We firstly find out a rather consistent trajectory of CO2 emissions in pre- and post-pandemic China over a 2-year time horizon, using the near-real-time datasets of daily CO2 emissions by Carbon Monitor and applying the Cox-Stuart trend test and mean equality test. We then examine the emission reduction effects by China's carbon ETS and its pilot market performances, using the methodologies of DID and PSM-DID as well as pre-pandemic region-level emission datasets by CEADs. Furthermore, it's found that the ETS pilot markets, which are immature with defects, have been performing more vulnerably in terms of liquidity and transaction continuity under pandemic shocks, thus undermining the emission reduction effects by ETS. These findings are providing insights into further mechanism design of the carbon ETS to the end of steady emission reductions even under shocks for post-pandemic China. It's of particular importance now that the nationwide market has been launched and needs to be enhanced based on lessons learned.The COVID-19 pandemic has caused great shocks on economic activities and carbon emissions. This paper aims to monitor the CO The standard deviation (SD) and coefficient of variation (CV) from January to August 2020 compared to the same period in 2019 indicate changes related to the pandemic. However, such changes began to diminish since September, and have almost vanished throughout the rest of 2020, with the SD and CV being quite close to the levels in 2019.The emission trajectory turned out to be quite stable though. Fluctuations in daily emissions before and after the pandemic outbreak were roughly synchronous over a longer time horizon. With the rapid economic recovery, the short-run impacts on emissions had diminished by the end of March, and daily emissions have returned to their normal trajectory ever since. 2 emissions before and after the pandemic. We firstly use the Cox-Stuart trend test (0: no downward trend in dataH1: downward trend in dataHHypothesisTesting2), i = 1, 2, …. When n is an even number, c groups of data pair are generated; otherwise, c-1 groups of data pair are generated, whereLet Di = xi − xi+c. S+ and S− are the numbers of positive or negative number of Di, respectively. K is the test statistic, and α is the nominal significance level. Further, when verifying HypothesisTesting1, then K = S−; when verifying HypothesisTesting2, then K = S+.It is easy to prove that if the H0 in the above hypothesis testing problems is true, then K follows the binomial distribution b, where m = S++S−. Finally, when considering HypothesisTesting1, then p = Pr(S− ≤ s−); when considering HypothesisTesting2, then p = Pr(S+ ≤ s+), where s+and s−, respectively, represents the observed values of S+ and S−. If p < α, then we reject H0 at the nominal significance level α.Let 2 emissions as illustrated in HypothesisTesting1. Results show that the p-values of the Cox-Stuart trend tests in January 2019 and 2020 are equal , and H0 is rejected at the nominal significance level of 5%. Daily emissions in January 2020 and 2019 were both showing the downward trend, and so were emissions in September 2019 and 2020.2 emissions seemed to be on the rise on the whole, and we consider HypothesisTesting2. The p-values for February through August in 2019 and 2020 are 6.26e-07 and 1.31e-24, respectively, and H0 is rejected at the nominal significance level of 5%. Daily emissions from February to August in 2020 and 2019 were both showing the upward trend. Similar results are observed for the periods from October to December in 2019 and 2020.For February through August, and for October through December, daily CO2 emissions in certain periods between 2019 and 2020, we further apply the mean equality test to verify the consistency between trends with the same direction. Calculate the monthly mean variations in emissions as sums of daily variations divided by the numbers of days within a month, and p-value being 0.81, the null hypothesis (H0: two contours are overlaps) was not rejected. This mean equality test combined with the Cox-Stuart test verifies that daily emissions in the same periods between 2019 and 2020 shared the same downward or upward trends with variations statistically indifferent from each other.Based on the Cox-Stuart trend test indicating downward or upward trends of daily CO2 emissions, even though there were abrupt shocks in the first wave of the pandemic. This finding is based on near-real-time estimates of pre- and post-pandemic emissions from fossil fuel use and industry using the same methodology by Liu et al. , Hubei, and Fujian. Although a nationwide ETS covering the power generation industry was introduced in 2017 and began its the first compliance cycle starting from 2021, the region-specific pilots with a broader coverage of sectors and enterprises are still going to play important roles in China's ETS. We take these pilot regions as treatment and the other provinces in mainland China (except for Tibet due to missing data) as control, and use the DID model as in Equation (1) to study the effects on COemissionit) denotes the log of CO2 emissions for region i in year t. DIDit is the interaction term of piloti × postit. piloti is the group dummy, piloti = 1 if i ∈ treatment and piloti = 0 if otherwise. postit is the time dummy, postit = 1, if t = 2013 for Beijing, Tianjin, Shanghai, and Guangdong, if t = 2014 for Chongqing and Hubei, if t = 2016 for Fujian; and postit = 0 if otherwise. Then, the coefficient β1 of piloti × postit indicates the average change in the log of CO2 emissions in pilot regions relative to that in non-pilot regions post policy implementation. provincei denotes the region-fixed effects on CO2 emissions from unobserved region-specific time-invariant determinants, while yeart denotes the time-fixed effects.where ln  and ln(popden), respectively, denote the log of real GDP per capita calculated at prices in 2005 and population density, controlling impacts on emissions related to the economic scale and population agglomeration.indshare and coalshare denote the proportions of added value from the secondary industry to GDP, and coal consumption to total energy consumption, respectively, representing the structure of the economic and energy system.ecintensity, calculated as consumption of standard coal equivalent per unit of real GDP, could be regarded as a proxy for technology advancement related to energy conservation and emission reduction.Energy consumption intensity denoted by urbanshare, eximshare, rdshare, and indpoinvestshare denote the proportions of urban population to total population, trade value to GDP, industrial enterprises' expenditures on R&D to GDP, and investment completed in the treatment of industrial pollution to GDP, respectively, controlling impacts on emissions related to urbanization, trade, technology innovation and environmental regulation.2 emission inventories in China by CEADs, and datasets on regional economy, energy use, and environment by NBS. See Section Data Availability Statement for details. 2 emissions in pilot regions is lower than that in non-pilot regions by almost 20%. It's reasonable with the mean of indshare, coalshare, and ecintensity being smaller and the mean of rdshare being greater in pilot regions, indicating positive effects in reducing CO2 emissions in an economic structure featured by less-intensive fossil fuel use and greater investment on technology innovation, which more than offset the emissions from a larger scale of economic output, population agglomeration and urbanization.We use the region-level CODID estimates indicate the emission reduction effects induced by ETS, with the control group providing effective counterfactual changes to emissions of the pilot regions. It's important to identify parallel trends in emissions across treatment and control groups over time, before we attribute variability across groups to the effects induced by ETS policies rather than pre-existing time trends. Since the ETS pilots were not randomly selected, it might not be appropriate if we take all non-pilot regions as control. For this concern, we use the Probit model as in Equation (2) to calculate propensity scores and match pilot regions to non-pilot regions that have similar characteristics in covariates of CO2 emissions. The k-nearest neighbor matching (NNM) within radius, with k=2 and t-test further show that for most variables the mean values across groups are insignificantly different, suggesting the validity of matching.Then, we match pilot and non-pilot regions year by year, using the estimated propensity scores and a most-commonly-used matching algorithm, the pilot × post under various regression scenarios are all statistically significant and negative, indicating significant effects in reducing emissions by ETS in pilot regions. Moreover, the PSM-DID coefficients (ranging from −0.04 to −0.09) are smaller in magnitude than DID coefficients , indicating that the emission reduction effects by ETS could have been exaggerated if we simply applied the DID methodology without caution. With more reliable estimates after PSM, we calculate the average treatment effects on the absolute magnitude of CO2 emissions in pilot regions post ETS implementation, relative to control groups of non-pilot regions (pre- or post-ETS) and pilot regions pre-ETS. Measured with different sizes of matched samples using the same matching algorithm, CO2 emissions in pilot regions post ETS are reduced by 4–8.6%.Columns (3)–(8) in ln(emission) within each group year by year from 2005 to 2019. We apply two diagnostic tests for parallel trend across treatment and control groups. Firstly, we calculate the average To further verify parallel trend, we follow the methods by Chen et al.  and estik-year(s) before ETS implementation with k = 1, 2, …, 11 covering the years from 2005 to 2015. Then, if the coefficient βk of where k = 1, 2, …, 11) are all statistically insignificant, or statistically not different from 0. This finding verifies that the assumption of parallel trend is not violated, and estimates using the PSM-DID methodology capture the emission reduction effects by ETS.1 as in Equation (1). We conduct a placebo test to further check robustness of our estimation results. Based on Monte Carlo simulation, regions and years are randomly selected to generate a virtual treatment group for 1,000 times. With these random permutations, we then use the DID regression to estimate βSince the ETS is a market-based mechanism for emission reduction, the reduction effects are bound to vary with the