alcohol could be used in the treatment of human influenza virus infections. Based on the above experiment data, patchouli alcohol is determined to be bound within NA protein. As the total energies and backbone root-mean-square-deviations (RMSD) in Figure 3 indicate, the energy-minimized patchouli alcohol-NA complex has been in equilibrium since about 0.5 ns, and then retains quite stable in the last 19.5 ns. It is consistent with the previous MD results of other NA inhibitors [23] [24] [25] [26] [27] [28] . Accordingly, the geometric and energetic analyses were made on the average structures of 0.5~20.0 ns MD trajectories, where the system has been already at equilibrium. The interaction energy (E inter ) of patchouli alcohol with NA was calculated at −40.38 kcal mol −1 , where the vdW rather than electrostatic interactions were found to play a dominant role, contribute to about 72% (−29.18 kcal mol −1 ). As shown in Figure 4 , the patchouli alcohol was bound at the active site which also bound to oseltamivir and zanamivir [28] . As Figure 5 shows, the oxygen atom of patchouli alcohol was oriented towards the sidechains of residues Glu119 and Tyr406, with one H-bond formed with each residue. The values of distances in Figure 6 further reveal that the docked complex remains rather stable throughout the simulation, with the average distances of Glu119:OE2patchouli alcohol:O and Tyr406:OH -patchouli alcohol:O less than 2.8 Å. The sum contributions (E sum ) of residues Glu119 and Tyr406 amounted to −8.46 and −7.37 kcal mol −1 , respectively (Table 3) . Besides, patchouli alcohol was stabilized by residues Arg118, Asp151, Arg152, Trp178, Ala246, Glu276, Arg292, Asn294 and Gln347, especially residues Asp151, Arg152 and Glu276 ( Figure 5 and Table 3 ). As a matter of fact, residues Asp151, Arg152, Glu119, Glu276 and Tyr406 of the NA protein have already received enough attention from rational drug designs [14, 30, 31] . The catalytic residues Asp151, Arg152 and Glu276 are crucial to the NA functions and the residues Glu119 and Tyr406 are important to stabilize the NA active sites [32, 33] . It suggests that the NA functions will be affected by the presence of patchouli alcohol, consistent with the above experiments. Patchouli alcohol matches with the NA active site and has an acceptable interaction energy. Considering the obvious structure discrepancies against current NA inhibitors, it represents an ideal lead compound for the designs of novel anti-influenza agents. Patchouli alcohol and oseltamivir were obtained from Sigma Chemical Co. (St. Louis, MO, USA, purity > 99%) and was stored in glass vials with Teflon sealed caps at −20 ± 0.5 °C in the absence of light. MDCK (Madin-Darby canine kidney) was purchased from Harbin Veterinary Research Institute (Harbin, Heilongjiang, China). The cells were grown in monolayer culture with Eagle's minimum essential medium (EMEM) supplemented with 10% fetal calf serum (FCS), 100 U/mL penicillin and 100 μg/mL streptomycin. The monolayers were removed from their plastic surfaces and serially passaged whenever they became confluent. Cells were plated out onto 96-well culture plates for cytotoxicity and anti-influenza assays, and propagated at 37 °C in an atmosphere of 5% CO 2 . The influenza strain A/Leningrad/134/17/1957 H2N2) was purchased from National Control Institute of Veterinary Bioproducts and Pharmaceuticals (Beijing, China). Virus was routinely grown on MDCK cells. The stock cultures were prepared from supernatants of infected cells and stored at −80 °C. The cellular toxicity of patchouli alcohol on MDCK cells was assessed by the MTT method.\n\nQuestion: What was the focus of this study?" }, { "role": "assistant", "content": "the anti-influenza A (H2N2) virus activity of patchouli alcohol" } ]

[ { "role": "user", "content": "Given a short query with keyphrases about a research idea in 2017 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.\n\nQuery: I want to train a model to classify images with only labeled images and a few labeled images\n\nKeyphrases: semi-supervised learning image\n\nDataset description:\nCIFAR-10: The CIFAR-10 dataset (Canadian Institute for Advanced Research, 10 classes) is a subset of the Tiny Images dataset and consists of 60000 32x32 color images. The images are labelled with one of 10 mutually exclusive classes: airplane, automobile (but not truck or pickup truck), bird, cat, deer, dog, frog, horse, ship, and truck (but not pickup truck).\nJFT-300M: JFT-300M is an internal Google dataset used for training image classification models. Images are labeled using an algorithm that uses complex mixture of raw web signals, connections between web-pages and user feedback.\nCOCO: The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.\nModaNet: ModaNet is a street fashion images dataset consisting of annotations related to RGB images. ModaNet provides multiple polygon annotations for each image.\n\nOptions:- A: CIFAR-10 B: JFT-300M C: COCO D: ModaNet" }, { "role": "assistant", "content": "CIFAR-10" } ]

[ { "role": "user", "content": "You will be shown a question, followed by excerpts from biomedical research papers. Please answer the question based on the provided context. Do not include any text in your response other than the answer.\n\nQuestion: Which is the treatment strategy followed in spinocerebellar ataxia type 3 for CAG removal?\n\nContext: Ataxin-3 protein modification as a treatment strategy for spinocerebellar ataxia type 3: removal of the CAG containing exon\nSpinocerebellar ataxia type 3 is caused by a polyglutamine expansion in the ataxin-3 protein, resulting in gain of toxic function of the mutant protein. The expanded glutamine stretch in the protein is the result of a CAG triplet repeat expansion in the penultimate exon of the ATXN3 gene\nwe propose a novel protein modification approach to reduce mutant ataxin-3 toxicity by removing the toxic polyglutamine repeat from the ataxin-3 protein through antisense oligonucleotide-mediated exon skipping while maintaining important wild type functions of the protein\nexon skipping may be a novel therapeutic approach to reduce polyglutamine-induced toxicity in spinocerebellar ataxia type 3\nAtaxin-3 protein modification as a treatment strategy for spinocerebellar ataxia type 3: removal of the CAG containing exon.\nAtaxin-3 protein modification as a treatment strategy for spinocerebellar ataxia type 3: removal of the CAG containing exon." }, { "role": "assistant", "content": "The novel treatment strategy proposed for treatment of Spinocerebellar ataxia type 3 is the removal of the toxic polyglutamine repeat from the ataxin-3 protein through antisense oligonucleotide-mediated exon skipping while maintaining important wild type functions of the protein." } ]

[ { "role": "user", "content": "You will be presented a sentence from biomedical research text. Extract all terms that correspond to chemical entities of biological interest (ChEBI).\nReturn your identified terms in a JSON array, formatted like this: [\"Entity1\", \"Entity2\", ...].\nIf no such entities are detected, respond by providing an empty JSON array [].\n\nBiomedical context:\nThescalebarsrepresent50mum." }, { "role": "assistant", "content": "[]" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research paper, followed by a question about the paper. Please extract text from the paragraph to answer the question. Do not include any text in your repsonse other than the answer.\n\nParagraph: In 2010, Dr. Yount and co-workers reported that the antiviral activity of IFITM3 is dependent on S-palmitoylation on the protein [10] . The S-palmitoylation [23] is a post-translational modification on proteins by C 16 saturated-fatty acids (palmitic acids) covalently attached to certain cysteine residues via a thioester linkage (Figure 1-B) . The modification is reversibly catalyzed by protein acyltransferases and acylprotein thioesterases, and confers unique properties to the protein, such as membrane binding and targeting, immunoreactivity,\n\nAmino-acid sequence alignment of IFITM5, IFITM1, IFITM2, and IFITM3 derived from mice. The conserved residues are highlighted in black. The three conserved cysteines are highlighted in red and numbered based on the sequence of IFITM5 (top) and IFITM3 (bottom). The residues unique in IFITM5 are highlighted in gray. The first and the second transmembrane domains, the extracellular sequences, and the cytoplasmic loop are indicated by arrows and denoted as TM1 and TM2, EC, and the CP loop, respectively. The TM domains were predicted by SOSUI. The aspartates at the C-terminal region in IFITM5 are shown in blue. B) The schematic illustration of the protein S-palmitoylation. The C 16 -palmitic acid is attached to cysteine via a thioester linkage. The palmitoylation and depalmitoylation are catalyzed by protein acyltransferases and acylprotein thioesterases, respectively. In this study, hydroxylamine, NH 2 OH, was used to reduce the thioester linkage. C) The amino acid sequence identity (similarity) among IFITM5, IFITM1, IFITM2, and IFITM3 is summarized. doi: 10.1371/journal.pone.0075831.g001 and protein-protein interaction. The authors revealed that IFITM3 is S-palmitoylated on three membrane proximal cysteines, Cys71 and Cys72 in the first transmembrane (TM1) domain, and Cys105 in the CP loop (Figure 1-A) [10] . In addition, IFITM3 lacking the S-palmitoylation is not clustered in the cell membrane and significantly diminishes the antiviral activity. Moreover, the cysteines in IFITM2, Cys70, Cys71, and Cys104 are also palmitoylated in the same manner, which affects the intracellular localization [24] . A resent study has revealed that murine IFITM1 has four cysteine residues (Cys49, Cys50, Cys83, and Cys103) for the S-palmitoylation, which is required for the antiviral activity and the protein stability [25] . The other IFITM family members also possess these cysteines (Figure 1-A) , and thus the role of the Spalmitoylation on the cysteines should be significant for the functions of IFITM proteins. Here, we focused on IFITM5, which is also known as bonerestricted IFITM-like (BRIL) protein [18] . Among the IFITM family proteins, IFITM5 is unique. (i) Expression of IFITM5: Unlike the other IFITM family proteins, the expression of IFITM5 is not induced by interferons because the region upstream of the ifitm5 gene lacks the interferon regulatory elements [26] . Furthermore, the expression of IFITM5 is mostly restricted to osteoblast cells [18, 19, 27] , while the other IFITM proteins are expressed ubiquitously (ii). Amino-acid sequence similarity: The amino acid sequence of IFITM5 is relatively dissimilar to IFITM1-3 proteins (~ 65% similarity), while IFITM1-3 proteins share ~ 85% similarity with each other (Figure 1 -C). In addition, IFITM5 has an aspartate-rich domain in the C-terminal region, which could be involved in calcium binding (Figure 1 -A) [26] . (iii) Role of IFITM5 in bone formation: The expression of IFITM5 is associated with mineralization during the bone formation process in osteoblast cells [18] [19] [20] [21] . Previous studies have confirmed the expression of IFITM5 in bone tissues in mice, rats, humans and tammar wallabies [2] . The ifitm5-gene knockout mice have smaller bones [19] . Moreover, the knockdown of the ifitm5 gene by small hairpin RNA induces a decrease in bone nodule formation, whereas overexpression of the gene in UMR106 cells has been shown to increase calcium uptake and bone nodule formation [18] . (iv) Role of IFITM5 for immune activity: Recent studies have revealed that IFITM5 interacts with the FK506-binding protein 11 (FKBP11) to form IFITM5-FKBP11-CD81-the prostaglandin F2 receptor negative regulator (FPRP) complex [28] . When the complex is formed, the expressions of 5 interferon-induced genes are induced, including bone marrow stromal cell antigen 2 (Bst2), interferon inducible protein 1 (Irgm), interferoninduced protein with tetratricopeptide repeats 3 (Ifit3), b(2)microglobulin (B2m), and MHC class I antigen gene. Consequently, these results indicate that IFITM5 is involved not only in the bone formation but also in the immune system activity. In this study, we investigated the S-palmitoylation of IFITM5 and its role in the interaction with FKBP11 in mouse osteoblast cells. Cells transfected by a plasmid DNA encoding mouse IFITM5 were grown in the presence of an established chemical reporter, 17-octadecynoic acid (17-ODYA) [29, 30] , or an inhibitor for the S-palmitoylation, 2-bromopalmitic acid (2BP) [31] . The biochemical assays using these compounds revealed that the wild-type IFITM5 is S-palmitoylated. To identify the Spalmitoylation site in IFITM5, we prepared cysteine-substituted mutants, IFITM5-C86A, -C52A/C53A, and -C52A/53A/86A (Cys-less). The chemical reporter assay suggested that at least two out of three cysteines in IFITM5 are S-palmitoylated. The interaction of IFITM5 with FKBP11 was examined by immunoprecipitation assay, resulting in the loss of the interaction in the presence of 2BP. The same result was obtained in the two mutants, C52A/C53A and Cys-less. These results suggested that the S-palmitoylation on Cys52 and/or Cys53 in the TM1 domain of IFITM5 is necessary for the interaction with FKBP11. On the other hand, Cys86 in the CP loop of IFITM5 was S-palmitoylated but not involved in the interaction. Because this interaction is important for the immunologically relevant gene expression, it was indicated that the role of the S-palmitoylation is to promote the interaction of IFITM5 with FKBP11 and to regulate the immune activity in the osteoblast cells. The possible interaction mechanism and the effect of the S-palmitoylation on the bone nodule formation will be discussed. For mammalian cell expression, plasmid vectors of wild-type IFITM5 (IFITM5-WT) and FLAG-fused FKBP11 (FKBP11-FLAG) were constructed by inserting the cloned genes into a pBApo-CMV Neo expression vector (Takara Bio, Shiga, Japan). The details of the recombinant DNA constructs were the same as described previously [19] . The genes of IFITM5 mutants (IFITM5-C86A, -C52A/53A, and -C52A/C53A/C86A (Cys-less)) were prepared using a QuikChange site-directed mutagenesis kit (Stratagene, La Jolla, CA). The plasmid vectors of FLAG-fused IFITM5-WT, -C52A/53A, and Cys-less were constructed by inserting the cloned genes into the pBApo-CMV Neo expression vector. For E. coli cell expression, the plasmid vector of IFITM5-WT was constructed by inserting the cloned gene into a pET22b (Novagen, Madison, WI) expression vector. The forward primer 5'-GGAATTCCATATGGACACTTCATATCCCCGTG-3' and the reverse primer 5'-CCGCTCGAGGTTATAGTCCTCCTCATCAAACTTGG-3' were used to amplify the gene encoding the entire IFITM5 from the plasmid vector for mammalian cell expression described above. The underlined letters denote an NdeI and an XhoI cleavage site, respectively. The plasmids of IFITM5 mutants were prepared using a QuikChange site-directed mutagenesis kit. The sense and anti-sense primers used were 5'-GGCAGTATGGCTCCAAAGCCAAGGCGTACAACATCCTGG CTGC-3' and 5'-GCAGCCAGGATGTTGTACGCCTTGGCTTTGGAGCCATACT GCC-3' for IFITM5-C86A; and 5'-GCACGATGTACCTGAATCTGGCGGCGCTTGGATTCCTGG CGC-3' and 5'-GCGCCAGGAATCCAAGCGCCGCCAGATTCAGGTACATCG TGC-3' for IFITM5-C52A/C53A, respectively (Sigma-Aldrich, St. Louis, MO). Osteoblast-like MC3T3 cells were provided by the RIKEN, Cell Bank (RCB 1126). The procedures for cell culture, transfection, and protein expression were the same as reported previously. When necessary, 2-bromopalmitic acid (2BP; Wako, Osaka, Japan) and 17-octadecynoic acid (17-ODYA; Sigma-Aldrich) were dissolved in 99.5% dimethyl sulfoxide (DMSO; Wako) and added to differentiation medium at concentrations of 100 μM and 50 μM in less than 0.1% DMSO, respectively [30, 31] . Wild-type and mutant IFITM5 proteins were also produced using an E. coli recombinant expression system. E. coli BL21(DE3) cells transformed by the expression plasmid were grown at 37°C in LB medium containing 50 μg/mL ampicillin. After four-hour induction by 1 mM isopropyl β-Dthiogalactopyranoside (IPTG), cells were harvested by centrifugation (6,400 × g for 10 min at 4°C). The cells were suspended in 50 mM Tris-HCl buffer (pH 8) and disrupted by a French press (Ohtake, Tokyo, Japan) (100 MPa × 4 times). The crude membrane fraction was collected by ultracentrifugation (178,000 × g for 90 min at 4°C). The collected fraction was solubilized with 1.5% n-dodecyl-β-Dmaltopyranoside (DDM) (Dojindo Lab, Kumamoto, Japan) in 50 mM Tris-HCl, pH 8, containing 0.3 M NaCl and 5 mM imidazole. After the ultracentrifugation, the supernatant was incubated with Ni 2+ -NTA agarose resin (Qiagen, Hilden, Germany). The resin was applied to a chromatography column and washed with 50 mM imidazole containing 50 mM Tris-HCl (pH 8), 0.3 M NaCl and 0.1% DDM. The DDM-solubilized IFITM5 was collected by elution with the same buffer containing 0.3 M imidazole. The sample media were replaced by the appropriate buffer solution by two passages over a PD-10 column (GE Healthcare UK, Ltd., Amersham Place, England). The experimental details are described in previous reports [19, 28] . Briefly, total proteins were extracted from the osteoblast cells which co-expressed IFITM5 and FKBP11-FLAG using a total protein extraction kit (BioChain Institute Inc., Newark, CA). Then, the cell lysate was incubated with anti-FLAG M2 agarose gel (Sigma-Aldrich) at 4°C for 2 h. To recover FKBP11-FLAG, 500 ng/μL 3 × FLAG peptide (Sigma-Aldrich) dissolved in Tris-buffered saline was added to the collected gel at 4°C for 1 h. The recovered proteins and the cell lysate containing total proteins were analyzed by SDS-PAGE (15% ePAGEL; ATTO, Tokyo, Japan) and western blot. The anti-IFITM5 polyclonal antibody, which was prepared from the amino-terminal peptide sequence (TSYPREDPRAPSSRC), and anti-FLAG monoclonal antibody (Sigma-Aldrich) were used as primary antibodies. The HRP-conjugated goat anti-rabbit IgG (H+L) (Zymed Laboratories, San Francisco, CA) and goat anti-mouse IgG (H+L) (Sigma-Aldrich) antibodies were used as secondary antibodies for the anti-IFITM5 and anti-FLAG primary antibodies, respectively. The proteins were detected by chemiluminescent reaction (MercK-Millipore, Billerica, MA). The cell lysate extracted from the osteoblast cells metabolically labeled by 17-ODYA was incubated with anti-FLAG M2 agarose gel to obtain purified FLAG-fused IFITM5 proteins. The 17-ODYA-labeled proteins were chemically labeled with azide-PEG 3 -5(6)-carboxytetramethylrhodamine (TAMRA-azide; Click Chemistry Tools, Scottsdale, AZ) with reference to previous studies [10, 29, 30, 32] and the manufacturer's guide. The proteins separated by SDS-PAGE were visualized using a 532-nm laser for excitation and the fluorescence by TAMRA (565 nm) was detected using a 575nm long-path filter (Typhoon FLA 9000; GE Healthcare).\n\nQuestion: What regulates the antiviral activity of IFITM3?" }, { "role": "assistant", "content": "S-palmitoylation on the protein" } ]

[ { "role": "user", "content": "You have to answer a biomedical question in binary format, i.e. only yes and no are the only acceptable answer formats. A list of paragraphs is provided as context to help you answer the question.\n\nQuestion: Could BRCA gene test used for breast and ovarian cancer risk?\n\nContext: Participation of Korean families at high risk for hereditary breast and ovarian cancer in BRCA1/2 genetic testing.\nThe prevalence of BRCA1/2 mutations in Korean ovarian cancer patients irrespective of the family history was significantly higher than previously reported. Possible founder mutations in Korean ovarian cancer patients were identified.\nGermline Mutations of BRCA1 and BRCA2 in Korean Ovarian Cancer Patients: Finding Founder Mutations.\nThe assessment of BRCA1 and BRCA2 coding sequences to identify pathogenic mutations associated with inherited breast/ovarian cancer syndrome has provided a method to identify high-risk individuals, allowing them to seek preventative treatments and strategies.\nMaximising survival: the main concern of women with hereditary breast and ovarian cancer who undergo genetic testing for BRCA1/2.\nLittle is known about how women with hereditary breast and/or ovarian cancer who test positive for a BRCA gene manage the impact of a positive test result on their everyday lives and in the longer term. This study defined the experience and needs of women with hereditary breast and ovarian cancer and a positive BRCA test over time.\nThe strongest evidence was for rs1466785 in the NEIL2 (endonuclease VIII-like 2) gene (HR: 1.09, 95% CI (1.03-1.16), p = 2.7 × 10(-3)) for association with breast cancer risk in BRCA2 mutation carriers, and rs2304277 in the OGG1 (8-guanine DNA glycosylase) gene, with ovarian cancer risk in BRCA1 mutation carriers (HR: 1.12 95%CI: 1.03-1.21, p = 4.8 × 10(-3)).\nFemale BRCA (breast cancer gene)-1 and BRCA-2 mutations are significantly associated with risk of developing breast and ovarian cancers, in turn, associated with female infertility.\nLarge BRCA1 and BRCA2 genomic rearrangements in Polish high-risk breast and ovarian cancer families.\nBRCA1 and BRCA2 are two major genes associated with familial breast and ovarian cancer susceptibility.\nUntil 2006, she supervised a diagnostic unit for BRCA gene testing at the Interdisciplinary Center for Hereditary Breast Cancer (Max Delbrück Center, Berlin, Germany).\nInherited BRCA gene mutations convey a high risk for breast and ovarian cancer, but current guidelines limit BRCA mutation testing to women with early-onset cancer and relatives of mutation-positive cases.\nWomen who carry a BRCA1 or BRCA2 gene mutation face a risk of developing breast or ovarian cancer at an earlier age than women without such a mutation.\nIn 2006, participants were recruited from Web sites for women with breast cancer or BRCA gene mutations.\nAbout 20 % of hereditary breast cancers are caused by mutations in BRCA1 and BRCA2 genes. Since BRCA1 and BRCA2 mutations may be spread throughout the gene, genetic testing is usually performed by direct sequencing of entire coding regions.\nSuggestion of an association between BRCA2 c.7806-2A>G and risk of breast cancer in males has emerged.\nThe presence of deleterious mutations in breast cancer (BRCA)-1 or BRCA-2 gene has a decisive influence on the development of various types of neoplasms, such as breast, ovarian, tubal, and peritoneal cancers.\nOBJECTIVE: Female BRCA (breast cancer gene)-1 and BRCA-2 mutations are significantly associated with risk of developing breast and ovarian cancers, in turn, associated with female infertility.\nBRCA1 and BRCA2 genes are responsible for 5-10% of breast and ovarian cancer cases.\nShe was daughter of a woman, a carrier of BRCA 1 gene mutation, with early onset of breast cancer and positive family history.CONCLUSIONS: BRCA 1 and BRCA 2 gene mutations are of particular importance in the increasing risk of ovarian cancer and early onset of breast cancer as well as some other malignancies.\nBACKGROUND: Women who are diagnosed with a deleterious mutation in either breast cancer (BRCA) gene have a high risk of developing breast and ovarian cancers at young ages.\nWe identified AJ individuals with breast and/or ovarian cancer undergoing hereditary breast/ovarian cancer risk assessment since 2006 without evidence of a deleterious mutation on BRCA gene sequencing who were screened for major gene rearrangements in BRCA1 and BRCA2.\nGermline BRCA gene mutations are reportedly associated with hereditary breast and ovarian cancers.\n[Detection and occurrence of BRCA 1 gene mutation in patients with carcinoma of the breast and ovary].\nWe investigated the relationship between BRCA mutations and the distribution of familial cancers other than breast or ovary in high-risk breast cancer patients.PATIENTS WITH BREAST CANCER WHO HAD AT LEAST ONE OF THE FOLLOWING RISK FACTORS WERE ENROLLED: reported family history of breast or ovarian cancer; 40 years of age or younger age at diagnosis; bilateral breast cancer; or male gender\nMutations in breast cancer susceptibility genes (BRCA1 and BRCA2) are associated with increased risks for breast, ovarian, and other types of cancer.To review new evidence on the benefits and harms of risk assessment, genetic counseling, and genetic testing for BRCA-related cancer in women.MEDLINE and PsycINFO between 2004 and 30 July 2013, the Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews from 2004 through the second quarter of 2013, Health Technology Assessment during the fourth quarter of 2012, Scopus, and reference lists.English-language studies about accuracy of risk assessment and benefits and harms of genetic counseling, genetic testing, and interventions to reduce cancer incidence and mortality.\nThe objective of this study was to assess the incidence of primary breast cancer (PBC) and contralateral breast cancer (CBC) in patients who had BRCA1/BRCA2-associated epithelial ovarian cancer (OC).From the database of the Rotterdam Family Cancer Clinic, patients who had BRCA-associated OC without a history of unilateral breast cancer (BC) (at risk of PBC; n = 79) or with a history of unilateral BC (at risk of CBC; n = 37) were selected\nStatistically significant earlier ages at diagnosis also were observed within subgroups of BRCA1 and BRCA2 mutations, maternal inheritance, paternal inheritance, breast cancer only, and breast cancer-identified and ovarian cancer-identified families.Breast and ovarian cancers in BRCA mutation carriers appeared to be diagnosed at an earlier age in later generations\nThe USPSTF also reviewed interventions aimed at reducing the risk for BRCA-related cancer in women with potentially harmful BRCA mutations, including intensive cancer screening, medications, and risk-reducing surgery.This recommendation applies to asymptomatic women who have not been diagnosed with BRCA-related cancer.The USPSTF recommends that primary care providers screen women who have family members with breast, ovarian, tubal, or peritoneal cancer with 1 of several screening tools designed to identify a family history that may be associated with an increased risk for potentially harmful mutations in breast cancer susceptibility genes (BRCA1 or BRCA2)\nIf a woman bearing a mutation develops cancer in one breast, her risk of developing cancer in the other breast depends on the particular gene that is mutated and on her age at the onset of disease.About half of all monogenically determined carcinomas of the breast and ovary are due to a mutation in one or the other of the highly penetrant BRCA genes (BRCA1 and BRCA2)\nA value of RHR greater than 1 indicated elevated breast cancer risk; a value of RHR less than 1 indicated elevated ovarian cancer risk.Mutations of BRCA1 or BRCA2.Breast and ovarian cancer risks.Among BRCA1 mutation carriers, 9052 women (46%) were diagnosed with breast cancer, 2317 (12%) with ovarian cancer, 1041 (5%) with breast and ovarian cancer, and 7171 (37%) without cancer\nThis study defined the experience and needs of women with hereditary breast and ovarian cancer and a positive BRCA test over time.METHODS: A grounded theory approach was taken using qualitative interviews (n = 49) and reflective diaries.\nLittle is known about how women with hereditary breast and/or ovarian cancer who test positive for a BRCA gene manage the impact of a positive test result on their everyday lives and in the longer term.\nThis study defined the experience and needs of women with hereditary breast and ovarian cancer and a positive BRCA test over time.A grounded theory approach was taken using qualitative interviews (n = 49) and reflective diaries.\nWomen with a harmful mutation in the BReast CAncer (BRCA) gene are at significantly increased risk of developing hereditary breast and ovarian cancer (HBOC) during their lifetime, compared to those without.\nGenetic testing for BRCA genes, associated with hereditary breast-ovarian cancer risk, is an accepted cancer control strategy.\nYounger patients, those with a family history of breast or ovarian cancer, and those diagnosed more recently were more likely to be BRCA tested.\nMutations in BRCA genes elevate risk for breast and ovarian cancer.\nObservational studies of prophylactic surgeries report reduced risks for breast and ovarian cancer in mutation carriers.No data describe the range of risk associated with BRCA mutations, genetic heterogeneity, and moderating factors; studies conducted in highly selected populations contain biases; and information on adverse effects is incomplete.A primary care approach to screening for inherited breast and ovarian cancer susceptibility has not been evaluated, and evidence is lacking to determine benefits and harms for the general population.\nWe identified AJ individuals with breast and/or ovarian cancer undergoing hereditary breast/ovarian cancer risk assessment since 2006 without evidence of a deleterious mutation on BRCA gene sequencing who were screened for major gene rearrangements in BRCA1 and BRCA2. For each proband, the pre-test probability of identifying a deleterious BRCA mutation was estimated using the Myriad II model. We identified 108 affected individuals who underwent large rearrangement testing (80 breast cancer, 19 ovarian cancer, nine both breast and ovarian cancer).\nTruncated proteins are easily discriminated from full size.RESULTS: Three BRCA 1 gene alterations were identified in the investigated group of women suffering from ovarian or breast cancer. One asymptomatic person--carrier of BRCA 1 gene mutation--was identified in this study. She was daughter of a woman, a carrier of BRCA 1 gene mutation, with early onset of breast cancer and positive family history.CONCLUSIONS: BRCA 1 and BRCA 2 gene mutations are of particular importance in the increasing risk of ovarian cancer and early onset of breast cancer as well as some other malignancies.\nGermline BRCA gene mutations are reportedly associated with hereditary breast and ovarian cancers. Identification of BRCA mutations greatly improves the preventive strategies and management of breast cancer.\nStatistically significant earlier ages at diagnosis also were observed within subgroups of BRCA1 and BRCA2 mutations, maternal inheritance, paternal inheritance, breast cancer only, and breast cancer-identified and ovarian cancer-identified families.CONCLUSIONS: Breast and ovarian cancers in BRCA mutation carriers appeared to be diagnosed at an earlier age in later generations.\nTruncated proteins are easily discriminated from full size.RESULTS: Three BRCA 1 gene alterations were identified in the investigated group of women suffering from ovarian or breast cancer.\nHowever, some single risk factors without family histories (early-onset breast cancer, male breast cancer, or multiple organ cancers) may limit the utility of BRCA gene testing in the Korean population.\nBRCA Mutations Increase Fertility in Families at Hereditary Breast/Ovarian Cancer Risk.\nBecause infertility is associated with breast and ovarian cancer risks, we hypothesized that the mutations in the BRCA gene may be associated with low response to fertility treatments.\nMoreover, in families of breast cancer patients without BRCA mutations, breast cancer risk depends on the patient's age at diagnosis.\nAmong the 554 women who underwent genetic testing for BRCA mutation, 78 were found to have a deleterious mutation in the BRCA1 gene, and 54 had a mutation in the BRCA 2 gene.\nFrequent recurrent mutations in the breast and ovarian cancer susceptibility (BRCA) genes BRCA1 and BRCA2 among Hispanics, including a large rearrangement Mexican founder mutation (BRCA1 exon 9-12 deletion [ex9-12del]), suggest that an ancestry-informed BRCA-testing strategy could reduce disparities and promote cancer prevention by enabling economic screening for hereditary breast and ovarian cancer in Mexico.\nIndividuals who carry a BRCA gene mutation have increased lifetime risks of developing hereditary breast and ovarian cancer syndrome-related cancers.\nBRCA gene mutations have been well described to carry an increased risk of both breast and ovarian cancer.\nOvarian cancer among 8,005 women from a breast cancer family history clinic: no increased risk of invasive ovarian cancer in families testing negative for BRCA1 and BRCA2.\nWomen who were BRCA carriers, women who had a history of breast cancer, DCIS, or breast biopsy, or had a family history of ovarian cancer were more likely to have undergone surgery for cancer risk reduction.\nGenetic testing for breast cancer susceptibility became a reality after two cancer predisposition genes, BRCA1 and BRCA2, were identified.\nGermline mutations in BRCA genes are associated with breast and ovarian cancer susceptibility.\nWe used person-years at risk to assess ovarian cancer rates in the study population, subdivided by genetic status (BRCA1, BRCA2, BRCA negative, BRCA untested) compared with the general population." }, { "role": "assistant", "content": "yes" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:\n\n- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.\n- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.\n- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.\n\nPlease format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.\n\nAs an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:\n\n[[\"artesunate\", \"artemether\", \"COMB\"], [\"Nifedipine\", \"Labetalol\", \"Prazosin\", \"POS\"]]\n\nThe paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.\n\nIn your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.\n\nparagraph: Bupropion differentially alters the aversive , locomotor and rewarding properties of nicotine in CD-1 mice . The present experiments determined the effects of bupropion on the motivational (aversive and rewarding) and locomotor properties of nicotine in CD-1 mice. Preliminary experiments determined effective nicotine doses (0.1-2.0 mg/kg) to produce a conditioned taste aversion (CTA) or conditioned place preference (CPP; Experiments 1a and 2a, respectively). Mice were administered vehicle or bupropion (1-20 mg/kg) followed by vehicle or nicotine after drinking saccharin during CTA training (Experiment 1b). Mice were administered vehicle or bupropion (1-20 mg/kg) 15 (Experiment 2b) or 30 (Experiment 2c) minutes (min) prior to vehicle or nicotine during CPP training. The two highest nicotine doses produced CTAs and a moderate nicotine dose (0.4 mg/kg) produced a CPP. bupropion dose-dependently blocked nicotine CTA. For the 15-min pretreatment interval, bupropion dose-dependently increased locomotor activity and produced CPPs when administered alone; whereas for the 30-min pretreatment interval, only the highest bupropion dose increased locomotor activity and produced a CPP. However, bupropion failed to alter nicotine CPP and the co-administration of bupropion and nicotine did not increase locomotor activity more so than when bupropion was administered alone regardless as to the pretreatment interval. Thus, bupropion selectively altered the aversive properties of nicotine in CD-1 mice.\n\nsentence: Bupropion differentially alters the aversive , locomotor and rewarding properties of nicotine in CD-1 mice ." }, { "role": "assistant", "content": "[[\"Bupropion\", \"nicotine\", \"POS\"]]" } ]

