When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typically depended upon to build libraries experimentally. Considering complex biological samples, such as blood and soil, the entirety of NMR spectra required for all possible compounds would be infeasible to ascertain due to limitations of available standards and experimental processing time. As an alternative, we introduce the in silico Chemical Library Engine (ISiCLE) NMR chemical shift module to accurately and automatically calculate NMR chemical shifts of small organic molecules through use of quantum chemical calculations. ISiCLE performs density functional theory (DFT)-based calculations for predicting chemical properties—specifically NMR chemical shifts in this manuscript—via the open source, high-performance computational chemistry software, NWChem. ISiCLE calculates the NMR chemical shifts of sets of molecules using any available combination of DFT method, solvent, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Calculated NMR chemical shifts are provided to the user for each molecule, along with comparisons with respect to a number of metrics commonly used in the literature. Here, we demonstrate ISiCLE using a set of 312 molecules, ranging in size up to 90 carbon atoms. For each, calculation of NMR chemical shifts have been performed with 8 different levels of DFT theory, and with solvation effects using the implicit solvent Conductor-like Screening Model. The DFT method dependence of the calculated chemical shifts have been systematically investigated through benchmarking and subsequently compared to experimental data available in the literature. Furthermore, ISiCLE has been applied to a set of 80 methylcyclohexane conformers, combined via Boltzmann weighting and compared to experimental values. We demonstrate that our protocol shows promise in the automation of chemical shift calculations and, ultimately, the expansion of chemical shift libraries.The online version of this article (10.1186/s13321-018-0305-8) contains supplementary material, which is available to authorized users. The compounds —remains ompounds –7. The compounds  can be pompounds , 10. Altompounds –13 and mompounds –16 have ompounds –21, deteompounds –25.The most practical approach expand reference libraries for comprehensive identification of compounds detected in metabolomics studies is through in silico calculation of molecular attributes. Molecular properties that can be both accurately predicted computationally and consistently measured experimentally may be used in “standards free” metabolomics identification approaches. The metabolomics community has made many advances in calculations of measurable chemical attributes, such as chromatographic retention time , 27, tanMetabolomics researchers unfamiliar with DFT or similar calculations may find the application of quantum chemical calculations complicated or challenging to apply quickly, and thus avoid these techniques. To this end, and to help bring DFT calculations to large sets of small organic molecules relevant to the mainstream metabolomics community, we have developed a Python-based workflow and analysis package, the ISiCLE  NMR chemical shift module employs DFT methods through use of NWChem , a high-ISiCLE is a Python module that provides straightforward automation of DFT using NWChem, an open source, high-performance computational quantum chemistry package, developed at Pacific Northwest National Laboratory (PNNL), for geometry optimization and chemical shift and solvent effect calculations. Figure Here, we describe each step of a typical ISiCLE run . File A must contain all input molecules either as (i) International Union of Pure and Applied Chemistry (IUPAC) International Chemical Identifier (InChI) strings , 53 or  and the reference molecule, respectively. i and the reference molecule, respectively.For each molecule, ISiCLE generates MDL Molfiles (.mol)  that conISiCLE also calculates errors in NMR chemical shifts if experimental data is provided in the MDL Molfiles in a required way as explained in the tutorial. The errors are quantified in terms of mean absolute error (MAE) Eq. , correctEmpirical scaling of isotropic shieldings or NMR chemical shifts is the most common approach to remove systematic errors. If experimental data is provided, ISiCLE uses two optional approaches for its linear regression method, where slope and intercept values are derived from (i) regression of computed NMR chemical shifts versus experimental NMR chemical shifts using Eq. , and/or Alternatively, if the user does not provide experimental NMR chemical shifts, ISiCLE can scale NMR chemical shifts using provided intercept and slope values. The scaled NMR chemical shifts are appended to MDL Molfiles.A detailed description of InChIs and InChIKeys, and why they were chosen, can be found in the Additional file Furthermore, installation details for OpenBabel and other required Python packages are provided in the tutorial  hybrid functional [1H and 13C NMR chemical shifts were computed relative to TMS using the Gauge Including Atomic Orbitals (GIAO) formalism [As a first demonstration of ISiCLE, a benchmark study was performed with 8 different DFT methods to predict nctional –96 and tnctional . This lenctional , 99. Isonctional , 95, B3Lnctional –99, B35Lnctional . DFT metnctional  or triplnctional ). All banctional –104. Forormalism . Chlorofin vacuo molecular dynamics (MD) simulations, using the sander MD software program from AmberTools (version 14) [For a second demonstration of ISiCLE, the NMR chemical shifts, along with frequency calculations (and subsequent Boltzmann weighting), two sets of axial and equatorial conformers (40 conformers each) of methylcyclohexane were processed. We performed sion 14) , to genesion 14) . Second,sion 14) , 107–109All results shown in this manuscript were generated using the Cascade high-performance computer .To test ISiCLE, we generated a set of 312 molecules. This set is large relative to other metabolomic molecule sets found in the literature, which in our literature survey averaged 34 molecules  is higher than those with cc-pVDZ (5–6 ppm). MAE of methods with a larger basis set deviate more compared to those with a smaller basis set. The smallest deviations are observed for B3LYP and B35LYP, both in MAE and MAXAE results. The same situation is observed for 1H NMR chemical shifts as well: MAE of each method with cc-pVTZ (~ 0.35 ppm) is higher than those with cc-pVDZ (~ 0.30 ppm). In contrast to 13C NMR chemical shifts, 1H NMR chemical shifts are better predicted with methods using larger basis sets (cc-pVTZ). Although the error differences among each method may be too low to confidently identify the outperforming method, B3LYP/cc-pVDZ is the most successful combination in the calculation of 13C and 1H NMR chemical shifts for our application shown here.A total of 2494 carbon nuclei and of 3127 hydrogen nuclei were calculated for all 312 molecules of the demonstration set and compared with experimental data. Deviation bars indicating MAE and MAXAE are plotted for each method in Fig. 13C and 1H NMR chemical shifts was an acceptable compromise between accuracy and computational performance, compared with the larger cc-pVTZ basis. This finding is similar to a recent benchmark study [13C chemical shifts calculation. The larger basis set (cc-pVTZ) took 2–3 times longer to complete than cc-pVDZ . The computational times of the isotropic shielding and chemical shift calculations for this demonstration set are given in the file of DemonstrationSet_CPUtimes.xlsx in the Additional file Figure rk study  that sho13C and 1H NMR chemical shifts, respectively. It provides confidence for applying linear regression effectively as it reduces the possibility of overfitting. Empirical scaling was applied to the data obtained with the best combination, B3LYP/cc-pVDZ, using two different relationships: computed shifts versus experimental chemical shifts  by 0.02 for both 13C and 1H NMR chemical shifts. Linear fits with correlation coefficients of 0.99  magnetic shieldings and chemical shifts derived from the various DFT methods are highly correlated, as shown by a correlation coefficient of 0.99  and sp3- (745 carbons) hybridized carbons  chemical shifts are significantly affected by intermolecular interactions, particularly in aqueous states, especially compared to 13C chemical shifts. Agreement with experimental values improves as empirical linear scaling is performed for 1H chemical shifts. GIAO/B3LYP/cc-pVDZ//B3LYP/6-31G(d) yields scaled 1H chemical shifts in chloroform solution having a MAE of 0.30 ppm in comparison with solution experimental values. The 1H chemical shifts in the range of 10–17 ppm show the largest deviation, occurring higher than 5 ppm.Proton , nitrogen (n = 17), and oxygen (n = 41). Oxygen-bound hydrogen nuclei have the largest errors (up to 10 ppm), which is to be expected due to the electronegative property of oxygen atoms, as discussed in the previous section. It is followed by less electronegative nitrogen-bound hydrogen atoms, with an MAE of 0.71 ppm and a MAXAE of 2.25 ppm. About 95% of the 1H NMR chemical shifts calculated for this set are from H–C attachments. These chemical shifts had a MAE of 0.27 ppm and a MAXAE of 4.41 ppm. The high occurrence of outliers could be evidence of how 1H NMR chemical shifts are sensitive to intermolecular interactions.In Fig. 1H NMR chemical shifts in the presence of H–O attachments.H–O attachments are highly sensitive , and it is non-trivial to determine the NMR chemical shift value of arbitrary protons experimentally as well as predict them by using a single, “catch all” DFT method, which explains the relatively low correlation coefficient of 0.93 Fig. c–d. For Application of empirical scaling to functional groups are given in detail in the Additional file As a final assessment for the data collected with the demonstration set, we assessed the stability and accuracy of the linear regression approach using cross-validation . Cross-v13C and 1H NMR chemical shifts generalize well to the groups that are not represented in the training fold.We observed that the estimated linear model parameters (i.e. slope and intercept) from the training set do not differ from that of the entire set. Therefore, the predictive linear model is stable to be accurately estimated and the subsets of Metabolites were experimentally interrogated using solution-state NMR, where the observed signal arises from the combined signals of present conformers. It is routine that NMR chemical shifts calculations are carried out on a single dominant conformer. However, it is well known that metabolites do not comprise a single conformer in solution and are instead found in a collection of various conformers , and the1H and 13C chemical shifts  to experimental values reported by Willoughby et al. [1H chemical shifts  and writes the data to appended MDL Molfiles. It also quantifies the error in calculated NMR chemical shifts if the user provides experimental values.The functionality of ISiCLE is demonstrated on a molecule set consisting of 312 molecules, with experimental chemical shifts reported in chloroform solvent. 1H and 13C NMR chemical shifts were calculated using 8 different levels of DFT , referenced to TMS in chloroform by carrying initial geometry optimizations out at B3LYP/6-31G(d) for all molecules. The optimal combination for this set was found to be B3LYP/cc-pVDZ//B3LYP/6-31G(d) with mean absolute error of 0.33 and 3.93 ppm for proton and carbon chemical shifts, respectively. We show that DFT calculations followed by linear scaling do in fact provide an analytically useful degree of accuracy and reliability. Finally, we used ISiCLE for the calculation of NMR chemical shifts of 80 Boltzmann-weighted conformers of methylcyclohexane and compared our results with earlier studies in the literature.ISiCLE is a promising automated framework for accurate NMR chemical shift calculations of small organic molecules. Through this tool, we hope to expand chemical shift libraries, without the need for chemical standards run in the laboratory, which could lead to significantly more identifiable metabolites. Future work includes wrapping individual steps of the ISiCLE NMR module into a formal workflow management system such as Snakemake, to include better fault tolerance, modularization, and improved data provenance. Furthermore, additional chemical properties will be included, such as ion mobility collision cross section and infrared spectra. Finally, ISiCLE will be adapted to run seamlessly on cloud computer resources such as Amazon AWS, Microsoft Azure, and Google Cloud. ISiCLE is a promising tool contributing to standards-free metabolomics, which depends on the ability to calculate properties for thousands of molecules and their associated conformers.Additional file 1. Supporting information document.Additional file 2. Supporting information files. Including tutorial, code, and all other files.