performances of pilot markets [See  for a reperformanceit is a set of variables capturing the characteristics of transactions on pilot markets if i ∈ treatment, and takes the value of 0 if otherwise indicating no market performances whatsoever in non-pilot regions. Following Liu et al. (priceit) and ln (volumeit), respectively. Considering that a market with greater trading volumes tends to be more active and maintains prospects for assets to be more easily exchanged, we use ln (volumeit) to capture the liquidity of pilot markets  as in Column (1), indicating the pilot markets are working in emission reductions through the fundamental signals of carbon prices, which reflect marginal abatement costs and provide incentives for emission reductions. Still, to increase the odds of trading prices efficiently reflecting marginal abatement costs, we rely on a moderate liquidity with reasonable trading volumes on pilot markets. As Column (2) reports, the coefficient of DID × ln (volume) is also statistically negative, indicating the emission trade in pilot regions is working in emission reductions through liquidity of carbon assets. Furthermore, we find statistically negative coefficients of DID × continuitycounts and DID × continuityprop. As the proportion of continuous trading days to total trading days within a year increases by 1 unit on pilot markets post implementation of ETS, the log of CO2 emissions are estimated to reduce by 0.167%. Apart from the trading prices and liquidity, the continuity of transactions on pilot markets is another important determinant for emission reductions. These findings are of particular importance for us to better understand the post-pandemic emission reductions by ETS.As important determinants for emission reduction effects by ETS, pilot market performances, especially in terms of liquidity and transaction continuity, have been experiencing severe shocks during the pandemic.Take the pilots of Shanghai and Beijing for instance. Transactions even halted for months on some markets in 2020. Take the pilot of Fujian for instance. There were no transactions at all for the first 6 months, compared to a total trading volume of 3.34 million tons for the same period in 2019. This transaction halt lasted for 187 days until July 2020 with a rather small trading volume of 3,748 tons, almost 98.25% less compared to the same period in 2019. Throughout 2020, total trading intervals without transactions amounted to 302 days on the Fujian Exchange.The pilot markets suffered from great shocks during the pandemic, including markedly decreasing trading volumes and long-lasting transaction halts. Considering the negative coefficients of liquidity and continuity as in If regarded as a natural experiment, the pandemic, or indeed any crisis whatsoever, is intensely exposing the ever-existing defects of China's carbon ETS and its pilot markets. Low liquidity with trading volume usually concentrated right before compliance deadlines, few and non-diverse participants and their lack of incentives in emission trading, and regulated firms' tendency to reserve emission allowances for upcoming stricter policies rather than trading, as well as regional barriers among exchanges due to differential regulation and technical methods, have contribute to the weak market performances. When shocked by the pandemic, the markets would only perform even more vulnerably. Consequently, the ETS, as a key driver for emission reductions, might just end up with limited reduction effects. Unless handled properly with careful and effective mechanism design, the defects and immaturity of ETS markets would continuously undermine the emission reduction efforts in post-pandemic China.2 emission trajectory for pre- and post-pandemic China, we use the near-real-time datasets of daily CO2 emissions by Carbon Monitor, and apply the Cox-Stuart trend test and mean equality test. A fairly consistent trajectory is observed over a 2-year time horizon before and after the pandemic outbreak, despite abrupt shocks in the first wave. Although for the time being we find no signs of significant changes in the emission trajectory, we believe it's necessary to further investigate the pandemic impacts on key forces underlying the trajectory and driving for emission reductions.There have been shocks on the economic activities and carbon emissions all around the world since the outbreak of the pandemic. They could be only temporary, though, if there are no fundamental changes in the emission trajectory and its determinants by reason of the pandemic. To examine the CO2 emissions by China's carbon ETS and its pilot market performances still need to be examined, especially when under pandemic shocks. To this end, we firstly estimate the reduction effects by ETS for pre-pandemic China, and then check on the pandemic impacts on pilot market performances with implications for emission reductions in post-pandemic China.Amongst these drivers, particular importance has been attached to the market-based ETS. China's carbon ETS, however, has been working mostly through the eight pilot markets, which are immature and bound to undergo shocks during the pandemic. The effects on CO2 emission datasets by CEADs, we find statistically significant emission reduction effects by China's carbon ETS. Estimated with different sizes of matched samples using the algorithm of k-NNM within radius, CO2 emissions in pilot regions post the implementation of ETS are significantly reduced, with the average treatment effects ranging from 4–8.6%. For robustness checks, we apply two diagnostic tests for parallel trend across treatment and control groups, as well as a placebo test with 1,000 random permutations based on Monte Carlo simulation.Using the methodology of PSM-DID and pre-pandemic region-level COWe also find statistically significant emission reduction effects by pilot market performances regarding the trading price, liquidity, and transaction continuity. The pilot markets are working in emission reductions through the fundamental signals of carbon prices, as well as the liquidity and continuous transactions of emission allowances. The pilot markets, however, have been experiencing great pandemic shocks. With markedly decreasing trading volumes and long-lasting transaction halts, the pilot markets have been performing more weakly and vulnerably under pandemic shocks compared to usual times. Consequently, the emission reduction effects by ETS during and after the pandemic could just end up undermined. Rather than being the root for such performance deterioration, however, the pandemic shocks are more like catalyzer, exposing the ever-existing defects on immature pilot markets intensely and aggravating the limited emission reductions by ETS.2 emissions at all levels covering a longer time horizon.If regarded as a natural experiment, just as previous crisis were, the pandemic might as well provide some lessons on the mechanism design of the carbon ETS for post-pandemic China. It's critical to ensure and maintain the market liquidity and transaction continuity, so as for the market-based ETS to fully realize its emission reduction effects. More efforts need to be devoted to increasing the trade varieties and introducing more and diverse participants into the markets. Encourage firms to get more involved in emission trading by the price discovery function of trading prices as they reflect the marginal abatement costs and provide incentives for emission trading, rather than just requiring them to meet control goals by compliances deadlines. Now that based on pilot operations, the nationwide market has entered into its first compliance cycle and started to play an increasingly core role in the carbon ETS, it's of particular value that we learn the lessons and improve the mechanism design of the national ETS for post-pandemic China. There are still a lot to be explored, especially regarding the desired properties of heterogeneous emission trading markets to the end of steadily reducing emissions even under shocks. We're to further our research, and expect to be in a better position to study with future access to more detailed datasets of CO2 emission estimates can be accessed through Carbon Monitor (https://carbonmonitor.org.cn/). Refer to Liu et al. . Refer to (https://www.cneeex.com/), Beijing Green Exchange (https://www.cbeex.com.cn/), Guangdong China Emissions Exchange (http://www.cnemission.cn/), Tianjin Climate Exchange (https://www.chinatcx.com.cn/), China Hubei Emission Exchange (http://www.hbets.cn/), Chongqing Carbon Emissions Trading Center (https://tpf.cqggzy.com/), as well as the carbon emission trading platform (http://www.tanjiaoyi.org.cn/). Datasets for other variables used in this study can be accessed through China Statistical Yearbook, China Energy Statistical Yearbook, and China Statistical Yearbook on Environment, compiled by the NBS .Datasets of daily COu et al. , 14 for Refer to –40 for tKL: conceptualization, methodology, analysis, and writing. AX: conceptualization and reviewing. RY: methodology, analysis, and reviewing. WL: methodology, data analysis, and writing. All authors contributed to the article and approved the submitted version.This research was supported by National Social Science Foundation of China (Grant No. 21BTJ068) and Zhejiang Provincial Philosophy and Social Science Planning Project of China (Grant No. 22NDQN284YB).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Introduction: Drug-coated balloon (DCB) has been an attractive option in de novo vessels. A systematic review and meta-analysis were conducted to evaluate the efficacy and safety of DCB vs. stent for treating de novo lesions in non-small vessels.Methods: Studies in PubMed, Embase, the Cochrane Central Register of Controlled Trials, and Web of Science were searched (from their commencement to March 2021). This meta-analysis was performed by Review Manager 5.3.Results: A total of 3 random controlled trials (RCTs) with 255 patients and 2 observational studies (OS) with 265 patients were included in this meta-analysis following our inclusion criteria. It could be observed that DCB presented no significant difference in cardiac death (CD) , myocardial infarction (MI) , target lesion revascularization (TLR)  , and late lumen loss (LLL)  for de novo non-small coronary artery disease (CAD) compared with stents, whereas minimal lumen diameter (MLD) including MLD1  and MLD2  was smaller in DCB group.Conclusion: This systematic review showed that DCB might provide a promising way on de novo non-small coronary artery disease compared with stents. However, more RCTs are still needed to further prove the benefits of the DCB strategy.