[ { "role": "user", "content": "You will be shown biomedical passages and your task is to the answer the provided question. Provide a concise and accurate response and do not include any additional text in the response other than the answer.\n\nQuestion: What part of the body is associated with Cauda equina\n\nContext: the right pedicle of L4, moved inside the vertebral canal (bridging the cauda equina) stopping just in front of the body of S2.\nThermoesthesia-and-algesthesia status in the dermatomes of cauda equina roots in patients with lumbar spine osteochondrosis\nThermoesthesia-and-algesthesia disorders have been registered in the dermatomes of cauda equina roots of patients with lumbar spine osteochondrosis in all the cases.\nMagnetic resonance images of the lumbar spine showed an intradural cystic lesion displacing and compressing the lower cord and cauda equina.\nCauda equina syndrome is a well described state of neurologic compromise due to lumbosacral root compression.\nAcute cauda equina syndrome secondary to a lumbar synovial cyst\nINTRODUCTION: Schwannoma is a relatively common benign spinal cord and/or cauda equina tumor; however, giant cauda equina schwannoma with extensive scalloping of the lumbar vertebral body is a rare pathology, and the treatment strategy, including the use of surgical procedures, is controversial.\nIn this report, we present a rare case of a giant lumbar schwannoma of the cauda equina with extremely large scalloping of the vertebral body, and we discuss the surgical strategy we used to treat this pathology.\nIn contrast, the caudal cord of Rana is reduced to a filum terminale consisting of little more than an ependymal tube; spinal nerves to all caudal myotomes leave the cord in the sacral region and reach their motor targets via a cauda equina and caudal plexus.\nThe spinal cords of other teleosts, the sun-fish and angler, also are abbreviated and possess a filum terminale and cauda equina.\nPenetrating spinal cord injury with foreign body included or myelography stop or showing cauda equina syndrome should be operated on.\nCauda Equina Conduction Time Determined by F-Waves in Normal Subjects and Patients With Neurogenic Intermittent Claudication Caused by Lumbar Spinal Stenosis\nAfter spinal cord injury, electrical stimulation of the roots inside the spinal column at the level of the cauda equina is a safe and effective way to regain some degree of control over lower body function, e.g. bladder and bowel management and leg movement.\nMalignant spinal cord compression(MSCC)is defined as a compression of the spinal cord or cauda equina with neuropathy caused by tumor spreading to the vertebral body.\nnction of the cauda equina, the collection of ventral and dorsal lumbar, sacral and coccygeal nerve roots that surround the filum terminale. This most\nINTRODUCTION: Schwannoma is a relatively common benign spinal cord and/or cauda equina tumor; however, giant cauda equina schwannoma with extensive scalloping of the lumbar vertebral body is a rare pathology, and the treatment strategy, including the use of surgical procedures, is controversial\nCauda equina syndrome is a relatively uncommon condition typically associated with a large, space-occupying lesion within the canal of the lumbosacral spine.\nCauda equina syndrome refers to dysfunction of the cauda equina, the collection of ventral and dorsal lumbar, sacral and coccygeal nerve roots that surround the filum terminale.\nThe involvement of intrinsic spinal cord neurons in the compression-induced cauda equina syndrome includes anterograde, retrograde and transneuronal degeneration in the lumbosacral segments.\nSingle or double-level compression of the lumbosacral nerve roots located in the dural sac results in a polyradicular symptomatology clinically diagnosed as cauda equina syndrome.\nThe cauda equina is an anatomic structure located in the lower part of the spinal canal consisting of multiple lumbar and sacral nerve roots." }, { "role": "assistant", "content": "spine" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nThe daily new confirmed Coronavirus disease 2019 (COVID-19) cases have decreased in some European and Asian countries. Many countries and areas have started to ease public restrictions. Here, we share our experiences and recommendations on how to conduct radiotherapy after public restrictions have eased or upon reopening. Firstly, COVID-19 nucleic acid test screening should be performed for all new admitted patients in areas with enough test capability. Secondly, radiotherapy can be conducted reference to consensus or recommendations on radiotherapy during COVID-19. Thirdly, it is not the time to consider compromising the guidance and the guidance on radiotherapy workflow and protection procedures still should be strictly followed." }, { "role": "assistant", "content": "[\"Prevention\"]" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nWuhan, the city in Hubei province in China is in the focus of global community due to the outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), formerly known as 2019-nCoV. The virus emerged in humans from Wuhan seafood market probably via zoonotic transmission. Within a few days the virus spread its tentacles rapidly to neighboring cities in China and to different geographical regions through travelers and to some extent by human to human transmission leading to significant disease burden globally. More than 2,00,000 people (including more than 8000 deaths) have been infected with this respiratory illness across 167 countries and territories worldwide leading to a pandemic. The present review provides an outline about emergence and spread of SARS-CoV-2 from Wuhan, China in 2019-2020. We have also provided information about the classification, genome, proteins, clinical presentation of COVID-19, type of clinical specimens to be collected and diagnostic methods adopted to identify the respiratory illness. In addition we have also provided information about transmission dynamics, prevention measures and treatment options that are available at the present. Subsequently, we have given a comprehensive overview of the spread of this infection from China to the other parts of the globe. Management of the ongoing outbreak of SARS-CoV-2 encompassing surveillance, clinical, immunological, genetic and evolutionary investigations are likely to provide the desired results. Joint efforts of global scientific community are needed at this hour in terms of enhancement of research on development of accurate diagnostics, antiviral therapeutics and finally into formation of an effective vaccine against the emerging novel coronavirus." }, { "role": "assistant", "content": "[\"Prevention\", \"Transmission\", \"Treatment\", \"Diagnosis\"]" } ]

[ { "role": "user", "content": "You will be shown biomedical passages and your task is to the answer the provided question. Provide a concise and accurate response and do not include any additional text in the response other than the answer.\n\nQuestion: What is the target of the drug remdesivir?\n\nContext: We recently reported that the nucleoside analogue GS-5734 (remdesivir) potently inhibits human and zoonotic CoVs in vitro and in a severe acute respiratory syndrome coronavirus (SARS-CoV) mouse model.\nTogether, these studies define the target of GS-5734 activity and demonstrate that resistance is difficult to select, only partial, and impairs fitness and virulence of MHV and SARS-CoV, supporting further development of GS-5734 as a potential effective pan-CoV antiviral.\nIn non-human primates, early initiation of polymerase inhibitors favipiravir and remdesivir improves survival, but whether they could be effective in patients is unknown." }, { "role": "assistant", "content": "polymerase" } ]

[ { "role": "user", "content": "Given a short query with keyphrases about a research idea in 2018 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.\n\nQuery: I want to use active learning to reduce the amount of labeled training data needed to achieve a target object\n\nKeyphrases: object detection image paragraph-level\n\nDataset description:\nFSDnoisy18k: The FSDnoisy18k dataset is an open dataset containing 42.5 hours of audio across 20 sound event classes, including a small amount of manually-labeled data and a larger quantity of real-world noisy data. The audio content is taken from Freesound, and the dataset was curated using the Freesound Annotator.\nDialogue State Tracking Challenge: The Dialog State Tracking Challenges 2 & 3 (DSTC2&3) were research challenge focused on improving the state of the art in tracking the state of spoken dialog systems. State tracking, sometimes called belief tracking, refers to accurately estimating the user's goal as a dialog progresses.\nCOCO: The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.\nOLID: The OLID is a hierarchical dataset to identify the type and the target of offensive texts in social media. The dataset is collected on Twitter and publicly available.\n\nOptions:- A: FSDnoisy18k B: Dialogue State Tracking Challenge C: COCO D: OLID" }, { "role": "assistant", "content": "COCO" } ]

[ { "role": "user", "content": "Given an abstract from a research paper, your task is to identify and label relationships between chemical compounds and genes mentioned in the abstract.\n\nThe relationship type must be one of ['DOWNREGULATOR', 'SUBSTRATE', 'INDIRECT-REGULATOR', 'PART-OF', 'MODULATOR-ACTIVATOR', 'REGULATOR', 'INHIBITOR', 'COFACTOR', 'UPREGULATOR', 'ACTIVATOR', 'ANTAGONIST', 'NOT', 'INDIRECT-DOWNREGULATOR', 'SUBSTRATE_PRODUCT-OF', 'INDIRECT-UPREGULATOR', 'AGONIST', 'PRODUCT-OF', 'MODULATOR', 'DIRECT-REGULATOR', 'UNDEFINED', 'AGONIST-INHIBITOR', 'AGONIST-ACTIVATOR', 'MODULATOR-INHIBITOR'].\n\nPlease format your output as a JSON array. Each entry in the array should express a single relation, formatted as [\"<Entity_A>\", \"<RELATION_A_B>\", \"<Entity_B>\"]. If no relations can be found, please output an empty JSON array [].\n\nAbstract:\n\nL-proline accumulation and freeze tolerance of Saccharomyces cerevisiae are caused by a mutation in the PRO1 gene encoding gamma-glutamyl kinase. We previously isolated a mutant which showed a high tolerance to freezing that correlated with higher levels of intracellular L-proline derived from L-proline analogue-resistant mutants. The mutation responsible for the analogue resistance and L-proline accumulation was a single nuclear dominant mutation. By introducing the mutant-derived genomic library into a non-L-proline-utilizing strain, the mutant was found to carry an allele of the wild-type PRO1 gene encoding gamma-glutamyl kinase, which resulted in a single amino acid replacement; Asp (GAC) at position 154 was replaced by Asn (AAC). Interestingly, the allele of PRO1 was shown to enhance the activities of gamma-glutamyl kinase and gamma-glutamyl phosphate reductase, both of which catalyze the first two steps of L-proline synthesis from L-glutamate and which together may form a complex in vivo. When cultured in liquid minimal medium, yeast cells expressing the mutated gamma-glutamyl kinase were found to accumulate intracellular L-proline and showed a prominent increase in cell viability after freezing at -20 degrees C compared to the viability of cells harboring the wild-type PRO1 gene. These results suggest that the altered gamma-glutamyl kinase results in stabilization of the complex or has an indirect effect on gamma-glutamyl phosphate reductase activity, which leads to an increase in L-proline production in Saccharomyces cerevisiae. The approach described in this paper could be a practical method for breeding novel freeze-tolerant yeast strains." }, { "role": "assistant", "content": "[[\"amino acid\", \"PART-OF\", \"gamma-glutamyl kinase\"], [\"L-glutamate\", \"SUBSTRATE\", \"gamma-glutamyl phosphate reductase\"], [\"Asn\", \"PART-OF\", \"gamma-glutamyl kinase\"], [\"L-glutamate\", \"SUBSTRATE\", \"gamma-glutamyl kinase\"], [\"Asp\", \"PART-OF\", \"gamma-glutamyl kinase\"], [\"L-proline\", \"PRODUCT-OF\", \"gamma-glutamyl phosphate reductase\"], [\"L-proline\", \"PRODUCT-OF\", \"gamma-glutamyl kinase\"]]" } ]

[ { "role": "user", "content": "You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.\n\nMain Abstract:\nAssigning a label to each pixel in an image, namely semantic segmentation, has been an important task in computer vision, and has applications in autonomous driving, robotic navigation, localization, and scene understanding. Fully convolutional neural networks have proved to be a successful solution for the task over the years but most of the work being done focuses primarily on accuracy. In this paper, we present a computationally efficient approach to semantic segmentation, while achieving a high mean intersection over union (mIOU), (70.33 ) on Cityscapes challenge. The network proposed is capable of running real-time on mobile devices. In addition, we make our code and model weights publicly available.\n\nCited Abstract(s):\n[1]: Currently, the neural network architecture design is mostly guided by the indirect metric of computation complexity, i.e., FLOPs. However, the direct metric, e.g., speed, also depends on the other factors such as memory access cost and platform characterics. Thus, this work proposes to evaluate the direct metric on the target platform, beyond only considering FLOPs. Based on a series of controlled experiments, this work derives several practical guidelines for efficient network design. Accordingly, a new architecture is presented, called ShuffleNet V2. Comprehensive ablation experiments verify that our model is the state-of-the-art in terms of speed and accuracy tradeoff." }, { "role": "assistant", "content": "Another important issue is the metric of performance for convolutional neural networks. The efficiency of CNNs is commonly reported by the total number of floating point operations (FLOPs). It is pointed out in [1] that, despite their similar number of FLOPs, networks may have different inference speeds, emphasizing that this metric alone can be misleading and may lead to poor designs. They argue that discrepancy can be due to memory access cost (MAC), parallelism capability of the design and platform dependent optimizations on specific operations such as cuDNN’s @math Conv. Furthermore, they offer to use a direct metric (e.g., speed) instead of an indirect metric such as FLOPs." } ]

[ { "role": "user", "content": "You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: [\"Intervention\", \"Outcome\", \"Participant\"].\n\nPlease return the output as a JSON object of the format: {\"Participant\" : [\"patients with COPD\", ...], \"Intervention\" : [\"Atenolol\", ...], \"Outcome\" : [\"blood pressure\", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].\n\nOnly output the JSON object and do not include any additional text.\n\nAbstract:\n\nEffects of creatine supplementation on repetitive sprint performance and body composition in competitive swimmers . In a double-blind and randomized manner , 18 male and female junior competitive swimmers supplemented their diets with 21 g.day-1 of creatine monohydrate ( Cr ) or a maltodextrin placebo ( P ) for 9 days during training . Prior to and following supplementation , subjects performed three 100-m freestyle sprint swims ( long course ) with 60 s rest/recovery between heats . In addition , subjects performed three 20-s arm ergometer maximal-effort sprint tests in the prone position with 60 s rest/recovery between sprint tests . Significant differences were observed among swim times , with Cr subjects swimming significantly faster than P subjects following supplementation in Heat 1 and significantly decreasing swim time in the second 100-m sprint . There was also some evidence that cumulative time to perform the three 100-m swims was decreased in the Cr group . Results indicate that 9 days of Cr supplementation during swim training may provide some ergogenic value to competitive junior swimmers during repetitive sprint performance ." }, { "role": "assistant", "content": "{\"Intervention\": [\"creatine supplementation\", \"creatine monohydrate ( Cr )\", \"maltodextrin placebo ( P )\", \"Cr\"], \"Outcome\": [\"cumulative time to perform the three 100-m swims\", \"swim times\", \"swim time\"], \"Participant\": []}" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research paper, followed by a question about the paper. Please extract text from the paragraph to answer the question. Do not include any text in your repsonse other than the answer.\n\nParagraph: Similarly, for virally vectored antigens, the existence of pre-existing immunity to the vector (particularly neutralizing antibody) will restrict delivery of the virus into cells, thereby effectively reducing the dose of the vectored antigen. Again, this might be expected to result in a reduction in the antigenicity of the vectored antigen. \n\nIn the case of bacterial vectors, the effect of pre-existing immune responses has only been tested using Salmonella serovars and Listeria spp. Concern that prior immunological experience of the host with either the homologous Salmonella vector strain or a related strain might compromise its ability to deliver heterologous vaccine antigen was first raised in 1987 (Dougan et al., 1987) . Bao and Clements subsequently reported experimental evidence of the consequences of prior exposure of animals to the vector strain (Bao & Clements, 1991) . This work showed that both serum and mucosal antibody responses against the foreign antigen were in fact upregulated in animals with prior exposure to the vector strain. Whittle & Verma (1997) reported similar findings. Mice immunized via the intra-peritoneal route with a Salmonella dublin aroA mutant expressing heterologous antigen after being exposed to the same vector showed a higher immune response to the vectored antigen in comparison to mice without any immunological memory against the vector. Subsequently, several studies have been conducted to examine the effect of pre-existing immunity in the host against Salmonella. These results are summarized in Table 1 . The various reports are contradictory in their findings and seem to paint a rather confusing picture. Some studies concluded that pre-existing immunity against the Salmonella vector leads to stronger immune responses against the delivered antigen (Bao & Clements, 1991; Jespersgaard et al., 2001; Kohler et al., 2000a, b; Metzger et al., 2004; Saxena et al., 2009; Sevil Domènech et al., 2008; Whittle & Verma, 1997) , with others considering pre-existing immunity to be a limiting factor in the long-term use of Salmonella as an efficient vector for antigen delivery (Attridge et al., 1997; Gahan et al., 2008; Roberts et al., 1999; Sevil Domènech et al., 2007; Vindurampulle & Attridge, 2003a, b) . A slight majority of the studies listed in Table 1 (10 versus eight) indicate the upregulation of immune responses after animals have been exposed to either homologous or related strains before the delivery of heterologous antigen using a Salmonella vector. A study by Metzger and co-workers on human volunteers using Salmonella Typhi as a vector suggested that there was no change in the T cell immune response against the heterologous antigen in human volunteers who were exposed to empty vector in comparison with volunteers who were immunologically naive of the vector strain (Metzger et al., 2004) . In these subjects, humoral responses were moderately elevated in preexposed individuals. Similarly, Saxena et al. (2009) indicated higher humoral and T cell responses in mice pre-exposed to homologous or heterologous Salmonella strains. The interleukin 4 (IL4) response was significantly higher when the animal host was exposed to the homologous strain, whereas pre-exposure to a related species did not have such an impact on IL4 responses. Conversely interferon (IFN)-c responses were higher, irrespective of the strain to which mice were pre-exposed. This study also indicated that the presence of homologous or heterologous opsonizing antibodies leads to a higher uptake of Salmonella by macrophages in vitro, which may explain the higher immune responses in exposed mice. As may be expected, uptake was higher when homologous sera were used as the opsonin rather than heterologous sera. This is depicted in Fig. 2 . Conversely, there are reports that indicate that pre-existing immunity against the bacterial vector downregulates immune responses against the delivered heterologous antigen using similar or related vectors. Attridge and coworkers reported that the presence of immunity against the bacterial vector prior to the delivery of vectored antigenic \n\nMicrobiology 159 protein can downregulate immune responses in mice against the delivered antigen (Attridge et al., 1997) . Similar results were reported by Roberts et al. (1999) and Vindurampulle & Attridge (2003a, b) . However, the latter authors found that the hypo-responsiveness could be largely eliminated by exposing animals to the foreign antigen prior to vectorpriming (Vindurampulle & Attridge, 2003b) . Unfortunately, this would appear to be impractical for an immunization regimen! A study presented by Gahan et al. (2008) immunized mice with S. Typhimurium expressing C fragment of tetanus toxin antigen from an expression plasmid or as a DNA vaccine. Vaccinated mice developed humoral responses to LPS and tetC (for the plasmid-bearing vaccines). Animals from all groups (including a previously unvaccinated group) were immunized on day 182 with Salmonella expressing tetC. At this time, the anti-LPS and tetC titres were beginning to wane. Fourteen days after the second immunization, the colonization of various mouse organs was assessed. The ability to colonize was found to be significantly reduced in groups that had been previously vaccinated with Salmonella. In view of this finding, it was perhaps not surprising that at day 210 the LPS titres were not significantly different between groups receiving one or two vaccinations. More interestingly, mice that had been primed with Salmonella alone, and then boosted with Salmonella expressing tetC, induced much lower anti-tetC responses than mice that had not been primed. This argues strongly that prior immunological immunity to the vector can seriously dampen subsequent antigen-specific humoral responses. Whether the same is true for cellular responses was not evaluated. Other studies have evaluated cellular responses. A study by Sevil Domènech and colleagues reported that pre-existing anti-vector immunity seriously compromises CD8 + responses in mice when exposed to a similar strain used as vector (Sevil Domènech et al., 2007) . In contrast, another study by the same authors reported that animals exposed to related vectors induce much higher CD8 + responses when compared with animals which do not have any pre-existing Salmonella immunity (Sevil Domènech et al., 2008) . The difference between these two studies was that in the first, the prime and boost were with identical serovars, while in the second study, different serovars were used. This may point to a way of avoiding downregulation of CD8 responses by pre-existing immunity. This is important, as one of the advantages of using Salmonella (an intracellular pathogen) is that strong cellular immune responses can be induced. It must be noted that in the case of Salmonella vaccines, effects other than strictly immunological responses (particularly adaptive responses) should be considered. In the context of innate immunity, it was shown that administration of non-virulent Salmonella to gnobiotic pigs eliminated disease following challenge with a virulent strain (Foster et al., 2003) . Interestingly, protection was not by competitive exclusion, as the virulent strain was in high numbers in the gut but did not distribute systemically. The protection was proposed to be mediated by the infiltration of a large number of polymorphonuclear leukocytes into the gut, and although perhaps impractical as a general prophylactic (as the time between vaccination and infection is short), this may be an option for short-term or perhaps therapeutic vaccination (as reviewed by Foster et al., 2012) . Chickens (Gallus gallus) are a natural animal reservoir for Salmonella, which makes them an important source of Salmonella-associated gastroenteritis in humans. The ability to use oral Salmonella vaccines to immunize against heterologous pathogens would be of enormous benefit to Uptake of STM-1 by J774 macrophages, relative to the highest uptake percentage. X, Opsonized with naive sera; m, opsonized with serum from mice exposed to Salmonella enteriditis; &, opsonized with serum from mice exposed to STM-1. Pre-existing immunity against vaccine vectors the poultry industry in both broiler and layer flocks. Both vertical and horizontal transmission is associated with Salmonella in chickens (Liljebjelke et al., 2005) . Vertical transmission via in ovo transmission is particularly important, because if there is prior exposure to the vaccine strain, subsequent vaccination using an oral Salmonella vector could be severely compromised. A considerable number of studies on cross-protective immunity and competitive exclusion have been undertaken in chickens. Protective cross-reactive immunity against Salmonella strains has been demonstrated against both homologous and heterologous challenges (Beal et al., 2006) , although cross-serogroup protection was not strong. Furthermore, a recent study reported that pretreatment of newly hatched chickens with different Salmonella strains could produce a complete invasioninhibition effect on any subsequent exposure to both homologous and heterologous strains (Methner et al., 2010) . Pre-exposure with a highly invasive form of Salmonella Enteritidis caused a large influx of heterophils to the caecal mucosa in 1-day-old chicks, and subsequent heterologous caecal colonization was inhibited for a period of 48 h (Methner et al., 2010) . The implications of this kind of colonization-inhibition study on the immunological status of the affected chickens are yet to be fully elucidated. It should be noted that the studies listed in Tables 1 and 2 are controlled laboratory studies, with the possibility of a competitive exclusion component to immunity not discussed. Similarly studies of L. monocytogenes and the effects of preexisting immune responses indicate conflicting results. A study by Bouwer et al. (1999) indicates that pre-existing immune responses against the Listeria vector do not diminish immune responses against the delivered heterologous antigen, and a similar study by Starks et al. (2004) also concluded that prior exposure of mice to the empty Listeria vector did not influence anti-cancer immune responses when a similar mutant was used as a carrier of a melanoma cancer antigen. Similar findings were reported by Whitney et al. (2011) in rhesus macaques in which L. monocytyogens was used as a carrier of gag-HIV antigen. Conversely, studies by Stevens et al. (2005) in which L. monocytogens was used to deliver feline immunodeficiency virus (FIV) gag protein and as a carrier of DNA vaccines to vaccinate cats against FIV envelope protein indicated lower immune responses against the delivered antigen in cats exposed to empty Listeria vector in comparison with naive animals (Stevens et al., 2005) . Similar findings have been reported by Tvinnereim et al. (2002) and Leong et al. (2009) . However, taken together, these studies conclude that prior exposure of host animals to empty vector does not abrogate immune responses to the vectored antigen, but only reduces them somewhat. Only the study by Vijh et al. (1999) indicated that exposure to the empty vector may completely abrogate immune responses against the delivered antigens (Vijh et al., 1999) . However, these studies also indicate that downregulation of antigenspecific immune responses is highly dependent on dose and time. Leong et al. (2009) also demonstrated that the negative impact of vector-specific immune responses can also be countered by repeated immunization with the same vaccine and dose; this in effect leads to higher priming of naive T cells against the delivered antigen. Of course, such repeated vaccination may not be practicable in real-world situations. Despite the many advantages which viral vectoring can offer, pre-existing immunity is a major obstacle of many viralvectored vaccines, such as Ad serotype 5 or herpes simplex virus type 1 (HSV-1), where the rate of seroprevalence to these viruses is very high [40-45 % and 70 % (or more) of the US population, respectively] (Hocknell et al., 2002; Pichla-Gollon et al., 2009) . Vector-specific antibodies may impede the induction of immune responses to the vaccine-encoded antigens, as they may reduce the dose and time of exposure of the target cells to the vaccinated antigens (Pichla-Gollon et al., 2009; Pine et al., 2011) . In a large-scale clinical trial (STEP) of an Ad serotype 5 (AdHu5)-based HIV-1 vaccine, the vaccines showed a lack of efficacy and tended to increase the risk of HIV-1 infection in vaccine recipients who had pre-existing neutralizing antibodies to AdHu5 (Buchbinder et al., 2008) . For an HSV-1-based vector vaccine, it has been demonstrated that pre-existing anti-HSV-1 immunity reduced, but did not abolish, humoral and cellular immune responses against the vaccine-encoded antigen (Hocknell et al., 2002; Lauterbach et al., 2005) . However, Brockman and Knipe found that the induction of durable antibody responses and cellular proliferative responses to HSVencoded antigen were not affected by prior HSV immunity (Brockman & Knipe, 2002) . Similarly, pre-existing immunity to poliovirus has little effect on vaccine efficacy in a poliovirus-vectored vaccine (Mandl et al., 2001) . Different effects of pre-existing immunity on the efficacy of recombinant viral vaccine vectors are summarized in Table 2 . There are several approaches to avoiding pre-existing vector immunity, such as the use of vectors derived from nonhuman sources, using human viruses of rare serotypes (Kahl et al., 2010; Lasaro & Ertl, 2009) , heterologous prime-boost approaches (Liu et al., 2008) , homologous reimmunization (Steffensen et al., 2012) and removing key neutralizing epitopes on the surface of viral capsid proteins (Gabitzsch & Jones, 2011; Roberts et al., 2006) . The inhibitory effect of pre-existing immunity can also be avoided by masking the Ad vector inside dendritic cells (DCs) (Steffensen et al., 2012) . In addition, mucosal vaccination or administration of higher vaccine doses can overcome pre-existing immunity problems (Alexander et al., 2012; Belyakov et al., 1999; Priddy et al., 2008; Xiang et al., 2003) . As we search for new vaccine approaches for the array of pathogens for which none is yet available, revisiting proven vaccines and developing these further has gained M. Saxena and others momentum.\n\nQuestion: What is the effect of host immune response to the delivery vector on the efficacy of vaccination?" }, { "role": "assistant", "content": "for virally vectored antigens, the existence of pre-existing immunity to the vector (particularly neutralizing antibody) will restrict delivery of the virus into cells, thereby effectively reducing the dose of the vectored antigen. Again, this might be expected to result in a reduction in the antigenicity of the vectored antigen." } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:\n\n- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.\n- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.\n- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.\n\nPlease format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.\n\nAs an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:\n\n[[\"artesunate\", \"artemether\", \"COMB\"], [\"Nifedipine\", \"Labetalol\", \"Prazosin\", \"POS\"]]\n\nThe paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.\n\nIn your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.\n\nparagraph: Combination chemotherapy with cyclophosphamide, vincristine, adriamycin, and dexamethasone (CVAD) plus oral quinine and verapamil in patients with advanced breast cancer. We evaluated the question of whether the chemosensitizers verapamil and quinine given orally to breast cancer patients failing combination chemotherapy alone would result in additional clinical responses. In vitro studies reported here showed verapamil sensitization of Adriamycin resistance in 18.8% of fresh human breast cancer specimens tested. Patients (27) were first treated with cyclophosphamide, vincristine, Adriamycin and dexamethasone (CVAD) alone. Verapamil and quinine were added in patients with tumors failing to respond or progressing on CVAD alone . Following treatment with CVAD alone there were no complete remissions and 3 patients (11%) developed partial remissions lasting 5.5, 8, 10.5 months. With the addition of verapamil and quinine to the CVAD regimen, one patient (4%) developed a complete remission of 11.8 months duration and 4 additional patients (15%) developed partial remissions lasting 2.8, 17.3, 19 and > 40 months. Thus, the overall rate of CVAD sensitization by verapamil and quinine was 19%. Treatment with CVAD plus verapamil and quinine was generally well tolerated with observed toxicities including: myelosuppression, neuropathy, Cushingoid symptoms and tinnitus and/or dizziness due to quinine. We conclude that addition of the non-cytotoxic chemosensitizers verapamil and quinine to CVAD in patients failing CVAD alone results in additional clinical responses in a small percentage of patients, some with long term durations. The results of this study lend credence to the notion that non-cytotoxic chemosensitizers can enhance the clinical activity of combination chemotherapy and the search for more effective and less toxic chemosensitizers continues.\n\nsentence: Verapamil and quinine were added in patients with tumors failing to respond or progressing on CVAD alone ." }, { "role": "assistant", "content": "[[\"Verapamil\", \"quinine\", \"POS\"]]" } ]