We estimated mean intake of key iodine sources by race and Hispanic origin. We present the first national estimates of mUIC for non-Hispanic Asian persons and examine the intake of soy products, a potential source of goitrogens. One-third of National Health and Nutrition Examination Survey (NHANES) participants in 2011–2014 provided casual urine samples; UIC was measured in these samples. We assessed dietary intake with one 24-h recall and created food groups using the USDA’s food/beverage coding scheme. For WRA, mUIC was 110 µg/L. For both non-Hispanic white (106 µg/L) and non-Hispanic Asian (81 µg/L) WRA mUIC was significantly lower than mUIC among Hispanic WRA (133 µg/L). Non-Hispanic black WRA had a mUIC of 124 µg/L. Dairy consumption was significantly higher among non-Hispanic white (162 g) compared to non-Hispanic black WRA (113 g). Soy consumption was also higher among non-Hispanic Asian WRA (18 g compared to non-Hispanic black WRA (1 g). Differences in the consumption pattern of key sources of iodine and goitrogens may put subgroups of individuals at risk of mild iodine deficiency. Continued monitoring of iodine status and variations in consumption patterns is needed.We estimated iodine status (median urinary iodine concentration (mUIC (µg/L))) for the US population (6 years and over;  Iodine is a trace element that is required for the synthesis of thyroid hormones, which are necessary for adequate growth, development, and metabolism . DeficieThe world’s oceans are the main reservoir of iodine, containing iodide ions, and organic and inorganic iodine species which are volatized from seawater to the atmosphere and then eventually deposited on land as components in rain water . Iodine Dietary supplements and iodized salt  are alsoRoughly 90% of all iodine consumed is excreted in the urine  and thusp = 0.001) [The U.S has been considered iodine sufficient for decades ,25. Howe= 0.001) . Similar= 0.001)  and amon= 0.001) . Iodine = 0.001) ,29,30, k= 0.001) .Beginning in 2011–2012, for the first time, NHANES has nationally representative data of urinary iodine status and food group consumption for non-Hispanic Asian persons. The goal of this analysis is to update estimates of iodine status for the US population and women of reproductive age (WRA). We present estimates of iodine status by subgroups of race and Hispanic origin, and examine dietary patterns associated with iodine status by race and Hispanic origin using the most recent data from NHANES 2011–2014.NHANES is a complex, stratified, multistage probability sample of the U.S. noninstitutionalized population, conducted by the National Center of Health Statistics (NCHS). Since 1999, NHANES has continuously collected and publicly released data on roughly 10,000 participants every 2 years. Participants receive a detailed in-home interview, followed by a dietary interview and a physical examination, which includes sample collection for laboratory tests, at a mobile exam center (MEC). Participants aged 18 and over provide consent, children and adolescents aged 7 to 17 years provide documented assent, and parental permission is obtained for those younger than 18 years. Non-Hispanic Asian, non-Hispanic black, and Hispanic individuals were oversampled for the 2011–2014 survey years . The NHA® DRC II)  [Spot urine samples were collected from a one-third sample of participants aged 6 years and over in the MEC. UIC was assessed using an Inductively Coupled Plasma Mass Spectrometer with Dynamic Reaction Cell Technology  ,34,35. BCT, USA) . The WHOCT, USA) . Method CT, USA) ,26,33,34Trained interviewers, using a computer-assisted dietary interview system that included a multiple-pass format with standardized probes , collectThe USDA’s Food and Nutrient Database for Dietary Studies (FNDDS) ,40 was uSince 2007–2008, NHANES has included a 24-h dietary supplement recall, administered at the same time as the dietary recall. We used the day 1 24-h supplement recall to identify participants who had reported consuming a supplement that contained iodine in the previous 24-h. We dichotomized participants based on this reported consumption.Responses to the salt use questions administered during the 24-h recall allowed us to group participants by usage frequency for food preparation and at the table . These questions do not ask specifically about iodized salt.Age is categorized into 8 groups for the US population  and 4 groups for WRA . We also used sex , race and Hispanic origin  to describe the data. Individuals with race and Hispanic origin classified as ‘other’ include those reporting multiple races, and are included in the overall estimates but not shown separately in the results. Pregnancy status for women aged 15–19 years, and 45 years and above is not included in the public use NHANES data files due to disclosure risk. We obtained this information through the Research Data Center .Statistical analyses were performed using SAS version 9.4  and SUDAAN version 11.0 . Survey design variables and sample weights, which account for differential probabilities of selection, nonresponse, noncoverage, and sample design, were used to obtain estimates representative of the noninstitutionalized US population. We used the day 1 dietary weights and adjusted for non-response in the urinary data (see below).Guidance regarding selecting the most appropriate sample weight advise selecting “the weight of the smallest analysis subpopulation” . The curp-values from adjusted Wald tests were less than 0.05. The hypothesis of no linear trend across ordinal variables was tested by using orthogonal contrast matrices (p < 0.05).Using our adjusted weights, we calculated estimates for mUIC and Wald 95% confidence intervals. Neither SAS nor SUDAAN directly test the difference between medians. Using SUDAAN to account for complex survey design and weighting, we indirectly tested whether differences in mUIC by sociodemographic characteristics, salt, and supplement use were significant by first categorizing individuals as above or below the overall median. We then tested whether a below-overall-median proportion for any group differs from 0.5 with logistic regression. This indirect method is considered to be equivalent to testing whether medians varied by group . We alsoIn NHANES 2011–2014, 14,489 participants aged 6 years and over provided a complete and reliable dietary interview. Of these, 4744 participants were also in the 1/3 subsample who were eligible for urine iodine measurement. We excluded 68 participants because they did not have a value for urinary iodine, although they were eligible for urine collection , and 64 women who were pregnant or lactating, leaving a final analytical sample of 4613 participants, aged 6 years and over. For the analysis of WRA, the final analytic sample size was 901, after restricting to non-pregnant, non-lactating women, aged 15–44 years.p < 0.05), with the lowest median among adults aged 40–49 years , and highest medians observed among children aged 6–11 years  and older adults aged 70 years and over . Women had a significantly lower mUIC compared to men, 122 µg/L  vs. 147 µg/L  (p < 0.05). The only significant difference in mUIC by race and Hispanic origin in the US population was between non-Hispanic Asian individuals, ), and non-Hispanic blacks,  (p < 0.05)). The mUIC for non-Hispanic white and Hispanic individuals was 134 µg/L  and 133 µg/L , respectively. Among those who consumed a dietary supplement containing iodine, mUIC was significantly higher: 174 µg/L  compared with 127 µg/L  among those with no consumption (p < 0.05). We found that mUIC did not vary by salt use at the table. However, mUIC was significantly higher among those reporting never using salt in food preparation: 172 µg/L  compared to all other patterns of salt use: rare, 138 µg/L , occasional, 128 µg/L , and very often, 128 µg/L  (p < 0.05).The mUIC in the US population was 133 µg/L   in 2011–p < 0.05). Among WRA, non-Hispanic Asian women had the lowest mUIC: 81 µg/L , significantly lower than Hispanic  women (p < 0.05). Differences between non-Hispanic Asian and non-Hispanic white women  and non-Hispanic black women 124 µg/L  were not significant. Differences in mUIC by supplement use were not significant. Among WRA with rare salt use at the table, mUIC was 122 µg/L  significantly higher than those with occasional salt use . WRA who reported rare salt use in food preparation has a significantly higher mUIC  compared with occasional  and very often use of salt in food preparation  (p < 0.05).The mUIC for US WRA, 15–44 years, in 2011–2014 was 110 µg/L  . We founp < 0.05). Grain consumption was highest among non-Hispanic Asian persons ), followed by Hispanic ) and non-Hispanic black ) and non-Hispanic white individuals ) . There were no statistical differences in egg consumption by race and Hispanic origin; the average consumption was 23 g . Both non-Hispanic blacks ) and non-Hispanic Asian individuals ) had higher fish consumption compared with non-Hispanic white ) and Hispanic individuals ) . Consumption of soy products was highest among non-Hispanic Asian individuals ) compared to non-Hispanic white ), Hispanic ), and non-Hispanic black individuals ) .p < 0.05). Differences in dairy consumption between Hispanic WRA  and other race and Hispanic ethnic groups and between non-Hispanic Asian women  were non-significant. The only significant difference in mean grain consumption was between non-Hispanic Asian women ), compared to 293 g  by non-Hispanic white women, (p < 0.05). Non-Hispanic black and Hispanic WRA consumed 308 g  and 343 g , respectively. There were no statistical differences in egg consumption by race and Hispanic origin; the average consumption was 22 g  among WRA. Non-Hispanic black WRA consumed significantly more fish ) compared with non-Hispanic white  and Hispanic WRA ) . Non-Hispanic Asian WRA consumed 24 g  of fish. Non-Hispanic black WRA consumed significantly less soy ) compared with Non-Hispanic Asian 18 g  and non-Hispanic white WRA ) . Hispanic WRA consumed 9 g  of soy.Among WRA , non-HisIn this analysis of NHANES 2011–2014 we found that the general US population aged 6 years and above had a mUIC of 133 µg/L and WRA had a mUIC of 110 µg/L, suggesting iodine sufficiency, according to WHO criteria . For theDespite the lack of a publicly available national nutrient database with iodine values for foods and beverages consumed in the US, there is consistent agreement that dairy, grains, eggs, and fish provide the bulk of iodine in the US diet ,30,48, aA novel finding of the current analysis is that non-Hispanic Asian individuals, who tended to have lower mUIC than other race/Hispanic origin groups, had higher consumption of soy products. Soymilk typically does not contain high amounts of iodine  comparedSalt iodization is considered the central strategy for eliminating iodine