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/#recordDetails. Coronary artery disease (CAD) is still the leading cause of human death and disability worldwide according to the latest epidemiological data from the Global Burden of Disease (GBD) . Percutade novo vessel disease and patients with a high risk of bleeding. In addition, there are other potential indications, such as bifurcation lesions, chronic total occlusion lesions, and others .In recent years, drug-coated balloon (DCB) has been investigated and applied in clinical for its no residues. It has become 1 of the preferred options for the treatment of ISR by the ESC guideline . There ad others –13. With lesions –16. Howe vessels –21. Lin  vessels  did a mede novo lesions in non-small vessels.Therefore, we conducted a systematic review and meta-analysis to evaluate the efficacy and safety of DCB vs. stent for treating This meta-analysis followed the Preferred Reporting Items for Systematic Meta-Analysis (PRISMA) statement . The proThe following electronic databases were searched: PubMed, Embase, the Cochrane Central Register of Controlled Trials, and Web of Science from their commencement to March 2021 for the relevant literature. A manual search of references was performed for additional omitted studies. The specific search strategies were presented in the supplemental.The literature was independently screened and evaluated by 2 authors (Sun and Liu). In total, 2 authors scanned the title and abstract according to the inclusion criteria and then screened again by reading the full text. If there were any disagreements, it would be discussed with another author (Wang) and resolved by consensus, or contacted the original author of the article if necessary.de novo lesions with lumen diameters ≥ 2.5 mm; (3) DCB as experimental group without any restriction on the type of DCB; (4) stent as control group for DES only; and (5) studies included RCT and observational study (OS).The inclusion criteria were as follows: (1) patients with CAD; (2) PCI for de novo lesions with lumen diameters < 2.5 mm; (3) studies were reviewed or conference abstract; and (4) data inefficient.The exclusion criteria were as follows: (1) patients with peripheral vascular diseases; (2) PCI for The study outcomes could be divided into clinical outcomes and angiographic outcomes. The clinical outcomes included cardiac death (CD), MI, and target lesion revascularization (TLR). CD was defined as death caused by cardiac factors. MI was defined based on the latest ESC guidelines . TLR wasThe following data were extracted from eligible studies independently by 2 authors (Sun and Liu): the study of the author, year, and country; patients' indication; the number of patients, age, and sex in each group; the vessel diameter and length; the main characteristics of DCB; the type of DCB and stents; lesion preparation for DCB and stents; clinical and angiographic outcomes and follow-ups.The quality of the eligible RCT studies and the risk of bias were assessed by 2 independent authors (Sun and Liu) using the Cochrane Handbook for Systematic Reviews of Interventions, version 5.1.0, which contains seven criteria: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective outcome reporting, and other bias. These seven criteria were rated as “low risk,” “unclear risk,” or “high risk” depending on the characteristics of each criterion reported in the study. For OS, the quality of the studies was assessed by the Newcastle–Ottawa Scale (NOS) with 8 items including selection, comparability, and outcome. A study with more than 6 stars was regarded as a high-quality one.de novo non-small vessels was measured by relative risks (RR) for all clinical outcomes and standard mean difference (SMD) for all angiographic outcomes. As several included studies did not offer the changes in the standard deviation (SD) of LLL or MLD from the baseline values, we calculated the SD change by the following formula (1). The coefficient was taken as 0.5 according to other eligible studies that provided the SD baseline, SD final, and SD change.The effect of DCB or stents for 2 + (SD posttreatment) 2 - (2* coefficient *SD pretreatment *SD posttreatment)] (1)SD change = √, p = 0.50). MI was observed in only 1 study  either. The specific description results were presented in the Of the 3 RCTs and 2 OS, CD was observed in only 1 study , with no 1 study , with noRR 0.64, 95% CI , p = 0.47). In OS, there was no significant difference in the rate of TLR  either. There was lower heterogeneity in RCT  and OS . The specific description results were presented in the In RCT, the results showed no significant difference between DCB and stents in the rate of TLR . In OS, only 1 study . In OS, only 1 study . In OS, only 1 study , MLD1 , and MLD2  were not significantly changed, which indicated the results were robust enough. We observed that the heterogeneity of LLL was declined (I2 from 90% turned to 58%) when the study of Gobic et al. , MLD1  when the follow-up was more than 6 months according to the subgroup analysis, it still remained a moderate heterogeneity and it was not able to determine the source of heterogeneity.There had been studies on the comparison between DCB and DES or other types of stents, but their data only focused on the small vessels or did not consider the vessel diameter of n et al. suggestednflation . Iwasakinflation  chose ronflation . It is snflation , NSE balidelines . TLR wased study –19. Fromed study  found CDed study . Thus, ted study , 27. QCAed study  did not ed study –19 were que area . The resAs the most widely used procedure of PCI, stents are unceasing, updating, and developing. BMS has improved the cardiac hemodynamics though there are a series of complications, such as in-stent restenosis (ISR). The first-generation DES, with antiproliferative drugs such as paclitaxel or sirolimus, was investigated and reduced the rate of ISR compared with BMS. However, the late and very late stent thrombosis still exists in the first-generation DES. The dual antiplatelet therapy will also increase the risk of bleeding. To overcome these complications, the second- or newer-generation DES has been investigated with improved stent platforms, biocompatible, durable, or biodegradable polymers, and newer antiproliferative agents, even new technologies, such as ultrathin strut and polymer-free DES, which were developed and assessed by several trials. Studies showed that the risk of early or late complications was reduced in ACS and showed a better effect in patients with diabetes. Besides, it allowed shorter dual antiplatelet therapy in patients at high risk of bleeding, avoiding bleeding complications. It could also be applied in more complex lesions, such as left main artery lesions, bifurcation, dissection, and calcification with the help of other devices –31. TherThere are also some limitations to our study. First, the number of studies we included is relatively small and the sample size is not large enough, which limited the power to detect the difference between DCB and stent group. Second, it still remains heterogeneity in the results of LLL and the origin of heterogeneity is still unknown though subgroup analysis was carried. It is difficult to discuss the source of heterogeneity with quantitative analysis such as meta-regression limited by the number of included studies. The publication bias had not been carried out since the studies included were less than 10. Third, some major adverse clinical events such as stent thrombosis and major bleeding were not added to this study because of the limited number of studies. Besides, the specific information on concomitant medication and risk factors were not reported in the included studies, and thus, it could not be analyzed for further evaluation. Finally, the difference among DCB technologies fails to analyze since there were limited data on new-generation sirolimus DCB. In this study, the antiproliferative drugs were all paclitaxel though the DCB brands were different. More RCT about new-generation sirolimus DCB are needed to be carried out.de novo non-small CAD compared with stents. However, more RCTs are still needed to further prove the benefits of the DCB strategy.This systematic review and meta-analysis of RCT showed that DCB might provide a promising way on The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.All authors contributed to the study's conception and design. Material preparation, data collection, and analysis were performed by KS and ZL. HW would solve the disagreements between KS and ZL. The first draft of the manuscript was written by KS and all authors commented on previous versions of the manuscript. All authors read and approved 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Momordica charantia (MC) is popular for its medicinal uses especially for treating diabetic-related complications. However, the antiulcer activity of essential oil derived from the seeds has not been systematically studied. This study aims to evaluate the gastroprotective activities of essential oil derived from the seed of MC induced by hydrochloride acid/ethanol (HCl/EtOH) and indomethacin and pylorus-ligation model. Gastric ulceration was induced by oral administration of HCl/EtOH solution or indomethacin on day 7 after animals have been pretreated with testing compounds. The first group received just distilled water and the second group received ranitidine (100 mg/kg). Groups 3, 4, and 5 received 10, 50, and 100 mg/kg of essential oil based on their body weight (10 mL/kg), respectively. Macroscopically, pretreatment of essential oil extracted from MC significantly decreased ulceration induced by HCl/EtOH and indomethacin in vivo. Microscopically, essential oil also significantly suppressed the formation of edema, epithelial disruption, and mucosa erosions. Moreover, essential oil significantly elevated the pH without decreasing the total acidity of the gastric juice and was able to increase the amount of adherent mucus compared to control. Current results provide scientific basis to the ethno-pharmacological usage of the MC in preventing ulcer formation induced by HCl/EtOH and indomethacin. Gastric ulcer, one of the chronic diseases affecting millions of people worldwide, is erosion of the mucosal integrity of the stomach which extends through the muscularis mucosa into submucosa or deeper resulting from various factors including reductions in the blood flow. The condition