[ { "role": "user", "content": "You will be shown inclusion or exclusion criteria for a clinical trial. Given these criteria, your task is to extract all unique entities of the following types: [\"Multiplier\", \"Drug\", \"Mood\", \"Temporal\", \"Value\", \"Measurement\", \"Qualifier\", \"Device\", \"Observation\", \"Visit\", \"ReferencePoint\", \"Procedure\", \"Condition\", \"Negation\", \"Person\", \"Scope\"].\n\nPlease return the output as a JSON object of the format: {\"Condition\" : [\"breast cancer\", ...], \"Device\" : [\"ports\", ...], \"Drug\" : [\"Atenolol\", ...], \"Measurement\" : [\"blood pressure\", ...], \"Mood\" : [\"suspected\", ...], \"Multiplier\" : [\"more than two\", ...], \"Negation\" : [\"no\", ...], \"Observation\" : [\"history\", ...], \"Person\" : [\"male\", ...], \"Procedure\" : [\"surgery\", ...], \"Qualifier\" : [\"severe\", ...], \"ReferencePoint\" : [\"enrollment\", ...], \"Scope\" : [\"infection\", ...], \"Temporal\" : [\"one day\", ...], \"Value\" : [\"50%\", ...], \"Visit\" : [\"ICU\", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].\n\nOnly output the JSON object and do not include any additional text.\n\nAbstract:\n\nrecurrent contracture in the finger to be treated\nneurologic condition causing the loss of function of the finger to be treated\ncontraindication for collagenase clostridium histolyticym (Xiapex/Xiaflex ®)\npregnant or breast feeding\nTPED > 135° (Tubiana stage 4) in finger to be treated\nrheumatoid arthritis\nprevious fracture in finger to be treated, which affects range of motion of MP or PIP joint\nage > 80 years" }, { "role": "assistant", "content": "{\"Condition\": [\"loss of function\", \"rheumatoid arthritis\", \"neurologic condition\", \"affects range of motion\", \"pregnant\", \"fracture\", \"contraindication\", \"contracture\"], \"Device\": [], \"Drug\": [\"Xiaflex\", \"collagenase clostridium histolyticym\", \"Xiapex\"], \"Measurement\": [\"TPED\", \"Tubiana\"], \"Mood\": [], \"Multiplier\": [], \"Negation\": [], \"Observation\": [\"breast feeding\"], \"Person\": [\"age\"], \"Procedure\": [], \"Qualifier\": [\"PIP joint\", \"recurrent\", \"finger to be treated\", \"PI age \\u003e\"], \"ReferencePoint\": [], \"Scope\": [\"Tubiana stage 4\", \"MP or PIP joint\", \"Xiapex/Xiaflex\", \"TPED \\u003e 135\\u00b0\"], \"Temporal\": [\"previous\"], \"Value\": [\"stage 4\", \"\\u003e 135\\u00b0\", \"\\u003e 80 years\"], \"Visit\": []}" } ]

[ { "role": "user", "content": "You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.\nYour response should be formatted as a `json` array. For instance, for the query \"Semi supervised image classification\", a sample response might be: [\"CIFAR-10\", \"CIFAR-100\"]. Do not include any extra text in the response other than the answer array.\n\nQuery: I want to train a zero-shot recognition model.\n\nKeyphrases: zero-shot recognition images\n\nDataset description:\nTasty Videos: A collection of 2511 recipes for zero-shot learning, recognition and anticipation.\nImageNet: The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.\nQuickDraw-Extended: Consists of 330,000 sketches and 204,000 photos spanning across 110 categories.\nSNIPS: The SNIPS Natural Language Understanding benchmark is a dataset of over 16,000 crowdsourced queries distributed among 7 user intents of various complexity: SearchCreativeWork (e.g. Find me the I, Robot television show), GetWeather (e.g.\nActivityNet: The ActivityNet dataset contains 200 different types of activities and a total of 849 hours of videos collected from YouTube. ActivityNet is the largest benchmark for temporal activity detection to date in terms of both the number of activity categories and number of videos, making the task particularly challenging.\n\nOptions:- A: Tasty Videos B: ImageNet C: QuickDraw-Extended D: SNIPS E: ActivityNet" }, { "role": "assistant", "content": "[\"ImageNet\", \"ActivityNet\"]" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nThe double burden of malnutrition is the coexistence of two different conditions, mainly reflected as excess or deficit in weight. Anemia is a specific nutritional deficit not always included in the double burden assessment. We reviewed overweight and/or obesity (OW/OB) and anemia studies from Latin-American Children over the last ten years up to 2019. Two authors evaluated the MEDLINE, SCOPUS, and LILACS databases. A scale of ten questions was used to assess the risk of bias in prevalence studies. Fourteen studies were selected. The population studies' size ranged from 147 to 20,342 children with different socio-economic backgrounds, such as urban, peri-urban and rural settings, socio-economic status, schooling, population (ethnic minorities and indigenous), and environmental differences (sea level or high altitude). The prevalence of OW/OB ranged from 4.9% to 42%. The prevalence of anemia was from 3.4% to 67%. The double burden, including OW/OB and anemia, ranged from 0.7% to 67%. A higher prevalence of excess weight and anemia was found in rural and high altitude above sea level environments, extreme poverty, low education level, and indigenous communities. These heterogeneous data, before the 2020 (COVID-19 pandemic), reflect the vast inequities between countries and within each country. Food insecurity linked to poverty and the induced change in eating habits and lifestyles threaten optimal child nutrition in ongoing and future scenarios. The existence of OW/OB and anemia and their simultaneous coexistence in the community, home, and individual levels, indicates that interventions should be comprehensive to face the double burden of malnutrition." }, { "role": "assistant", "content": "[\"Prevention\"]" } ]

[ { "role": "user", "content": "You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.\nYour response should be formatted as a `json` array. For instance, for the query \"Semi supervised image classification\", a sample response might be: [\"CIFAR-10\", \"CIFAR-100\"]. Do not include any extra text in the response other than the answer array.\n\nQuery: Emotionally-aware chatbot development.\n\nKeyphrases: emotionally-aware chatbot text\n\nDataset description:\narXiv Summarization Dataset: This is a dataset for evaluating summarisation methods for research papers.\nSEMAINE: The SEMAINE videos dataset contains spontaneous data capturing the audiovisual interaction between a human and an operator undertaking the role of an avatar with four personalities: Poppy (happy), Obadiah (gloomy), Spike (angry) and Prudence (pragmatic). The audiovisual sequences have been recorded at a video rate of 25 fps (352 x 288 pixels).\nCTC: A dataset that allows exploration of cross-modal retrieval where images contain scene-text instances.\nDailyDialog: DailyDialog is a high-quality multi-turn open-domain English dialog dataset. It contains 13,118 dialogues split into a training set with 11,118 dialogues and validation and test sets with 1000 dialogues each.\nTour20: Contains 140 videos with multiple human created summaries, which were acquired in a controlled experiment.\n\nOptions:- A: arXiv Summarization Dataset B: SEMAINE C: CTC D: DailyDialog E: Tour20" }, { "role": "assistant", "content": "[\"SEMAINE\", \"DailyDialog\"]" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: And there is no clear guideline for how to social distance that can reduce the risk of contracting COVID-19.\n\nAbstract:\nCoronavirus Disease 2019 (COVID-19) is a pandemic affecting many countries worldwide.\nGiven the increasing incidence especially in elderly and individuals with comorbid conditions, it is advised by health authorities to stay home if possible, maintain social distancing and stay away from those who are sick or could be infected.\nPatients with comorbidities especially cardiovascular disease are at higher risk of getting infected with COVID-19 and have worse prognosis.\nAmong efforts to safely manage warfarin patients during this pandemic, we introduced a hospital drive-up anticoagulation testing service.\nThis service can reduce the risk of exposure of anticoagulation patients to COVID-19 by reducing the contact time with the different personnel at the hospital and by maintaining those patients at a safe distance from others." }, { "role": "assistant", "content": "{\"verdict\": \"CONTRADICT\", \"evidence\": [\"Given the increasing incidence especially in elderly and individuals with comorbid conditions, it is advised by health authorities to stay home if possible, maintain social distancing and stay away from those who are sick or could be infected.\"]}" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: COVID-19 spreads mainly among people who are in close contact (within about 6 feet) for a prolonged period.\n\nAbstract:\nBACKGROUND: The Australian and New Zealand governments both initiated strict social distancing measures in response to the COVID-19 pandemic in late March.\nIt remains difficult to quantify the impact this had in reducing the spread of the virus.\nMETHODS: Bayesian structural time series model provide a model to quantify the scenario in which these government-level interventions were not placed.\nOur models predict these strict social distancing measures caused a 79% and 61% reduction in the daily cases of COVID-19 across Australia and New Zealand respectively.\nCONCLUSION: This provides both evidence and impetus for governments considering similar measures in response to COVID-19 and other pandemics." }, { "role": "assistant", "content": "{\"verdict\": \"SUPPORT\", \"evidence\": [\"Our models predict these strict social distancing measures caused a 79% and 61% reduction in the daily cases of COVID-19 across Australia and New Zealand respectively.\"]}" } ]

[ { "role": "user", "content": "Given an abstract from a research paper, your task is to identify and label relationships between chemical compounds and genes mentioned in the abstract.\n\nThe relationship type must be one of ['DOWNREGULATOR', 'SUBSTRATE', 'INDIRECT-REGULATOR', 'PART-OF', 'MODULATOR-ACTIVATOR', 'REGULATOR', 'INHIBITOR', 'COFACTOR', 'UPREGULATOR', 'ACTIVATOR', 'ANTAGONIST', 'NOT', 'INDIRECT-DOWNREGULATOR', 'SUBSTRATE_PRODUCT-OF', 'INDIRECT-UPREGULATOR', 'AGONIST', 'PRODUCT-OF', 'MODULATOR', 'DIRECT-REGULATOR', 'UNDEFINED', 'AGONIST-INHIBITOR', 'AGONIST-ACTIVATOR', 'MODULATOR-INHIBITOR'].\n\nPlease format your output as a JSON array. Each entry in the array should express a single relation, formatted as [\"<Entity_A>\", \"<RELATION_A_B>\", \"<Entity_B>\"]. If no relations can be found, please output an empty JSON array [].\n\nAbstract:\n\nThe effects of mitiglinide (KAD-1229), a new anti-diabetic drug, on ATP-sensitive K+ channels and insulin secretion: comparison with the sulfonylureas and nateglinide. Mitiglinide (KAD-1229), a new anti-diabetic drug, is thought to stimulate insulin secretion by closing the ATP-sensitive K+ (K (ATP)) channels in pancreatic beta-cells. However, its selectivity for the various K (ATP) channels is not known. In this study, we examined the effects of mitiglinide on various cloned K (ATP) channels (Kir6.2/SUR1, Kir6.2/SUR2A, and Kir6.2/SUR2B) reconstituted in COS-1 cells, and compared them to another meglitinide-related compound, nateglinide. Patch-clamp analysis using inside-out recording configuration showed that mitiglinide inhibits the Kir6.2/SUR1 channel currents in a dose-dependent manner (IC50 value, 100 nM) but does not significantly inhibit either Kir6.2/SUR2A or Kir6.2/SUR2B channel currents even at high doses (more than 10 microM). Nateglinide inhibits Kir6.2/SUR1 and Kir6.2/SUR2B channels at 100 nM, and inhibits Kir6.2/SUR2A channels at high concentrations (1 microM). Binding experiments on mitiglinide, nateglinide, and repaglinide to SUR1 expressed in COS-1 cells revealed that they inhibit the binding of [3H]glibenclamide to SUR1 (IC50 values: mitiglinide, 280 nM; nateglinide, 8 microM; repaglinide, 1.6 microM), suggesting that they all share a glibenclamide binding site. The insulin responses to glucose, mitiglinide, tolbutamide, and glibenclamide in MIN6 cells after chronic mitiglinide, nateglinide, or repaglinide treatment were comparable to those after chronic tolbutamide and glibenclamide treatment. These results indicate that, similar to the sulfonylureas, mitiglinide is highly specific to the Kir6.2/SUR1 complex, i.e., the pancreatic beta-cell K (ATP) channel, and suggest that mitiglinide may be a clinically useful anti-diabetic drug." }, { "role": "assistant", "content": "[[\"glibenclamide\", \"INDIRECT-REGULATOR\", \"insulin\"], [\"Mitiglinide\", \"INHIBITOR\", \"ATP-sensitive K+ (K (ATP)) channels\"], [\"repaglinide\", \"INDIRECT-REGULATOR\", \"insulin\"], [\"glucose\", \"INDIRECT-REGULATOR\", \"insulin\"], [\"KAD-1229\", \"INHIBITOR\", \"ATP-sensitive K+ (K (ATP)) channels\"], [\"mitiglinide\", \"DIRECT-REGULATOR\", \"SUR1\"], [\"KAD-1229\", \"REGULATOR\", \"insulin\"], [\"tolbutamide\", \"INDIRECT-REGULATOR\", \"insulin\"], [\"mitiglinide\", \"REGULATOR\", \"insulin\"], [\"Mitiglinide\", \"INDIRECT-UPREGULATOR\", \"insulin\"], [\"sulfonylureas\", \"REGULATOR\", \"K (ATP) channel\"], [\"[3H]glibenclamide\", \"DIRECT-REGULATOR\", \"SUR1\"], [\"KAD-1229\", \"REGULATOR\", \"ATP-sensitive K+ channels\"], [\"mitiglinide\", \"REGULATOR\", \"ATP-sensitive K+ channels\"], [\"mitiglinide\", \"REGULATOR\", \"K (ATP) channel\"], [\"repaglinide\", \"DIRECT-REGULATOR\", \"SUR1\"], [\"mitiglinide\", \"AGONIST\", \"K (ATP) channel\"], [\"glibenclamide\", \"DIRECT-REGULATOR\", \"SUR1\"], [\"nateglinide\", \"DIRECT-REGULATOR\", \"SUR1\"], [\"mitiglinide\", \"INDIRECT-REGULATOR\", \"insulin\"], [\"KAD-1229\", \"INDIRECT-UPREGULATOR\", \"insulin\"], [\"nateglinide\", \"INDIRECT-REGULATOR\", \"insulin\"]]" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research paper, followed by a question about the paper. Please extract text from the paragraph to answer the question. Do not include any text in your repsonse other than the answer.\n\nParagraph: The OW Lassa virus (LASV) , causative agent of Lassa fever (LF), is the most significant OW mammarenaviral pathogen. LASV is estimated to infect several hundred thousand individuals annually in Western Africa, resulting in a high number of LF cases associated with high morbidity and lethality. Moreover, LASV endemic regions are expanding [7] , and the association of the recently identified mammarenavirus Lujo virus with a VHF outbreak in Southern Africa [8, 9] has raised concerns about the emergence of novel VHF-causing mammarenaviruses. The most significant NW mammarenavirus is Junín virus (JUNV), which causes Argentinian hemorrhagic fever [10] . The worldwide-distributed OW mammarenavirus lymphocytic choriomeningitis virus (LCMV) is a neglected human pathogen of clinical significance especially in congenital infections [11] [12] [13] [14] [15] . Moreover, LCMV poses a particular threat to immunocompromised individuals, as has been illustrated by fatal cases of LCMV infection associated with organ transplants [16, 17] . However, LCMV research can be safely performed at BSL-2 containment, rather than the BSL-4 containment necessary for live LASV or JUNV research [18] . No US Food and Drug Administration (FDA)-licensed vaccines are available for the treatment of arenavirus infections, although a live attenuated vaccine strain of JUNV, Candid#1, is licensed in Argentina. Likewise, current anti-mammarenavirus therapy is limited to an offlabel use of the nucleoside analogue ribavirin that is only partially effective and can cause significant side effects [19] [20] [21] . Development of effective anti-mammarenavirus drugs has been hampered by the lack of detailed understanding of virus/host-cell interactions required for mammarenavirus multiplication that could represent amenable targets for antiviral therapy. the potential problem that overexpression of a single viral gene product may potentiate PPI interactions that are not relevant during the course of a natural virus infection. To overcome this issue, we designed a recombinant LCMV (rLCMV) encoding a tandem [WSHPQFEK (GGGS) 3 WSHPQFEK] Strep-tag fused to the amino-terminus of NP (rLCMV/Strep-NP) (Fig 1A and 1B) . To facilitate the identification of specific PPI between NP and host cell proteins, we used our mammarenavirus tri-segmented (r3) platform [30] to design an r3LCMV expressing a C-terminus Strep-tag version of enhanced green fluorescent protein (r3LCMV/eGFP-Strep) that we used as a negative control (Fig 1A and 1B) . We rescued rLCMV/Strep-NP and r3LCMV/eGFP-Strep and confirmed the expression of strep-tagged NP and eGFP in rLCMV/ Strep-NP-and r3LCMV/eGFP-Strep-infected cells, respectively (Fig 1C) . Next, we examined the growth properties of rLCMV/Strep-NP and r3LCMV/eGFP-Strep in three different cells lines from hamsters, humans, and nonhuman primates (BHK-21, A549, and Vero E6 cells, respectively) (Fig 1D) . The fitness of rLCMV/Strep-NP and r3LCMV/eGFP-Strep was modestly decreased compared to that observed with wild-type (WT) Armstrong (rLCMV ARM) and Clone 13 (rLCMV Cl-13) strains of LCMV. However, both rLCMV/Strep-NP and r3LCMV/eGFP-Strep had WT-like growth kinetics and reached high titers. As with WT LCMV, infection with rLCMV/Strep-NP prevented production of bioactive IFN-I by cells in response to Sendai virus (SeV) infection as determined using an IFN bioassay based on protection against the cytopathic effect (CPE) induced by infection with vesicular stomatitis virus (VSV) (Fig 1E) . Vero cells treated for 16 h with tissue cultured supernatants (TCS) from A549 cells infected first with WT LCMV or rLCMV/Strep, followed by 24 h infection with SeV, remained fully susceptible to VSV-induced CPE. In contrast, Vero cells treated with TCS from A549 cells infected with rLCMV/NP(D382A), a mutant unable to prevent induction of IFN-I [30] , and subsequently with SeV, were protected against VSV induced CPE. We selected the human A549 cell line because lung epithelial cells are one of the initial cell targets of humans following inhalation of mammarenavirions. We infected A549 cells (multiplicity of infection [MOI] = 0.1) with either rLCMV/Strep-NP or r3LCMV/eGFP-Strep (Fig 2A) . At 48 h post-inoculation (pi), we prepared total cell lysates for pull-down (PD) assays using a sepharose resin coated with strep-tactin. Aliquots of the protein complexes present in the PD samples were fractionated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) (Fig 2B) followed by SYPRO Ruby protein gel staining. We compared the pattern of stained protein bands detected between rLCMV/Strep-NP-and r3LCMV/eGFP-Strepinfected samples and confirmed the presence of Strep-NP and eGFP-Strep in pertinent samples (Fig 2B) . Protein complexes in the rest of eluates from the PD samples were concentrated by trichloroacetic acid (TCA) precipitation and subjected to trypsin digestion (Fig 2A) . Digested peptides were subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis using a hybrid mass spectrometer consisting of linear quadrupole ion dual cell trap (LTQ) Velos and an Orbitrap analyser. We classified host-cell proteins identified by LC-MS/MS analysis from two independent biological replicates into two groups: 1) proteins found only in Strep-NP PD samples with at least five spectral counts ( Table 1) , and 2) proteins found in both Strep-NP and eGFP-Strep PD samples with five or higher spectral counts in Strep-NP samples and at least 2-fold higher spectral counts in Strep-NP PD compared to eGFP PD samples ( Table 2) . Filtering the data using these criteria resulted in identification of 139 candidate host-cell proteins as NP-interacting partners. Among 53 proteins found present in both NP-and eGFP-PD samples, 36 had spectral counts in the NP-PD sample that were less than two-fold higher than their corresponding spectral counts in the eGFP-PD sample (Fig 2C and S1 Table) . Based on the criteria we described above, we considered these proteins to be highly unlikely specific NPinteractors with an involvement in the LCMV life cycle, and therefore we did not consider these hits for further analysis. However, we acknowledge that we cannot formally rule out that some of these hits could still play a role on the life cycle of LCMV. The protein annotation through evolutionary relationship (PANTHER) protein family classification (Biological Process) of the NP-interacting protein candidates revealed that a large number of proteins were involved in metabolic and cellular processes (Fig 2D) . We also analyzed the molecular functions of the NP-interacting protein candidates according to the PAN-THER protein profile classification (Fig 2E) , which revealed diversified biochemical functions enriched for nucleic acid-binding proteins and chaperones. To initially assess pro-or anti-viral roles of NP-interacting host-cell proteins identified by LC-MS/MS, we examined the effect of small interfering RNA (siRNA)-mediated knockdown (kd) of each of the corresponding genes on multiplication of rLCMV expressing reporter gene ZsGreen (ZsG) in A549 cells (Fig 3A) . The siRNAs we used were from the genome-wide ON TARGET-Plus (OTP) Human siRNA library (18,301 genes, 4 siRNAs/gene). OTPs are latest generation of siRNAs and offer significant advantages over previous generations. Off-target effects are primarily driven by antisense strand microRNA (miR)-like seed activity. In OTPs, the sense strand is modified to favor antisense strand uptake whereas the antisense strand seed region is modified to drastically reduce seed-related off-targeting [33] . In addition, OTPs are designed on the foundation of the SMARTselection algorithm (Dharmacon), widely considered to be the best algorithm for rational siRNA design strategy. Numerous host-cell factors showed an anti-LCMV effect (increased ZsG expression by kd of the genes), including microtubule-associated protein 1B (MAP1B) [ [38] , dengue virus 2 (DENV-2) [39] , and chikungunya virus (CHIKV) [40] . To begin assessing the potential biological implications of the identified NP-host cell protein interactions, we selected ATP1A1 and PHB given the availability of reagents, existing knowledge about their roles in cell physiology, and evidence of participation in multiplication of other viruses. We confirmed that cells transfected with siRNA specific to ATP1A1 and PHB exhibited the predicted reduced levels in ATP1A1 and PHB protein expression (Fig 3B) . Likewise, we examined whether siRNA-mediated reduced expression levels of ZsGreen correlated with reduced LCMV progeny titers. For this, we transfected A549 cells with siRNA targeting Expression of Strep-tagged proteins. A549 cells seeded (5.0 x 10 5 cells/well) in a 6-well plate and cultured overnight were infected (MOI = 0.1) with the indicated rLCMVs. At 48 h pi, total cell lysates were prepared, and protein expression was analyzed by western blotting. (D) Growth properties of rLCMV expressing Strep-tagged proteins. BHK-21 (1.75 x 10 5 cells/well), A549 (1.25 x 10 5 cells/well), or Vero E6 (1.25 x 10 5 cells/well) cells seeded in 24-well plates and cultured overnight were infected (MOI = 0.01) with the indicated rLCMVs. At the indicated times pi, TCSs were collected and virus titers determined by IFFA. Results represent means ± SD of the results of three independent experiments. (E) Lack of induction of IFN-I in cells infected with rLCMV/Strep-NP. A549 cells were infected (MOI = 0.1) with the indicated rLCMV or mock-infected, and 36 h later infected with SeV (MOI = 1). At 24 h pi with SeV, TCS were collected and used, following virus inactivation by U.V., to treat Vero E6 cells for 16 h, followed by infection with rVSV (MOI = 0.1) [rVSV(+)] or mockinfection [rVSV (-) ]. At 24 h pi with rVSV, cells were fixed with 4% PFA and stained with crystal violet to assess rVSV-induced cytopathic effect. We used as control rLCMV/NP(D382A) that contains mutation D382A within NP, which has been shown to abrogate the NP's ability to counteract the induction of IFN-I production. https://doi.org/10.1371/journal.ppat.1006892.g001 ATP1A1 or with NC siRNA 72 h prior to infection with rLCMV/ZsG. We found that siRNAmediated kd of ATP1A1 dramatically inhibited ZsGreen expression (Fig 3Ci) , which was associated with a significant reduction of infectious LCMV progeny (Fig 3Cii) . Our attempts to see interaction between NP and ATP1A1 or NP and PHB by co-immunoprecipitation were unsuccessful. Several possibilities could account for this, including interactions of low affinity or high on/off rate or both. Another consideration is that only a minor fraction of NP might be engaged in the interaction with a given host cell protein, and therefore, detection of these interactions would require highly sensitive methods such as LC-MS/MS. To overcome this problem we used confocal microscopy to examine the co-localization of NP with ATP1A1 and PHB in LCMV-infected cells. Weighted co-localization coefficients (CC), determined by taking into consideration the brightness of each channel signal, were significantly higher than non-weighted CC, indicating the presence of brighter pixels in the co-localized regions compared to the non-co-localized regions (Fig 4) . The cardiac glycoside ouabain is an inhibitor of ATP1A1 that has been used to treat congestive heart failure in European countries [41] . The PHB inhibitor rocaglamide is a flavagline from an Aglaia tree used in traditional Chinese medicine [42] that has potent anticancer activity [43] . To examine whether pharmacological inhibition of ATP1A1 or PHB inhibited LCMV multiplication, we pretreated human (A549 and HEK 293T), nonhuman primate (Vero E6), and rodent (murine L929 and hamster BHK-21) cells with ouabain or rocaglamide and infected them with rLCMV/eGFP (S1 Fig). Ouabain treatment resulted in a strong dosedependent inhibition of eGFP expression in infected human-and nonhuman primate cells, but did not affect eGFP expression intensity in infected rodent cells (S1A Fig) . This finding is consistent with rodents expressing an ATP1A1 allele that is resistant to ouabain inhibition [44] . Likewise, we observed a dose-dependent rocaglamide inhibition of eGFP expression in all cell lines infected with rLCMV/eGFP (S1B Fig) . Consistent with these findings, production of infectious LCMV progeny was reduced by treatment with either ouabain or rocaglamide ( Fig 5A) within a concentration range that had minimal impact on cell viability (Fig 5B) . To examine the correlation between efficacy and cytotoxicity of these compounds, we determined their therapeutic index (TI = CC 50 /IC 50 (Fig 5Bi) ; whereas rocaglamide had TIs of >105 (CC 50 > 1000 nM, IC 50 = 9.51 nM) and 10.3 (CC 50 = 100 nM, IC 50 = 9.75 nM) in A549 and Vero E6 cells, respectively (Fig 5Bii) .\n\nQuestion: What is the cause of Lassa fever?" }, { "role": "assistant", "content": "OW Lassa virus (LASV)" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: Are Advil and Motrin bad for a coronavirus fever or headache? The short answer is YES.\n\nAbstract:\nOBJECTIVE: It was recently suggested that ibuprofen might increase the risk for severe and fatal coronavirus disease 2019 (COVID-19) and should therefore be avoided in this patient population.\nWe aimed to evaluate whether ibuprofen use in individuals with COVID-19 was associated with more severe disease, compared with individuals using paracetamol or no antipyretics.\nMETHODS: In a retrospective cohort study of patients with COVID-19 from Shamir Medical Centre, Israel, we monitored any use of ibuprofen from a week before diagnosis of COVID-19 throughout the disease.\nPrimary outcomes were mortality and the need for respiratory support, including oxygen administration and mechanical ventilation.\nRESULTS: The study included 403 confirmed cases of COVID-19, with a median age of 45 years.\nOf the entire cohort, 44 patients (11%) needed respiratory support and 12 (3%) died.\nOne hundred and seventy-nine (44%) patients had fever, with 32% using paracetamol and 22% using ibuprofen, for symptom-relief.\nIn the ibuprofen group, 3 (3.4%) patients died, whereas in the non-ibuprofen group, 9 (2.8%) patients died (p 0.95).\nNine (10.3%) patients from the ibuprofen group needed respiratory support, compared with 35 (11%) from the non-ibuprofen group (p 1).\nWhen compared with exclusive paracetamol users, no differences were observed in mortality rates or the need for respiratory support among patients using ibuprofen.\nCONCLUSIONS: In this cohort of COVID-19 patients, ibuprofen use was not associated with worse clinical outcomes, compared with paracetamol or no antipyretic." }, { "role": "assistant", "content": "{\"verdict\": \"CONTRADICT\", \"evidence\": [\"When compared with exclusive paracetamol users, no differences were observed in mortality rates or the need for respiratory support among patients using ibuprofen.\", \"CONCLUSIONS: In this cohort of COVID-19 patients, ibuprofen use was not associated with worse clinical outcomes, compared with paracetamol or no antipyretic.\"]}" } ]