deficiency . In the The use of a dietary supplement containing iodine was positively associated with mUIC in the US population aged 6 years and above. A similar association between mUIC and use of a dietary supplement containing iodine was suggested for WRA; however, a significant difference was not detected, possibly because so few women in this age group consumed a dietary supplement with iodine. Like folic acid, iodine is critical for brain development in the early weeks of pregnancy when many women do not yet know they are pregnant . Unlike While our analysis did not include pregnant women, the Recommended Dietary Allowance for iodine increases from 150 µg/day when not pregnant to 220 µg/day during pregnancy. Thus, it is possible that without some changes in dietary intake, some women may not have sufficient iodine intake if they were to become pregnant. Severe iodine deficiency during pregnancy is detrimental for child survival and development, but the effects of mild-to-moderate iodine deficiency are less well defined. While challenging methodologically to assess this relationship because there is no established method for assessing an individual’s iodine status, mild iodine deficiency in pregnancy has been associated with poorer educational outcomes at 8–9 years among cohorts in Tasmania  and the This study is not without limitations. It is well documented that self-reported measures of dietary intake are subject to random and systematic error due to day-to-day differences in intake, systematic underreporting, difficulty remembering foods, and errors in the food and nutrient database that intakes are linked to ,47. As windividual intake, neither does a single spot urine sample capture an individual’s iodine status, as measured by UIC [The determination of iodine status as assessed by UIC also has challenges. The WHO definition of population iodine status does not include adjustment for creatinine . Howeverd by UIC . We therDespite merging two survey cycles, there was limited statistical power to identify differences in food group consumption by race and Hispanic origin among WRA. A separate issue is the considerable heterogeneity within race and Hispanic ethnic groups. For example, the non-Hispanic Asian group includes south Asian, Korean, Japanese, and Chinese, and eating patterns are likely to vary greatly among these subgroups, and the moderate iodine deficiency seen for among non-Hispanic Asian WRA may be more or less problematic in some racial subgroups.Some analyses were beyond the scope of this study. Seaweed is a known source of iodine; however, the iodine content in seaweed is highly variable  and it iThe strengths of this analysis include the most recent, nationally representative estimates of iodine intake and mUIC for the US population, WRA, and for the first time, non-Hispanic Asian persons. We estimated mUIC by the important sources of iodine in the US diet: food and beverages, supplements, and salt use. Another novel contribution of this work is the exploration of soymilk and soy products as a source of goitrogens in the US diet that may block the utilization of iodine and contribute to mild iodine deficiency.There is no overt sign of widespread iodine deficiency in the US, based on the observed mUIC from NHANES 2011–2014. However, non-Hispanic Asian WRA had a mUIC of 81 mg/L, indicating mild iodine deficiency in that subgroup. We found that mUIC did not follow the expected pattern of association with dietary intake of key food and beverage sources of iodine among all race and Hispanic origin groups. In the context of decreasing iodine status, variation in iodine status by race and Hispanic origin, and variation in dietary intake of key food sources of iodine, continued monitoring of iodine status and factors associated with iodine status is needed.


Tobacco smoking is a highly prevalent, addictive behaviour and a key public health priority. However available cessation therapies have low quit and high relapse rates, indicating an urgent need for more effective treatments. Predicated on promising preclinical and pilot clinical data, this paper presents a rationale and protocol for the trial of N-acetylcysteine (NAC) as a novel anti-craving smoking cessation aid.n = 120) of at least 10 cigarettes a day are recruited through online advertisements, print publications and dissemination of flyers. Participants are randomised on a 1:1 ratio to receive either 16-week treatment of 1.8 g/day of NAC or placebo with all participants receiving quit support from the online QuitCoach tool. Participants are attending visits at baseline, 8 and 16 weeks with a 42-week post-discontinuation follow-up. The primary outcome measure is sustained abstinence at six months after treatment based on self-reported rating scales and confirmed by exhaled carbon monoxide and salivary cotinine levels. Secondary outcomes are timing of the first lapse and relapse, between-group cigarette consumption, withdrawal symptoms, general wellbeing and mood/anxiety symptoms. Between-group differences in adverse events and subgroup analyses for variables including gender and Diagnostic Statistics Manual 5 diagnostics will also be investigated.Current smokers , The online version of this article (10.1186/s13063-019-3628-5) contains supplementary material, which is available to authorized users. Tobacco smoking is the leading cause of preventable morbidity and mortality globally  and killIt is essential to trial new strategies and medications to make further significant gains in reducing tobacco smoking. Developing a safer, better tolerated pharmacotherapy for smoking cessation is a critical step towards making further gains. Vulnerable groups and special populations may especially benefit from a low-cost, over-the-counter, effective pharmacotherapy with a better safety profile than existing pharmacotherapies such as varenicline and bupropion –8.N-acetylcysteine (NAC) has antioxidant properties, both increasing glutathione and modulating glutamatergic, neurotropic, mitochondrial and inflammatory pathways . NAC is n = 22), treated for 3.5 days with NAC (3.6 g/day) or placebo, identified that NAC-treated participants reported that their first cigarette was significantly less rewarding when compared with the first cigarette of placebo-treated smokers [n = 19) treated with NAC and varenicline reported a reduction in cigarettes smoked per day [n = 33, compared with placebo), there was a significant decrease in the number of cigarettes smoked, but no reduction in craving, withdrawal symptoms or level of carbon monoxide.There are four small published pilot studies investigating the effects of NAC in nicotine dependence. A short-term abstinence study of heavy smokers ( smokers . A four- per day . A randon = 17) or placebo (n = 17) adjunctive to addiction-focused cognitive behavioural therapy. NAC treatment significantly reduced the number of cigarettes smoked daily, exhaled carbon monoxide and improved depression scores. Quit rates were 47.1% in those treated with NAC versus 21.4% of placebo-treated patients. There were no significant differences in treatment emergent adverse events (AEs) between both groups. These pilot data are very promising [In another pilot trial, participants were randomised to 12 weeks of 3 g/day NAC n =  or placeThe aim of this study is to investigate the efficacy of NAC (1.8 g/day) for smoking cessation in a randomised, placebo-controlled trial of current smokers who wish to quit smoking. The primary outcome measure will be 24 weeks of continuous abstinence from end of treatment  in tobacco smoking, confirmed by biological measures. Secondary outcome measures include point prevalence abstinence, time to relapse and total cigarette consumption. Safety, tolerability and subgroup analyses will also be conducted.It is hypothesised that: (1) treatment with NAC will be superior to placebo for smoking cessation at follow-up (week 42), confirmed by assaying exhaled carbon monoxide, salivary cotinine (COT); and (2) treatment with NAC will be superior to placebo for smoking cessation at treatment endpoint (week 16), confirmed by assaying exhaled carbon monoxide, salivary COT.This is a double-blind, randomised, placebo-controlled trial, to compare 1.8 g/day of NAC with placebo for smoking cessation, conducted over a period of 16 weeks. A six-month post-treatment discontinuation (week 42) follow-up is assessing ongoing abstinence. Data are collected by interview at baseline and weeks 8 and 16, and at the follow-up visit, six months after completion of the trial or 42 weeks in total. The trial has approval from the relevant research and ethics committees and is being conducted in accordance with the Good Clinical Practice (GCP), Australian Clinical Trial guidelines and the National Ethical guidelines for Human Research. The trial is registered on the Australian New Zealand Clinical Trials registry (ANZCTR), ACTRN12617001478303. This study was approved by the Barwon Health Human Research Ethics Committee (reference: 17/15).n = 120) are randomised to 16 weeks of treatment with NAC (1.8 g/day) or placebo effervescent tablets taken with water. The first participant was recruited in November 2017 and recruitment is ongoing. The study is being sponsored by Barwon Health and is supported by the ARC Harry Windsor Research Grants Scheme 2017.The study is being conducted at two sites, Barwon Health, Geelong and the Deakin University Burwood campus. Participants  use before the baseline visit. Female participants are required to be utilising effective contraception if of childbearing age and sexually active.Participants are withdrawn from the trial under the following conditions: failure to take the trial medication for seven consecutive days; pregnancy; emergence of serious AEs suspected to be associated with the trial medication; or commencement of a different pharmacotherapy for smoking cessation during the 16-week treatment phase. Participants will be questioned about these events and their adherence to the study protocol at the bi-weekly telephone interviews during the treatment phase of the study. Withdrawal of consent at any time in the study will result in immediate withdrawal from the trial.Recruitment is anticipated to occur mainly through targeted online advertising. Other recruitment techniques will include the use of flyers, which will be displayed in the waiting rooms of health services and other conspicuous locations. Print and radio advertisements will be included where possible. Following initial contact by potential participants, a researcher will establish that inclusion and non-inclusion criteria are satisfied. Written informed consent for the trial will be obtained from all participants at the first meeting.All participants will provide informed written consent before they undergo a baseline face-to-face interview with a