imbalances between aggressive and defensive factors and increases release of reactive oxygen species in the gastric mucosa –4. The cPhyllanthus niruri [Euphorbia umbellata [Diverse studies have shown that most of the herbal drugs will reduce the offensive factors and proved to be safe, clinically effective, better patient tolerance, relatively less expensive, and globally competitive . There as niruri  and Euphmbellata .Momordica charantia L., or commonly known as bitter melon or bitter gourd, belongs to the Cucurbitaceae family, and native to the semi-tropical climate of Thailand, India, and Africa. Apart from consuming it as vegetable, it has been traditionally used as folk remedy specially to treat diabetic-related complications. The whole plant of M. charantia, from the fruit to its roots, is known to have medicinal values. It has been used in treating eczema, gout, jaundice, psoriasis, pneumonia, and peptic ulcers, besides diabetes [M. charantia (MC) were studied extensively, and interestingly, it is widely best known for the anti-diabetic activity [diabetes . The bioactivity . Apart factivity , antiulcactivity , antioxiactivity , antihypactivity , antimutactivity , and antactivity  propertiM. charantia has been shown to have antiulcer activity [Momordica charantia L. seeds.Based on the previous studies, activity , 19. HowHydrochloric acid and indomethacin were purchased from Sigma, Malaysia, while the chemicals and reagents used for histology study such as DPX Mountant, haematoxylin and eosin, 37% formalin, 99.5% ethanol were from System, Malaysia; Alcian blue, diethyl ether, paraffin from Merck, Germany and xylene from BDH Chemicals, UK.Essential oils extracted from the seeds of MC were a gift from Magna Bio-Laboratories Sdn. Bhd. Malaysia . Extraction method from Noguchi et al.  and Kanaad libitum throughout the experiment. The experiments were performed in accordance with the guidelines and were approved by the Institutional Animal Care and Use Committee (IACUC), Faculty of Medicine and Health Sciences, Universiti Putra Malaysia (UPM/FPSK/PADS/BR-UUH/00275). All animals were acclimatized for at least one week before the experiments.A total of thirty-six male Sprague-Dawley rats, weighing 150 g–200 g obtained from the Animal House, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, were used in this study. The animals were housed in a group of six in the standard cages and maintained in a controlled environment (12:12-hour light and dark cycle) and temperature (25°C ± 3°C). The animals were fed with standard pellet diet and water The experiment was performed based on a slight modification of the method described by Mizui and Doteuchi . Brieflyth day, the rats were euthanized 3 hours after the induction of gastric ulcer under an overdose of ether and the stomachs were immediately excised. The stomachs were gently rinsed with normal saline to remove the gastric contents and blood clots. Then, the stomachs were dissected to examine macroscopically for haemorrhagic lesions. The number and severity of the ulcers were observed microscopically. Scoring system reported in Miñano et al. [On the 7o et al.  was usedth day, all the 24 hours' fasted rats were administered with 1 mL of indomethacin solution  1 hour after pretreatment. After 6 hours, the rats were sacrificed and the stomachs were removed. Each stomach was examined macroscopically for ulcer lesion and the ulcer index of each animal was calculated based on the method mentioned above [The experiment was performed according to Jainu and Devi  with slied above .μm thickness were then stained with haematoxylin and eosin (H&E) followed by mounting with DPX mounting medium. Slide specimens were then observed under the light microscope for microscopic evaluation. The severity of ulceration was scored based on the scoring system reported by Farrell et al. [Gastric tissues were fixed in 10% formalin solution for 24 hours. Sections of 5 l et al. .In order to investigate the underlying mechanism of MCEO in treating pyloric ligation-induced gastric ulcers in rats, method from Shay et al.  was adapGastric content obtained from each pylorus-ligated animal was centrifuged for 10 min at 2500 rpm. A total of 1 mL of clear gastric content was then analysed for hydrogen ion concentration by titration with 0.01 N NaOH. Gastric acidity was expressed in mEq/L.Adherent gastric mucus was determined as described by Corne et al.  by addinp < 0.05 considered as significant.Data were analysed using one-way analysis of variance (ANOVA). Mean comparison among the treatments and inducers were analysed using the Dunnett test at HCl/EtOH at the dose of 1 mL has significantly induced ulcer formation in the disease control animals . FurtherAs shown in Histological evaluation was performed to confirm the morphological changes in gastric tissues. As expected, there was extensive damage to the gastric mucosa showing prominent features of oedema and vacuolation, epithelial disruption, and mucosa erosions  in the dBased on the histopathological analysis, the formation of oedema or vacuolation, epithelial disruption, and mucosae erosion were observed in the disease control group induced with indomethacin only . MCEO pr2) compared with disease control group . Nevertheless, all the concentrations of MCEO failed to increase the gastric volume. However, 50 and 100 mg/kg of MCEO significantly elevated the pH without decreasing the total acidity. Oral treatment of MCEO at concentrations of 50 and 100 mg/kg caused an increase in the amount of adherent mucus compared to the disease control group , superoxide dismutases (SOD), and catalase (CAT). Thus, it can be postulated that the inhibitory properties of MCEO may also be due to its antioxidant activity and the ability to scavenge reactive oxygen species produced by indomethacin.Over-the-counter non-steroidal anti-inflammatory drugs (NSAIDs) are used to relieve pain and inflammation. However, frequent and long-term administration of NSAIDs, such as aspirin and indomethacin, could become a risk factor of gastric ulceration. NSAIDs cause damage to the gastric mucosa via several mechanisms, including topical irritant effect on epithelium, disruption of mucosa barrier properties, inhibition of prostaglandin synthesis, decrease in mucosal blood flow, and interference with the re-epithelisation of the ulcer . PreviouM. charantia which were revealed by the previous studies [In order to determine the mechanism of actions, MCEO was tested on pylorus ligation-induced ulcer model. It was reported that the ulcer formation in gastric is due to the imbalance between offensive and defensive mucosal factors . Therefo studies . CurrentThe results obtained from this study suggested that MCEO could evidently suppress the ulcerations induced by acidified ethanol, indomethacin-induced, and pylorus-ligated. Thus, this study has proved that MCEO is found to exhibit anti-ulcer potential via suppression of free radicals, upregulation of prostaglandins synthesis, and mucus secretion, which favours the healing process for gastric ulcers. These activities may be partly contributed by the phytochemical constituents, present in the MCEO. However, further research is needed for better understanding of the mechanisms and the active bio-compounds present in this essential oil in order to provide a new alternative for the clinical management of gastric ulcers.


Considering the large number of natural disasters on the planet, many areas in the world are at risk of these hazards; therefore, providing an integrated map as a guide map for multiple natural hazards can be applied to save human lives and reduce financial losses. This study designed a multi-hazard map for three important hazards  to identify endangered areas in Kermanshah province located in western Iran using ensemble SWARA-ANFIS-PSO and SWARA-ANFIS-GWO models. In the first step, flood and landslide inventory maps were generated to identify at-risk areas. Then, the occurrence places for each hazard were divided into two groups for training susceptibility models (70%) and testing the models applied (30%). Factors affecting these hazards, including altitude, slope aspect, slope degree, plan curvature, distance to rivers, distance to roads, distance to the faults, rainfall, lithology, and land use, were used to generate susceptibility maps. The SWARA method was used to weigh the subclasses of the influencing factors in floods and landslides. In addition, a peak ground acceleration (PGA) map was generated to investigate earthquakes in the study area. In the next step, the ANFIS machine learning algorithm was used in combination with PSO and GWO meta-heuristic algorithms to train the data, and SWARA-ANFIS-PSO and SWARA-ANFIS-GWO susceptibility maps were separately generated for flood and landslide hazards. The predictive ability of the implemented models was validated using the receiver operating characteristics (ROC), root mean square error (RMSE), and mean square error (MSE) methods. The results showed that the SWARA-ANFIS-PSO ensemble model had the best performance in generating flood susceptibility maps with ROC = 0.936, RMS = 0.346, and MSE = 0.120. Furthermore, this model showed excellent results  for generating a landslide map. Finally, the best maps and PGA map were combined, and a multi-hazard map (MHM) was obtained for Kermanshah Province. This map can be used by managers and planners as a practical guide for sustainable development. According to global statistics, 40% of economic and social damage is caused by natural hazards2. A hazard can be described as a potentially destructive physical event with the possibility of human death or injury, socio-economic losses, or destruction of the natural environment3. Natural hazards include floods, earthquakes, landslides, tsunamis, volcanoes, and erosion4. In one region, one of these hazards or even several different hazards occur depending on the origin and effects3. Therefore, it is of great importance to study many of these hazards together to achieve integrated management in an area. The multi-hazard was first proposed by the United Nations Environment Program (Agenda 21) to manage urban areas susceptible to natural disasters5. Today, economic and human losses due to these hazards are rapidly increasing worldwide6. Iran is also one of the regions exposed to various natural disasters that have caused significant financial and human losses. Therefore, providing a multi-hazard map (MHM) can be an effective tool for managers and planners to reduce economic losses and casualties. In this