[ { "role": "user", "content": "You will be shown a question, followed by excerpts from biomedical research papers. Please answer the question based on the provided context. Do not include any text in your response other than the answer.\n\nQuestion: What is the relationship of fyn kinase and tau?\n\nContext: Fyn is an attractive target for AD therapeutics, not only based on its activation by Aβ via cellular prion protein but also due to its known interaction with tau, uniquely linking the two key pathologies in AD.\nThis PrPC-Aβo complex activates Fyn kinase which, in turn, hyperphosphorylates tau (P-Tau) resulting in synaptic dysfunction, neuronal loss and cognitive deficits." }, { "role": "assistant", "content": "The Fyn kinase interacts with tau. The activated Fyn kinase hyperphosphorylates the tau protein." } ]

[ { "role": "user", "content": "You will be presented with a citation segment from the section of a research paper. Classify the intent behind this citation by choosing from one of the following categories:\n\n- Method: Cites the paper for its methodology or procedure.\n- Background: Cites the paper to provide background information.\n- Result: Cites the paper for its findings or results.\n\nYour answer should be a single word from the following list of options: [\"Method\", \"Background\", \"Result\"]. Do not include any other text in your response.\n\nCitation sentence:\n\nBased on recent knowledge, cells may not opt for the germline mutation in an attempt to counteract haploinsufficiency, which, as shown for BRCA1, results in genomic instability and premature senescence in human breast epithelial cells [29]." }, { "role": "assistant", "content": "Background" } ]

[ { "role": "user", "content": "Given a short query with keyphrases about a research idea in 2020 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.\n\nQuery: A method for neural architecture search that searches over multiple paths.\n\nKeyphrases: neural architecture search images\n\nDataset description:\nImageNet: The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.\nFreiburg Groceries: Freiburg Groceries is a groceries classification dataset consisting of 5000 images of size 256x256, divided into 25 categories. It has imbalanced class sizes ranging from 97 to 370 images per class.\nNATS-Bench: A unified benchmark on searching for both topology and size, for (almost) any up-to-date NAS algorithm. NATS-Bench includes the search space of 15,625 neural cell candidates for architecture topology and 32,768 for architecture size on three datasets.\nComplexWebQuestions: ComplexWebQuestions is a dataset for answering complex questions that require reasoning over multiple web snippets. It contains a large set of complex questions in natural language, and can be used in multiple ways: By interacting with a search engine; As a reading comprehension task: the authors release 12,725,989 web snippets that are relevant for the questions, and were collected during the development of their model; As a semantic parsing task: each question is paired with a SPARQL query that can be executed against Freebase to retrieve the answer.\n\nOptions:- A: ImageNet B: Freiburg Groceries C: NATS-Bench D: ComplexWebQuestions" }, { "role": "assistant", "content": "ImageNet" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nAn outbreak of coronavirus disease 2019 (COVID-19) caused by the 2019 novel coronavirus (SARS-CoV-2) began in the city of Wuhan in China and has widely spread worldwide. Currently, it is vital to explore potential intermediate hosts of SARS-CoV-2 to control COVID-19 spread. Therefore, we reinvestigated published data from pangolin lung samples from which SARS-CoV-like CoVs were detected by Liu et al. [1]. We found genomic and evolutionary evidence of the occurrence of a SARS-CoV-2-like CoV (named Pangolin-CoV) in dead Malayan pangolins. Pangolin-CoV is 91.02% and 90.55% identical to SARS-CoV-2 and BatCoV RaTG13, respectively, at the whole-genome level. Aside from RaTG13, Pangolin-CoV is the most closely related CoV to SARS-CoV-2. The S1 protein of Pangolin-CoV is much more closely related to SARS-CoV-2 than to RaTG13. Five key amino acid residues involved in the interaction with human ACE2 are completely consistent between Pangolin-CoV and SARS-CoV-2, but four amino acid mutations are present in RaTG13. Both Pangolin-CoV and RaTG13 lost the putative furin recognition sequence motif at S1/S2 cleavage site that can be observed in the SARS-CoV-2. Conclusively, this study suggests that pangolin species are a natural reservoir of SARS-CoV-2-like CoVs." }, { "role": "assistant", "content": "[\"Mechanism\"]" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nThe coronavirus disease 2019 outbreak is evolving rapidly worldwide. The lungs are the target of the primary infection and patients with lung cancer seem to have a poor prognosis. To our knowledge, this is the first reported investigation of a possible role of interleukin-17 target therapy in patients with lung cancer and concomitant severe acute respiratory syndrome-coronavirus-2 infection." }, { "role": "assistant", "content": "[\"Treatment\", \"Mechanism\"]" } ]

[ { "role": "user", "content": "You will be presented with a citation segment from the section of a research paper. Classify the intent behind this citation by choosing from one of the following categories:\n\n- Method: Cites the paper for its methodology or procedure.\n- Background: Cites the paper to provide background information.\n- Result: Cites the paper for its findings or results.\n\nYour answer should be a single word from the following list of options: [\"Method\", \"Background\", \"Result\"]. Do not include any other text in your response.\n\nCitation sentence:\n\nEach explanation was also augmented by the provision of a teaching analogy, which illustrated the basic principles of the concept (Kulasegaram et al. 2012)." }, { "role": "assistant", "content": "Method" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: Anti-inflammatory drugs, which includes steroids such as prednisone and non-steroidal drugs like ibuprofen, work by decreasing inflammation\n\nAbstract:\nFever has been reported as a common symptom occurring in COVID-19 illness.\nOver the counter antipyretics such as ibuprofen and acetaminophen are often taken by individuals to reduce the discomfort of fever.\nRecently, the safety of ibuprofen in COVID-19 patients has been questioned due to anecdotal reports of worsening symptoms in previously healthy young adults.\nStudies show that ibuprofen demonstrates superior efficacy in fever reduction compared to acetaminophen.\nAs fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness." }, { "role": "assistant", "content": "{\"verdict\": \"SUPPORT\", \"evidence\": [\"As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness.\"]}" } ]

[ { "role": "user", "content": "Given a short query with keyphrases about a research idea in 2006 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.\n\nQuery: I'm trying to reconstruct a 3D model of a person\n\nKeyphrases: 3d face reconstruction range images\n\nDataset description:\nFRGC: The data for FRGC consists of 50,000 recordings divided into training and validation partitions. The training partition is designed for training algorithms and the validation partition is for assessing performance of an approach in a laboratory setting.\nPeople Snapshot Dataset: Enables detailed human body model reconstruction in clothing from a single monocular RGB video without requiring a pre scanned template or manually clicked points.\nVITON: VITON was a dataset for virtual try-on of clothing items. It consisted of 16,253 pairs of images of a person and a clothing item .\nIntrA: IntrA is an open-access 3D intracranial aneurysm dataset that makes the application of points-based and mesh-based classification and segmentation models available. This dataset can be used to diagnose intracranial aneurysms and to extract the neck for a clipping operation in medicine and other areas of deep learning, such as normal estimation and surface reconstruction.\n\nOptions:- A: FRGC B: People Snapshot Dataset C: VITON D: IntrA" }, { "role": "assistant", "content": "FRGC" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nOBJECTIVES: Heightened anxiety among dental healthcare professionals (DHPs) during the COVID-19 pandemic stems from uncertainties about the effectiveness of personal protective equipment (PPE) against dental aerosols and risk levels of asymptomatic patients. Our objective was to assess the risks for DHPs providing dental care during the pandemic based on available scientific evidence. METHODS: We reviewed the best available evidence and estimated the annualized risk (p=das(1-1-p0p1(1-e)(y)(n)) for a DHP during the COVID-19 pandemic based on the following basic parameters: p0, the prevalence of asymptomatic patients in the local population; p1, the probability that a DHP gets infected by an asymptomatic patient; e, the effectiveness of the PPE; s, the probability of becoming symptomatic after getting infected from asymptomatic patient; da, the probability of dying from the disease in age group a; n, number of patients seen per day; and y, number of days worked per year. RESULTS: With the assumption that DHPs work fulltime and wear a N95 mask, the annualized probability for a DHP to acquire COVID-19 infection in a dental office, become symptomatic, and die from the infection is estimated at 1:13,000 (0.008 %) in a medium sized city in the US at the peak of the pandemic. The risk estimate is highly age-dependent. Risk to DHPs under the age of 70 is negligible when prevalence of asymptomatic cases is low in the local community. CONCLUSIONS: Risk of COVID-19 transmission in dental office is very low based on available evidence on effectiveness of PPE and prevalence of asymptomatic patients. Face shields and pre-procedure oral rinses may further reduce the risks. CLINICAL SIGNIFICANCE: DHPs should follow guidelines on pre-appointment protocols and on PPE use during dental treatments to keep the risk low." }, { "role": "assistant", "content": "[\"Prevention\"]" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: The invisible light can kill viruses and pathogens like the one that causes COVID-19\n\nAbstract:\nThe coronavirus known as SARS-CoV-2, which causes COVID-19 disease, is presently responsible for a global pandemic wherein more than 3.5 million people have been infected and more than 250,000 killed to-date.\nThere is currently no vaccine for COVID-19, leaving governments and public health agencies with little defense against the virus aside from advising or enforcing best practices for virus transmission prevention, which include hand-washing, physical distancing, use of face covers, and use of effective disinfectants.\nIn this study, a novel iodine complex called CupriDyne® was assessed for its ability to inactivate SARS-CoV-2.\nCupriDyne was shown to be effective in inactivating the virus in a time-dependent manner, reducing virus titers by 99% (2 logs) after 30 minutes, and reducing virus titers to below the detection limit after 60 minutes.\nThe novel iodine complex tested herein offers a safe and gentle alternative to conventional disinfectants for use on indoor and outdoor surfaces." }, { "role": "assistant", "content": "{\"verdict\": \"NEI\", \"evidence\": []}" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research paper, followed by a question about the paper. Please extract text from the paragraph to answer the question. Do not include any text in your repsonse other than the answer.\n\nParagraph: Text: Severe acute respiratory syndrome coronavirus (SARS-CoV), a member of the genus Betacoronavirus within the family Coronaviridae, is an enveloped virus with a single-stranded positive-sense RNA genome of approximately 30 kb in length. The 5 two-thirds of the genome encodes large polyprotein precursors, open reading frame (ORF) 1 and ORF1b, which are proteolytically cleaved to generate 16 non-structural proteins (Tan et al., 2005) . The 3 one-third of the genome encodes four structural proteins, spike (S), envelope (E), matrix (M) and nucleocapsid (N), and non-structural proteins, along with a set of accessory proteins (3a, 3b, 6, 7a, 7b, 8a, 8b, and 9b) (Perlman and Dandekar, 2005; Tan et al., 2005) . SARS-CoV is the etiological agent of SARS (Drosten et al., 2003; Fouchier et al., 2003; Ksiazek et al., 2003; Kuiken et al., 2003; Peiris et al., 2003) . At least 8,098 laboratory-confirmed cases of human infection, with a fatality rate of 9.6%, were reported to the World Health Organization from November 2002 to July 2003. High levels of proinflammatory cytokines, including tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6, were detected in autopsy tissues from SARS patients (He et al., 2006) . Although dysregulation of inflammatory cytokines may be involved in lung injury and the pathogenesis of SARS-CoV, the underlying molecular mechanisms are not fully understood. The innate immune systems utilizes pattern recognition receptors (PRRs) to detect pathogen-associated molecular patterns (Medzhitov, 2001; Kawai and Akira, 2010) . Recognition of virus infection plays an important role in limiting virus replication at the early stages of infection. Nod-like receptor family, pyrin domain-containing 3 (NLRP3) is activated by a wide variety of stimuli, including virus infection (Bauernfeind et al., 2011) . Four models describing activation of the NLRP3 inflammasome have been proposed thus far (Hornung and Latz, 2010; Schroder et al., 2010; Tschopp and Schroder, 2010) . First, the disturbances in intracellular ionic concentrations, including K + efflux and Ca 2+ influx, play an important role (Fernandes-Alnemri et al., 2007; Petrilli et al., 2007; Arlehamn et al., 2010; Ichinohe et al., 2010; Ito et al., 2012; Murakami et al., 2012; Munoz-Planillo et al., 2013) . Second, cathepsin B and L, which are specific lysosomal cysteine proteases, are though to play a role after phagocytosis of cholesterol crystals (Duewell et al., 2010) , fibrillar peptide amyloid-beta , silica crystals, and aluminum salts . Third is the release of reactive oxygen species (ROS) or mitochondrial DNA from damaged mitochondria (Zhou et al., , 2011 Nakahira et al., 2011; Shimada et al., 2012) . Finally, viral RNA or RNA cleavage products generated by RNase L activate the NLRP3 inflammasome via the DExD/H-box helicase, DHX33 (Allen et al., 2009; Mitoma et al., 2013; Chen et al., 2014; Chakrabarti et al., 2015) . Upon activation, the NLRP3 is recruited to the mitochondria via association with mitochondrial antiviral signaling (MAVS) or mitofusin 2 expressed on the outer mitochondrial membrane Subramanian et al., 2013) ; these molecules then recruit the apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) and pro-caspase-1 to form the NLRP3 inflammasome. This event activates the downstream molecule, caspase-1, which catalyzes the proteolytic processing of pro-IL-1β and pro-IL-18 into their active forms and stimulates their secretion (Kayagaki et al., 2015; Shi et al., 2015) . It is increasingly evident that NLRP3 detects RNA viruses by sensing the cellular damage or distress induced by viroporins (Ichinohe et al., 2010; Ito et al., 2012; Triantafilou et al., 2013; Nieto-Torres et al., 2015) , transmembrane pore-forming proteins, encoded by certain RNA viruses; these proteins alter membrane permeability to ions by forming membrane channels (Tan et al., 2005; Chen and Ichinohe, 2015) . A recent study shows that the SARS-CoV E protein, which comprise only 76 amino acids, forms Ca 2+ -permeable ion channels and activates the NLRP3 inflammasome (Nieto-Torres et al., 2015) . Although the E and 3a proteins of SARS-CoV, which comprise 274 amino acids and contain three transmembrane domains (Zeng et al., 2004; Lu et al., 2006) , are thought to act as Na + /K + and K + channels, respectively (Wilson et al., 2004; Lu et al., 2006; Torres et al., 2007; Parthasarathy et al., 2008; Pervushin et al., 2009; Wang et al., 2011) , the role of the 3a protein in activating the NLRP3 inflammasome remains unknown. Here, we examined the role of the 3a protein in activating the NLRP3 inflammasome. Six-week-old female C57BL/6 mice were purchased from The Jackson Laboratory. All animal experiments were approved by the Animal Committees of the Institute of Medical Science (The University of Tokyo). Bone marrow-derived macrophages (BMMs) were prepared as described previously (Ichinohe et al., 2009) . In brief, bone marrow was obtained from the tibia and femur by flushing with Dulbecco's modified Eagle's medium (DMEM; Nacalai Tesque). Bone marrow cells were cultured for 5 days in DMEM supplemented with 30% L929 cell supernatant containing macrophage colony-stimulating factor, 10% heat-inactivated fetal bovine serum (FBS), and L-glutamine (2 mM) at 37 • C/5% CO 2 . HEK293FT cells (a human embryonic kidney cell line) and HeLa cells (a human epithelial carcinoma cell line) were maintained in DMEM supplemented with 10% FBS, penicillin (100 units/ml), and streptomycin (100 µg/ml) (Nacalai Tesque). MDCK cells (Madin-Darby canine kidney cells) and HT-1080 cells (a human fibrosarcoma cell line) were grown in Eagle's minimal essential medium (E-MEM; Nacalai Tesque) supplemented with 10% FBS, penicillin (100 units/ml), and streptomycin (100 µg/ml) (Nacalai Tesque). Influenza A virus strain A/PR8 (H1N1) was grown at 35 • C for 2 days in the allantoic cavities of 10-day-old fertile chicken eggs (Ichinohe et al., 2009) . The viral titer was quantified in a standard plaque assay using MDCK cells (Pang et al., 2013) . Plasmids cDNAs encoding the E and M proteins of SARS-CoV Frankfurt 1 strain (Matsuyama et al., 2005) were obtained by reverse transcription and PCR of total RNA extracted from SARS-CoVinfected Vero cells, followed by PCR amplification using specific primers. pcDNA3.1D-3a-V5His was provided by Ming-Fu Chang (National Taiwan University College of Medicine, Taipei, Taiwan). To generate the plasmids pLenti6-E-V5His, pLenti6-3a-V5His, and pLenti-M-V5His, cDNA fragments of E, 3a, and M were amplified from pcDNA3.1D-E-V5His, pcDNA3.1D-3a-V5His, and pcDNA3.1D-M-V5His using specific primer sets and then ligated into pLenti6-TOPO vectors (Invitrogen). To generate plasmids pCA7-flag-E, pCA7-flag-3a, and pCA7flag-M, pCA7-HA-E, pCA7-HA-3a, and pCA7-HA-M, cDNA fragments of E, 3a, and M were amplified from pcDNA3.1D-E-V5His, pcDNA3.1D-3a-V5His, and pcDNA3.1D-M-V5His using specific primer sets, digested with EcoR I and Not I, and subcloned into the EcoR I-Not I sites of the pCA7-flag-ASC plasmid or pCA7-HA-M2 plasmid, respectively (Ito et al., 2012) . To construct plasmids expressing the E mutant V25F, the mutated E fragments were amplified by inverse PCR with wildtype E-containing plasmids and specific primer sets. The PCR products were cleaved by Dpn I, ligated in a ligase-and T4 kinase-containing reaction and then transformed into DH5α competent cells (TOYOBO). To construct plasmids expressing the 3a mutant 3a-CS, fragments were amplified from wildtype 3a-containing plasmids using 3a-specific primer sets and transformed as described above. HEK293FT cells were seeded in 24-well cluster plates and transfected with 1 µg pLenti6-E/3a/M-V5His, pLenti-GFP (green fluorescent protein), or pLenti-M2 using polyethylenimine (PEI) Max. At 24 h post-transfection, the cells were lysed with RIPA buffer (50 mM Tris-HCl, 1% NP-40, 0.05% sodium dodecyl sulfate (SDS), 150 mM NaCl and 1 mM EDTA). And the lysates were subjected to SDS-polyacrylamide gel electrophoresis (PAGE) followed by electroblotting onto polyvinylidene difluoride (PVDF) membranes. The membranes were incubated over night with mouse anti-V5-tag (R960-25, Invitrogen), mouse anti-influenza A virus M2 (14C2, Abcam), mouse anti-GFP (GF200, Nacalai Tesque), or rabbit antitubulin (DM1A, Santa Cruz) antibodies, followed by horseradish peroxide-conjugated anti-mouse IgG (Jackson Immuno Research Laboratories) or anti-rabbit IgG (Invitrogen). After washing 3 times with washing buffer (0.05% Tween-20/PBS), the membranes were exposed using Chemi-Lumi One Super (Nacalai Tesque), and the chemiluminescent signals were captured by an ImageQuant LAS-4000 mini apparatus (GE Healthcare). To generate lentiviruses expressing V5-tagged SARS-CoV E, 3a, and M proteins, the full-length cDNA encoding each viral protein was cloned into the pLenti6.3/V5-TOPO vector (Invitrogen) using the following primers: SARS-CoV E forward, 5 -caccatgtactcattcgtttcgga-3 , and reverse, 5 -gaccagaagatcaggaactc-3 ; SARS-CoV 3a forward, 5caccatggatttgtttatgagatt-3 , and reverse, 5 -caaaggcacgctagtagtcg-3 ; SARS-CoV M forward, 5 -caccatggcagacaacggtactat-3 , and reverse, 5 -ctgtactagcaaagcaatat-3 . Sub-confluent monolayers of HEK293FT cells seeded in a collagen-coated dish (10 cm in diameter) were transfected with 3 µg of pLenti6.3/V5-TOPO vector expressing each viral protein or EGFP together with ViraPower Packaging Mix (Invitrogen) using Lipofectamine 2000 (Invitrogen). The supernatants containing lentiviruses were harvested and filtered through a 0.45 µm filter (Millipore) at 72-96 h post-transfection (Ito et al., 2012) . The lentiviral titer was then quantified using HT-1080 cells as described previously . Bone marrow-derived macrophages were plated at a density of 8 × 10 5 in 24-well plate and infected with A/PR8 influenza virus or lentivirus at a multiplicity of infection (MOI) of 5 or 0.2 for 1 h, respectively. Then, BMMs were stimulated with 1 µg/ml of LPS and cultured for additional 23 h in complete media. Supernatants were collected at 24 h post-infection and centrifuged to remove cell debris. The amount of IL-1β in the supernatants was measured in an enzyme-linked immunosorbent assay (ELISA) using paired antibodies (eBioscience) (Ichinohe et al., 2010 . To clarify the cellular localization of the wild-type and mutant 3a proteins of SARS-CoV, HeLa cells were cultured on coverslips and transfected with 1 µg of pCA7-flag-3a or pCD7-flag-3a-CS together with 0.5 µg of ER-mCherry or DsRed-Golgi (Ito et al., 2012) .\n\nQuestion: Is the SARS coronavirus single-stranded or double-stranded?" }, { "role": "assistant", "content": "single-stranded" } ]

[ { "role": "user", "content": "You will be presented with a citation segment from the section of a research paper. Classify the intent behind this citation by choosing from one of the following categories:\n\n- Method: Cites the paper for its methodology or procedure.\n- Background: Cites the paper to provide background information.\n- Result: Cites the paper for its findings or results.\n\nYour answer should be a single word from the following list of options: [\"Method\", \"Background\", \"Result\"]. Do not include any other text in your response.\n\nCitation sentence:\n\nAlthough the study of heat transfer in magmatic systems has a venerable history (e.g. Ingersoll et al., 1954; Shaw, 1965; Jaeger, 1968; Spera, 1979; Carrigan, 1988; Huppert & Sparks, 1988; Bergantz, 1989; Marsh, 1989), the explicit connection between heat transfer and the trace element and isotopic…" }, { "role": "assistant", "content": "Background" } ]