trained researcher. Participant contact will be conducted using procedures adapted from the treatment manual for the Healthy Lifestyles Program , 19. ConSaliva will be collected at baseline and at weeks 8, 16 and 42 for COT measurements. Before the baseline meeting, participants will be provided with the following instructions: (1) avoid foods with high sugar or acidity, or high caffeine content immediately before sample collection; (2) do not eat a major meal within 60 min of sample collection; (3) do not consume alcohol within 12 h of sample collection; (4) participants should not brush their teeth within 45 min before sample collection; (5) dental work should not be performed within 24 h before sample collection. The trial clinician will document consumption of alcohol, nicotine, caffeine and medications in the 12 h before collection, as well as vigorous physical activity and the presence of oral disease or injury. Saliva collection is performed by instructing participants to allow saliva to pool in the mouth and then drool through the Salimetrics Saliva Collection Aid into a cryovial. This sample is stored in a – 80 °C freezer until it is time for analysis. An enzyme-linked immunosorbent assay (ELISA) will be performed to determine levels of COT in the samples. Samples are collected at each participant meeting.Individuals will be assigned in a 1:1 ratio using permutated block randomisation to treatment with NAC or placebo, in a double-blind fashion. The randomisation code is generated by an independent researcher and held by the pharmacy to maintain blinding. The randomisation code remains concealed until all data analysis has been completed (triple-blind design). Unblinding for emergency situations is undertaken by the pharmacy, with the approval of the Principle Investigator.The trial medications will be supplied by the trial pharmacist; participants will be instructed to return all containers to allow capsule counts. Concordant with SPIRIT guidelines, adherence will be assessed by pill counts of returned medication packs. Use of QuitCoach will be monitored by participant self-report  < 10 ppm measured using a Micro+ Smokerlyzer (Bedfont Scientific) and salivary COT < 50 ng/L, which is a sufficient margin to allow for passive tobacco smoking. COEXH may be < 10 ppm in non-abstinent participants who have not smoked within 2 h [EXH levels are < 10 ppm and COT is < 50 ng/mL. Where participants self-report use of non-tobacco nicotine, COEXH will be used to confirm abstinence. Secondary outcomes will include the timing of the first lapse and first relapse, based on a dichotomous variable and defined as self-reported smoking seven days in a row at any time between two weeks after quitting and the trial end. Prolonged abstinence will also be reported and defined as any slips or lapses following the quit date [The primary outcome of this aid-to-cessation trial will be between-group differences in continuous abstinence for the 26-week period between weeks 16 and 42. The primary outcome is measured at six months post-treatment discontinuation (week 42) rather than at treatment discontinuation (week 16), in line with the Russell Standard for international smoking cessation research . To assethin 2 h . Smokinguit date .EXH and COT measures will be taken.At the baseline visit, the Fagerström Test for Nicotine Dependence and a smoking history questionnaire will be administered. The smoking history questionnaire will explore how long the participant has smoked for , their average consumption of cigarettes and the number of previous attempts to quit smoking. Data will also be collected regarding how determined they are to give up smoking on this attempt  and to rate their chances of permanently quitting on this attempt . The Minnesota Nicotine Withdrawal Scale will be administered to assess urge to smoke among other withdrawal symptoms, depressed mood, irritability, anxiety, difficulty concentrating, restlessness, increased appetite and sleep. Participants will also complete the Brief Questionnaire of Smoking Urges, which assesses cravings related to desire to smoke and expectations of positive effects anticipation of relief from negative affect. Demographic data, lifetime history of smoking , level of social support, self-reported medical and psychiatric history will also be collected at baseline. A psychiatric diagnostic interview (SCID-5-RV), based on the DSM-5 will be conducted at baseline. The WHO ASSIST and AUDIT will be collected at baseline and visits at weeks 8 and 42. The Standardised Assessment of Personality – Abbreviated Scale (SAPAS), a brief screen for personality disorder, will be used at baseline. The WHO-5, Depression, Anxiety, and Stress Scale (DASS-21) and K10 will be administered at baseline and at weeks 8, 16 and 42 , will be examined separately as well as pooled as treatment failures. Non-cigarette tobacco use, but not non-tobacco nicotine use, will be categorised as smoking.Intended use of bupropion, varenicline or NRT during the 42-week trial period will not be permitted but is only a withdrawal criterion if used during the 16-week treatment period. Some participants may decide to use NRT during the 42-week study. Although this is contrary to the directions given to participants in the study, it is not a study withdrawal criterion and these participants may remain in the study. COT levels will be measured using chromatographic techniques.Records of participation in this study will be held confidential so far as permitted by law. This will include de-identification of all documents relating to the trial by assigning a random number that will identify participants in terms of a dataset and not an individual. However, researchers, regulatory agencies and the Barwon Health Human Research Ethics Committee (HREC) will be able to inspect and have access to confidential data that identify participants by name.The measures listed under ‘Variables and instruments’ in the study design section will be co-rated by trained trial clinicians. Inter-rater reliability will be checked before commencement of the trial and repeated every six months during the trial, using a standardised videotaped patient interview. Raters will need to achieve an intraclass  correlation score of 0.8 and will undergo further training as necessary during the study to maintain inter-rater reliability.The sample size was initially determined to be 360. In order to detect a 7% difference between the groups , the sample size has been calculated for a Cochran-Mantel-Haenszel (CMH) test to acknowledge a cluster randomised design with three recruitment centres as strata . A sample size of 180 in the NAC group and 180 in the control group  achieves 80% power to detect an odds ratio (OR) = 7, assuming a two-sided type I error of 0.05. The sample size also achieves 80% power to detect a 7% difference in six-month smoking cessation between NAC and placebo groups assuming two-sided alpha = 0.05 and an 8% inflation of the required sample size due to clustering. However, the current trial has a recruitment target of 120 in total, with the intention of scaling up as more funding is acquired.A modified ‘intention-to-treat’ approach, following CONSORT Statement guidelines, will be used. Missing values will be scrutinized to check for non-random distribution and analyses that utilize baseline data will be executed twice: once using observed data and once using multiple imputation under multivariate normal assumptions. The CMH test will be used to compare the proportions of relapse between the treatment groups (control versus intervention). The common OR and its 95% confidence interval will also be reported as well as the results of the Breslow-Day test for homogeneity of the ORs across the strata. In further supportive analyses, generalized linear mixed models (GLMMs) will be used to compare the rates of relapse after adjusting for baseline measurements and to explore possible interactions between baseline factors and the intervention. Average treatment group differences for the continuous secondary outcomes will be examined using a likelihood based mixed-effects model, repeated measures approach (MMRM). The MMRM models include the fixed categorical effects of treatment, visit and treatment-by-visit interaction, as well as the continuous fixed covariates of baseline score and baseline score-by-visit interaction. Effect sizes will be calculated using Cohen’s guidelines. All comparisons will be conducted using a two-sided alpha level of 0.05. There will be no interim analysis.Barwon Health is the sponsor of this study. The sponsor is indemnified for any harms arising from trial participation and it approves protocol amendments when ethics approval has been obtained. Principal investigators and trial clinicians manage the day-to-day running of the trial. Principal investigators are three well-established and experienced researchers in relevant fields. Itemised lists of various trial staff members are as follows:Trial designPublication of study reportsStudy planningProvision of expertise to problem resolutionMedia promotionFunding application and managementCase report form creation and managementResearch staff managementParticipant recruitment, contact and interviewingLiaison with external bodies Maintenance of trial equipmentTraining of research staffOrganisation of research team meetingsThere is no Data Management Committee for this trial due to the small sample size; however, independent data integrity will be assessed by independent researchers as required. Trial progress and processes are assessed every two weeks by the principal investigators at a research team meeting.A summary of the data will be provided to each participant along with whether they took the active or placebo medication. This information will be provided at the soonest reasonable opportunity after trial completion and will be provided electronically. The results will be published and disseminated throughout both formal and informal collegiate settings.There is currently no plan to share participant-level data with external individuals.Tobacco smoking is a major preventable cause of morbidity and mortality. NAC may provide a safe, novel and effective treatment for smoking cessation, at low cost. The tolerability and safety of NAC as well as its efficacy in co-morbid psychiatric symptoms may have advantages in special populations compared to other pharmacotherapies for smoking cessation. If positive, of the use of NAC could be translated immediately into practice and established as a new treatment for smoking cessation. NAC additionally has a clearly elucidated potential mechanism of action in addiction. The planned trial, if positive, may result in substantial changes to the management of smoking with overt public health implications.Additional file 1:SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents. (DOCX 18 kb)