regard, using spatial methods and considering several hazards in an area, it is possible to identify at-risk areas7. Remote sensing (RS) and Geographic Information System (GIS) are effective and quick tools for identifying areas susceptible to hazards by collecting, storing, combining, manipulating, retrieving, analyzing, and displaying information8.One of the main environmental problems that have affected different countries in recent years is natural hazards9. Iran, which is classified as an earthquake-prone country, has experienced 18 earthquakes with a magnitude of more than 7 Richter in the last 90 years with severe economic and social damage and high mortality10. Therefore, it is necessary to conduct research on earthquakes to determine probable areas of earthquakes. Floods are also high-risk natural disasters, and one of the main reasons for their occurrence is land use change. Moreover, the removal of vegetation and soil, formation of drainage networks, and increased surface runoff and floods11. This hazard has affected the lives of more than 20,000 people annually and has caused considerable damage12. Therefore, it is of importance to generate a susceptibility map for regions prone to floods15. Another important natural hazard that causes great damage to the mountainous areas is landslides16. Factors affecting landslides depend on the features of the region, including natural features such as extreme rainfall, snowmelt, and human-made factors17. Recently, landslides occurred in Iran have been mostly due to land tectonics, climatic, vegetative, and human activities17. Therefore, it is necessary to generate a susceptibility map of this hazard, which has been studied in many areas of the world22.According to the statistics reported, earthquakes are considered as one of the most catastrophic and unpredictable natural hazards, ranking second in terms of the effects and risks of human life among all types of natural disasters23, the analytical hierarchy process (AHP)24, multi-criteria evaluation25 and soft computing models, such as decision trees26, random forest (RF)27, artificial neural networks (ANNs)29, fuzzy logic31, support vector machine method (SVM)32, and adaptive neuro-fuzzy inference system algorithm (ANFIS)33 have been applied to assess various hazards. In addition, a combination of machine learning and meta-heuristic learning algorithms have been developed with successful results for studying natural hazards34. Meta-heuristic algorithms to implement learning machines improve and increase the predictability of models35. In this study, the ANFIS machine learning algorithm was selected because it uses both ANN and fuzzy logic. To find the optimum weight of the parameters of this learning algorithm and increase its capability, grey wolf optimizer (GWO) and particle swarm optimization (PSO) algorithms were selected36. Moreover, the PSO and GWO techniques were employed to overcome the limitations of the ANFIS method via optimization.To date, various methods have been applied to generate hazard susceptibility maps. Some of these methods include multivariate statistical methods such as logistic regression (LR)37, landslides, floods, erosions, and earthquakes in Greece38, climatic hazards in the United States39, climatic hazards in Chile40, and avalanches, rock falls, and floods in Iran41. Different characteristics of each hazard and interactions between hazards may provoke each other. This means that the occurrence of one hazard can cause another hazard. For example, earthquakes can cause landslides or even occur simultaneously42. In addition, landslides and floods are closely related to each other and are often accompanied by heavy or prolonged rainfall43. Heavy rains also cause sudden floods, resulting in soil erosion and landslides occurrence44.In recent years, the simultaneous study of several natural hazards has attracted the attention of many researchers worldwide. Examples include landslides and earthquakes in India45. In April 2019, one of the great floods in recent years occurred in this province and caused considerable economic damage (https://kurdpress.com). Moreover, this province is one of the mountainous areas of the Zagros Mountains in Iran, which is at risk of landslides. These three natural hazards, which have caused considerable human and financial losses in this province, have not yet been studied together in Kermanshah province. Therefore, this study investigates these three natural hazards  in individuals and in combination with each other in order to determine the areas prone to these natural hazards in Kermanshah Province. The SWARA-ANFIS-PSO ensemble model was used for the first time in multi-hazard studies to prepare a multi-hazard susceptibility map (MHSM). The results were then compared with those of the SWARA-ANFIS-GWO ensemble model.The earthquake occurred on Sunday evening, November 12, 2017 near Ezgeleh in Kermanshah province (7.3 Richter), is one of the largest earthquakes in recent years, in which 600 to 700 people died and nearly 10,000 people injuredMulticollinearity analysis of influencing factors. Multicollinearity test was used in the present study to investigate the correlation between factors affecting natural hazards of floods and landslides. Inflation coefficient of variance (VIF) and Tolerance indicate the effect of collinearity between the factors. If there is linearity between the factors, the factor should be removed from the modeling. The results of this method for the hazard of landslides showed that factor “Lithology” has the highest VIF value 1.696) and the lowest tolerance (0.590). The results of this method for the hazard of floods showed that the factor “lithology” has the highest VIF value 2.068) and the lowest tolerance (0.483). The results of the analysis showed that all the factors used in the assessment of flood and landslide hazards can be applied in modeling. In other words, there is no multi-collinearity between the factors used  maps were separately generated using the SWARA-ANFIS-GWO-Flood (SAGF) and SWARA-ANFIS-PSO-Flood (SAPF) ensemble models Fig. a,b. ThesThe power of the applied models was tested using the ROC curve, RMSE, and MSE. For flood hazard, the results illustrated that the SAPF ensemble model had the maximum AUC value 0.936) and the least error (RMSE = 0.346 and MSE = 0.120) in the testing step, followed by the SAGF ensemble model . For landslide hazard, the results illustrated that the SAPL ensemble model had the highest prediction power.AUC = 0.894, RMASE = 0.410, and MSE = 0.168), followed by the SAGL ensemble model   were combined to generate a multi-hazard map using a combined tool in ArcGIS software. The multi-hazard map (MHM) was obtained as:Figure https://www.recare-hub.eu/soil-threats/floods-and-landslides). Despite these substantial differences in these hazards, they can still be assessed together in a study and a comprehensive map can be prepared. In recent years, researchers' interest in studying multiple natural hazards has increased significantly38. Therefore, generating a multi-hazard map is of great importance for the integrated management of natural resources because it can help to reduce or even prevent economic and human losses. Natural hazards can have major effects and interact with each other. The mechanism of these interactions to come into being is different, and one may cause the occurrence or stimulation of another event48. Landslides, for example, can cause dangerous floods, especially when landslides in creeks are broken. Flooding also increases the possibility of landslides49. Liu et al.48 also stated that earthquakes cause landslides and storms cause floods. Temporary small-scale floods can significantly affect soil erosion. Floods on slopes are related to soil erosion and landslides in various ways, such as surface flow, sheet flow, return flow, and groundwater furrow. Moreover, the accompanying flood may destroy soil cavities and soil organisms that make up the soil structure. Therefore, the simultaneous study of several hazards in one study covered all gaps in individual studies. Multiple hazard assessments were performed to address the limitations of a single risk assessment.First, it should be noted that there are substantial differences in the natural hazards of earthquakes, floods and landslides. An earthquake is a sudden and rapid movement that is caused by breaking and moving rocks deep inside the earth. Moreover, a flood can be defined as an overflow of water from the natural range of a watercourse or body of water and or the accumulation of drainage water in areas that are not normally underwater. Landslide is also defined as the mass movement of rock, debris, and downward movement toward gravity under gravity, which causes the loss of one or more soil functions  simplicity, (2) ease of operation, (3) no overlap, and (4) no calculation of mutation51. Moreover, the GWO algorithm also has the following advantages: (1) its simplicity, (2) flexibility, (3) robustness, (4) ease of operation, (5) low control parameters required, and (6) avoidance of local optimization52.Each model has their own advantages and drawbacks. The advantages of the ANFIS algorithm are as follows: (1) the ability to process numerous inputs, (2) the ability to maintain the advantages of combining two fuzzy algorithms and an artificial neural network, and (3) a robust method54. To ensure and support the results of this study, a comparison was made with previous studies related to the field of study. A combination of machine learning algorithm (ANFIS), ant colony optimization (ACOR), and differential evolution (DE) algorithms were used to study landslide susceptibility by Razavi-Termeh et al55. The results showed that the ANFIS-DE model was the suitable model (0.946). Wang et al.36 also reported that the combination of ANFIS-BBO (AUC = 0.9045) and ANFIS-ICA (0.9044) algorithms performed better than the standalone ANFIS model (AUC = 0.8407) in assessing flood susceptibility. The study by Mehrabi et al.33 also emphasized that the combination of GA-ANFIS, PSO-ANFIS, DE-ANFIS, and ACO-ANFIS models had proper performance for assessing landslide susceptibility. Arora et al.56 used ANFIS-GA, ANFIS-PSO and ANFIS-DE models to model flood susceptibility in a study in India. The ANFIS-GA model showed good results for determining flood susceptibility in the region. They concluded that the hybrid meta-heuristic and ANFIS models performed well and their performance evaluation with the AUC diagram confirmed the results. In the study of Arora et al.56, the