[ { "role": "user", "content": "You will be presented with the full text of a biomedical research paper. Please write an abstract for this paper. Your response should include the abstract and no additional text.\n\nPaper text:\nobesity is a growing problem and more than 30% of the european population is obese with a body mass index ( bmi ) > 30 \nweight loss decreases the risk of obesity related complications such as type 2 diabetes , cardiovascular events , and joint and musculoskeletal diseases as well as improves fertility and reduces the risk of spontaneous abortion .\nthe expected economic implications of weight loss among the obese are reduced sick leave and substantially lower demand on health support .\ncontrolling dietary intake and increasing physical activity through behavioral change programs in a face - to - face setting have previously been demonstrated to produce significant weight loss .\nhowever , implementing such programs into general practice has shown to be difficult due to a number of barriers .\nface - to - face consultations are time consuming both for the health professionals and for the patient , and many general practitioners do not offer sufficiently extensive behavioral support to fully achieve the potential effect . in order to achieve a major behavioral change ,\ninformation must be so clearly relevant for the patient that they can not easily choose to ignore it . when face - to - face consultations are used on their own ( without extensive follow - up measures ) , long - term effects compared to controls are difficult to detect .\nfurthermore , in denmark access to professional dieticians is limited due to the costs of the public health care system .\nthe effects in primary care have been variable , but using the internet seems to be more cost - effective , even when the magnitude of the effect is not affected .\npersonal individual advice can be delivered either synchronously or asynchronously . by delivering the advice asynchronously important communication\ncan be managed at a very low cost due to the fact that digital communication is stored and parts of it can be reused for many patients in templates or articles\n. matched peer support through online communities where patients can meet other patients in a similar situation as themselves can offer important support , and established relations between patients and health professionals seem to be important drivers for successful outcomes [ 6 , 12 , 15 ] . in a recent prospective pilot study without a control group we investigated the effect of a medium intensive online dietician advice combined with a community using the existing commercial online weight loss management program \nslankedoktor . we found a mean weight loss from baseline of 7.0 kg ( 95% ci : 4.69.3 kg ) after a mean maintenance period of 20 months among 21 patients with an initial bmi of 36.4 kg / m .\n\n to evaluate the impact of a complex intervention using face - to - face contact with trained dieticians combined with interactive online support and follow - up , as compared with usual care , on bmi and metabolic risk factors.to explore the feasibility of the intervention by assessing patients ' sociodemographic characteristics and use of the different services in the intervention in relation to their weight loss.to explore the usability and applicability of the intervention in relation to the health professionals ' view and perceptions of the intervention ( their role and the advice and the support that they provide ) . \n to evaluate the impact of a complex intervention using face - to - face contact with trained dieticians combined with interactive online support and follow - up , as compared with usual care , on bmi and metabolic risk factors . to explore the feasibility of the intervention by assessing patients ' sociodemographic characteristics and use of the different services in the intervention in relation to their weight loss .\nto explore the usability and applicability of the intervention in relation to the health professionals ' view and perceptions of the intervention ( their role and the advice and the support that they provide ) .\nthe study will recruit 340 patients registered in general practices within 46 medical centers , representing a population of approximately 40,000 citizens .\nthey will be both rural and city centers and have between 2 and 10 doctors working at each center .\npatients are included consecutively until there is a total number of 340 patients randomized to either intervention group or control group , respectively .\nwe expect to include initial 500 patients before randomization as our experience from the pilot study is that 25% of those who agree to participate do not fill out the online registration form required to be randomized ( figure 1 ) . \n\nthe patient has a bmi 30 kg / m.the patient is 1870 years old.the patient provides informed consent.the patient has home access to the internet.the patient is not pregnant.the patient has no serious or life threatening disease.the patient has no weight loss > 3 kg within the last 2 months . \n \nthe patient has no weight loss > 3 kg within the last 2 months . \n\nthe patient fails to complete the initial questionnaire online.the patient becomes pregnant during the study.the patient experiences serious or life threatening disease during the study.the patient moves to another gp practice not participating in the study.the patient has a serious eating disorder or develops one during the study ( e.g. , rapid weight changes ) . \n \nthe patient has a serious eating disorder or develops one during the study ( e.g. , rapid weight changes ) .\npatients who receive information concerning the study from doctors or practice staff and who agree to participate are registered and scheduled for an appointment with a nurse .\nthe patients will be able to bring a friend or relative in accordance with ethical guidelines for biomedical experiments with humans .\nan appointment with a nurse is scheduled within 714 days after the information ; thus the patient has sufficient time to reflect on the decision to participate .\nthe nurse obtains the approved informed consent and proceeds with weighing and measuring the patient . the patient is then instructed to use a web link to a standard quality of life questionnaire including sf12 and other relevant questions from the webpage www.praksis.sundhedsdoktor.dk .\npatients are randomized immediately after the questionnaire is filled out , using an automated computer algorithm .\nthis procedure ensures that dropouts can be recorded as well as certain characteristics for the patients who choose to drop out .\nhttp://www.praksis.sundhedsdoktor.dk/ as well as a consultation with a certified clinical dietician within 2 weeks .\nthe website has been developed over a 12-year period with focus groups , usability testing , and user involvement from both patients and health care professionals . at \nthe patients fill in a daily diet record as well as their comments , concerns , and questions to the dietician , who will have access to all patient profiles .\nthey have access to a community where they can discuss and chat with other patients and share weight loss experiences as well as give advice and support to each other .\npatients receive subsequent 1530 min consultations with the dietician by appointment at the start and up to every 6 weeks for 6 months to a total of 5 ( figure 2 ) .\nthe certified clinical dieticians also provide individual asynchronous online consultation according to their patients ' needs and based on information supplied via the website .\nthe online consultations are weekly during the first 6 months and after that they are monthly .\nthe dietician generates a daily caloric reduction plan of approximately 24003200 kj based on the patients ' starting weight , diet record , and physical activity .\nthe dietary advice will be as standardized as possible . in collaboration with the patient goals for obesogenic behavior changes\nare set up like eat breakfast every day , no late night meal or snack , and so forth that follow the dietary guidelines given at http://www.praksis.sundhedsdoktor.dk/ and the danish health and medicine authority ( sundhedsstyrelsen ) .\na personal trainer evaluates the exercise by monitoring information given by the patients and encourages them to increase their physical activity to a level of at least .\npatients will be encouraged to increase their physical activity to a level with at least 30 min daily .\nthree times a week the physical activity is suggested to be of moderate to high intensity .\npatients randomized to the control group will receive usual treatment through the medical center , which consists of approximately monthly face - to - face consultations with a nurse or doctor .\nplacebo treatment in the form of a login to a website that looks like http://www.praksis.sundhedsdoktor.dk/ , but contains only general non - interactive and non - personalized dietary and exercise advice ( e.g. all about diet from the national food agency ( fdevarestyrelsen ) ) , but with neither dietician consultations nor community membership .\nanswers to the standard quality of life questionnaire are collected at the medical center by a nurse at inclusion at 6 months and at 24 months .\npatient height , waist and hip circumference , blood lipids , hba1c , and weight are measured at inclusion after 6 months and 24 months .\nthe blood samples will be collected by the bioanalyst in the practice in accordance with guidelines for the handling of blood measurements in danish general practice and analyzed at the certified laboratory at odense university hospital .\ndata will be continuously added to a database by the patient , nurse , and dietician .\nnumber of logins , number of entrances in the different sections of the site , and user patterns will be collected from the database at 6 months and again at 24 months .\ndieticians , nurses , doctors , and other health professionals from the medical center will be interviewed about the intervention in relation to their work , their role , their perception of the treatment offered , and the strength and weaknesses seen from their perspective in accordance with the mast models organizational dimension ( table 1 ) . in the case of exclusion before the end of the trial , for example , by pregnancy , the patient will if feasible be asked to complete a final questionnaire and have objective parameters measured in order to provide data for an intention to treat analysis .\ndata and answers to questionnaires will be collected at 6 months and 24 months by independent observers that will assign each patient to a number to mask the identity for the analysts .\nthe primary objective of this study is measurement of changes in body weight and waist circumference .\nweight loss in the intervention group and control group will be analyzed using appropriate statistical procedures .\na weight loss of 57 kg in the study group and 2 - 3 kg in the control group is expected after 6 months of treatment .\nafter 2 years we expect the control group to return to the starting weight , while the study group is expected to maintain a weight loss of 35 kg .\na power calculation , based on standard deviations observed in a previous pilot project , shows that to detect a difference in weight loss of 2.5 kg with a power of 90% requires 142 patients per group .\nsecondary outcome such as logins , web site activity , and user patterns will be analyzed in relation to the different quartiles .\nthe most active quartile will be compared to the least active quartile in relation to weight loss , and other measured parameters .\nif the difference in sustained weight loss after 2 years is greater than 2.5 kg , the planned total of 340 patients will allow analyses of interactions between treatment , gender , age and obesity level .\ndue to this , the randomization will be stratified by gender , while potential effects of and interactions with other recorded characteristics such as smoking , age and obesity level will be analyzed as continuous or discrete variables as appropriate .\nall data will be blinded and the randomization code and identity of the patients will not be revealed to the data manager before analyses are completed .\nafter the study , all data will be made accessible on the internet in anonymized form to allow full peer scrutiny and facilitate secondary research .\nthe intervention to be assessed in the present study has been developed since 2002 by a team of dieticians , computer programmers , and physicians as the commercial weight management program \nthe guiding principle was to improve the cost - effectiveness of established best practice for dietician - supported weight management by using the internet to facilitate interactive communication between the dieticians and the users as well as among the users ( peer support through online community ) .\nthis program was developed iteratively from an initial prototype through trial and error to what is now a well - established commercial product used by 10.000 predominantly healthy overweight or moderately obese users in 2013 .\nregarding the use in general practice for treatment of obese patients , this program has been tried on a pilot scale with good results .\nhowever an appropriately designed randomized controlled trial is required in order to assess the actual cost - effectiveness of this approach compared with other options . in the danish health care system ,\ngeneral practitioners are obliged to identify and offer appropriate support to obese patients whose health would benefit from a weight loss , and a prespecified sum per patient is available to finance this support . in most cases\nthis support ( usual care ) consists of 46 monthly face - to - face consultations with a health professional , usually a nurse or physician , which includes provision of general weight management information such as brochures and educational internet sites .\nso the present study has been designed to allow direct comparison between the intervention ( dietician - supported internet community ) and a single - blind control treatment .\nthe two arms provide the same number of face - to - face consultations which include the sessions to measure and sample the patients .\nthe usual care control treatment will be provided in a way so the patients are not aware which arm they are on by using a placebo website that superficially resembles the interactive treatment without providing any personalized support .\nthis study will utilize the danish general practice setting , where it is possible to test the combination of face - to - face consultations with dieticians ( establishing the relation ) , real - time online reporting , life style advice , and community peer support as a full scale trial .\nthe online tool in this study will be integrated into the exiting electronic journal system of the general practitioners to emulate how it would be implemented if it was part of the standard offer .\nadditional information will be collected from patients and health professionals as feedback to enable further improvements , primarily regarding how to optimize the experience for both patients and health professionals as well as how to identify which patients are most likely to benefit from this type of intervention , in order to optimize resource allocation to this and other options for weight management . a potential limitation to the chosen study design\nis that the number of doctors recruited is limited and those who take part might be more interested in new technologies than the average general practitioner .\nanother weakness of the present study is that the intervention comprises several dimensions of complexity , which preclude evaluation of each aspect of the intervention separately .\nhowever , with this new technology doctors will be able to prescribe exercise and diets and obtain insight into patient performance at a much more detailed level than seen before .\ncompared with other published studies such as the study is a long - term study without monetary incentives for patients , is designed to work in a routine primary care setting , and takes into account the value chain established in the danish health care system .\nif the study is successful , this will make it easy to implement the program nationwide and internationally for the benefit of many overweight patients .\nadditionally the organizational learning provided by this study will be of importance for implementing other medical online support systems in the future and providing new opportunities for the handling of patients in primary care with modern technology and patient empowerment ." }, { "role": "assistant", "content": "background . \n internet - based complex interventions aiming to promote weight loss and optimize healthy behaviors have attracted much attention . however , evidence for effect is lacking . \n obesity is a growing problem , resulting in an increasing demand for cost efficient weight loss programs suitable for use on a large scale , for example , as part of standard primary care . in a previous pilot project by brandt et al . \n ( 2011 ) without a control group , \n we examined the effects of online dietician counseling and found an average weight loss of 7.0 kg ( 95% ci : 4.6 to 9.3 kg ) after 20 months . aims and methods . to analyze the effects of a complex intervention using trained dieticians in a general practice setting combined with internet - based interactive and personalized weight management support compared with conventional advice with a noninteractive internet support as placebo treatment in 340 overweight patients during a 2-year period . \n primary endpoints are weight loss and lowering of cholesterol ( ldl ) \n . we will also explore patients ' sociodemographics and use of the intervention as well as the health professionals ' views and perceptions of the intervention ( their role and the advice and support that they provide ) . perspective . \n the project will generate knowledge on the cost - effectiveness of a complex internet - based intervention in a general practice setting and on barriers and acceptability among professionals and patients ." } ]

[ { "role": "user", "content": "You will be presented with a citation segment from the section of a research paper. Classify the intent behind this citation by choosing from one of the following categories:\n\n- Method: Cites the paper for its methodology or procedure.\n- Background: Cites the paper to provide background information.\n- Result: Cites the paper for its findings or results.\n\nYour answer should be a single word from the following list of options: [\"Method\", \"Background\", \"Result\"]. Do not include any other text in your response.\n\nCitation sentence:\n\nStrain estimation was performed as follows: The postcompression A-line was stretched globally by the applied strain (Céspedes 1993; Varghese and Ophir 1997b)." }, { "role": "assistant", "content": "Method" } ]

[ { "role": "user", "content": "You will be shown a question, followed by excerpts from biomedical research papers. Please answer the question based on the provided context. Do not include any text in your response other than the answer.\n\nQuestion: What is masitinib an inhibitor of?\n\nContext: This study evaluated the therapeutic potential of masitinib, an oral tyrosine kinase inhibitor with activity against c-Kit and platelet-derived growth factor receptors (PDGFR), to reduce ischemic brain area and neurological deficit.\nMasitinib, a selective tyrosine kinase inhibitor, was investigated as a radiosensitizer in three primary feline injection-site sarcoma (ISS) cell lines.\nDual actions of masitinib as an inhibitor of mast cell-glia axis and a Fyn kinase blocker are discussed in the context of AD pathology." }, { "role": "assistant", "content": "Masitinib is an inhibitor of mast cell-glia axis and a Fyn kinase blocker. It is an oral tyrosine kinase inhibitor with activity against c-Kit and platelet-derived growth factor receptors (PDGFR)." } ]

[ { "role": "user", "content": "You will be presented with a citation segment from the section of a research paper. Classify the intent behind this citation by choosing from one of the following categories:\n\n- Method: Cites the paper for its methodology or procedure.\n- Background: Cites the paper to provide background information.\n- Result: Cites the paper for its findings or results.\n\nYour answer should be a single word from the following list of options: [\"Method\", \"Background\", \"Result\"]. Do not include any other text in your response.\n\nCitation sentence:\n\nImmunoblotting using primary antibodies for anti-eNOS (BD Biosciences), anti-phospho-eNOS Thr495 (Cell Signaling), anti-phosphoeNOS Ser1177 (Millipore), anti-eNOS (BD Transduction Laboratories), anti-RhoA (Abcam), and anti-b-actin (Sigma) was performed as described previously, following a 1 h incubation with IL-17 (mouse rIL-17A, 1 mg/mL; eBioscience).(28,29) Immunoblotting was also performed for these proteins in IL17-treated cells following co-treatment with an IL-17 neutralizing antibody (20 ng/mL for 30 min; BioLegend), the protein kinase C (PKC) inhibitor Gö6976 (1 mmol/L for 30 min; Sigma), the Rho-kinase inhibitor Y-27632 (50 mmol/L for 30 min; Cayman Chemical Co." }, { "role": "assistant", "content": "Background" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:\n\n- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.\n- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.\n- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.\n\nPlease format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.\n\nAs an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:\n\n[[\"artesunate\", \"artemether\", \"COMB\"], [\"Nifedipine\", \"Labetalol\", \"Prazosin\", \"POS\"]]\n\nThe paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.\n\nIn your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.\n\nparagraph: Ceritinib plus Nivolumab in Patients with Advanced ALK-Rearranged Non-Small Cell Lung Cancer: Results of an Open-Label, Multicenter, Phase 1B Study. Induction of programmed death ligand 1 (PD-L1) expression due to constitutive oncogenic signaling has been reported in NSCLC models harboring echinoderm microtubule associated protein like 4 gene (EML4)-ALK receptor tyrosine kinase gene (ALK) rearrangements. We assessed the safety and activity of ceritinib plus nivolumab in these patients . ### methods In this open-label, phase 1B, multicenter, dose escalation and expansion study, previously treated (with ALK receptor tyrosine kinase [ALK] inhibitor [ALKI]/chemotherapy) or treatment-naive patients with stage IIIB or IV ALK-rearranged NSCLC received nivolumab, 3 mg/kg intravenously every 2 weeks, plus ceritinib, 450 mg/300 mg daily, with a low-fat meal. ### results In total, 36 patients were treated (a 450-mg cohort [n=14] and a 300-mg cohort [n=22]). In the 450-mg cohort, four patients experienced dose-limiting toxicities. In the 300-mg cohort, two patients experienced dose-limiting toxicities. Among ALKI-naive patients, the overall response rate (ORR) was 83% (95% confidence interval [CI]: 35.9-99.6) in the 450-mg cohort and 60% (95% CI: 26.2-87.8) in the 300-mg cohort. Among ALKI-pretreated patients, the ORR was 50% (95% CI: 15.7-84.3) in the 450-mg cohort and 25% (95% CI: 5.5-57.2) in the 300-mg cohort. The ORR point estimate was observed to be greater in patients who were positive for PD-L1 than in those who were negative for PD-L1, with overlapping CIs (e.g., at a cutoff ≥1% PD-L1, 64% of patients [95% CI: 35.1-87.2] had confirmed responses as compared with those with negative PD-L1 staining (31% [95% CI: 11.0-58.7]). The most frequently reported grade 3 or 4 adverse events were increased alanine aminotransferase level (25%), increased gamma-glutamyl transferase level (22%), increased amylase level (14%), increased lipase level (11%), and maculopapular rash (11%). The incidence of all-grade rash (grouped term) was 64% in both cohorts; grade 3 rash was reported in 29% and 14% of patients in the 450-mg and 300-mg cohorts, respectively; no grade 4 rash was reported. ### conclusion ceritinib plus nivolumab has activity; ORR appears to correlate with PD-L1 at baseline. Toxicity, especially rash, is more common than with either single agent.\n\nsentence: We assessed the safety and activity of ceritinib plus nivolumab in these patients ." }, { "role": "assistant", "content": "[[\"ceritinib\", \"nivolumab\", \"COMB\"]]" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research paper, followed by a question about the paper. Please extract text from the paragraph to answer the question. Do not include any text in your repsonse other than the answer.\n\nParagraph: In this review, we summarize the evidence supporting these concepts. Text: Chikungunya virus (CHIKV), a mosquito-borne pathogen listed by National Institute of Allergy and Infectious Diseases (NIAID) as a Category C Priority Pathogen that causes Chikungunya fever (CHIKF), has been spreading throughout Asia, Africa, and parts of Europe in recent times [1, 2, 3] . CHIKV is an arthropod-borne virus (arbovirus) and is transmitted to humans primarily by Aedes aegypti, the infamous yellow fever propagator [4, 5] . CHIKV infection is marked by severe joint pain, contorting its victims into unusual postures [6] . The disease gets its name from the Kimakonde vernacular language of Tanzania and Mozambique, and the word chikungunya means ''that which contorts or bends up'' and translates in Swahili to ''the illness of the bended walker'' [7, 8, 9] . In Africa, CHIKV is maintained in a sylvatic cycle among forest-dwelling Aedes spp. mosquitoes, wild primates, squirrels, birds, and rodents ( Figure 1 ) [10] . In Asia, the disease is vectored by Ae. aegypti and Ae. albopictus [11] . Transmission in Asia occurs in an urban cycle whereby the mosquito spreads the disease from an infected human to an uninfected human, following an epidemiological pattern similar to dengue fever [12] . The 2005-2006 epidemic of CHIKV in La Reunion islands in the Indian Ocean, spurred the discovery of a new vector species, Ae. albopictus [5] . Wrecking over one-third of the island's population, this epidemic peaked its devastation between January and February 2006, when over 46,000 cases came into light every week, including 284 deaths [5, 13] . Ae. albopictus is common in urban areas of the United States and is already flourishing in 36 states, raising grave concerns to the immunologically naive populace of the United States [14] . Accordingly, this review elaborately details the epidemiology and global expansion of CHIKV, describes its clinical features and pathogenesis and its symptoms and complications, and finally nominates a possible vaccine approach against CHIKV infection. CHIKV has been isolated into three genotypes based on phylogenetic studies. These genotypes, based on the gene sequences of an Envelope protein (E1), are Asian, East/Central/ South African, and West African [4, 11, 15] . Using phylogenetic models, Cherian et al. estimate that the Asian genotype of CHIKV emerged between 50 and 310 y ago, and the West and East African genotypes diverged between 100 and 840 y ago [15] . Since then, CHIKV has come a long way, with several mutations incorporated, and has continued to wreak epidemics in several regions. Recent activities of CHIKV include the Indian epidemic in 2005-2006, which was followed by a sudden explosion of cases in 2007. An estimated 1.3 million people across 13 states were reported to be infected in India [12, 16] , and CHIKV was also widespread in Malaysia, Sri Lanka, and Indonesia [17] . In July-August of 2007, CHIKV was reported in Italy, probably brought in by travelers from CHIKV-prone regions of India, Africa, and Indian Ocean islands such as Mauritius, Madagascar, and Seychelles. Few of the Italian isolates were found to have evolved from the Kerala isolate, which was associated with a A226V shift in E1 gene that represents a successful evolutionary adaptation in the mosquito vector similar to the ones observed in Reunion Island [2, 18, 19] . In recent times, with an increase in global travel, the risk for spreading CHIKV to non-endemic regions has heightened [1] . Several travelers have brought CHIKV home with them after visiting areas with actively infected populations [12, 20] . Such cases have been documented in European countries, Australia, Asia, and the United States [8, 21] . The United States has already reported at least twelve cases of travel-associated CHIKV, while France has reported 850 cases, and the United Kingdom 93 [8, 14] . Beyond this, CHIKV-infected travelers have also been diagnosed in Australia, Belgium, Canada, Czech Republic, French Guiana, Germany, Hong Kong, Italy, Japan, Kenya, Malaysia, Martinique, Norway, Switzerland, and Sri Lanka [21] . Some travelers were viremic, worrying public health officials about the spread of CHIKV to new areas [1, 8] . The incubation time for CHIKV is relatively short, requiring only 2-6 d with symptoms usually appearing 4-7 d post-infection [22] . Vazeille et al. detected CHIKV in the salivary glands of Ae. albopictus only 2 d after infection [5] . Upon infection, CHIKF tends to present itself in two phases. The first stage is acute, while the second stage, experienced by most but not all, is persistent, causing disabling polyarthritis. Characteristics of the acute phase include an abrupt onset of fever, arthralgia, and in some cases, maculopapular rash [6, 23] . The acute phase causes such intense joint and muscular pain that makes movement very difficult and prostrates its victims [6, 20] . Ninety-five percent of infected adults are symptomatic after infection, and of these, most become disabled for weeks to months as a result of decreased dexterity, loss of mobility, and delayed reaction. Eighteen months after disease onset, 40% of patients are found to still have anti-CHIKV IgM [6, 18, 23, 24] . The chronic stage of CHIKF is characterized by polyarthralgia that can last from weeks to years beyond the acute stage [6] . CHIKV has been shown to attack fibroblasts, explaining the involvement of muscles, joints, and skin connective tissues. The high number of nociceptive nerve endings found within the joints and muscle connective tissues can explain pain associated with CHIKF [25, 26] . More than 50% of patients who suffer from severe CHIKF are over 65 y old, and more than 33% of them die. Most adults who suffer from severe CHIKF have underlying medical conditions [6, 24, 27] . The other group that is disproportionately affected by severe CHIKV is children. Other complications associated with CHIKV, from most common to least common, include respiratory failure, cardiovascular decompensation, meningoencephalitis, severe acute hepatitis, severe cutaneous effects, other central nervous system problems, and kidney failure [6, 18, 20, 23, 24, 26, 27] . CHIKV undertakes a complex replication cycle upon host infection (Figure 2 ), which makes its genome susceptible to mutations [28, 29] . For instance, Ae. aegypti, responsible for epidemics in Kenya, Comoros, and Seychelles, carried CHIKV with an alanine in the 226 position of the E1 gene (E1-A226) [4, 18] . However, when the virus struck La Reunion Islands, a decline in population of Ae. aegypti, due to massive dichlorodiphenyltrichloroethane usage and dearth of Ae. albopictus species' www.plosntds.org population, resulted in an ecological pressure, favoring replacement of alanine at position 226 with valine (E1-A226V) [5] . This mutation allowed CHIKV's secondary vector species, Ae. albopictus, to supplement Ae. aegypti as its primary vector [5] . Within a year, the E1-A226V mutation was present in La Reunion Island, and Ae. albopictus apparently vectored the large epidemic infecting 34% of La Reunion Island's population [5] . All of the CHIKV strains isolated from Mayotte carried the E1-A226V mutation, and the mutation was also found in Madagascar in 2007 [5] . The E1-A226V mutation was not present at the beginning of the Indian Ocean Islands outbreak (before September 2005). However, more than 90% of later viral strains found there had incorporated the mutation (December-March 2006), indicating a genotype switch during the winter season [5, 18, 20] . The E1-A226V mutation also enabled an increase in infectivity of Ae. albopictus when compared to its infectivity of Ae. aegypti [4, 11, 18, 30] , and with several factors taken together, Ae. albopictus has become the new preferred and more lethal vector for CHIKV [4, 5, 11] . In fact, Tsetsarkin et al. found that a Green Fluorescent Protein tagged E1-A226V virus was 100 times more infective to Ae. albopictus than it was to Ae. aegypti [4] . In all the Indian Ocean Islands, Ae. albopictus became the main vector for CHIKV within 1-2 y after CHIKV was introduced to the region [31] . Of note is that Ae. aegypti has most likely been established in North America for over 300 y, while Ae. albopictus has been in many areas of the US, since 1985, primarily in Florida [32] and since then has expanded its range in the country. Reiskind et al. set out to determine if Ae. aegypti and Ae. albopictus mosquitoes captured in Florida were susceptible to CHIKV infection by a La Reunion isolate [32] . Each mosquito tested was highly susceptible to infection by a full-length infectious clone of the La Réunion Island isolate, CHIKV LR2006 OPY1 strain. Even though the Ae. albopictus strains were more susceptible to infection, overall ecology and differences in human biting patterns need to be studied further Characteristically, there are two rounds of translation: (+) sense genomic RNA (49S9 = 11.7 kb) acts directly as mRNA and is partially translated (59 end) to produce non-structural proteins (nsp's). These proteins are responsible for replication and formation of a complementary (2) strand, the template for further (+) strand synthesis. Subgenomic mRNA (26 S = 4.1 kb) replication occurs through the synthesis of full-length (2) intermediate RNA, which is regulated by nsp4 and p123 precursor in early infection and later by mature nsp's. Translation of the newly synthesized sub-genomic RNA results in production of structural proteins such as Capsid and protein E2-6k-E1 (from 39 end of genome). Assembly occurs at the cell surface, and the envelope is acquired as the virus buds from the cell and release and maturation almost simultaneous occurred. Replication occurs in the cytoplasm and is very rapid (,4 h) [28, 29] . doi:10.1371/journal.pntd.0000623.g002 www.plosntds.org to gain a more accurate understanding of a potential CHIKV epidemic in the US [32] . During the 7 d preceding birth, no human mother has been reported to transmit the disease vertically. However, about 50% of newborns delivered while the mother was infected with CHIKV contracted the disease from their mother, despite the method of delivery. Furthermore, there have been instances of CHIKV transmission from mother to fetus causing congenital illness and fetal death [33] . During the 2005-2006 La Reunion Island outbreaks, Ramful et al. discovered that mothers could transmit CHIKV to their progeny during the perinatal period (Day 24 to Day +1) [33, 34] , and it is associated with a high degree of morbidity. By mean Day 4 of life, all of the neonates were symptomatic for CHIKV, exhibiting common CHIKF symptoms. Six neonates were confirmed to have contracted CHIKV and developed mengoencephalitis. Of those mothers who, during the La Reunion Island epidemic, were infected long before delivery, only three fetal deaths were reported [12, 33] . Ramful et al. theorized that motherto-child transmission most likely happens transplacentally shortly before delivery [33] . A similar study by Gerardin et al. reported nineteen cases of neonatal infection associated with intrapartum maternal viremia that progressed to develop encephalitis owing to vertical transmission from infected mothers [34] . Clinical and epidemiological similarities with dengue fever make CHIKV diagnosis difficult, which may lead physicians to misdiagnose CHIKV as dengue fever; therefore, the incidence of CHIKV may actually be higher than currently believed (Table 1 ) [6, 12, 35] . The amount of time elapsed since disease onset is the most critical parameter when choosing a diagnostic test. CHIKV can be detected and isolated by culturing with mosquito cells (C6/36), Vero cells (mammalian), or in mice [26] . However, this method can take at least a week and only achieves a high sensitivity during the viremic phase, which usually only lasts up to 48 h after the bite. Five days post-infection, the viral isolation approach has a low sensitivity but is still the preferred method for detecting the CHIKV strain [12, 26, 31, 35] . RT-PCR on the other hand is a faster and more sensitive method that can be used within the first week of disease onset [26] , and it is currently the most sensitive method for detecting and quantifying viral mRNA [4, 36] . Classic serological detection, by assays such as ELISA [37] , immunofluorescence [5, 38] , complement binding, and haemagglutination inhibition [39] , constitutes the second diagnostic tool used for biological diagnosis of CHIKV infection. These proven techniques are useful for detection of Antigen in mosquitoes during epidemiological studies. These assays detect virus-specific IgM and IgG, however the sensitivity and specificity of these assays has been poorly characterized. Viral competence, or the potential of viral infection and transmission, is an important parameter that can be quantified by ELISA, viral culture, and PCR. A study by Ng et al. showed biomarkers indicative of severe CHIKV infection [40] . They found decreased levels of RANTES and increased levels of Interleukin-6 (IL-6) and Interleukin-1b (IL-1b) that could be sued for CHIKV detection in patients as indicators of CHIKV-driven cytokine storm. Couderc et al. demonstrate another cytokine, type-I IFN, as a key player in the progression to CHIKV infection [26] .\n\nQuestion: What are consequences of infection?" }, { "role": "assistant", "content": "Ninety-five percent of infected adults are symptomatic after infection, and of these, most become disabled for weeks to months as a result of decreased dexterity, loss of mobility, and delayed reaction." } ]