Furthermore, HDAC4 was targeted for proteasomal degradation early after infection with VACV, and VACV protein C6, an inhibitor of type I IFN signaling, was necessary and sufficient for this degradation. In summary, HDAC4 is a restriction factor for large DNA viruses.Histone deacetylases (HDACs) are regulators of host gene expression. HDAC4 is shown here to have an important role in type I interferon (IFN) signaling. Here, multiple cell lines lacking HDAC4 had impaired responses to IFN-α and were rescued by reintroduction of HDAC4. The biological significance of HDAC4 was demonstrated by the enhanced replication and spread of two DNA viruses, vaccinia virus (VACV) and herpes simplex virus type I, in HDAC4 −/− cells was rescued by reintroduction of HDAC4 or catalytically inactive HDAC4, but not HDAC1 or HDAC5. ChIP analysis showed HDAC4 was recruited to ISG promoters following IFN stimulation and was needed for binding of STAT2 to these promoters. The biological importance of HDAC4 as a virus restriction factor was illustrated by the observations that (i) the replication and spread of vaccinia virus (VACV) and herpes simplex virus type 1 (HSV-1) were enhanced in HDAC4−/− cells and inhibited by overexpression of HDAC4; and (ii) HDAC4 is targeted for proteasomal degradation during VACV infection by VACV protein C6, a multifunctional IFN antagonist that coprecipitates with HDAC4 and is necessary and sufficient for HDAC4 degradation.Interferons (IFNs) represent an important host defense against viruses. Type I IFNs induce JAK-STAT signaling and expression of IFN-stimulated genes (ISGs), which mediate antiviral activity. Histone deacetylases (HDACs) perform multiple functions in regulating gene expression and some class I HDACs and the class IV HDAC, HDAC11, influence type I IFN signaling. Here, HDAC4, a class II HDAC, is shown to promote type I IFN signaling and coprecipitate with STAT2. Pharmacological inhibition of class II HDAC activity, or knockout of HDAC4 from HEK-293T and HeLa cells, caused a defective response to IFN-α. This defect in HDAC4 Histone deacetylases (HDACs) can repress gene expression by deacetylating histones leading to strengthened histone–DNA interactions and chromatin condensation . HDACs cIn humans there are 18 HDACs that are classified in four subfamilies: class I ; class II HDACs, subdivided into class IIa  and class IIb (HDACs 6 and 10); class III (sirtuins 1–7); and class IV (HDAC11) (Type I interferons (such as IFNα/β) are secreted glycoproteins that induce antimicrobial states in cells, orchestrate the inflammatory response to invading pathogens, and activate the adaptive immune system , 6. HDACHDAC activity also affects type I IFN-stimulated gene (ISG) expression as shown by impairment of ISG transcription by addition of TSA  or the a+ T cells  and Epstein-Barr virus (EBV) –24. Simi T cells , 26. Dur T cells . In huma T cells , 29. IntAlthough interplay between viruses and class I HDACs is well established, less is known about viral interactions with members of the class II HDAC family, such as HDAC4. HSV-1 protein ICP0 was reported to coprecipitate with HDAC4, however, the functional consequence of this is unknown . EBV nucThis study reports that HDAC4 is required for type I IFN signaling and restricts the replication of HSV-1 and vaccinia virus (VACV). Mechanistically, HDAC4 coprecipitates with STAT2 and is recruited to IFN-stimulated response element (ISRE)-containing promoters following addition of type I IFN. Without HDAC4, binding of STAT2 to these promoters after IFN-α addition is greatly reduced. Lastly, HDAC4 is targeted for proteasomal degradation during VACV infection. VACV expresses many inhibitors of innate immunity and IFN signaling , 35 and To investigate further the roles of HDACs in type I IFN signaling, the effect of TSA on type I ISRE-dependent reporter gene expression was assessed in HeLa cells. Consistent with previous reports, type I IFN signaling was largely inhibited by TSA A. Next, IFIT3, IFIT1, and 2′5′-OAS (OAS1)] . These data indicate that class II HDAC activity is needed for ISRE-dependent gene expression in response to IFN-α but not for the expression of IL-1β–induced genes that require NF-κB activation.To explore this further, the effect of LMK235 on endogenous gene expression in response to IFN-α and IL-1β was analyzed in HeLa cells by reverse transcription-quantitative PCR (RT-qPCR). LMK235 inhibited the induction of mRNA of three IFN-α–responsive genes [ (OAS1)] D–F but n−/− cell lines generated by CRISPR/Cas9 genome editing , and two HDAC4−/− HeLa cell lines, genome edited with gRNA1, were selected as described in SI Appendix, Fig. S2A. Sequencing of the genomic region targeted by the gRNAs confirmed frameshift mutations had been introduced into each allele and that no wild-type (WT) allele remained . Consistent with this, immunoblotting showed loss of HDAC4 expression . These cell lines showed no significant difference in growth rate compared with the parental cell lines, indicating that although HDAC4−/− mice displayed skeletal defects and a very limited life span  were then used in reporter gene assays. ISRE-luciferase expression after IFN-α stimulation was significantly diminished in H4KO1 and H4KO2 cells compared with parental HEK-293T cells (Left), whereas the NF-κB response to TNF-α was normal (Right). So, consistent with the results using pharmacological inhibitors of HDACs, two independent HDAC4−/− cell lines showed impaired type I IFN signaling. Similar analysis in HDAC4−/− HeLa cells (H4KO3 and H4KO4) showed a greater deficiency in response to IFN-α stimulation (Left). In contrast, IFN-γ–activated sequence (GAS)-luciferase and TNF-α–induced NF-κB–luciferase were not significantly different in these HDAC4−/− cell lines (Center and Right). The role of HDAC4 in type I IFN signaling was also investigated by RT-qPCR of endogenous ISGs  in HeLa HDAC4−/− cells. For each ISG there was a significant reduction in the response to IFN-α compared with control cells , and the effect analyzed. Immunoblotting demonstrated dose-dependent FLAG-HDAC4 expression. In HDAC4−/− cells there was a dose-dependent increase in ISRE-luciferase activity following type I IFN stimulation .Four HDAC4ll lines A and WT mulation A. Howeve−/− cells and found to complement HDAC4 deficiency as efficiently as WT HDAC4, indicating that interaction with 14-3-3 is not necessary for type I IFN signaling .Given that HDAC4 deacetylase activity was not needed for type I IFN signaling, the inhibition of this pathway by the HDAC inhibitor LMK235 suggests that enzymatic activity of another class II HDAC is required for type I IFN signaling. Consistent with this, LMK235 still inhibited type I FN signaling in two HDAC4IFIT1, IFIT3, and ISG15) were enriched by the other anti-HDAC4 antibody after IFN-α stimulation compared with mock-treated cells, and, as expected, there was no enrichment in H4KO3 cells. Similar analysis with two different anti-STAT2 antibodies showed enhanced binding of STAT2 following addition of IFN-α to WT cells, but binding of STAT2 to the IFIT1, IFIT3, and ISG15 promoters was greatly reduced in H4KO3 cells compared with WT cells  assays were undertaken with antibodies against HDAC4 and STAT2. HeLa and H4KO3 cell lines were treated with IFN-α and then fixed with formaldehyde to crosslink chromatin-associated proteins. After chromatin fragmentation, samples were immunoprecipitated with two antibodies against HDAC4 or STAT2 and the enriched chromatin was analyzed by qPCR. One anti-HDAC4 antibody did not work in this assay. However, as shown in WT cells B and C. The reduced STAT2 binding to the IFN-α–stimulated promoters suggested that HDAC4 might interact with components of the ISGF3 complex  and this was investigated by immunoprecipitation. FLAG-tagged HDAC4 coprecipitated with STAT2 but not STAT1, while FLAG-tagged TANK did not coprecipitate with either STAT1 or STAT2 A. The knSI Appendix, Fig. S6). HDAC4 expression was then induced (+dox) or mock induced (−dox) and cells were infected with either VACV  , 46 were/+ cells A and B. /− cells C. Furthentivirus  reduced ntivirus C. In sumC6L gene . It was shown that pharmacological inhibition of HDACs by TSA reduced the response to type I IFN  and thatectively , inhibitectively . But neiPharmacological inhibition of HDAC activity by TSA, or of class II HDAC activity by LMK235, and knockout of HDAC4 in four independent cell lines, each caused a defective response to type I IFN using reporter gene assay and RT-qPCR of endogenous ISGs. This defect was rescued by reintroduction of HDAC4, but not HDAC5 or HDAC1. In addition, ChIP analysis of HDAC4 and STAT2 showed that HDAC4 is recruited to multiple ISG promoters following IFN-α stimulation, and HDAC4 is needed for the recruitment of STAT2 to ISG promoters. Given that HDACs are needed for IRF9-mediated recruitment of RNA polymerase II to ISG promoters , the ChI−/− cell lines . LMK235 is most potent against HDAC5, but it inhibits several other class II HDACs. HDAC6 up-regulates IFN-β expression after stimulation with dsRNA . The second study knocked out HDAC4 from Hep-2 cells and reported that this caused reduced HSV-1 replication  were maintained in MEM (Gibco) supplemented with 10% FBS and 50 μg/mL P/S.Immortalized primary human fetal foreskin fibroblasts (HFFF-TERTs) , human HPlasmids used in this study were from the following sources: pcDNA3.HDAC4-FLAG , pcDNA3.HDAC4 3SA-FLAG , pcDNA3.HDAC5-FLAG , and pcDNA3.HDAC1-FLAG . pcDNA3.HA-STAT2, pcDNA3.HA-STAT1, pcDNA3.IRF9-TAP, pcDNA3.IRF9-S2C, pcDNA3.TAP-C6, and pcDNA3.N1-TAP were described . The repC6L were described (WT VACV strain Western Reserve (WR) and derivative strains expressing GFP fused to the capsid protein A5 (A5GFP VACV) , or lackescribed . HSV-1 sescribed .The following antibodies were used: Rabbit (Rb) anti-HDAC4 , Rb anti-FLAG , Rb anti-STAT2 , Rb anti-STAT2 , Rb anti-STAT1 , Rb anti-C6 (described in ref. 6) were seeded in a 10-cm dish on day 1. On day 2, the cells were transfected with 3 μg pLKOneo.EGFPnlsTetR together with 3 μg of each pMD-G and pCMV.dR8.91 plasmids. Three hours posttransfection, the cell culture medium was removed and replaced with DMEM with 30% FBS and 50 μg/mL P/S. On day 3, the cell culture supernatant was collected and replaced with 5 mL DMEM containing 30% FBS. The collected supernatant was passed through a 0.45-μm filter and 2 μg/mL Polybrene  was added. This lentivirus stock was used to infect U2OS cells that were seeded on day 2. On day 4, the same lentivirus infection was repeated. Following the lentivirus infection, transduced cells were selected with 500 µg/mL neomycin , and thereafter neomycin was maintained in the transduced cell culture medium. The same method was used to prepare HDAC4-FLAG expression lentivirus with plasmid pLKO.TetO.HDAC4-FLAG. Following