AUC values are from 0.768 and 0.924. In this study, these AUC values were obtained from 0.880 to 0.936, which indicates the excellent performance of the models used in this study. Compared to another study using a combination of ANFIS and meta-heuristic algorithms, it was found that the performance of the present study is better than the study conducted by Hong et al.57 in which ANFIS-GA (0.8488) and ANFIS-DE (AUC = 0.8523) models were used to assess flood susceptibility. Moreover, compared with the study of Ahmadlou et al.58, it was observed that the results of the AUC values of the current study have higher accuracy in the study of flood susceptibility compared to ANFIS-BA and ANFIS-BBO models (0.703). Finally, it can be concluded that a combination of optimization and machine learning algorithms can be used to develop measures for reducing losses and sustainable management. In addition, the results of this study are practical and useful for assessing natural hazards.Ensemble methods have dramatically increased because of their high efficiency in helping researchers conduct studies on natural hazards (landslides and floods). Moreover, ensemble models reduce the uncertainty of each algorithm and increase its reliabilityThis study had some limitations. Fundamental changes in factors affecting natural hazards are the main causes of hazards. However, knowledge about the factors affecting natural hazards is incomplete, and some of these unknown factors may still be present. Another limitation of this study was the limited data available. In future studies, it is suggested that more influencing factors should be used to assess hazards. It is also suggested that in future studies, infrastructure  should be considered for their optimal assessment and location.Designing a multi-hazard map for an area can reduce economic losses and mortality and result in integrated and organized management. The multi-hazard map in this study is a combination of three important hazards . In this regard, susceptibility maps of SAPL, SAGL, SAPF, and SAGF were generated for the Kermanshah province located in western Iran. The accuracy of the results was assessed using the ROC curve, RMSE and MSE values, and it was concluded that the SAPF and SAPL models had the best performance for both flood and landslide hazards. In addition, a PGA map was generated to assess earthquake hazards. Finally, a multi-hazard map was generated from the combination of SAPL, SAPF, and PGA. The results showed that the southwestern areas of Kermanshah Province are affected by all three hazards, covering 2.93% of the region, while 28.94% of the province is safe from these hazards. Landslides cover the largest area (29.74%) of the region. In the context of sustainable management, the results of this work can be applied as a practical tool for managers and experts in order to reduce losses. In addition to being able to be used to study several hazards together, these models can also be used individually in other contexts of natural disasters such as floods, landslides, erosions, forest fires, etc.2 .The study area, Kermanshah Province, lies between 45°20 39″ to 48°01 58″ longitude and 33°37 08″ to 35°17 08″ latitude, with a total area of 24,650 kmhttps://earthengine.google.com). 617 flood points were extracted to prepare a flood inventory map in the ArcGIS platform. 70% of the points (432 points) and 30% of the points (185 points) were used for modeling and testing the models, respectively. Landslide location points were identified using historical data and field surveys by applying a global positioning system (GPS). 115 landslide points were used to prepare the landslide inventory map. 81 points (70%) was used for modeling and 34 points (30%) was used for testing the models. Most of the landslides occurred in the study area are of rotational and translational types.This study considered three main hazards  in Kermanshah Province, Iran. The earthquake inventory map was obtained from the catalog of historical earthquakes in Iran provided by the International Institute of Earthquake Engineering and Seismology. The flooded areas were recognized using Google Earth Engine (GEE) and Sentinel-3 images considering the latest flood occurrences in the study area in 2019 and 2020, and they were then transformed into point data. The flood detection code was written on the GEE platform  was used to generate the altitude map Fig. a.Figure 34. The slope aspect map for Kermanshah Province was classified into nine classes  from meteorological stations located in Kermanshah Province were used to generate a flood susceptibility map. A flood map was obtained using the IDW interpolation method  in regression analysis. The two methods of inflation coefficient of variance and tolerance are used to examine multicollinearity68 introduced a decision-making model with the aim of weighting the criteria and sub-criteria. In this model, each expert based on his/her experience, knowledge, and information assigns a weight to each factor according to their importance. The steps in implementing this model are as follows. (1) Factor and sub-factor are selected. (2) Sub-factors are rated by experts based on their relative importance. The highest rate and the lowest rate are assigned to the most important sub-factor (first row) and the least important sub-factor (last row), respectively. For more information refer to Keršulienė and Turskis68.Keršulienė and Turskis69. This method can solve complex nonlinear problems. Takagi and Sugeno’s fuzzy method uses two if–then rules. Membership values are generated from the proper fuzzy sets using the membership function. The output of each node indicates the power of each rule70. See Zhang et al. 69 for more details.ANFIS is an artificial neural network and fuzzy logic proposed by Jang in 199371 based on the random population and social behavior of birds in the wild72. This algorithm was used in the swarm intelligence (SI) algorithm group. The particles in this method show solutions to the problem, and the solutions  are randomly identified by the vector. The velocity and position are the two main criteria for executing the algorithm. Each particle chooses the direction of movement based on the current position and the best position experienced between the particles. See Kennedy and Eberhart71 for more information.PSO is proposed by Kennedy and Eberhart73. In this algorithm, (α), (β), and (δ) wolves are the leaders of hunting, and the ω wolves follow them to identify the optimum solution. The GWO was modeled as follows: Social hierarchy, encircling prey, hunting, attacking prey, and searching the prey. Link available for more information: http: //www. alimirjalili.com/GWO. html.The GWO algorithm is a technique inspired by the social life of grey wolves in wildIn the current study, the GWO and PSO meta-heuristic methods were applied for training instead of the classic ANFIS model functions. The hybrid SWARA-ANFIS-PSO and SWARA-ANFIS-GWO algorithms were implemented using MATLAB software. In this regard, training and testing data for floods and landslides are required. Therefore, 70% of the data related to floods were defined for training hybrid models, and 30% were defined for testing models with code 1. The same number of non-flood points (70% training and 30% testing) was selected, and code 0 was assigned to them. In addition, for data on landslides, 70% of the training data (1) and 30% of the testing data (1) were selected, and the same number of non-landslide points (70% of training and 30% of testing) were defined with code 0. These points were then matched with the factors influencing natural hazards, and the corresponding values were obtained.74. In this study, a probabilistic method is used. In the probabilistic seismic hazard analysis method, all important earthquakes and springs with different distances to the site were considered, considering the occurrence probability of all events. The main assumption in the analysis of earthquake estimation using the probabilistic method is the randomness, and because these events are statistically independent, the time distribution function of these events is expressed by the Poisson distribution function. In addition to Poisson functions, there is another model called the iteration model, in which the occurrence of an event is related to the occurrence of previous events75. The steps in analyzing probabilistic earthquakes using the probabilistic method are: (1) identifying springs, (2) determining seismicity parameters, (3) selecting appropriate reduction relationships, and (4) calculating severe ground motion parameters76. Acceleration maps were estimated for a 475-year return period.Seismic hazard analysis methods can be used to predict the seismic behavior of a certain area. These methods study the probability of earthquake occurrences with different magnitudes in the study area using the seismic history of a region, historical seismic information, and seismotectonic investigation. Earthquake risk estimation methods include experimental-statistical, deterministic, and probabilistic methods46. The three criteria of RMSE, MSE, and ROC diagram were employed to estimate the accuracy of the ensemble models. RMSE and MSE are two standard statistical criteria for evaluating the accuracy of models35. These criteria were calculated as follows:In natural hazard studies, the accuracy of the results was verified after the implementation of the models62. The values of the area under the curve are in the range [0.5–1], so that its numerical value determines the accuracy of the models used. The more the area under the curve move toward 1, the higher the accuracy of the model is, whereas the more the area under the curve moves toward 0.05, the lower the accuracy of the model is62. The ROC was obtained from Eq.  and true-positive values (y-axis)from Eq. .4\documeA multi-hazard map of the total hazards of earthquakes, floods, and landslides was generated for the Kermanshah Province. First, SWARA-ANFIS-PSO-Flood (SAPF) and SWARA-ANFIS-PSO-Landslide (SAPL) susceptibility maps were generated and then classified into five classes. In the next step, a PGA map was generated for the earthquake hazard. The best selected models were again divided into two classes: 0  and 1 (high and very high classes). In addition, the PGA map was reclassified into two classes: 0 (low and moderate) and 1 (high class). Finally, a multi-hazard map was generated by combining two-class maps of earthquakes, floods, and landslides for the Kermanshah province located in western Iran.