[ { "role": "user", "content": "You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\".\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.\n\nFor instance, if the model were given the claim \"the COVID vaccine is safe for healthy adults\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults.\"]\n}\n\nClaim: The newly introduced sars-cov-2 variant a222v is rapidly spreading in lazio region , italy\n\nAbstract:\nA new SARS-CoV-2 clade (GV) characterized by S substitution A222V, first reported from Spain in March, is rapidly spreading across Europe.\nTo establish the A222V variant involvement in the infection rise in Italy, all GISAID sequences from Italy and those from our Laboratory (Lazio) in the period June-October were analysed.\nA222V, first recognized in August, represents 11.2% of sequences in this period, reaching 100% of autochthonous sequences in October, supporting increased GV circulation in Italy." }, { "role": "assistant", "content": "{\"verdict\": \"SUPPORT\", \"evidence\": [\"To establish the A222V variant involvement in the infection rise in Italy, all GISAID sequences from Italy and those from our Laboratory (Lazio) in the period June-October were analysed.\", \"A222V, first recognized in August, represents 11.2% of sequences in this period, reaching 100% of autochthonous sequences in October, supporting increased GV circulation in Italy.\"]}" } ]

[ { "role": "user", "content": "You will be presented a sentence from biomedical research text. Extract all terms that correspond to chemical entities of biological interest (ChEBI).\nReturn your identified terms in a JSON array, formatted like this: [\"Entity1\", \"Entity2\", ...].\nIf no such entities are detected, respond by providing an empty JSON array [].\n\nBiomedical context:\n(B)SouthernblotanalysisofmousegenomicDNA." }, { "role": "assistant", "content": "[]" } ]

[ { "role": "user", "content": "You will be presented with the full text of a biomedical research paper. Please write an abstract for this paper. Your response should include the abstract and no additional text.\n\nPaper text:\nepstein - barr virus ( ebv ) and cytomegalovirus ( cmv ) are members of the herpesvirus family .\nco - infection with these two viruses occurs occasionally in children , but co - reactivation of these viruses has not been reported .\nebv is a double - stranded dna herpesvirus that infects and persists in > 90% of humans worldwide .\nebv infection frequently causes self - limiting infectious mononucleosis ; latent infection is preferentially sustained in b cells over the lifetime of the host .\ncmv is also a common viral infection in humans , which occurs in 40100% of humans worldwide .\nprimary cmv infection is followed by either chronic infection or viral latency from which the virus may be reactivated .\ncmv infection of the gastrointestinal tract occurs mainly in immunocompromised individuals , including those with inflammatory bowel disease ( ibd ) and those who have received transplants .\nwe herein report , to our knowledge , the first case of an immunodeficient patient with severe hemorrhagic colitis associated with the reactivation of both ebv and cmv , and whose endoscopic findings mimicked ibd .\na 56-year - old man was diagnosed with severe aplastic anemia ( saa ) , showing pancytopenia and severe bone marrow hypocellularity ; therefore , he was treated with antithymocyte globulin ( atg ) and cyclosporine ( csp ) .\nafter 2 years of atg / csp therapy , he suddenly started passing bloody diarrhea and developed a high fever .\nblood tests revealed the following results : hemoglobin level 4.2 g / dl , platelet count 3.7 10 cells / l , and white blood cell count 3,230 cells / l .\nthe patient 's c - reactive protein level was 4.7 mg / dl and serum cmv antigen c7-hrp was positive in 2/50,000 cells .\nwe initially thought the colitis to be associated with cmv infection because of the endoscopic features and positive result for serum cmv antigen in spite of negative results obtained using immunohistochemical analysis .\ntherefore , the patient was treated with ganciclovir for 2 weeks ; however , his symptoms did not resolve .\nhowever , his symptoms persisted for the next 2 weeks . therefore , assuming a potential misdiagnosis , a second colonoscopy was performed , which showed multiple deep ulcerations ( fig .\n2b ) , and in situ hybridization revealed ebv - encoded small rna-1 ( eber-1)-positive cells ( fig . 2c ) . additionally , serum c7-hrp was positive in 33/50,000 cells , and both blood and colon tissues were positive for ebv dna , which was detected using pcr analysis .\nwe finally diagnosed the patient with colitis associated with the reactivation of cmv and ebv .\nafter cessation of csp and treatment with gamma globulin and ganciclovir , his symptoms resolved .\na subsequent blood sample was negative for ebv dna , and colon cells were negative for eber-1 , but positive for ebv dna .\ninterestingly , 6 months after the first remission , the patient had a recurrence of severe bloody diarrhea after an increase in the csp dose .\nboth blood and colon tissues were positive for ebv dna and a colon biopsy showed eber-1-positive cells ; however , we did not detect cmv reactivation .\nafter a second round of treatment with gamma globulin and ganciclovir and cessation of csp , his symptoms resolved . the patient has had no abdominal symptoms for 1.5 years with the scheduled antiviral treatments and after cessation of csp .\nto our knowledge , this is the first reported case of severe colitis associated with reactivation of both ebv and cmv in a patient with saa after atg / csp therapy .\nebv primary infected b cells , cmv was designed to enter monocytes besides lymphocytes , whereas both of them also infected epithelial cells .\nreactivation of ebv or cmv after atg / csp therapy has been reported in patients with saa [ 1 , 2 ] . after atg / csp therapy in patients with saa , ebv reactivation occurred in 87% and cmv reactivation in 33%\n. however , reactivation of both these viruses has not been reported , and the clinical features are not well known . in this case , we have several reasons to associate ebv with the severe colitis : the serum samples from the patient were positive for ebv dna and the colonic tissue showed the presence of eber-1-positive cells on in situ hybridization . in contrast , at the time of colitis remission , neither ebv dna in the blood nor eber-1-positive cells in the colon were detected .\ninterestingly , the patient had two colitis attacks with identical clinical symptoms and ebv results . therefore , colitis likely reflects ebv reactivation , which is indicated by the presence of ebv dna in the blood and eber-1-positive cells in the colon .\nthere is only one report of ebv colitis after atg therapy , however ebv and cmv colitis after atg therapy have never been reported . in the case of this patient\n, it was necessary to distinguish severe colitis from other ebv - associated diseases , including chronic active ebv infection , ebv - associated t / natural killer cell lymphoproliferative disorder ( ebv - t / nk - lpd ) and ebv - associated lymphomagenesis .\nthis case did not satisfy chronic active ebv infection guidelines for diagnosis of lymphomagenesis [ 6 , 7 ] .\nebv - t / nk - lpd has 4 categories : a1 , a2 , a3 and b .\nohshima et al . reported that ebv - t / nk - lpd could develop into category a1 ( smoldering ) , a2 ( chronic ) or a3 ( leukemia / lymphoma ) .\nour patient was successfully treated twice with antiviral drugs only and after cessation of csp treatment and without the use of chemotherapy such as rituximab .\nin addition , he had no recurrence of symptoms for 1.5 years after treatment . therefore , this case was considered category a1 , i.e. smoldering ebv - t / nk - lpd . however , careful follow - up is necessary as colitis is not a well - known symptom of ebv - t / nk - lpd .\nthere have been some reports of ebv / cmv infection in patients with ibd [ 9 , 10 , 11 ] . those studies used pcr analysis to show the presence of ebv in gastrointestinal tissue from patients with ibd . however , these reports never used immunohistochemical analysis or tested blood samples to detect the presence of ebv dna .\nweinberg et al . reported the difficulty of differentiating between ebv - associated diarrhea and ibd .\nbesides , the mechanisms of ulcer formation and the differences in endoscopic features caused by ebv are not well understood . in the future ,\nmore case studies are necessary to differentiate ebv - associated intestinal diseases from ibd in patients with ebv infections . in conclusion , to our knowledge , this is the first reported case of a patient with saa who developed severe hemorrhagic colitis owing to the reactivation of both ebv and cmv ." }, { "role": "assistant", "content": "epstein - barr virus ( ebv ) and cytomegalovirus ( cmv ) are members of the herpesvirus family and common causes of viral infection in humans . \n cmv infection of the gastrointestinal tract occurs mainly in immunocompromised individuals , on the other hand ebv infection and reactivation involving the gastrointestinal tract is very rare . \n a 56-year - old man was diagnosed with severe aplastic anemia and treated with antithymocyte globulin ( atg ) and cyclosporine ( csp ) . \n after 2 years of atg / csp therapy , he suddenly started passing bloody diarrhea and developed a high fever despite csp treatment . \n endoscopic features included severe edema and multiple superficial ulcers ; the patient was initially diagnosed with severe colitis resembling inflammatory bowel disease ( ibd ) \n . however , his symptoms did not resolve with steroid treatment . \n immunohistochemical analysis of samples obtained from a second colonoscopy showed cells positive for cmv , and in situ hybridization revealed ebv - encoded small rna-1-positive cells . \n additionally , the patient 's serum was positive for c7-hrp , and both blood and colon tissues were positive for ebv dna , which was detected using pcr analysis . \n we finally diagnosed the patient with colitis associated with reactivation of both cmv and ebv . \n the patient remains diarrhea - free after 1.5 years with scheduled globulin treatment and after cessation of immunosuppressive drug therapy . \n to our knowledge , this is the first reported case of an immunodeficient patient with severe hemorrhagic colitis that was associated with reactivation of both ebv and cmv , and whose endoscopic findings mimicked ibd ." } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nBACKGROUND: Little is known about the coronavirus SARS-CoV-2 disease (COVID-19) in solid organ transplanted patients. We here report a series of heart transplanted patients with COVID-19 from two centers of Italy. METHODS: All heart transplanted patients of Transplant Centers of Bergamo and Torino with a microbiologically confirmed SARS-CoV-2 infection were enrolled. Data collection included clinical presentation, laboratory and radiological findings, treatment and outcome. Follow-up was performed by visit or phone. RESULTS: From February to March 2020 twenty-six heart transplanted patients (age 62+/-12 years; 77% males; time from transplant 10+/-10 years; 69% with comorbidities) had a microbiologically confirmed COVID-19. The most frequent symptom was fever, followed by cough. Seventeen patients had a pneumonia, 8 of them severe pneumonia. Seven patients died (27%) and 17 (65%) were hospitalized. Discontinuation of immunosuppression was associated with death (71 vs 21%, p=0.02). Conversely, all patients receiving steroids survived (p<0.001). Patients who received heart transplantation during COVID-19 outbreak survived and no acute graft rejection occurred. Patients who died were older than survivors, had a longer time from transplant and a worse clinical presentation at diagnosis. The current regimen enabled the prolonged survival and function of orthotopic cardiac xenografts in altogether 6 of 8 baboons, of which 4 were now added. These results exceed the threshold set by the Advisory Board of the International Society for Heart and Lung Transplantation. CONCLUSIONS: COVID-19 has a significant impact on long term heart transplanted patients. Conversely, SARS-CoV-2 infection seems to have a limited influence on more recent transplants. Our experience may suggest that heart transplantation programs can be maintained even during the pandemic phase if specific and tailored paths to prevent and to limit virus transmission are provided." }, { "role": "assistant", "content": "[\"Treatment\", \"Prevention\"]" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nThere is a heightened concern for exposure to infectious aerosols during the intubation of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) patients. We took our previously designed portable, inexpensive, and easily constructed device and modified it for the prehospital setting. Using polyvinyl chloride pipe and automobile collision wrap, a prehospital unit can be constructed in less than 30 minutes, and the cost of material is under 50 U.S. dollars. The box stores easily in an ambulance and can be assembled on the scene within two minutes. This easily built device likely provides some limited protection from aerosolization during video laryngoscopy and can be replicated easily." }, { "role": "assistant", "content": "[\"Prevention\"]" } ]

[ { "role": "user", "content": "You will be shown biomedical passages and your task is to the answer the provided question. Provide a concise and accurate response and do not include any additional text in the response other than the answer.\n\nQuestion: Is Huntington's disease caused by a dominate or recessive gene?\n\nContext: Huntington's Disease (HD) is an autosomal dominant neurodegenerative disease characterized by gradual deterioration of motor and cognitive functions and development of psychiatric deficits. Animal models provide powerful means to study the pathological\nHuntington's disease (HD) is an inherited NDD caused by autosomal-dominant expanded CAG trinucleotide repeat mutation in the gene coding for Huntingtin (Htt).\nHuntington's disease (HD) is an autosomal-dominant, progressive neurodegenerative disease characterized by movement disorder, psychiatric symptoms and cognitive decline.\nThe D4S10 locus, defined by the probe G8 and linked to the gene for Huntington's disease (HD), has permitted us to identify individuals with a high probability of being homozygous for this autosomal dominant neurodegenerative disorder.\nHuntington's disease is a fatal autosomal dominant neurodegenerative disease caused by an abnormal CAG expansion in huntingtin's gene.\nHuntington's disease is a fatal autosomal dominant neurodegenerative disease caused by an abnormal CAG expansion in huntingtin's gene\nHuntington's disease is an autosomal dominant neurodegenerative disease caused by a toxic gain of function mutation in the huntingtin gene (Htt)\nHuntington's disease (HD) is a late onset, incurable, autosomal dominantly-inherited, progressive neuropsychiatric disease, characterised by chorea, changes in personality, mood and behaviour, and dementia.\nHuntington's disease (HD) is a genetically dominant neurodegenerative condition caused by an unique mutation in the disease gene huntingtin.\nHuntington disease is an autosomal-dominant neurodegenerative disease of mid-life onset caused by expansion of a polymorphic trinucleotide (CAG) repeat.\nHuntington disease (HD) is a well-defined autosomal dominant neurodegenerative disease caused by CAG repeat expansions in HD gene." }, { "role": "assistant", "content": "dominant" } ]

[ { "role": "user", "content": "You will be shown sections from a scientific research paper, together with a question about the paper. Your task is to answer the question based on the contents of the paper. Your response should be a `json` object with two fields:\n\n\"answer\": An array of strings extracted directly from the paper which, collectively, answer the question.\n\"evidence\": An array of strings. Each should be an excerpt from the paper, in which one or more of the extracted answers can be found.\n\nFor instance, for the question \"What baselines did the authors compare against?\", a sample response might be:\n\n{\n \"answer\": [\"BERT\", \"RoBERTa\"],\n \"evidence\": [\"In our experiments, we compare the performance of our model against BERT and RoBERTa.\"]\n}\n\nDo not include any text in your response other than the json.\n\nIf the question is unanswerable given the provided excerpts, respond with the single word \"null\".\n\nPaper: Emotion helps Sentiment: A Multi-task Model for Sentiment and Emotion Analysis\n\nIn this paper, we propose a two-layered multi-task attention based neural network that performs sentiment analysis through emotion analysis. The proposed approach is based on Bidirectional Long Short-Term Memory and uses Distributional Thesaurus as a source of external knowledge to improve the sentiment and emotion prediction. The proposed system has two levels of attention to hierarchically build a meaningful representation. We evaluate our system on the benchmark dataset of SemEval 2016 Task 6 and also compare it with the state-of-the-art systems on Stance Sentiment Emotion Corpus. Experimental results show that the proposed system improves the performance of sentiment analysis by 3.2 F-score points on SemEval 2016 Task 6 dataset. Our network also boosts the performance of emotion analysis by 5 F-score points on Stance Sentiment Emotion Corpus.\n\nIntroduction\nThe emergence of social media sites with limited character constraint has ushered in a new style of communication. Twitter users within 280 characters per tweet share meaningful and informative messages. These short messages have a powerful impact on how we perceive and interact with other human beings. Their compact nature allows them to be transmitted efficiently and assimilated easily. These short messages can shape people's thought and opinion. This makes them an interesting and important area of study. Tweets are not only important for an individual but also for the companies, political parties or any organization. Companies can use tweets to gauge the performance of their products and predict market trends BIBREF0. The public opinion is particularly interesting for political parties as it gives them an idea of voter's inclination and their support. Sentiment and emotion analysis can help to gauge product perception, predict stock prices and model public opinions BIBREF1.\nSentiment analysis BIBREF2 is an important area of research in natural language processing (NLP) where we automatically determine the sentiments (positive, negative, neutral). Emotion analysis focuses on the extraction of predefined emotion from documents. Discrete emotions BIBREF3, BIBREF4 are often classified into anger, anticipation, disgust, fear, joy, sadness, surprise and trust. Sentiments and emotions are subjective and hence they are understood similarly and often used interchangeably. This is also mostly because both emotions and sentiments refer to experiences that result from the combined influences of the biological, the cognitive, and the social BIBREF5. However, emotions are brief episodes and are shorter in length BIBREF6, whereas sentiments are formed and retained for a longer period. Moreover, emotions are not always target-centric whereas sentiments are directed. Another difference between emotion and sentiment is that a sentence or a document may contain multiple emotions but a single overall sentiment.\nPrior studies show that sentiment and emotion are generally tackled as two separate problems. Although sentiment and emotion are not exactly the same, they are closely related. Emotions, like joy and trust, intrinsically have an association with a positive sentiment. Similarly, anger, disgust, fear and sadness have a negative tone. Moreover, sentiment analysis alone is insufficient at times in imparting complete information. A negative sentiment can arise due to anger, disgust, fear, sadness or a combination of these. Information about emotion along with sentiment helps to better understand the state of the person or object. The close association of emotion with sentiment motivates us to build a system for sentiment analysis using the information obtained from emotion analysis.\nIn this paper, we put forward a robust two-layered multi-task attention based neural network which performs sentiment analysis and emotion analysis simultaneously. The model uses two levels of attention - the first primary attention builds the best representation for each word using Distributional Thesaurus and the secondary attention mechanism creates the final sentence level representation. The system builds the representation hierarchically which gives it a good intuitive working insight. We perform several experiments to evaluate the usefulness of primary attention mechanism. Experimental results show that the two-layered multi-task system for sentiment analysis which uses emotion analysis as an auxiliary task improves over the existing state-of-the-art system of SemEval 2016 Task 6 BIBREF7.\nThe main contributions of the current work are two-fold: a) We propose a novel two-layered multi-task attention based system for joint sentiment and emotion analysis. This system has two levels of attention which builds a hierarchical representation. This provides an intuitive explanation of its working; b) We empirically show that emotion analysis is relevant and useful in sentiment analysis. The multi-task system utilizing fine-grained information of emotion analysis performs better than the single task system of sentiment analysis.\n\nProposed Methodology\nWe propose a novel two-layered multi-task attention based neural network for sentiment analysis where emotion analysis is utilized to improve its efficiency. Figure FIGREF1 illustrates the overall architecture of the proposed multi-task system. The proposed system consists of a Bi-directional Long Short-Term Memory (BiLSTM) BIBREF16, a two-level attention mechanism BIBREF29, BIBREF30 and a shared representation for emotion and sentiment analysis tasks. The BiLSTM encodes the word representation of each word. This representation is shared between the subsystems of sentiment and emotion analysis. Each of the shared representations is then fed to the primary attention mechanism of both the subsystems. The primary attention mechanism finds the best representation for each word for each task. The secondary attention mechanism acts on top of the primary attention to extract the best sentence representation by focusing on the suitable context for each task. Finally, the representations of both the tasks are fed to two different feed-forward neural networks to produce two outputs - one for sentiment analysis and one for emotion analysis. Each component is explained in the subsequent subsections.\n\nProposed Methodology ::: Two-Layered Multi-Task Attention Model ::: Sentence Attention\nThe sentence attention (secondary attention) part focuses on each word of the sentence and assigns the attention coefficients. The attention coefficients are assigned on the basis of words' importance and their contextual relevance. This helps the model to build the overall sentence representation by capturing the context while weighing different word representations individually. The final sentence representation is obtained by multiplying each word vector representation with their attention coefficient and summing them over. The attention coefficient $\\alpha _t$ for each word vector representation and the sentence representation $\\widehat{H}$ are calculated as:\nwhere $W_s$ and $b_{s}$ are parameters to be learned.\n$\\widehat{H}$ denotes the sentence representation for sentiment analysis. Similarly, we calculate $\\bar{H}$ which represents the sentence for emotion classification. The system has the flexibility to compute different representations for sentiment and emotion analysis both.\n\nProposed Methodology ::: Distributional Thesaurus\nDistributional Thesaurus (DT) BIBREF31 ranks words according to their semantic similarity. It is a resource which produces a list of words in decreasing order of their similarity for each word. We use the DT to expand each word of the sentence. The top-4 words serve as the candidate terms for each word. For example, the candidate terms for the word good are: great, nice awesome and superb. DT offers the primary attention mechanism external knowledge in the form of candidate terms. It assists the system to perform better when presented with unseen words during testing as the unseen words could have been a part of the DT expansion list. For example, the system may not come across the word superb during training but it can appear in the test set. Since the system has already seen the word superb in the DT expansion list of the word good, it can handle this case efficiently. This fact is established by our evaluation results as the model performs better when the DT expansion and primary attentions are a part of the final multi-task system.\n\nDatasets, Experiments and Analysis\nIn this section we present the details of the datasets used for the experiments, results that we obtain and the necessary analysis.\n\nDatasets, Experiments and Analysis ::: Results and Analysis\nWe compare the performance of our proposed system with the state-of-the-art systems of SemEval 2016 Task 6 and the systems of BIBREF15. Experimental results show that the proposed system improves the existing state-of-the-art systems for sentiment and emotion analysis. We summarize the results of evaluation in Table TABREF18.\nThe primary attention mechanism plays a key role in the overall system as it improves the score of both sentiment and emotion analysis in both single task as well as multi-task systems. The use of primary attention improves the performance of single task systems for sentiment and emotion analysis by 2.21 and 1.72 points, respectively.Similarly, when sentiment and emotion analysis are jointly performed the primary attention mechanism improves the score by 0.93 and 2.42 points for sentiment and emotion task, respectively. To further measure the usefulness of the primary attention mechanism and the Distributional Thesaurus, we remove it from the systems S2, E2, and M2 to get the systems S1, E1, and M1. In all the cases, with the removal of primary attention mechanism, the performance drops. This is clearly illustrated in Figure FIGREF21. These observations indicate that the primary attention mechanism is an important component of the two-layered multi-task attention based network for sentiment analysis. We also perform t-test BIBREF40 for computing statistical significance of the obtained results from the final two-layered multi-task system M2 for sentiment analysis by calculating the p-values and observe that the performance gain over M1 is significant with p-value = 0.001495. Similarly, we perform the statistical significance test for each emotion class. The p-values for anger, anticipation, fear, disgust, joy, sadness, surprise and trust are 0.000002, 0.000143, 0.00403, 0.000015, 0.004607, 0.069, 0.000001 and 0.000001, respectively. These results provide a good indication of statistical significance.\nTable TABREF19 shows the comparison of our proposed system with the existing state-of-the-art system of SemEval 2016 Task 6 for the sentiment dataset. BIBREF7 used feature-based SVM, BIBREF39 used keyword rules, LitisMind relied on hashtag rules on external data, BIBREF38 utilized a combination of sentiment classifiers and rules, whereas BIBREF37 used a maximum entropy classifier with domain-specific features. Our system comfortably surpasses the existing best system at SemEval. Our system manages to improve the existing best system of SemEval 2016 task 6 by 3.2 F-score points for sentiment analysis.\nWe also compare our system with the state-of-the-art systems proposed by BIBREF15 on the emotion dataset. The comparison is demonstrated in Table TABREF22. Maximum entropy, SVM, LSTM, Bi-LSTM, and CNN were the five individual systems used by BIBREF15. Overall, our proposed system achieves an improvement of 5 F-Score points over the existing state-of-the-art system for emotion analysis. Individually, the proposed system improves the existing F-scores for all the emotions except surprise. The findings of BIBREF15 also support this behavior (i.e. worst result for the surprise class). This could be attributed to the data scarcity and a very low agreement between the annotators for the emotion surprise.\nExperimental results indicate that the multi-task system which uses fine-grained information of emotion analysis helps to boost the performance of sentiment analysis. The system M1 comprises of the system S1 performing the main task (sentiment analysis) with E1 undertaking the auxiliary task (emotion analysis). Similarly, the system M2 is made up of S2 and E2 where S2 performs the main task (sentiment analysis) and E2 commits to the auxiliary task (emotion analysis). We observe that in both the situations, the auxiliary task, i.e. emotional information increases the performance of the main task, i.e. sentiment analysis when these two are jointly performed. Experimental results help us to establish the fact that emotion analysis benefits sentiment analysis. The implicit sentiment attached to the emotion words assists the multi-task system. Emotion such as joy and trust are inherently associated with a positive sentiment whereas, anger, disgust, fear and sadness bear a negative sentiment. Figure FIGREF21 illustrates the performance of various models for sentiment analysis.\nAs a concrete example which justifies the utility of emotion analysis in sentiment analysis is shown below.\n@realMessi he is a real sportsman and deserves to be the skipper.\nThe gold labels for the example are anticipation, joy and trust emotion with a positive sentiment. Our system S2 (single task system for sentiment analysis with primary and secondary attention) had incorrectly labeled this example with a negative sentiment and the E2 system (single task system with both primary and secondary attention for emotion analysis) had tagged it with anticipation and joy only. However, M2 i.e. the multi-task system for joint sentiment and emotion analysis had correctly classified the sentiment as positive and assigned all the correct emotion tags. It predicted the trust emotion tag, in addition to anticipation and joy (which were predicted earlier by E2). This helped M2 to correctly identify the positive sentiment of the example. The presence of emotional information helped the system to alter its sentiment decision (negative by S2) as it had better understanding of the text.\nA sentiment directly does not invoke a particular emotion always and a sentiment can be associated with more than one emotion. However, emotions like joy and trust are associated with positive sentiment mostly whereas, anger, disgust and sadness are associated with negative sentiment particularly. This might be the reason of the extra sentiment information not helping the multi-task system for emotion analysis and hence, a decreased performance for emotion analysis in the multi-task setting.\n\nAcknowledgements\nAsif Ekbal acknowledges the Young Faculty Research Fellowship (YFRF), supported by Visvesvaraya PhD scheme for Electronics and IT, Ministry of Electronics and Information Technology (MeitY), Government of India, being implemented by Digital India Corporation (formerly Media Lab Asia).\n\nTABLE I DATASET STATISTICS OF SEMEVAL 2016 TASK 6 AND SSEC USED FOR SENTIMENT AND EMOTION ANALYSIS, RESPECTIVELY.\n\nTABLE II F-SCORE OF VARIOUS MODELS ON SENTIMENT AND EMOTION TEST DATASET.\n\nTABLE III COMPARISON WITH THE STATE-OF-THE-ART SYSTEMS OF SEMEVAL 2016 TASK 6 ON SENTIMENT DATASET.\n\nQuestion: How is multi-tasking performed?" }, { "role": "assistant", "content": "{\"answer\": [\"The proposed system consists of a Bi-directional Long Short-Term Memory (BiLSTM) BIBREF16, a two-level attention mechanism BIBREF29, BIBREF30 and a shared representation for emotion and sentiment analysis tasks.\", \"Each of the shared representations is then fed to the primary attention mechanism\"], \"evidence\": [\"We propose a novel two-layered multi-task attention based neural network for sentiment analysis where emotion analysis is utilized to improve its efficiency. Figure FIGREF1 illustrates the overall architecture of the proposed multi-task system. The proposed system consists of a Bi-directional Long Short-Term Memory (BiLSTM) BIBREF16, a two-level attention mechanism BIBREF29, BIBREF30 and a shared representation for emotion and sentiment analysis tasks. The BiLSTM encodes the word representation of each word. This representation is shared between the subsystems of sentiment and emotion analysis. Each of the shared representations is then fed to the primary attention mechanism of both the subsystems. The primary attention mechanism finds the best representation for each word for each task. The secondary attention mechanism acts on top of the primary attention to extract the best sentence representation by focusing on the suitable context for each task. Finally, the representations of both the tasks are fed to two different feed-forward neural networks to produce two outputs - one for sentiment analysis and one for emotion analysis. Each component is explained in the subsequent subsections.\"]}" } ]