the HDAC4-FLAG expression lentivirus infection, cells were selected with 1 µg/mL puromycin .HEK-293T cells .HDAC4g) for 1 min. Samples were then analyzed by SDS-polyacrylamide gel electrophoresis (PAGE) alongside protein molecular mass markers . Proteins separated by SDS/PAGE were transferred onto nitrocellulose membranes  by using Trans-Blot Turbo transfer system (Bio-Rad) in 25 mM Tris⋅HCl, 250 mM glycine, and 20% methanol. Membranes were blocked with 5% skimmed milk in PBST or 5% BSA in TBST at 4 °C overnight. Blocked membranes were then incubated with primary antibodies overnight at 4 °C with consistent agitation, washed three times in PBST or TBST, and then incubated with secondary antibodies for 2 h at room temperature. The membranes were then washed three times with PBST or TBST, dried at room temperature, and imaged using the LI-COR Odyssey imaging system.Cells were lysed in passive lysis buffer  and lysates were boiled at 98 °C for 5 min. The samples were cooled to room temperature and the insoluble debris was collected by centrifugation at . The cell lysate was kept at −20 °C and the firefly and Renilla luciferase activity were measured within 2 wk. To measure the luciferase activity, 50 μL firefly luciferase reagent , or 50 μL Renilla luciferase reagent (2 μg/mL coelenterazine in PBS)  was added to 10 μL cell lysate. The luminescence value was measured with a microplate reader (BMG Labtech). Firefly luciferase values were normalized to the Renilla luciferase values and the fold inductions in each reporter gene assay were calculated relative to the unstimulated controls. Experiments were performed in triplicate and conducted at least three times.HEK-293T, HeLa, or derivative HDAC48 cells for each condition (with/without IFN-α treatment). Cells were stimulated or mock treated with IFN-α  for 3 h and processed as described with slight modification  by qPCR. Primer sequences used in the above qPCR were reported (HeLa and H4KO3 cells were seeded at 1 × 10fication . Brieflyreported  previous6) were seeded on six-well plates 1 d before stimulation with 1,000 units/mL IFN-α or 100 ng/mL interleukin (IL)-1β for 4 h. The cells were harvested and the total mRNA was extracted using the RNeasy Mini kit (Qiagen) according to the manufacturer’s instructions. Thereafter, 500 ng of RNA was used to synthesize cDNA using SuperScript III reverse transcriptase (Invitrogen).Cells . ViiA 7 real-time PCR system (Thermo Fisher Scientific) was used to determine the cycle threshold of each reaction and determine the fold induction of the investigated genes. Gene amplification was normalized to GAPDH amplification and the fold induction was determined relative to control cells that had not been stimulated with IFN-α.RT-qPCR analysis of the level of mRNA for specific ISGs was performed on HDAC4C6L were described (13 cells and titrated by plaque assay on BSC-1 cells. HSV-1 strain s17 expressing GFP fused to virus protein 26 (VP26GFP) was provided by Prashant Desai (n = 20) was measured at 50× magnification using AxioVision 4.8 software and a ZEISS Axio Vert.A1 fluorescent microscope.WT VACV strain WR and derivative strains expressing GFP fused to the capsid protein A5 (A5GFP VACV)  or lackiescribed . VACV stnt Desai . This vin = 4).To measure virus replication, monolayers of HeLa or H4KO3 were infected at 0.001 pfu per cell and the yield of infectious total virus present at 2 d (A5GFP VACV) or 3 d (VP26GFP HSV-1) postinfection was determined by plaque assay on BSC-1 cells or U2OS cells for VACV and HSV-1, respectively. Measurements were made from multiple independent experiments , P > 0.05, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.Unpaired Student’s Supplementary File


Its greenhouse effect will cause serious environmental problems, such as the global warming and climate change. Therefore, the worldwide scientists have devoted great efforts to control CO2 emissions through various strategies, such as capture, resource utilization, sequestration, etc. Among these, the catalytic conversion of CO2 to methane is considered as one of the most efficient routes for resource utilization of CO2 owing to the mild reaction conditions and simple reaction device. Pioneer thermodynamic studies have revealed that low reaction temperature is beneficial to the high catalytic activity and CH4 selectivity. However, the low temperature will be adverse to the enhancement of the reaction rate due to kinetic barrier for the activation of CO2. Therefore, the invention of highly efficient catalysts with promising low temperature activities toward CO2 methanation reaction is the key solution. The Ni based catalysts have been widely investigated as the catalysts toward CO2 methanation due to their low cost and excellent catalytic performances. However, the Ni based catalysts usually perform poor low-temperature activities and stabilities. Therefore, the development of highly efficient Ni based catalysts with excellent low-temperature catalytic performances has become the research focus as well as challenge in this field. Therefore, we summarized the recent research progresses of constructing highly efficient Ni based catalysts toward CO2 methanation in this review. Specifically, the strategies on how to enhance the catalytic performances of the Ni based catalysts have been carefully reviewed, which include various influencing factors, such as catalytic supports, catalytic auxiliaries and dopants, the fabrication methods, reaction conditions, etc. Finally, the future development trend of the Ni based catalysts is also prospected, which will be helpful to the design and fabrication of the Ni catalysts with high efficiency toward CO2 methanation process.With the development and prosperity of the global economy, the emission of carbon dioxide (CO In 2017, the total CO2 emissions reached 41 billion tons, attracting the increasing worldwide attention. Therefore, how to control and reduce the amount of CO2 in the atmosphere has become an urgent issue  due to the exothermic feature of this process. Therefore, when the reaction temperature is higher than 627°C, it is supposed to obtain lower CO2 conversion and CH4 selectivity. However, the change in Gibbs free energy will be >0 according to thermodynamic calculation and the reverse reaction will take place, namely, CH4 reacts with H2O to form CO2  with strong C = O bond into CH4 (−4). Low temperature will reduce the reaction rate based on the dynamic theory  , tetragonal (t-ZrO2), and cubic structure  catalyst was affected by the composition of the Ce/Zr ratio  catalyst was higher than other catalysts. Specifically, the addition of ZrO2 increased the oxygen mobility in the lattice of cerium oxide and promoted the formation of vacancies, which in turn affected the consumption of H2 and the activation of CO2 rapidly  among all the catalysts.As regard to the Al2-Al2O3 has excellently sintering-resistant and thermally stable properties  was obviously higher than that of 20Ni/Al2O3. When the ZrO2 content of the support was <40%, the weakening effect of ZrO2 on the NiO-Al2O3 interaction was more obvious, and the reduction was easier to proceed with the increase of ZrO2 content  exhibited higher catalytic activity and better stability than non-mesoporous materials(NPA) and Ni/ɤ-Al2O3 due to its outstanding structural property as shown in 2 , which could enhance the metal-support interaction and improve the high temperature stability of Ni. Furthermore, Xu et al.  was obviously higher than that of Ni/OMA. In addition, Guo and Lu (2 and CO2). However, excessive Mg doping can also cause blockage of the active center of the catalyst, resulting in the decrease of the catalytic activity  and microwave assisted methods (M). The CO2 conversion rates of NiAl2O3-M were higher than that of NiAl2O3-I at the equal amount of Ni loadings in 2O3-M catalyst, indicating that the Ni particles were highly dispersed in nano size state, lower than the XRD detection limit (3.0 nm). As a comparison, the Ni20Al2O3-I catalyst presented much higher metallic Ni diffraction peaks, suggesting the worse dispersion of metallic Ni particles. Therefore, the microwave method could facilitate the uniform distribution of Ni on the support. In addition, microwave assisted method contributes to greater catalytic stability and sintering resistance of the catalyst  was beneficial to the enhancement of the CO2 methanation reaction. As shown in 2 methanation reaction gradually dominated with the increase of the Ni loading amount. They found that the catalyst could achieve the best activity for methanation and low yield of CO when the Ni loading was 20 wt%. Therefore, it could be concluded that the increase of active sites (Ni0) was beneficial to the achievement of high CO2 conversion. However, when the nickel loading amount exceeded a certain range, further increasing the loading amount would cause seriously thermal agglomeration of the metallic nickel active centers, thereby destroying the structure of the catalyst  reaction and thereby promoting the conversion of CO2 to CH4  reaction between intermediate CO and the excess of water. In addition, water vapor may cause dilution of the gaseous reactants, inhibiting the interaction of H2 with CO2  analysis. As observed in 2 molecules during the process of its activation. The activated CO2 dissociated on the surface of Ni, forming carbonate intermediate species. Finally, the atomic hydrogen reacted with the carbonate intermediate to form methane. Takano et al. (2 catalyst were observed and the carbonate was the main adsorbate in the reaction during the process of the DRIFTS analysis. Thus, carbonates were the reaction intermediate for the formation of CH4 on the Ni/ZrO2 catalyst. They found that the bidentate carbonates were probably the most important intermediates adsorbed on these highly active Y doped catalysts. The combination of Y3+ and Ni2+ with ZrO2 created oxygen vacancies in the oxide, which would help to form a stable bidentate carbonate adsorbate on the catalyst.Another viewpoint that CO is not the COo et al.  also fou2 methanation processes (Solis-Garcia and Fierro-Gonzalez, 2 methanation reaction over Ni-based catalysts supported on different metal oxides. Although almost no CO2 methanation reaction occurred over Ni/La2O3 catalyst at 250°C, the chemisorption of CO2 by Ni/La2O3 was more obvious than other samples. In contrast, the strong chemisorption of CO2 was not observed over the Ni/Y2O3 and Ni/Sm2O3 catalysts. For Ni/Y2O3 catalysts, the main reaction intermediates of the CO2 methanation reaction were carbonate and formate species. The carbonate species was the initial reaction intermediates and then it was gradually converted into monodentate formate and bidentate formate through hydrogenation process. The main reaction pathway for CH4 production was hydrogenation of monodentate