The awareness of epigenetic alterations leading to neoplasia attracted the attention of researchers toward its potential use in the management of cancer, from diagnosis to prognosis and prediction of response to therapies. Our group has focused its attention on the epigenomics of thyroid neoplasms. Although most of the epigenetic studies have been applied on histological samples, the fact is that cytology, through fine-needle aspiration, is a primary diagnostic method for many pathologies, of which thyroid nodules are one of the most paradigmatic examples. This has led to an increasing literature report of epigenetic studies using these biological samples over the past decade. In this review, our group aimed to document recent research of epigenetic alterations and its associated assessment techniques, based on cytology material. Our review covers the main epigenetic categories—DNA methylation, histone modification, and RNA-silencing—whose evidence in thyroid cytology samples may represent solid soil for future prospectively designed studies aiming at validating patterns of epigenetic alterations and their potential use in the clinical management of thyroid neoplasms. Epigenetic alterations are potential candidates for the identification of specific markers for cancer detection, diagnosis, and prognosis . The utiPTEN promoter presents with hypermethylation in ~50% of papillary thyroid carcinomas (PTCs) and nearly 100% of follicular thyroid carcinomas (FTCs) and follicular adenomas (FAs), suggesting that it may be involved in thyroid tumorigenesis  tumor-suppressor gene  have been linked to the development and progression of cancer and have been proposed as markers for diagnosis, including of TC –24. Theyuding TC ; miRNAs uding TC .FNA is a standard method for diagnosis of thyroid nodules, but it holds some limitations. Evidence exists supporting the hypothesis that epigenomic profiling could identify markers to differentiate benign from malignant thyroid neoplasms.P = 0.44), as assessed by a combined bisulfite restriction analysis polymerase chain reaction (PCR) protocol, the immunohistochemical staining 5-methylcytidine score was significantly higher in tumors in comparison with normal tissue counterparts, for FAs (P < 0.001), FTCs (P = 0.04), and PTCs (P = 0.02). Interestingly, PTCs showed the highest expression among all other tumors, which was significantly different from FTCs (P = 0.015), but not FAs (P = 0.09) , which represented a concordant presence of methylation results. This study pointed to the usefulness of methylation markers where FNA shows limitations by the histopathologic nature of lesions.DNA methylation is an epigenetic mechanism normally tested in the diagnosis of thyroid nodules. Keelawat et al.  assessed = 0.09) . Several = 0.09) . Stephen = 0.09)  analyzedP < 0.0001).In 2008, Nikiforova et al.  analyzedThe utility of thyroid cytological samples' epigenetic signatures for the management of TC can be seen under the lens of an improvement of prognosis and disease risk stratification, or under a more farfetched objective—targeting epigenetic changes as a mechanism of disease to modulate cancer hallmarks with a treatment intent. The former bases its usefulness on the assumption that specific epigenetic marks detected on a cytology sample could guide the surgical approach and the decision to implement adjuvant treatment with radioactive iodine (RAI), including dosages, and TSH suppression. The latter assumes that epigenetic changes can be reverted by means of a pharmacological compound with the possibility of reverting radioiodine refractoriness, potentially prolonging disease-free survival (DFS).Under the context of cytology specimens, epigenetic alterations should be able to support a presurgical prognostic assessment to be applied in clinical practice, as validated in the form of a molecular signature. Such clinical application would ideally cover Bethesda categories III–VI, where not only the malignancy risk is increasingly higher, but also the need for an assessment of estimated risk of recurrence is needed. One of the main treatment objectives of TC is to minimize the risk of recurrence and metastatic dissemination, and therefore adequate surgery is the most important treatment influencing prognosis .BRAF-positive tumors, and MET was identified as a potential target for the downregulated miR-34b and miR-130b, with a significantly higher MET expression in aggressive PTCs. Chou et al. . In addition, they showed that miR-183, miR-221, and miR885-5p were significantly downregulated in HCC with metastases .Within the prognosis and risk stratification fields, the most promising epigenetic markers that can be detected in FNA are miRNAs. Yip et al.  showed tu et al.  have alsu et al.  have repu et al.  analyzedDAPK1 and ESR1 methylation were significantly associated with extrathyroidal extension  in FTC and HCC cases. In the same study, methylation of DAPK1 and ESR1 was significantly associated with late-stage disease . Various studies have shown the potential of RASSF1A hypermethylation as a biomarker of aggressive tumors  and Wilms tumor 1 (WT1) could be candidate prognostic markers related to recurrence-free survival both in PTCs and FTCs. On the same study, kallikrein 10 gene (KLK10) was hypomethylated and overexpressed in BRAF-mutated tumors, which was recently supported by the evidence by Buj et al.  that either provide a clear-cut diagnosis or accurately predict the prognosis. Meanwhile, advances in the epigenetic field supporting the differentiation between benign, borderline, and malignant lesions, as well as their role as prognostic factors in malignant neoplasms of various organ systems, such as breast, prostate, lung, or liver, are increasingly acknowledged. Recently, thyroid also started to be studied by various epigenetic techniques. The application of epigenetic-based methods on tissue material of thyroid and various organs has been targeted by researchers in the past two decades, leading to a growing need to establish its applicability to FNA material. Following what has been reported so far, this review amassed the potential usage and adoption of epigenetic-based techniques on thyroid FNA material aimed to better understand the oncobiology of thyroid neoplasia.SC and AL: conceptualization. SC, AL, and MP: writing – original draft. SC, AL, MP, and VM: writing – review & editing. VM: supervising. All authors contributed to the article and approved the submitted version.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.


Agro-food industrial residues (AFIRs) are generated in large quantities all over the world. The vast majority of these wastes are lignocellulosic wastes that are a source of value-added products. Technologies such as solid-state fermentation (SSF) for bioconversion of lignocellulosic waste, based on the production of a wide range of bioproducts, offer both economic and environmental benefits. The versatility of application and interest in applying the principles of the circular bioeconomy make SSF one of the valorization strategies for AFIRs that can have a significant impact on the environment of the wider community. Important criteria for SSF are the selection of the appropriate and compatible substrate and microorganism, as well as the selection of the optimal process parameters for the growth of the microorganism and the production of the desired metabolites. This review provides an overview of the management of AFIRs by SSF: the current application, classification, and chemical composition of AFIRs; the catalytic function and potential application of enzymes produced by various microorganisms during SSF cultivation on AFIRs; the production of phenolic compounds by SSF; and a brief insight into the role of SSF treatment of AFIRs for feed improvement and biofuel production. The term “residue” includes materials that are not intentionally generated in the production process but are not necessarily considered waste . SignifiAFIRs are mostly lignocellulosic materials composed of three polymers: cellulose (40–50%), hemicellulose (20–30%), and lignin (20–35%). Lignin is the main component of the cell wall ,10. AccoBy-products from lignocellulosic biomass are an important alternative energy source, playing an important role in the circular bioeconomy. The management of this resource promotes the reuse of raw materials, high industrial production yields, and the generation of minimal waste . The effThis paper provides a comprehensive overview of the possibilities of valorization of lignocellulosic biomass produced in the agro-food industry. Particular attention is paid to the composition of the different types of AFIRs, taking into account that they come in different forms and in many processing routes. SSF experiments on the valorization of AFIRs for the production of enzymes (ligninolytic and hydrolytic enzymes) and a wide number of value-added products through the use of different microorganisms are discussed. In addition, the valorization of lignocellulosic biomass treated with microorganisms for use in feed and biofuel production is presented.The increasing expansion of agro-industrial activities in recent decades has resulted in the accumulation of a large amount of lignocellulosic residues (wastes or by-products) worldwide, which are not properly disposed of and thus contribute to climate change, as well as soil, water, and air pollution ,17. An eAgricultural residues include the waste left on fields after harvesting and the waste after processing of raw materials  . HarvestResidues resulting from the processing of raw materials in the various food industries  consist of pips, skins, stalks, pomace, oil cake, oil pomace, brewer’s grains, bran, germ, etc. . Grape pVitis vinifera is one of the most widely grown crops in the world, with an average annual production of 71 million tons (data for period 2008–2017) [08–2017) . It is e08–2017) . The rea08–2017) .db, while the proportion of grape skins can be as high as 65%db [Grape pomace consists of seeds, skin, and sometimes stems. According to the literature, the ratio of grape seeds in grape pomaces varies in the range of 15–52%as 65%db , althougas 65%db  and biofThe term cereals refers to nine species: wheat, rye, barley, oats, rice, millet, corn, sorghum, and triticale (a hybrid of wheat and rye). Cereals consists of hull and kernel, where kernel consists of bran, germ, and endosperm . The cerOn the basis of the carbon source, Mitchell et al.  classifySuch material is complex and heterogeneous, as can be seen from its chemical composition. Agronomic measures of cultivation, weather conditions, variety, harvesting methods, storage conditions, and the analytical methods used to measure the individual components are all factors that influence the chemical composition of the material.Commonly used analytical methods to determine the chemical composition of such material are ash determination , determination of total organic carbon , total pLignocellulosic structure of AFIRs can be disrupted by biocatalytic activities of different microorganisms. In order for one to choose the best method  for its reuse, such residues should be firstly chemically characterized.SSF is a fermentation process in which microorganisms grow on moist, solid material under controlled conditions, without the presence of free water or with a minimal amount of free water. Inert or non-inert materials can be used as solid substrate in SSF processes . AFIRs aBasidiomycota and Ascomycota [The microorganisms used in SSF are filamentous fungi, yeasts, and bacteria. Due to their physiological, biochemical, and enzymatic properties, filamentous fungi (multicellular organisms) are the most commonly used, especially those from fungal kingdom sub-division comycota ,61. In ocomycota ,62. The comycota , for ligcomycota  for the comycota . It is acomycota  and the comycota . This iscomycota .The advantages of SSF over submerged fermentation (SmF) are its similarity to the natural habitat of microorganisms, higher productivity, lower cost , lower water consumption, lower use of chemicals, lower generation of