[ { "role": "user", "content": "You will be presented with the full text of a science research paper. Please write an abstract for this paper. Your response should include the abstract and no additional text.\n\nPaper text:\nin 1999 the first successful detection of optical polarization from a gamma - ray burst ( grb ) afterglow was obtained @xcite . since then , several polarimetric measurements of grb afterglows have been performed ( see @xcite and @xcite for a review ) . albeit being an observationally challenging task ,\nthe scientific community has shown wide interest in this field .\nindeed , polarization has a high diagnostic power over a broad range of physical processes , from the emission mechanisms to the fireball structure and the properties of the close and far environment of the burst .\nthe search for polarizion was driven by the hypothesis that the afterglow emission is due to synchrotron emission @xcite .\nits discovery , by itself , is now regarded as a strong evidence for this emission mechanism . for unresolved sources , like distant grb afterglows\n, polarimetry also offers a unique opportunity to probe the geometry of the system .\nin fact , in order to have a net nonzero polarization , some kind of asymmetry is required , provided for example by a collimated fireball .\ntime - resolved polarimetry is also a reliable tool to discriminate among different scenarios for the blastwave evolution .\nlast , polarimetry of grb afterglows also offers a direct way to study the interstellar medium around grb progenitors and in general along the line of sight .\nthe diagnostic power of polarimetry rests upon the characteristic time evolution of the polarization degree and position angle @xcite produced by an ultrarelativistic outflow . in the simplest case , the angular energy distribution is homogeneous .\nmore physical models consider more complex beam and magnetic field patterns @xcite .\nthese works show that , even if the light curve is barely affected by these parameters , the polarization and position angle evolutions change substantially ( fig .\n[ fig : polev ] ) . in the homogeneous jet ( hj ) model ,\nthe polarization curve has two maxima bracketting the jet break , and , more important , the polarization angle has a sudden rotation of 90@xmath0 at the same moment ( fig .\n[ fig : polev ] , dashed line ) . on the contrary\n, the structured jet ( sj ) model predicts that the maximum of the polarization curve is reached right at the time of the break in the light curve , the position angle keeping constant throughout the afterglow evolution ( fig .\n[ fig : polev ] , solid line ) . at early and late time\nthe polarization should essentially vanish in either cases .\nrotation for the position angle . from @xcite.[fig : polev],scaledwidth=70.0% ] this latter fact constitutes an important point because , indipendently of the model details , the prediction for the early - time polarization changes substantially if the fireball expansion is driven by a large - scale magnetic field .\nthis important issue has been recently developed and discussed , e.g. , by @xcite , @xcite and @xcite .\nlike hydrodynamic jets , magnetized ones can be homogeneous and structured .\nin any case , a non negligible degree of polarization at early times is expected , a strong difference with respect to purely hydrodynamical models . polarimetry may therefore be the most powerful available tool to investigate the fireball structure and its early dynamical evolution . from the observational point of view ,\nbesides several isolated measurements , a rich enough coverage of the polarization evolution could be obtained only in three cases : grb020813 @xcite , grb021004 @xcite , and grb030329 @xcite . however , firm conclusions could be derived only for grb020813 , the best available case for model testing .\nits light curve was remarkably smooth @xcite and a break in the light curve could be clearly singled out .\na bunch of polarimetric observations were carried out providing for the first time polarization data both before and after the light curve break time @xcite .\n@xcite , with a quantitative approach , carried out a formal analysis by taking into account both the dust - induced ( host galaxy + milky way ) and the intrinsic afterglow polarization .\nall current jet models were considered , including homogeneous and structured jets , with and without a coherent magnetic field .\nthe available dataset did not allow us to single out a unique best - fitting model .\nhowever , it was possible to rule out homogeneous jet models at a confidence level larger than @xmath1 , mainly due to the lack of the predicted @xmath2 position angle rotation .\nthis is an important result with possible consequences for the use of grbs as probes for cosmology structure studies .\nall magnetized models and structured jets fit satisfactorily the data , the ambiguity being mainly due to the lack of early - time measurements , i.e. when the magnetization properties mostly matter ( fig .\n[ fig:020813 ] ) . ,\nsince the beginning of afterglow observations , it was apparent that a fraction of grbs ( the so - called dark grbs ) did not show any detectable optical counterpart , the first example being grb970828 @xcite .\nreaction times and sensitivity have constantly improved , allowing faster and deeper searches , and the dark grb fraction has continuously decreased . also , the definition of `` darkness '' is subject to discussion .\nlikely , a good classification should make use of information from other bands ( especially the x rays ; @xcite ) , in order to individuate anomalies in the spectral shape and single out the events with an optical deficit .\nthe x - ray radiation is in fact much less affected by extinction , and does not suffer from ly@xmath3 suppression at large redshifts .\nmoreover , from the observational point of view , an x - ray afterglow was discovered in virtually all cases .\nseveral solutions are viable to explain the existence of dark bursts , and probably more than one mechanism is at work .\nthe simplest idea is that dark grbs have just very faint afterglows @xcite , due perhaps to the different conditions in the environment or in the emission mechanism .\nthis hypothesis is supported by the analysis of bepposax x - ray data @xcite .\nanother possibility is that these afterglows are heavily extinguished by material along the line of sight @xcite , a likely possibility given the association between grbs and young stars @xcite .\nlast , an intriguing possibility is that some grbs are optically dark since they are at high redshift ( @xmath4 ) , so that the ly@xmath3 dropout suppresses visible radiation . in the last two cases , observing in the near infrared ( nir ) alleviates the problem , since this band is less affected by dust and dropout ( up to @xmath5 ) extinction . to tackle this issue , our group has undertaken an observing campaign devoted to detect and follow - up grb afterglows both in the optical and in the nir , in order to spot dark / faint / extinguished events .\nwe report here about three integral bursts .\nthe long - duration grb040223 had a peak flux of @xmath6 erg @xmath7 s@xmath8 ( @xmath9 kev ; @xcite ) .\nfollowing the discovery of the x - ray afterglow by xmm - newton @xcite , we observed the field with the eso - ntt telescope at several epochs , in the @xmath10 filters . despite our images\nare quite deep , no variable nir afterglow was detected @xcite .\nfigure [ fig : sed ] shows the nir - to - x - ray spectral energy distribution , showing that the @xmath11 datum lies well below the x - ray extrapolation ( dashed lines ) .\nalso , the presence of a break ( e.g. due to the cooling frequency ) can not explain the nir faintness : given the x - ray spectral index @xmath12 @xcite , in the standard syncrotron model the slope redward of the break should be @xmath13 ( dotted lines ) . even assuming that this break is just at the edge of the observed x - ray band , the nir point is still a factor at least @xmath14 below the extrapolation .\ngiven the large measured column density , @xmath15 @xmath7 , well in excess with respect to the galactic value , we therefore conclude that this burst is likely significantly extinguished ( s. covino et al . , manuscript in preparation ) .\nthis faint burst was observed by integral , lasting 8 s @xcite .\nvlt observations started very soon , just 2 hours after the grb , in the @xmath16 , @xmath17 , and @xmath11 bands . in this case , despite the large extinction and the field crowding , an afterglow could be discovered in the @xmath11 band @xcite .\nthis is one of the faintest objects ever detected , and only by promptly reacting with a large telescope could the afterglow be discovered .\na redshift is lacking for this event , thereby the energetics is unknown .\nhowever , a bright host galaxy ( @xmath18 , one of the brightest among grb hosts ) was discovered coincident with the afterglow , suggesting a closeby event .\nalso , the afterglow was quite faint when compared to its host galaxy ( being 2.3 mag brighter 2 h after the grb ) .\nall these facts suggest a very faint event , perhaps bridging classical grbs and dim events like grb980425 and grb031203 ( the `` w s '' ) .\nthis burst was also discovered by integral @xcite , showing no remarkable properties in its gamma - ray emission .\nunlike most integral triggers , it was not on the galactic plane , allowing more effective observations . in this case\n, an x - ray afterglow was discovered @xcite , in turn allowing the discovery of a nir transient by several groups @xcite .\nalso in this case , the afterglow was quite faint when compared with the host galaxy ( no redshift is available ) , suggesting an intrinsically faint event .\nanalysis of x - ray data @xcite showed a significant extinction ( @xmath19 @xmath7 , somewhat uncertain due to the unknown redshift ) , well in excess with respect to the galactic value .\nthis case may indeed be the best example of an extiguished grb .\noptical limits are consistent with this column .\nobservation of a large number of bursts is now possible , thanks to swift @xcite .\nmany swift afterglows are indeed among the faintest ever observed , promising to have soon a large sample . among these events\n, some will be just `` faint '' , and some will be extinguished .\ncoupling optical and x - ray observations will allow to clearly disentangle this issue , and to select really dark bursts , possibly at very high redshift ." }, { "role": "assistant", "content": "we review some open problems in the physics of afterglows , namely their polarization properties and the existence of dark / faint bursts . \n polarization studies yield precious insights in the physical structure and dynamical evolution of grb jets , revealing their magnetization properties and their energy profile . \n polarimetric observations of grb020813 already allowed to exclude a homogeneous jet for this event . \n we then present observations of faint / dark bursts , showing that some of them may be obscured by dust , while others are possibly just intrinsically dim ." } ]

[ { "role": "user", "content": "You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\".\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.\n\nFor instance, if the model were given the claim \"the COVID vaccine is safe for healthy adults\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults.\"]\n}\n\nClaim: Increased cellular immunity to sars-cov-2 in severe covid-19 patients\n\nAbstract:\nThe World Health Organization has declared SARS-CoV-2 virus outbreak a world-wide pandemic.\nIndividuals infected by the virus exhibited different degrees of symptoms, the basis of which remains largely unclear.\nCurrently, though convalescent individuals have been shown with both cellular and humoral immune responses, there is very limited understanding on the immune responses, especially adaptive immune responses, in patients with severe COVID-19.\nHere, we examined 10 blood samples from COVID-19 patients with acute respiratory distress syndrome (ARDS).\nThe majority of them (70%) mounted SARS-CoV-2-specific humoral immunity with production of neutralizing antibodies.\nHowever, compared to healthy controls, the percentages and absolute numbers of both NK cells and CD8+ T cells were significantly reduced, accompanied with decreased IFNg expression in CD4+ T cells in peripheral blood from severe patients.\nMost notably, we failed in detecting SARS-CoV-2-specific IFNg production by peripheral blood lymphocytes from these patients.\nOur work thus indicates that COVID-19 patients with severe symptoms are associated with defective cellular immunity, which not only provides insights on understanding the pathogenesis of COVID-19, but also has implications in developing an effective vaccine to SARS-CoV-2." }, { "role": "assistant", "content": "{\"verdict\": \"CONTRADICT\", \"evidence\": [\"Currently, though convalescent individuals have been shown with both cellular and humoral immune responses, there is very limited understanding on the immune responses, especially adaptive immune responses, in patients with severe COVID-19.\", \"However, compared to healthy controls, the percentages and absolute numbers of both NK cells and CD8+ T cells were significantly reduced, accompanied with decreased IFNg expression in CD4+ T cells in peripheral blood from severe patients.\", \"Most notably, we failed in detecting SARS-CoV-2-specific IFNg production by peripheral blood lymphocytes from these patients.\", \"Our work thus indicates that COVID-19 patients with severe symptoms are associated with defective cellular immunity, which not only provides insights on understanding the pathogenesis of COVID-19, but also has implications in developing an effective vaccine to SARS-CoV-2.\"]}" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research paper, followed by a question about the paper. Please extract text from the paragraph to answer the question. Do not include any text in your repsonse other than the answer.\n\nParagraph: Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess\n\nhttps://doi.org/10.3390/jcm9030657\n\nSHA: 0938d2fb07611897abf38cea727ddbeea77b73d9\n\nAuthors: Nishiura, Hiroshi\nDate: 2020\nDOI: 10.3390/jcm9030657\nLicense: cc-by\n\nAbstract: To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards. Text: An outbreak of novel coronavirus disease (COVID-19) has occurred on a cruise ship, the Diamond Princess [1] . The primary case remains unknown, but the index case, defined as the first identified case, is a passenger who started coughing from 19 January 2020 on board, disembarking the ship in Hong Kong on 25 January. As t he case was diagnosed on 1 February , the ship was requested to remain in the ocean near Yokohama from 3 February onwards. Subsequently, the movement of all passengers was restricted on board from 5 February, for a matter of 14 days of quarantine. Out of a total of 3711 persons (consisting of 2666 passengers and 1045 crew members), 199 symptomatic cases have been diagnosed on board as of 24 February, and additional asymptomatic infections and symptomatic cases after disembarkation have also been reported. One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2] . Using a sophisticated statistical model with doubly intervalcensored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3] . To understand the time-dependent risk of infection throughout the course of outbreak and estimate the effectiveness of the quarantine measure from 5 to 19 February 2020, I aimed to estimate the incidence of infection with COVID-19 and also predict the likely number of infections prevented by the quarantine measure. I analyzed the epidemic curve, ct, on day t, illustrated by the number of confirmed cases by the date of illness onset. The confirmatory diagnosis was made, using the reverse transcriptase polymerase chain reaction (RT-PCR). The date of illness onset was defined as the first date of fever. In addition to the date of illness onset, cases were classified by contact history inside the cabin and also by the type of membership, i.e., crew or passenger. Close contact was defined as having at least one cabinmate who was confirmed by RT-PCR. We estimate the number of cases by time of infection, it. Using the probability mass function of the incubation period of length s, fs, the incidence of infection is known to satisfy\n\nwhere E(.) represents the expected value. As for fs, it is known that the mean and standard deviation are 5.0 and 3.0 days, respectively, best fitted by lognormal distribution [3] . Employing a step function, the incidence of infection was statistically estimated via a maximum likelihood method. The estimation was implemented independently by the history of contact and type of membership. Regarding the real-time forecasting, we employed the so-called Richards model, an analogue to the generalized logistic model [4, 5] :\n\nwhere is the cumulative incidence on day t, Z is the cumulative incidence at the end of the outbreak, s is the parameter that governs the flexibility of the logistic curve, a is the early growth rate of cases and ti is the inflection point of the cumulative incidence curve. Assuming that the cumulative incidence is Gaussian distributed, four unknown parameters were estimated. The Richards model was fitted to two different datasets, i.e., (i) the dataset of the entire course of the epidemic and (ii) the dataset by 4 February 2020. The latter dataset corresponds to the time period without any impact of movement restriction that was in place from 5 February onwards. Figure 1 shows the epidemic curve by contact history and type of membership. The highest incidence of illness onset was observed on 7 February. The epidemic curve in a latter half period was dominated by crew members whose movement was not strictly controlled due to the need to continue service on the ship. The second dominating group was passengers with close contact history. The last illness onset date on board of a passenger without close contact was on 14 February. Estimating the incidence of infection, the peak incidence was identified for the period from 2 to 4 February among passengers both with and without close contact (Figure 2 ). The incidence of infection abruptly dropped after 5 February, the date of movement restriction. Among passengers without close contact, the incidence was estimated to be zero, except for 8-10 February 2020, during which 0.98 persons (95% confidence intervals (CI): 0, 7.74) per day were estimated to have been infected. The epidemic peak among crew members was seen for the period from 8 to 10 February 2020. Figure 3 compares the cumulative incidence with and without movement restriction policy from 5 February. In the presence of intervention, the cumulative incidence among passengers with and without close contact and crew members were 102, 47 and 48 cases, respectively, as of 24 February 2020. These were well realized by the Richards model. Without intervention from 5 February onwards, it was predicted that the cumulative incidence with and without close contact would have been 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively. A large outbreak of COVID-19 occurred on a cruise ship. Estimating the incidence, the peak time of infection was shown to have been from 2 to 4 February, and the incidence abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February, on which the movement restriction policy was imposed, and at most there was, on average, one case of infection per day from 8 to 10 February. Other than continued exposure among crew members, the estimated incidence in this study indicates that the movement restriction policy from 5 February 2020 was highly successful in greatly reducing the number of secondary transmissions on board. Based on an analysis of illness onset data on board (and before the disembarkation of a large number of passengers), the risk of infection among passengers without close contact was considered to be very limited Among disembarked passengers, symptomatic cases have started to be reported on the ground in and outside of Japan. In particular, cases arising from passengers without close contact indicate a possible pathway of infection via mechanisms that were not covered by the abovementioned analysis that relied on symptomatic cases. Although the transmission via direct human-to-human contact was prevented by movement restrictions, the role of other modes of transmission, e.g., environmental and asymptomatic transmissions, should be further explored. The author declares no conflict of interest.\n\nQuestion: When was the first passenger patient on the Diamond Princess cruise ship diagnosed with COVID-19?" }, { "role": "assistant", "content": "he case was diagnosed on 1 February" } ]

[ { "role": "user", "content": "Given a short query with keyphrases about a research idea in 2019 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.\n\nQuery: I want to train a fully supervised model for image classification.\n\nKeyphrases: image classification images paragraph-level\n\nDataset description:\nConvAI2: The ConvAI2 NeurIPS competition aimed at finding approaches to creating high-quality dialogue agents capable of meaningful open domain conversation. The ConvAI2 dataset for training models is based on the PERSONA-CHAT dataset.\nImageNet: The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.\nDCASE 2014: DCASE2014 is an audio classification benchmark.\nACDC: The goal of the Automated Cardiac Diagnosis Challenge (ACDC) challenge is to: compare the performance of automatic methods on the segmentation of the left ventricular endocardium and epicardium as the right ventricular endocardium for both end diastolic and end systolic phase instances; compare the performance of automatic methods for the classification of the examinations in five classes (normal case, heart failure with infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy, abnormal right ventricle). The overall ACDC dataset was created from real clinical exams acquired at the University Hospital of Dijon.\n\nOptions:- A: ConvAI2 B: ImageNet C: DCASE 2014 D: ACDC" }, { "role": "assistant", "content": "ImageNet" } ]

[ { "role": "user", "content": "You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: [\"UnapprovedDrug\", \"Drug\", \"DrugGroup\", \"Brand\"].\n\nPlease return the output as a JSON object of the format: {\"Brand\" : [\"Aspirin\", ...], \"DrugGroup\": [\"Salicyclate\", ...], \"Drug\": [\"Phenobarbital\", ...], \"UnapprovedDrug\": [\"Heroin\", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].\n\nOnly output the JSON object and do not include any additional text.\n\nAbstract:\n\nOral Anticoagulants: In some normal volunteers, the concomitant administration of diflunisal and warfarin, acenocoumarol, or phenprocoumon resulted in prolongation of prothrombin time. This may occur because diflunisal competitively displaces coumarins from protein binding sites. Accordingly, when diflunisal is administered with oral anticoagulants, the prothrombin time should be closely monitored during and for several days after concomitant drug administration. Adjustment of dosage of oral anticoagulants may be required. Tolbutamide: In diabetic patients receiving diflunisal and tolbutamide, no significant effects were seen on tolbutamide plasma levels or fasting blood glucose. Hydrochlorothiazide: In normal volunteers, concomitant administration of diflunisal and hydrochlorothiazide resulted in significantly increased plasma levels of hydrochlorothiazide. Diflunisal decreased the hyperuricemic effect of hydrochlorothiazide. Furosemide: In normal volunteers, the concomitant administration of diflunisal and furosemide had no effect on the diuretic activity of furosemide. Diflunisal decreased the hyperuricemic effect of furosemide. Antacids: Concomitant administration of antacids may reduce plasma levels of diflunisal. This effect is small with occasional doses of antacids, but may be clinically significant when antacids are used on a continuous schedule. Acetaminophen: In normal volunteers, concomitant administration of diflunisal and acetaminophen resulted in an approximate 50% increase in plasma levels of acetaminophen. Acetaminophen had no effect on plasma levels of diflunisal. Since acetaminophen in high doses has been associated with hepatotoxicity, concomitant administration of diflunisal and acetaminophen should be used cautiously, with careful monitoring of patients. Concomitant administration of diflunisal and acetaminophen in dogs, but not in rats, at approximately 2 times the recommended maximum human therapeutic dose of each (40 to 52 mg/kg/day of diflunisal/acetaminophen) resulted in greater gastrointestinal toxicity than when either drug was administered alone. The clinical significance of these findings has not been established. Methotrexate: Caution should be used if diflunisal is administered concomitantly with methotrexate. Nonsteroidal anti-inflammatory drugs have been reported to decrease the tubular secretion of methotrexate and to potentiate its toxicity. Cyclosporine: Administration of nonsteroial anti-inflammatory drugs concomitantly with cyclosporine has been associated with an increase in cyclosporine-induced toxicity, possibly due to decreased synthesis of renal prostacyclin. NSAIDs should be used with caution in patients taking cyclosporine, and renal function should be carefully monitored. Nonsteroidal Anti-Inflammatory Drugs: The administration of diflunisal to normal volunteers receiving indomethacin decreased the renal clearance and significantly increased the plasma levels of indomethacin. In some patients the combined use of indomethacin and diflunisal has been associated with fatal gastrointestinal hemorrhage. Therefore, indomethacin and diflunisal should not be used concomitantly. The concomitant use of diflunisal tablets and other NSAIDs is not recommended due to the increased possibility of gastrointestinal toxicity, with little or no increase in efficacy. The following information was obtained from studies in normal volunteers. Aspirin: In normal volunteers, a small decrease in diflunisal levels was observed when multiple doses of diflunisal and aspirin were administered concomitantly. Sulindac: The concomitant administration of diflunisal and sulindac in normal volunteers resulted in lowering of the plasma levels of the active sulindac sulfide metabolite by approximately one-third. Naproxen: The concomitant administration of diflunisal and naproxen in normal volunteers had no effect on the plasma levels of naproxen, but significantly decreased the urinary excretion of naproxen and its glucuronide metabolite. Naproxen had no effect on plasma levels of diflunisal. Drug laboratory Test Interactions Serum Salicylate Assays: Caution should be used in interpreting the results of serum salicylate assays when diflunisal is present. Salicylate levels have been found to be falsely elevated with some assay methods." }, { "role": "assistant", "content": "{\"Brand\": [\"aspirin\", \"Aspirin\"], \"Drug\": [\"naproxen\", \"Diflunisal\", \"diflunisal\", \"hydrochlorothiazide\", \"methotrexate\", \"phenprocoumon\", \"Hydrochlorothiazide\", \"furosemide\", \"warfarin\", \"Sulindac\", \"Cyclosporine\", \"acetaminophen\", \"Methotrexate\", \"acenocoumarol\", \"Tolbutamide\", \"Furosemide\", \"cyclosporine\", \"sulindac\", \"Naproxen\", \"indomethacin\", \"Acetaminophen\", \"tolbutamide\"], \"DrugGroup\": [\"Nonsteroidal Anti-Inflammatory Drugs\", \"antacids\", \"anticoagulants\", \"NSAIDs\", \"coumarins\", \"Anticoagulants\", \"Nonsteroidal anti-inflammatory drugs\", \"Salicylate\", \"nonsteroial anti-inflammatory drugs\", \"Antacids\"], \"UnapprovedDrug\": []}" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nSince the coronavirus disease 2019, called COVID-19, has overwhelmed the high-income countries with ample resources and established health-care system, we argue that there are plausible concerns why it may devastate the low-income countries like Pakistan. Focusing on Pakistan, we highlight the underlying reasons, eg, demographic features, ineffective health-care system, economic and political inequalities, corruption, and socio-cultural characteristics, that create fertile grounds for COVID-19 to overwhelm low-income countries. This study presents Pakistan's brief profile to demonstrate these underlying structures that may make low-income countries like Pakistan more vulnerable in the face of an unceasing COVID-19 pandemic. The study concludes that the country may make appropriate and possibly effective short-term preparedness measures to halt or slow the transmission of the virus, and deal with its current implications as well as it may pay significant attention to long-term measures to deal effectively with COVID-19's longer-term effects. These measures will help them, including Pakistan, to deal appropriately with a similar future critical event." }, { "role": "assistant", "content": "[\"Prevention\"]" } ]

[ { "role": "user", "content": "You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: [\"CellType\", \"Protein\", \"CellLine\", \"RNA\", \"DNA\"].\n\nPlease return the output as a JSON object of the format: {\"DNA\" : [\"TAL1\", ...], \"RNA\": [\"mRNAs\", ...], \"CellLine\": [\"T cells\", ...], \"CellType\": [\"monocytes\", ...], \"Protein\": [\"IL-2\", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].\n\nOnly output the JSON object and do not include any additional text.\n\nAbstract:\n\nCloning and expression of the glucocorticoid receptor from the squirrel monkey (Saimiri boliviensis boliviensis), a glucocorticoid-resistant primate. New World primates such as the squirrel monkey have elevated cortisol levels and glucocorticoid resistance. We have shown that the apparent binding affinity of the glucocorticoid receptor in squirrel monkey lymphocytes is 5-fold lower than that in human lymphocytes (apparent Kd, 20. 9 + /-1. 8 and 4. 3 + /-0. 2 nmol / L, respectively; n = 3), consistent with previous studies in mononuclear leukocytes isolated from the two species. As a first step in understanding the mechanism of decreased binding affinity in New World primates, we used reverse transcription-PCR to clone the glucocorticoid receptor from squirrel monkey liver and have compared the sequence to receptor sequences obtained from owl monkey liver, cotton-top tamarin B95-8 cells, and human lymphocytes. The squirrel monkey glucocorticoid receptor is approximately 97% identical in nucleotide and amino acid sequence to the human receptor. The ligand-binding domain (amino acids 528-777) of the squirrel monkey glucocorticoid receptor contains four amino acid differences (Ser551 to Thr, Ser616 to Ala, Ala618 to Ser, and Ile761 to Leu), all of which are present in owl monkey and cotton-top tamarin receptors. The DNA-binding domain (amino acids 421-486) is completely conserved among human, squirrel monkey, owl monkey, and cotton-top tamarin receptors. Twenty-two differences from the human sequence were found in the N-terminal region (amino acids 1-421) of the squirrel monkey receptor. None of the substitutions in the ligand-binding domain matched mutations known to influence binding affinity in other species. To determine whether the substitutions per se were responsible for decreased affinity, squirrel monkey and human glucocorticoid receptors were expressed in the TNT Coupled Reticulocyte Lysate System. Expressions of human and squirrel monkey glucocorticoid receptors and a squirrel monkey receptor in which Phe774 was mutated to Leu (F774L) were similar. When expressed in the TNT System, squirrel monkey and human glucocorticoid receptors had similar, high affinity binding for dexamethasone (apparent Kd, 5. 9 + /-1. 2 and 4. 3 + /-0. 5 nmol / L, respectively; n = 3), whereas the squirrel monkey F774L receptor had lower affinity binding (apparent Kd, 20. 4 + /-2. 0 nmol / L; n = 3). Thus, substitutions within the ligand-binding domain of the squirrel monkey glucocorticoid receptor can not account for the decreased binding affinity of these receptors in squirrel monkey cells. Rather, the binding affinity is probably influenced by the expression of cytosolic factors that affect glucocorticoid receptor function." }, { "role": "assistant", "content": "{\"CellLine\": [\"cotton - top tamarin B95 - 8 cells\"], \"CellType\": [\"mononuclear leukocytes\", \"squirrel monkey lymphocytes\", \"squirrel monkey cells\", \"human lymphocytes\"], \"DNA\": [], \"Protein\": [\"glucocorticoid receptor\", \"cytosolic factors\", \"ligand - binding domain\", \"N - terminal region\", \"owl monkey and cotton - top tamarin receptors\", \"squirrel monkey receptor\", \"human receptor\", \"human , squirrel monkey , owl monkey , and cotton - top tamarin receptors\", \"DNA - binding domain\", \"amino acids 528 - 777\", \"amino acids 421 - 486\", \"amino acids 1 - 421\", \"glucocorticoid receptors\", \"human glucocorticoid receptors\", \"squirrel monkey F774L receptor\"], \"RNA\": []}" } ]