formate because the reaction rate of monodentate was faster than that of bidentate. CO2 methanation process over the Ni/La2O3 catalyst did not experience bicarbonate and formate intermediates because of the high desorption temperature of CO2. CH4 was formed by experiencing the formate intermediate rather than the CO pathway over the Ni/ZrO2 catalyst. Furthermore, Pan et al. (2O3 and Ni/Y2O3 were similar. As regard the Ni/Al2O3, CO2 reacted directly with surface hydroxyl groups and surface oxygen to form bicarbonate and monodentate carbonate intermediates. The reaction between CO2 and the surface hydroxyl group could be attributed to the nucleophilic attack of the oxygen atom of the hydroxyl group on the CO2 carbon atom (Solis-Garcia and Fierro-Gonzalez, 2. As the temperature increased, methane characteristic peaks began to form and the intensity of formate slowly decreased. According to previous reports (Guilera et al., 2 methanation catalysts commonly possess weak basicity site, medium basicity site, and strong basicity site. The weak basicity sites are usually derived from surface hydroxyl groups and the moderate and strong basicity sites are derived from surface oxygen. Moderate basicity sites promote the decomposition of formate salts. Strong alkaline sites have a negative effect on the activation of carbonates, thereby inhibiting the generation of CH4. Therefore, the hydrogenation of monodentate carbonates was hindered by the strong basicity sites of surface oxygen in Ni/Al2O3. The hydrogenation of bidentate carbonates was the main reaction pathway for CH4 formation. The methanation reaction of Ni/CeO2-ZrO2 was different with that of Ni/Y2O3. The hydrogen carbonate, bidentate carbonate and monodentate carbonate intermediates appeared over Ni/CeO2-ZrO2 during the methanation reaction. As the temperature increased, the number of carbonate species gradually decreased and the number of bidendate species gradually increased. This indicated that the bidentate species were main intermediates in the reaction (Pan et al., 2 was mainly converted to 2 catalyst while CO2 was converted to bicarbonate on Ru/α-Al2O3 catalyst. Besides, Wei et al. (Liu J. et al., 2 methanation. As shown in 2 molecule to carbonate/hydrocarbonate species and Ni/CNT lacked base sites. Further, CO2 was mainly converted into methane via the formate intermediate over the Ni-based catalyst prepared by the ammonia evaporation method. However, the formate intermediate could not be formed over the Ni/CeO2-ZrO2 catalyst prepared by wet impregnation method (Ashok et al., 2.It was reported that different supports also could cause different reaction intermediates during the COn et al.  also fou2, some scholars believe that the activation of CO2 occurs over the metallic Ni active site (Aziz et al., 2 methanation on Ni/MSN. Specifically, CO2 and H2 molecules were firstlyadsorbed on Ni active sites, followed by dissociation to form CO, O, and H atoms, and migrated onto the MSN surface. The CO then interacted with oxide surfaces of the MSN and bidentate formate was also formed through the interaction with atomic hydrogen. Meanwhile, the O atom spilt over onto the surface of the MSN and was stabilized in the oxygen vacancy site near the Ni sites. However, the viewpoint of Jangam et al. (2 with a surface basic oxyanion on the metal oxide. Therefore, the activation of CO2 occurred on the support. Besides, Aldana et al. (2 was activated on the CeO2-ZrO2. Therefore, up to now, the real activation site of the CO2 molecule has still been the controversy of the CO2 methanation reaction.As for the activation site of COm et al.  was oppoa et al.  also fou2 emissions are increasing, resulting in a series of global environmental problems. Therefore, it is of greatly practical significance to study CO2 methanation technology in order to solve the problem of energy shortage and reduce the concentration of CO2 in the atmosphere. Besides, it is of great urgency to develop highly efficient Ni based catalyst to accelerate this process because of the kinetic limitations of CO2 methanation.Nowadays, CO2 methanation process. In terms of reaction conditions, such as temperature, pressure, humidity, etc., they are also considered as important factors affecting the catalytic behavior of the catalyst, which have been carefully summarized in this review. In addition, the reaction mechanism of Ni based catalysts toward CO2 methanation are also carefully reviewed. It was believed that the nature of the catalytic support, additive and preparation strategy of the catalyst could affect the dominant reaction pathway and intermediates during the process of the methanation of CO2.In recent years, Ni-based catalysts have been widely used due to their good catalytic performance and low price. In order to develop Ni-based catalysts with good low-temperature activity, the global scientists have made great efforts to investigate different influencing factors, such as catalytic support, dopant, preparation method. This review generally summarizes different ways to improve catalyst performance. From the perspective of preparation methods, the traditional preparation methods of Ni-based catalysts, such as impregnation and coprecipitation, have become basically mature technologies. Therefore, the researchers have begun to develop new methods and strategies, such as microwave assisted method and plasma method. The catalytic performance of the catalyst prepared by these methods is usually superior to that by the conventional preparation method. In the viewpoint of dopants, their addition can adjust the acidity-alkalinity and electronic/redox property of the catalyst, further improving the dispersion and coordination environment of the metallic active sites. As a result, the additive-modified Ni-based catalyst has the advantages of good reactivity and long lifespan. In this review, the additives are divided into four categories, namely rare earth metals, alkaline earth metals, transition metals and precious metals, and their effects on the catalyst are described and summarized in detail. As for the catalytic supports, they can obviously influence the textural property of the catalyst, thereby affecting the catalytic performances toward CO2 methanation should still be placed on the improvement of both low-temperature catalytic performance and anti-sintering property of the metallic Ni active site. The development of new supports ought to be the main research line. Besides, the investigation of CO2 methanation mechanism on the Ni-based catalyst is beneficial to finding routes to improve the activity of catalysts. Meanwhile, it is of great significance to optimize the preparation method in order to scale up the synthesis of the catalysts in the future industrialization process. Finally, taking the cost of preparing catalysts into consideration is necessary in order to achieve green catalysis and catalysts should be applied to industrial CO2 methanation by improving reactors and other methods.In future research, the hot spots of research on Ni-based catalysts toward COMC, LX, and CL: conceptualization. YC and XH: software. MC, LX, and CW: validation. XW, YL, and BY: investigation. MC, XH, and QS: resources. ZM, BY, and CW: data curation. CL: writing—original draft preparation. CL, LX, and MC: writing—review and editing. MC and LX: supervision, methodology, and project administration.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This process can achieve the efficient resource utilization of CO2 and CH4 and reduce greenhouse gases. Therefore, CRM has been considered as a significantly promising route to solve environmental problems caused by greenhouse effect. Ni-based catalysts have been widely investigated in CRM reactions due to their various advantages, such as high catalytic activity, low price, and abundant reserves. However, Ni-based catalysts usually suffer from rapid deactivation because of thermal sintering of metallic Ni active sites and surface coke deposition, which restricted the industrialization of Ni-based catalysts toward the CRM process. In order to address these challenges, scientists all around the world have devoted great efforts to investigating various influencing factors, such as the option of appropriate supports and promoters and the construction of strong metal-support interaction. Therefore, we carefully summarized recent development in the design and preparation of Ni-based catalysts with advanced catalytic activity and enhanced anti-coke performance toward CRM reactions in this review. Specifically, recent progresses of Ni-based catalysts with different supports, additives, preparation methods, and so on, have been summarized in detail. Furthermore, recent development of reaction mechanism studies over Ni-based catalysts was also covered by this review. Finally, it is prospected that the Ni-based catalyst supported by an ordered mesoporous framework and the combined reforming of methane will become the future development trend.CO They found that the catalytic performance of the catalyst was affected by the size of the Ni nanoparticle and the metal–support interaction between Ni and SiO2. Besides, the shape of SiO2 nanospheres did not obviously change even under high calcination and CRM reaction temperatures, demonstrating good thermal stability. Li et al. . The interaction of Ni and NiPhy materials on the Ni@Niphy@SiO2 catalyst increased because of the presence of the SiO2 shell, which inhibited the growth of Ni nanoparticles. Thus, the growth of CNTs was eliminated and high carbon-resistant performance could be obtained. Das et al.  CRM reaction because of the confinement effect of the sandwich structure and the bifunctional mechanism of dry reforming.SiOi et al.  synthesis et al.  synthesi2O3 support, it can effectively disperse Ni particles because of its large surface area, favorable thermal stability, and strong metal–support interaction  as a support to prepare the NI/CF-LA2O3 catalyst. The addition of La2O3 improved the activity of the Ni/CF catalyst because La2O3 could improve the dispersion of Ni and enhance the metal–support interaction between Ni and support. In addition, the conversion of La2O3 to La2O2CO3 affected the removal rate of deposited carbon and improved the catalyst activity of Ni/CF-La2O3.As an alkaline support, Lai et al.  tested to et al.  doped th2 support possesses excellent redox properties; however, its thermal stability was relatively poor, especially under CRM conditions  over the CeO2 surface has been considered as an effective strategy  is a sort of zeolite with weak acidity owing to no alumina component in the zeolite framework  , well-known as a new nano-carbon catalyst support, possesses many advantages, such as large surface area, unique electronic properties, tubular structure, chemical inertness, thermal stability, and high mechanical strength  to the Ni/γ-Al2O3/ACF catalyst was beneficial to improvement of the CRM catalytic activity. ACF could reduce the grain size of NiAl2O4 spinel in Ni-based catalysts, which was conducive to the conversion of methane. The addition of ACF could provide abundant functional groups on the catalyst surface and effectively promote the catalytic performance of the CRM reaction.As for carbon fiber, it has a similar thermal stability and high specific surface area to the activated carbon. Besides, their fibrous properties make them more beneficial to producing structurally defined catalysts , performing an effect toward CRM. It was found that MgO could greatly improve the dispersion and metal area of the metallic Ni active site. The Ni/5MgO-Al2O3 catalyst performs the best anti-coke property and highest H2/CO ratio among these catalysts. Singha et al. , high oxygen capacity, and abundant activated oxygen species  catalysts by co-precipitation and impregnation methods toward CRM reaction. The CeO2-Ni-MgO-Al2O3 catalyst exhibited much higher activity, better stability, and more excellent anti-coking performance than the Ni-MgO-Al2O3 catalyst because of the improvement of Ni dispersion and the metal–support interaction by CeO2 promotion. Wang et al. , which contributed to the elimination of the carbon deposition on the surface of the support  and plasma (Ni/ZrO2-P) methods for the CRM reaction. Compared with NiZrO2-C, the Ni/ZrO2-P catalyst displayed more Ni(111) planes, smaller metallic Ni particles, and more oxygen vacancies. As a result, the Ni/ZrO2-P catalyst displayed better catalytic activity than Ni/ZrO2-C toward CRM reaction. Fang et al. 4 nanosheets in the catalyst precursor. Among them, the strong electrolytic capacity of NaOH made the most Ni3Si2O5(OH)4 nanoflakes formed in the Ni-MSC-1 catalyst, which results in the highest Ni dispersity and highest catalytic activity. Park et al.  the gradual decomposition and dehydrogenation of CH4 to *, (2) the recombination of H* to generate H2, and (3) the desorption of the catalyst surface at high temperature  sites to generate carbon atom and hydrogen atom. Finally, the oxygen atom reacted with the carbon atom to produce CO. Furthermore, it could be observed in 2O2CO3 by inhibiting the oxygen supply from the filamentous carbon chains to the metal surface. The metal nanoparticles were kept in close contact with the supporting site to obtain a stable oxygen supply and CO generation. When a large amount of coke was formed, the metal particles were removed from the scaffold by filamentous carbon. As a result, there was no oxygen supply from La2O3. The carbon atoms formed on the metal surface could not be effectively eliminated and the polymerization of the carbon atoms accelerated the coking process. Therefore, the close contact between the metallic active site and the support had an important impact on the high activity and stability of the CRM catalyst because the CO formation reaction might take place at the metal–support interface. In summary, so far there has not been a single reaction mechanism that can summarize all CRM reactions. However, extensive research on CRM reaction mechanism contributes to a deeper understanding of CRM reaction and then design of the catalyst with better catalytic activity.Chong et al.  reported. et al.  found thu et al.  preparedm et al.  studied 2 has been considered as one of the major incentives of many environmental problems, such as global warming and extreme weather. CRM not only effectively utilizes the CO2 resource and reduce carbon emissions but also produces the value-added syngas, which can be further employed as the building unit of the synthesis of alcohols, olefins, and other valuable products. For now, the main challenge of the CRM reaction is to develop a highly efficient catalyst with high catalytic activity, sinter proof, coke resistance, and low cost.CONi-based catalysts have been widely regarded as promising alternatives to noble metal catalysts. However, their industrial application is limited due to the serious sintering of Ni nanoparticles and rapid catalyst deactivation caused by coke deposition. Various strategies of improving the performance of catalysts are carefully and comprehensively summarized in this review. In order to reduce carbon deposition on Ni-based catalysts, researchers have tried to add promoters to change the alkalinity of the support, such as alkaline earth metal oxides and rare-earth metal oxides, which can enhance the stability and decrease carbon formation. It is found that the catalytic performances can be affected by the preparation methods. Besides, the choice of the support is also very crucial. Various materials, such as metal oxides, ordered mesoporous silica gel materials, zeolite materials, and carbon materials, can be used as the supports of the Ni-based catalysts.2/CO ratio of syngas by changing the feedstock gas ratio, which will provide different approaches for large-scale industrial applications of CRM.In future research, it can be prospected that the research hotspot of Ni-based catalysts in the field of CRM will focus on the Ni-based catalysts supported or confined by novel materials, such as ordered mesoporous materials and hollow zeolites. Specifically, the mesoporous framework in these catalysts facilitates the dispersion of active sites, and the confinement effect of mesoporous channels or hollow cavity can effectively control the size of Ni nanoparticles during CRM reactions. Besides, the combination of CRM with other reactions, such as SRM and POM, can alter the HLX conceived of the presented idea. LX encouraged XWu to investigate the project and supervised the whole progress of this work. CL, YC, XWen, CW, BY, and ZM assisted XWu to carry out the literature survey and summary. XWu, LX, and MC wrote the manuscript with support from XH. LX, MC, and XH supervised the whole project. All authors discussed the results and contributed to the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that combined music information retrieval with spatial Fourier Independent Components Analysis  to probe the interplay between the spatial profiles and the spectral patterns of the brain network emerging from music listening. Correlation analysis was performed between time courses of brain networks extracted from EEG data and musical feature time series extracted from music stimuli to derive the musical feature related oscillatory patterns in the listening brain. We found brain networks of musical feature processing were frequency-dependent. Musical feature time series, especially fluctuation centroid and key feature, were associated with an increased beta activation in the bilateral superior temporal gyrus. An increased alpha oscillation in the bilateral occipital cortex emerged during music listening, which was consistent with alpha functional suppression hypothesis in task-irrelevant regions. We also observed an increased delta–beta oscillatory activity in the prefrontal cortex associated with musical feature processing. In addition to these findings, the proposed method seems valuable for characterizing the large-scale frequency-dependent brain activity engaged in musical feature processing. Understanding how our brain perceives complex and continuous inputs from the real-world has been an attractive problem in cognitive neuroscience in the past few decades. Brain imaging technology provides an opportunity to address this issue. However, revealing brain states is generally more difficult during real-word experiences than those recorded brain activities during resting-state or simplified abstract stimuli like controlled and rapidly repeated stimuli   is a well-established data-driven approach increasingly used to factor resting-state fMRI data into temporally covarying, spatially independent sources or networks. By contrast, in the analysis of EEG/MEG data, ICA has mainly been applied for artifact rejection. However, spatial Fourier–ICA was proposed for data-driven characterization of oscillatory brain activity using EEG/MEG data. Compared with other ICA method applied to the context of music listening, spatial Fourier–ICA used in the current study can automatically extract narrowband oscillations from broadband data without having to manually specify a frequency band of interest. So far, spatial Fourier–ICA has already been proved to be fruitful in gaining insights into electrophysiological underpinnings of networks  for each source point while a relative conductivity coefficient was assigned to each tissue (with default MNI MRI template).To solve the inverse problem, minimum-norm estimate . Now the challenge is to determine which one of these represents the genuine brain responses. In all ICA based methods, it is a general question that which independent components need to be retained or which component just reflects noise. Here, we examine which components were modulated significantly by the musical features. We computed the correlation (Pearson’s correlation coefficient) between the time courses of musical features and the time courses of those ICs  in order to select stimulus-related activations. We used the Monte Carlo method and permutation tests presented in our previous research  for initializing the algorithm. We used the minimum description length (MDL) to determine the number of clusters M. Afterwards we countered the number of subjects involved in ICs in each cluster. If the number of subjects in one cluster is less than half of the all subjects, this cluster would be discarded for the reason that such a cluster does not reveal information shared among enough participants. For the retained clusters, the spatial-spectral-temporal information was obtained, which was represented by the centroid of the cluster, the spectra of ICs and the numbers of subjects whose temporal courses were involved in this cluster.Five musical features were extracted by MIRtoolbox  firstly need to be extracted from the MEG data and were concatenated in certain dimensionality; ICA was then performed to concatenated data (Nugent et al. In this study, we introduced a novel framework with several techniques including Fourier ICA, source estimation, acoustic feature extraction, and clustering for exploiting the spectral–spatial structure of brain during naturalistic stimulus. A complex-value ICA applied to source-space time–frequency representation of EEG data. Following this, a modified ICASSO was performed to evaluate the stability of ICA estimate and a cluster analysis was applied to examine the inter-subject consistency. The identified networks involved in music perception were in line with those previous studies. Further, we found that brain networks under music listening were frequency-specific and three frequency-dependent networks associated with processing musical features were observed.