[ { "role": "user", "content": "Given a short query with keyphrases about a research idea in 2020 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.\n\nQuery: This paper proposes a mobile manipulation system which integrates deep reinforcement learning with visual perception. It has an\n\nKeyphrases: mobile manipulation images depth maps\n\nDataset description:\nMuJoCo: MuJoCo (multi-joint dynamics with contact) is a physics engine used to implement environments to benchmark Reinforcement Learning methods.\nRL Unplugged: RL Unplugged is suite of benchmarks for offline reinforcement learning. The RL Unplugged is designed around the following considerations: to facilitate ease of use, the datasets are provided with a unified API which makes it easy for the practitioner to work with all data in the suite once a general pipeline has been established.\nHoME: HoME (Household Multimodal Environment) is a multimodal environment for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context. HoME integrates over 45,000 diverse 3D house layouts based on the SUNCG dataset, a scale which may facilitate learning, generalization, and transfer.\nFlightmare Simulator: Flightmare is composed of two main components: a configurable rendering engine built on Unity and a flexible physics engine for dynamics simulation. Those two components are totally decoupled and can run independently from each other.\n\nOptions:- A: MuJoCo B: RL Unplugged C: HoME D: Flightmare Simulator" }, { "role": "assistant", "content": "MuJoCo" } ]

[ { "role": "user", "content": "You will be presented with a citation segment from the section of a research paper. Classify the intent behind this citation by choosing from one of the following categories:\n\n- Method: Cites the paper for its methodology or procedure.\n- Background: Cites the paper to provide background information.\n- Result: Cites the paper for its findings or results.\n\nYour answer should be a single word from the following list of options: [\"Method\", \"Background\", \"Result\"]. Do not include any other text in your response.\n\nCitation sentence:\n\n%) fallow deer were positive to A. phagocytophylum DNA, however a work recently conducted by Michalik et al. (2009) on a population of 44 fallow deer living in West–Central Poland using only a PCR approach, showed a prevalence rate (20.5" }, { "role": "assistant", "content": "Result" } ]

[ { "role": "user", "content": "You will be shown a question, followed by excerpts from biomedical research papers. Please answer the question based on the provided context. Do not include any text in your response other than the answer.\n\nQuestion: Which is the function of the PRDM9 protein in mammals?\n\nContext: Developmental progress of germ cells through meiotic phases is closely tied to ongoing meiotic recombination. In mammals, recombination preferentially occurs in genomic regions known as hotspots; the protein that activates these hotspots is PRDM9,\nIn mammals, genetic recombination during meiosis is limited to a set of 1- to 2-kb regions termed hotspots. Their locations are predominantly determined by the zinc finger protein PRDM9, which binds to DNA in hotspots\nMeiotic recombination ensures proper segregation of homologous chromosomes and creates genetic variation. In many organisms, recombination occurs at limited sites, termed 'hotspots', whose positions in mammals are determined by PR domain member 9 (PRDM9)\nThese results, which provide the first detailed mapping of PRDM9 binding to DNA and, to our knowledge, the most detailed analysis yet of DNA binding by a long zinc-finger array, make clear that the binding specificities of PRDM9, and possibly other long-array zinc-finger proteins, are unusually complex.\nPRDM9 is a major determinant of meiotic recombination hotspots in humans and mice.\nHere, we demonstrate that a major player for hotspot specification is the Prdm9 gene.\nDuring mammalian meiosis, double-strand breaks are deliberately made throughout the genome and then repaired, leading to the exchange of genetic material between copies of chromosomes. How the locations of breaks are specified was largely unknown until a fortuitous confluence of statistical genetics and molecular biology uncovered the role of PRDM9, a DNA binding protein\nIn many mammals, including humans and mice, the zinc finger histone methyltransferase PRDM9 performs the first step in meiotic recombination by specifying the locations of hotspots, the sites of genetic recombination.\nThese results, together with the fact that PRDM9 is the only known mammalian histone methyltransferase with both H3K4 and H3K36 trimethylation activity, suggest that trimethylation of H3K36 plays an important role in the recombination process." }, { "role": "assistant", "content": "PRDM9 is a major determinant of meiotic recombination hotspots in humans and mice. Here, we demonstrate that a major player for hotspot specification is the Prdm9 gene. In many organisms, recombination occurs at limited sites, termed 'hotspots', whose positions in mammals are determined by PR domain member 9 ( PRDM9). In mammals, genetic recombination during meiosis is limited to a set of 1- to 2-kb regions termed hotspots. Developmental progress of germ cells through meiotic phases is closely tied to ongoing meiotic recombination. In many mammals, including humans and mice, the zinc finger histone methyltransferase PRDM9 performs the first step in meiotic recombination by specifying the locations of hotspots, the sites of genetic recombination. Developmental progress of germ cells through meiotic phases is closely tied to ongoing meiotic recombination. In mammals, recombination preferentially occurs in genomic regions known as hotspots; the protein that activates these hotspots is PRDM9,. In mammals, genetic recombination during meiosis is limited to a set of 1- to 2-kb regions termed hotspots. in mammals , recombination preferentially occurs in genomic regions known as hotspots. the protein that activates these hotspots is prdm9 meiotic recombination" } ]

[ { "role": "user", "content": "You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:\n\n- \"verdict\": The fact-checking verdict. If the information in the abstract supports the claim, write \"SUPPORT\". If the abstract contradicts the claim, write \"CONTRADICT\". If the abstract does not provide enough information to arrive at a verdict, write \"NEI\" (for \"not enough information\").\n- \"evidence\": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was \"NEI\", then return an empty array.\n\nFor instance, if the model were given the claim \"wearing masks can prevent the spread of COVID\", the output might be\n{\n \"verdict\": \"SUPPORT\",\n \"evidence\": [\"Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19.\"]\n}\n\nClaim: There is no proof vitamin c can treat or cure coronavirus.\n\nAbstract:\nOBJECTIVE Coronavirus disease 2019 (COVID-19) is a fatal and fast-spreading viral infection.\nTo date, the number of COVID-19 patients worldwide has crossed over six million with over three hundred and seventy thousand deaths (according to the data from World Health Organization; updated on 2 June 2020).\nAlthough COVID-19 can be rapidly diagnosed, efficient clinical treatment of COVID-19 remains unavailable, resulting in high fatality.\nSome clinical trials have identified vitamin C (VC) as a potent compound pneumonia management.\nIn addition, glycyrrhizic acid (GA) is clinically as an anti-inflammatory medicine against pneumonia-induced inflammatory stress.\nWe hypothesized that the combination of VC and GA is a potential option for treating COVID-19.\nMETHODS The aim of this study was to determine pharmacological targets and molecular mechanisms of VC + GA treatment for COVID-19, using bioinformational network pharmacology.\nRESULTS We uncovered optimal targets, biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of VC + GA against COVID-19.\nOur findings suggested that combinatorial VC and GA treatment for COVID-19 was associated with elevation of immunity and suppression of inflammatory stress, including activation of the T cell receptor signaling pathway, regulation of Fc gamma R-mediated phagocytosis, ErbB signaling pathway and vascular endothelial growth factor signaling pathway.\nWe also identified 17 core targets of VC + GA, which suggest as antimicrobial function.\nCONCLUSIONS For the first time, our study uncovered the pharmacological mechanism underlying combined VC and GA treatment for COVID-19.\nThese results should benefit efforts to address the most pressing problem currently facing the world." }, { "role": "assistant", "content": "{\"verdict\": \"SUPPORT\", \"evidence\": [\"Although COVID-19 can be rapidly diagnosed, efficient clinical treatment of COVID-19 remains unavailable, resulting in high fatality.\"]}" } ]

[ { "role": "user", "content": "You will be presented with the full text of a biomedical research paper. Please write an abstract for this paper. Your response should include the abstract and no additional text.\n\nPaper text:\nthe study was conducted in the department of oral medicine and radiology and a cancer centre .\nthe total sample consisting of 90 individuals was divided into a study group of 60 individuals and a control group of 30 individuals .\nthe study group had 60 oscc patients ( both male and female ) between the ages of 25 and 75 years with histologically proven oral cancer but before onset of any form of treatment .\nindividuals with other malignancies , liver disease , tuberculosis , diabetes mellitus , cardiovascular diseases , or any other chronic systemic diseases were excluded from the study .\na group of 30 healthy volunteers aged 2575 years without any history of debilitating systemic illness and no history of tobacco or alcohol consumption formed the control .\ndetails of the study are explained to the volunteers and written informed consent is obtained .\nserum l - fucose level was estimated using clinical chemistry autoanalyzer based on winzler method .\nchicago : spss inc .. to compare the mean values between two groups ( between genders ) , independent samples t - test was used . to compare the mean values between three or more groups ( stages of cancer ) , one - way anova was used .\nchicago : spss inc .. to compare the mean values between two groups ( between genders ) , independent samples t - test was used . to compare the mean values between three or more groups ( stages of cancer ) , one - way anova was used .\na comparison of the overall serum l - fucose levels between the oscc patients and healthy controls showed the mean value of serum l - fucose levels of oscc patients to be 10.85 mg / dl and the healthy controls had 3.47 mg / dl , thereby showing a difference of 7.38 mg / dl .\nstatistical analysis revealed a significant p value ( p < 0.001 ) [ graph 1 ] .\nserum level of levo - fucose between oral cancer and healthy individuals among the 60 oscc , 2 belong to stage i with a mean serum l - fucose level of 8.13 mg / dl .\nthe serum l - fucose level progressively increased with its level being 9.18 mg / dl in stage ii , 10.53 mg / dl in stage iii , and 11.59 mg / dl in stage iv .\nstage iv showed the highest level with a maximum value of 12.54 mg / dl and minimum of 10.55 mg / dl .\nstatistical analysis shows a significant p value ( p < 0.001 ) [ table 1 ] .\nserum level of l - fucose in various stages of oral cancer an attempt to correlate the serum l - fucose levels with histopathological grading between genders and ages yielded no significant results thereby inferring that serum l - fucose levels are directly indicative of the degree of tissue destruction .\ngroup of neoplasms affecting any region of the oral cavity is termed as oral cancer , among which oscc represents > 90% of all the neoplasm .\nrecently , the knowledge about cancer biomarkers has increased , and numerous studies have been carried out regarding these .\nthis has paved the way for improving the management of cancer patients by enhancing the accuracy of detection and efficacy of treatment .\nunderstanding the relevance of biomarkers before using them is very important for diagnosis , treatment , and proper follow - up .\ntumor markers are produced either by the tumor itself , as a tumor by product , by the body in response to the presence of cancer or certain benign ( noncancerous ) conditions .\nthese can aid in the diagnosis of cancer and in the assessment of tumor burden .\nl - fucose is a monosaccharide , which is a common component of many n- and o - linked glycans and glycolipids produced by mammalian cells .\nlack of a hydroxyl group on the carbon at the 6-position ( c-6 ) and the l - configuration is the two structural features which help to distinguish fucose from other six - carbon sugars present in mammals .\nit is the most essential sugars that the body demands for normal cell - to - cell communication .\nphysiologically , the concentrations in serum are less but are increased in cancer and other diseases .\nit is important in many of the signaling pathways which turns a healthy cell into a dysplastic cell .\nthe protein diversity is achieved by varying sequence and structure of sugar moieties or glycan attachment .\nmammalian cells either express or mediate many of their properties through the cell surface . change in glycosylation of cell surface proteins\nis essential in tumor progression , especially the terminal epitopes of glycoproteins , which have been proposed to play an essential role in cell cell interactions , cell adhesion , malignant transformation , and metastasis .\nfucosylation of glycoproteins ( the addition of l - fucose at the terminal end of the oligosaccharide chain ) is one of the most important features that mediate several specific biologic functions .\ntumor cells alter their surface by increasing fucosylation levels to escape recognition ; this contributes to numerous abnormal characteristics of tumor cells such as decreased adhesion and uncontrolled tumor growth .\nseveral studies have suggested that estimating the serum / tissue fucose levels could be a promising approach for the early detection , diagnosis , and prognosis of various cancer types .\ngroup of enzymes catalyze incorporation of fucose from activated nucleotide donor guanosine diphosphate - fucose to the reducing end of complex glycans in a linkage - specific manner .\nthese enzymes are expressed in many tissues and are elevated in serum and tumors of cancer patients .\nit has been mentioned in the article that increased fucosylation is associated with elevated fuct activity .\ncancer cells which are shed or released into circulation from the primary tumor often overexpress fucosylated glycans on their surface .\nthe expression of fucosylated glycoproteins ( i.e. , fucoproteins ) has been detected by means of specific lectins .\nprofound fucosylation of the serum microenvironment may be a reason that interrupts adhesion and induces the formation of metastases ( for example ) , several fucose - containing natural ligands \nincreased expression of fucosylated cell surface antigens , such as lewis x / y ( lex / y ) or sialyl lex/ , and the upregulation of 1 , 3/4-fuct have been associated with malignant transformation and increased metastatic potential of tumors , which leads to poor prognosis of patients with cancer .\n-l - fucosidase is a lysosomal enzyme that catalyzes the hydrolytic cleavage of terminal fucose residue that is involved in maintaining the homeostasis of fucose metabolism .\nextensive studies on the nature of metastasis have shown that only a small subpopulation of cells in tumors possess the characteristics necessary for their release from the primary tumor and transport to and establishment of tumor foci in distant organs .\ncarbohydrate moieties on cell surface glycoconjugates play an important role in this metastatic spread since it could be demonstrated that they are involved in adhesion processes .\nseveral studies have mentioned that estimation of serum l - fucose levels could be a reassuring approach for the early detection , diagnosis , and prognosis of various types of cancer including oral carcinoma .\nthus , the present study was undertaken to estimate the serum level of l - fucose ( tumor marker ) among various tnm stages in oral cancer patients and compare them with healthy individuals .\npresent study suggested that serum level of l - fucose can not be correlated with age and gender .\nthis was similar to other studies which were published in the literatures . in our study , out of 60 cancer patients ,\n31 were well differentiated , 27 - moderately differentiated , and 2 poorly differentiated and anaplastic - nil .\nhowever , there was a negative correlation between serum fucose levels and histopathological tumor differentiation in our study as well as in the literatures . in our study\n, the mean serum value of l - fucose in cancer group ( 10.85 mg / dl ) and control group ( 3.47 mg / dl ) shows a wide margin of difference ( 7.38 mg / dl ) .\nmoreover , all the 60 patients in the cancer group were categorized according to tnm staging .\ncomparison of all the four tnm stages in cancer group showed increase in fucose levels as the stages progressed .\nthey assessed the levels of glycoprotein - associated carbohydrates such as hexose ; hexosamine , fucose , and sialic acid .\nthey found a significant rise in the level in cases when compared to control subjects .\nfurthermore , there was a progressive rise in these markers as the stages of oral cancer advances . in cancer patients , elevated levels\nhave been observed more so in advanced stages and in cases with metastasis than in subjects without metastasis .\nsome studies have concluded that it is the most effective of the essential sugars when it comes to slowing the growth of cancer cells .\nfall in serum fucose levels after treatment has been reported in many studies although it is emphasized that the follow - up period has to be long enough for significant serological alteration .\nunfortunately , rise in serum fucose level is not specific for cancers , as elevated serum fucose levels have also been reported in other pathological states such as cirrhosis liver , meningitis , rickets , osteomalacia , tuberculosis , cardiovascular disorders as well as in depressive disorders .\nfurthermore , it has been observed that the serum fucose level is raised in different groups of malignancies such as breast cancer , ovarian cancer , colorectal adenocarcinomas , and leukemia as well as brain tumors .\nthus , it becomes important to exclude other degenerative and proliferative diseases , while estimating the serum fucose levels in oral cancer .\nliterature is replete with studies on fucose levels in various malignancies including a few on oral cancer .\nbased on the analysis of the results of our study , we can conclude that there was a positive correlation between the serum l - fucose levels and tnm stages of oscc .\nserum l - fucose levels remained constant among healthy individuals and was raised proportionately in oral cancer patients , commensurate with the stage of cancer . in conjunction with clinic - diagnostic procedures ,\nserum l - fucose levels can be used as an easy , noninvasive , cost - effective , biochemical indicator of cancer detection , staging , therapeutic success , prognosis , and as a posttreatment evaluation tool .\nfurther investigation on a large scale would in all probability prove serum l - fucose as an effective tumor marker in the diagnosis and management of oral cancer ." }, { "role": "assistant", "content": "background : oral cancer is a result of disordered cellular behavior initiated by various stimuli which is characterized by the alteration of serum glycoproteins consisting of different monosaccharides . \n one of these is levo - fucose ( l - fucose ) , a methyl pentose . \n elevated levels of protein - bound fucose have been reported in various malignancies.aim:the present study attempted to correlate levels of serum l - fucose as a biomarker with the various tumor node metastasis ( tnm ) stages of oral cancer.methodology:the study was carried out on 90 subjects consisting of 30 healthy controls and 60 histopathologically proven oral squamous cell carcinoma ( oscc ) cases . \n the serum fucose level estimation was done based on the method adopted by winzler . \n statistical analysis included independent sample 's t - test , one - way anova test , karl pearson correlation test , and tukey 's hsd post hoc test to evaluate the significance and variability of values between groups.results:significant elevation in serum fucose levels was noticed among oscc patients when compared with the controls and a progressive ascent of l - fucose levels were noted as the stage of severity increased . \n serum fucose levels were independent of histopathological grading , age , and sex.conclusion:serum l - fucose levels were increased in oscc patients , and a positive correlation was observed between serum l - fucose levels and tnm staging of oscc . \n thus , serum l - fucose can be used as an effective diagnostic and prognostic biomarker in oscc patients ." } ]

[ { "role": "user", "content": "You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.\n\nLiterature Review Title: Cooperative recurrent modular neural networks for constrained optimization: a survey of models and applications \nChapter Title: AR signal system and parameter estimation \n1. Abstract of Cited Paper (BIB001): A new family of algorithms is developed for adaptive parameter estimation of constrained autoregressive moving-average (ARMA) signals in the presence of noise. These algorithms utilize a priori known information concerning the signal's properties, such as its spectral shape or a spatial domain characteristic. Special cases include autoregressive (AR) and band-pass spectrum signals in the presence of noise, signal deconvolution and image deblurring. \n2. Abstract of Cited Paper (BIB002): The objective is the order determination of non-Gaussian and nonminimum phase autoregressive moving average (ARMA) models, using higher-order cumulant statistics. The two methods developed assume knowledge of upper bounds on the ARMA orders. The first method performs a linear dependence search among the columns of a higher-order statistics matrix by means of the Gram-Schmidt orthogonalization procedure. In the second method, the order of the AR part is found as the rank of the matrix formed by the higher-order statistics sequence. For numerically robust rank determination the singular value decomposition approach is adopted. The argument principle and samples of the polyspectral phase are used to obtain the relative degree of the ARMA model, from which the order of the MA part can be determined. Statistical analysis is included for determining the correct MA order with high probability, when estimates of third-order cumulants are only available. Simulations are used to verify the performance of the methods and compare autocorrelation with cumulant-based order determination approaches. > \n3. Abstract of Cited Paper (BIB003): Presents a new neural network which improves existing neural networks for solving general linear programming problems. The network, without setting parameter, uses only simple hardware in which no analog multipliers are required, and is proved to be completely stable to the exact solutions. Moreover, using this network the author can solve linear programming problems and its dual simultaneously, and cope with problems with nonunique solutions whose set is allowed to be unbounded. \n4. Abstract of Cited Paper (BIB004): The problem of estimating the unknown parameters of an autoregressive (AR) signal observed in white noise, including the signal power and the noise variance, is studied. A new type of least-squares method is developed which is based on a simple technique of estimating the observation noise variance by increasing the degree of the underlying AR model by one. The main feature of the presented method is that the consistent estimates of AR parameters can be directly achieved, with no need to prefilter noisy data or to make any parameter transformation.\n\nLiterature Review:" }, { "role": "assistant", "content": "Consider the parameter estimation problem of the noisy AR signal system where a ¼ ½a 1 ; . . .; a p T is the unknown AR parameter vector; x t ¼ ½xðt À 1Þ; . . .; xðt À pÞ T is the regression vector of the AR process x(t) of the known order p; w(t) is driving noise; and u(t) is measurement noise which is assumed to be uncorrelated with w(t). Let the noisy signal vector be denoted by y t ¼ ½yðt À 1Þ; . . .; yðt À pÞ T ; and let where nðtÞ ¼ u t T a À uðtÞ À wðtÞ: Our objective is to get an optimal estimate of the AR parameters by using noisy observations {y(t)} 1 N under a wider range of noise distributions, where N is the number of data points. A basic approach to estimate the AR coefficient vector a is the least square (LS) method. The LS estimate is given by However, there is an error between the true parameter a à and the LS solution a LS with where R ¼ E½y t y t T and r 2 is the variance of the measurement noise. Many significant methods for improving the LS estimation based on the LS solution were presented. For example, Young, Soderstrom and Stoica developed the instrumental variable method to improve the LS solution BIB001 BIB002 . Zheng further presented several improving techniques BIB005 . We also presented using the LCLS data fusion technique to enhance the quality of the LS solution by doing K statistically independent trials of finding the LS solution BIB004 . The above mentioned methods are based on second-order statistics. In order to deal with non-Gaussian environments, high-order statistic methods have been developed in BIB003 , where measurement noise is Gaussian distributed." } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nWe present a series of 10 hospitalized patients with confirmed coronavirus 2019 infections who developed severe neurovascular complications and discuss the possible reasons for these findings and their relationship to the novel Severe Acute Respiratory Syndrome coronavirus 2 infection." }, { "role": "assistant", "content": "[\"Case Report\"]" } ]

[ { "role": "user", "content": "You will be shown a paragraph from a biomedical research paper, followed by a question about the paper. Please extract text from the paragraph to answer the question. Do not include any text in your repsonse other than the answer.\n\nParagraph: Responding to the COVID-19 pandemic in complex humanitarian crises\n\nhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/\n\nSHA: d013e42811c6442b184da3b9bbfd9e334031a975\n\nAuthors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21\nDOI: 10.1186/s12939-020-01162-y\nLicense: cc-by\n\nAbstract: nan\n\nText: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.\n\nQuestion: What is possible in many resource -limited settings?" }, { "role": "assistant", "content": "Widespread introduction of alcohol-based hand rubs" } ]

[ { "role": "user", "content": "You will be presented with a citation segment from the section of a research paper. Classify the intent behind this citation by choosing from one of the following categories:\n\n- Method: Cites the paper for its methodology or procedure.\n- Background: Cites the paper to provide background information.\n- Result: Cites the paper for its findings or results.\n\nYour answer should be a single word from the following list of options: [\"Method\", \"Background\", \"Result\"]. Do not include any other text in your response.\n\nCitation sentence:\n\nData on sex, age, health characteristics such as hospital stay, antibiotic therapy during the previous three months and surgery within the past 30 days, current healthcare-associated infection and/ or antibiotic therapy, presence of urinary or vascular catheters, pressure sores and other wounds as well as case history for MDRO were obtained for all participants, using the well-established HALT questionnaire (healthcare-associated infections in LTCFs) in Europe [32]." }, { "role": "assistant", "content": "Method" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nThe government of India implemented social distancing interventions to contain the COVID-19 epidemic. However, effects of these interventions on epidemic dynamics are yet to be understood. Rates of laboratory-confirmed COVID-19 infections per day and effective reproduction number (Rt ) were estimated for 7 periods (Pre-lockdown, Lockdown Phases 1 to 4 and Unlock 1-2) according to nationally implemented interventions with phased relaxation. Adoption of these interventions was estimated using Google mobility data. Estimates at the national level and for 12 Indian states most affected by COVID-19 are presented. Daily case rates ranged from 0.03 to 285.60/10 million people across 7 discrete periods in India. From 18 May to 31 July 2020, the NCT of Delhi had the highest case rate (999/10 million people/day), whereas Madhya Pradesh had the lowest (49/10 million/day). Average Rt was 1.99 (95% CI 1.93-2.06) and 1.39 (95% CI 1.38-1.40) for the entirety of India during the period from 22 March 2020 to 17 May 2020 and from 18 May 2020 to 31 July 2020, respectively. Median mobility in India decreased in all contact domains during the period from 22 March 2020 to 17 May 2020, with the lowest being 21% in retail/recreation, except home which increased to 129% compared to the 100% baseline value. Median mobility in the 'Grocery and Pharmacy' returned to levels observed before 22 March 2020 in Unlock 1 and 2, and the enhanced mobility in the Pharmacy sector needs to be investigated. The Indian government imposed strict contact mitigation, followed by a phased relaxation, which slowed the spread of COVID-19 epidemic progression in India. The identified daily COVID-19 case rates and Rt will aid national and state governments in formulating ongoing COVID-19 containment plans. Furthermore, these findings may inform COVID-19 public health policy in developing countries with similar settings to India." }, { "role": "assistant", "content": "[\"Prevention\"]" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nSARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). Although this analysis represents patients with cardiac comorbidities (hypertension), the inclusion of biomarkers from other pathophysiologies implicated in COVID-19 (e.g., D-dimer for thrombotic events, CRP for infection or inflammation, and PCT for bacterial co-infection and sepsis) may improve future predictions for a more general population. These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes." }, { "role": "assistant", "content": "[\"Treatment\", \"Diagnosis\"]" } ]

[ { "role": "user", "content": "You will be presented a sentence from biomedical research text. Extract all terms that correspond to chemical entities of biological interest (ChEBI).\nReturn your identified terms in a JSON array, formatted like this: [\"Entity1\", \"Entity2\", ...].\nIf no such entities are detected, respond by providing an empty JSON array [].\n\nBiomedical context:\nSOX9isexpressedinXYgonadsandcellscontactingFGF9-coatedbeads(dottedcirclelabeled\"F\")inXXgonads(IandK)butnotinXXcellscontactingBSA-coatedcontrolbeads(\"B\")(J)." }, { "role": "assistant", "content": "[]" } ]

[ { "role": "user", "content": "You will be presented a sentence from biomedical research text. Extract all terms that correspond to chemical entities of biological interest (ChEBI).\nReturn your identified terms in a JSON array, formatted like this: [\"Entity1\", \"Entity2\", ...].\nIf no such entities are detected, respond by providing an empty JSON array [].\n\nBiomedical context:\nFollowinglabeling,cellswereimmediatelyplacedoniceandwashedfor10minutesinice-colddye-freemedia,andfixedwith4%formaldehydeinPBS,for20minutesonice." }, { "role": "assistant", "content": "[\"dye\", \"formaldehyde\"]" } ]

[ { "role": "user", "content": "You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:\n\n- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.\n- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.\n- Prevention: The content covers measures to prevent the spread of COVID-19.\n- Mechanism: The paragraph explains the biological mechanisms of the virus.\n- Case Report: The content is a report of a COVID-19 case.\n- Transmission: The paragraph discusses how COVID-19 is transmitted.\n- Diagnosis: The content is about diagnosing COVID-19 in individuals.\n\nYour classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: [\"Topic1\", \"Topic2\", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.\n\nArticle:\n\nPURPOSE: This study aims to understand how spatial structures, the interconnections between counties, matter in understanding the coronavirus disease 2019 (COVID-19) period prevalence across the United States. METHODS: We assemble a county-level data set that contains COVID-19-confirmed cases through June 28, 2020, and various sociodemographic measures from multiple sources. In addition to an aspatial regression model, we conduct spatial lag, spatial error, and spatial autoregressive combined models to systematically examine the role of spatial structure in shaping geographical disparities in the COVID-19 period prevalence. RESULTS: The aspatial ordinary least squares regression model tends to overestimate the COVID-19 period prevalence among counties with low observed rates, but this issue can be effectively addressed by spatial modeling. Spatial models can better estimate the period prevalence for counties, especially along the Atlantic coasts and through the Black Belt. Overall, the model fit among counties along both coasts is generally good with little variability evident, but in the Plain states, the model fit is conspicuous in its heterogeneity across counties. CONCLUSIONS: Spatial models can help partially explain the geographic disparities in the COVID-19 period prevalence. These models reveal spatial variability in the model fit including identifying regions of the country where the fit is heterogeneous and worth closer attention in the immediate short term." }, { "role": "assistant", "content": "[\"Epidemic Forecasting\"]" } ]

[ { "role": "user", "content": "Given a short query with keyphrases about a research idea in 2017 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.\n\nQuery: I want to train a supervised model for fair classification.\n\nKeyphrases: fair classification image\n\nDataset description:\nDCASE 2014: DCASE2014 is an audio classification benchmark.\nConvAI2: The ConvAI2 NeurIPS competition aimed at finding approaches to creating high-quality dialogue agents capable of meaningful open domain conversation. The ConvAI2 dataset for training models is based on the PERSONA-CHAT dataset.\nDialogueFairness: The Dialogue Fairness dataset is used to evaluate and understand fairness in dialogue models, focusing on gender and racial biases.\nImageNet: The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.\n\nOptions:- A: DCASE 2014 B: ConvAI2 C: DialogueFairness D: ImageNet" }, { "role": "assistant", "content": "ImageNet" } ]