waste streams, and lower energy consumption ,66,67,68The most important factors that have effect on the efficiency of SSF process are substrate , inoculum , external carbon and/or nitrogen addition, addition of a specific enzyme’s inducers for microorganism’s growth and/or desired metabolite production, mixing, temperature, pH, and oxygen concentration.The basic information of substrates and microorganisms that are commonly used in SSF are provided further in this paper.2+, and K+) are needed in concentrations greater than 10−4 M, whereas carbon in the growth medium is the main source of energy. Microelements  and vitamins, growth hormones, and metabolic precursors are needed in concentration less than 10−4 M [The choice of substrate is usually determined by its cost and availability, its chemical composition , and itsn 10−4 M . AFIRs an 10−4 M . Sometimn 10−4 M . For SSFn 10−4 M . The finn 10−4 M . If the n 10−4 M .Particle size and shape of the substrate can affect the accessibility of nutrients to the microorganism. Smaller particle size causes the smaller inter-particle spaces and the greater pressure drops when air flows through the substrate mass. The particles with a larger surface area tend to be contiguous with the flat surfaces and thus actually exclude oxygen, limiting the growth of microorganisms . The parFilamentous fungi, yeasts, and bacteria can be used in the SSF process to produce value-added compounds. Unicellular organisms such as bacteria and yeast grow as a biofilm, while multicellular filamentous organisms grow in the form of a mycelium, which is comprised of aerial and penetrative hyphae. If the layer of hyphae is thick, then water moves by capillary action from the substrate, resulting with layer into a moist biofilm. A biofilm can also be formed in the case when the bed is mixed, since mixing causes squashing of aerial hyphae onto the surface of the substrate . The mosFilamentous fungi comprise almost the entire kingdom of fungi and represent the most diverse group of microorganisms that produce filamentous hyphae. SSFs mimic the natural habitats of filamentous fungi and grow on the surface of and within substrate parts due to their hyphal growth. The term filamentous fungi is used in contrast to yeasts, which are essentially unicellular fungi . FilamenTrametes under SSF conditions on different AFIRs for the purpose of laccase production. For example, when comparing the cultivation of T. hirsuta on grape seeds in two types of laboratory-scale bioreactors (immersion and tray bioreactors), one study found the tray bioreactor to be better in terms of the highest laccase activity achieved (2.5 × 105–3 × 105 nkat/L) [T. versicolor, in addition to laccase production, is also effective in the recovery of phenolic acids during SSF on corn silage in laboratory jars. Thanks to the complex enzyme system of T. versicolor, which successfully degrades lignin, there was an increase in the extraction yield of phenolic acids  during the biological treatment compared to the initial biologically untreated corn silage.There are numerous studies on the cultivation of filamentous fungi of the genus  nkat/L) . Studies nkat/L)  have shoAspergillus and Rhizopus are commonly used in studies investigating the SSF process because they produce several enzymes with broad substrate specificity that are stable at lower pH and high temperatures and play an important role in the hydrolysis of phenolic conjugates [A. niger and R. oligosporus on apricot pomaces under SSF conditions. The obtained results showed that there is an increase in total phenolic content when R. oligosporus was used until the ninth day of fermentation, and in the case of A. niger until the sixth day of fermentation. They also concluded that SSF with filamentous fungi contributes to a greater recovery of lipids from apricot kernels and obtains oil with a high content of linoleic acid.Filamentous fungi of the genera njugates . Dulf etnjugates  investigActinomycetes such as Streptomyces sp. are resistant to extreme conditions and can colonize the substrate abundantly; thus, they are also used in SSF [Besides filamentous fungi, yeasts and bacteria are also used in SSF. Filamentous fungi are more resistant to bacterial contamination, and yeasts and some types of bacteria have the ability to thrive when grown in low water activity environments. d in SSF ,99.Bacillus sp. BBXS-2 was used to produce protease and amylase in non-sterile open SSF. Wheat straw proved to be the best of several substrates used . The activity of protease was about 12,200 U/g dry matter and amylase 6900 U/g dry matter after 5 days of fermentation. Produced enzymes were used as an additive to detergent, which increased its efficiency in removing starchy stains up to 2.5 times [Kluyveromyces marxianus is a yeast that belongs to the GRAS  group of microorganisms and is considered a microorganism that can grow on a variety of substrates and under extreme conditions. Therefore, it is frequently used in bioprocesses such as SSF [K. marxianus on five different substrates  under SSF conditions to produce aroma compounds. Cassava bagasse and palm bran were found to be the best substrates for yeast growth, and the components produced in the highest amounts were ethyl acetate, ethanol, and acetaldehyde.Bacteria are mostly used for enzyme production , and yeasts are known for the production of clorogenic acid, aromatics, etanol, etc. For example, .5 times . Kluyverh as SSF ,101. MedData on the utilization of various AFIRs and their products after solid-state cultivation of bacteria  and yeasDuring the biotransformation process of AFIRs for the purpose of producing various value-added products, biofuels, or animal feeds, the conversion of lignocellulosic biomass into fermentable sugars, sugar acids, and/or phenols is carried out by a complex enzymatic system of selected microorganisms .SSF can offer significant benefits in the economic aspects of the enzyme production compared to SmF, since it uses low-cost and easily available substrates, such as lignocellulosic substrates, especially AFIRs . Selectip-coumaryl, coniferyl, and sinapyl. Their quantities depend on various factors, such as plant species, maturity, and the space localization in the cell [Lignin is a complex, aromatic, and optically inert hydrophobic amorphous three-dimensional polymer consisting mainly of three different phenylpropane alcohols: the cell . Lignin the cell . The enzthe cell .T. versicolor, T. pubescens, Ganoderma lucidum, and Pleurotus eryngii. Osma et al. [T. pubescens under SSF conditions for laccase production. They indicated that by using this type of non-expensive substrates, it is possible to produce enzymes with higher activities at lower production costs. Produced laccase had a maximum activity of 1500 U/L and was found to be more efficient in decolorization of anthraquinone dyes compared to commercial laccase. Potato peel waste, pretreated with distilled water, is also one of the examples of economical substrates for the production of highly active laccase (6708.3 U/L) under SSF conditions with P. ostreatus [Laccases are multi-copper glycoproteins that use molecular oxygen to oxidize various aromatic and non-aromatic compounds by a radical-catalyzed reaction mechanism. Laccase can be used in food and beverage industries for modification of color appearance, in the pulp and paper industry for delignification, and in the textile industry for textile bleaching or dye synthesis, as well as for many other purposes such as soil bioremediation, herbicide degradation, synthetic chemistry, cosmetics, and biosensors ,135. Laca et al.  showed tstreatus .2O2 to oxidize MnII to MnIII–chelate. This enzyme is mostly produced by numerous species of fungi (Basidiomycetes), especially white-rot fungi, and bacteria (Actinomycetes). It belongs to group of enzymes that have a significant role in efficient bioconversion of plant residues. MnP finds its use in various industries—paper, food, dye, textile, cosmetics, and many others [Manganese peroxidase (MnP) belongs to the peroxidase family. It is an extracellular glycosylated heme enzyme that uses Hy others .2O2 for catalysis. LiP is enzyme capable of producing radical cations through one-electron oxidation of nonphenolic aromatic compounds as well as phenolic aromatic compounds such as veratryl alcohol or 1,4-dimethoxybenzene [Inonotus obliquus produces all three of the above ligninolytic enzymes  under SSF conditions. Xu et al. [Lignin peroxidase (LiP) is a water-soluble glycosylated enzyme that also uses Hybenzene . This enybenzene ,134. Theu et al.  optimizeCellulose is an unbranched long polymer of β-D-glucose units linked by (1→4) glycosidic bonds to form cellobiose-repeating units in the cellulose chain. A numerous hydroxyl groups SSF can offer significant benefits on the inner and outer surface of cellulose-forming hydrogen bonds, while cellulose chains are interlinked by hydrogen bonds and Van der Waals forces. Owing to different orientations throughout the structure, cellulose molecules have different levels of crystallinity—low crystallinity (amorphous regions) and high crystallinity  .Cellulases are enzymes that have the ability to break cellulose and convert it into simple sugars. They include endoglucanases , exoglucanases or cellobiohydrolases , and β-glucosidases or cellobiases (β-D-glucoside glucohydrolase). Endoglucanases (EC 3.2.1.4) randomly hydrolyze internal glycosidic linkages , resulting in shorter polymer chains and an increase of released number of reducing ends.Endoglucanases find their application in the formulation of detergent compositions for increasing the production yield. They can also be used for improving the nutritive quality of products obtained in different food industry sectors . They are known to be used in feed production  and in tEndoglucanases are mainly produced by fungi and bacteria cultivated on AFIRs. The most important producers of endoglucanases are given in I. obliquus also produces cellulolytic enzymes under SSF conditions. The maximum activities of the enzymes carboxymethylcellulase, filter paper cellulase, and β-glucosidase obtained under optimal process conditions using wheat bran as substrate at 40% inoculum, pH 6.0, and substrate/moisture ratio of 1:2.5 were 27.15, 3.16, and 2.53 IU/g, respectively [β-Glucosidases (EC 3.2.1.21) catalyze the hydrolysis of the β-glucosidic linkages, β-linked oligosaccharides, and oligosaccharides with the release of glucose. They reduce cellobiose-mediated repression and thus enable cellulolytic enzymes to be more effective . Due to ectively .Trichoderma is one of the microorganisms that have been extensively studied for the production of various industrially important enzymes, mainly cellulase, exoglucanase, and β-glucosidase under SSF conditions using different AFIRs as substrates. The studies conducted by Shazhadi et al. [w/w moisture, 6 mL inoculum, pH 6.0, 35 °C) for successful growth of co-culture of T. viride and G. lucidum on corn stover resulted in production of exoglucanase and β-glucosidase enzymes and their activities of 485 ± 6.5 U/mL and 255 ± 3.3 U/mL after 5 days of incubation, respectively. They also investigated the influence of additional carbon and nitrogen sources regulating enzyme synthesis during growth of white-rot fungi, and the combination of glucose and ammonium sulfate proved to be the best in the production of exoglucanase and β-glucosidase.i et al.  aimed atHemicellulose is a complex of polysaccharide matrixes composed of different units of sugars . It is the second most abundant polysaccharide in plant cell wall. Xylan is the most abundant hemicellulose polymer, constituting around 70% of hemicelluloses. Galcto(gluco)mannans and xyloglucans are another two major hemicelluloses in plant cell wall. In order to degrade such a complex material, microorganisms should have ability to produce a large set of hemicellulases, which act in interaction.Hemicellulases include xylanases (EC 3.2.1.8), β-mannanases (EC 3.2.1.78), arabinofuranosidases (EC 3.2.1.55), and β-xylosidases (EC 3.2.1.37). Endo-1,4-β-xylanases  belong to the glycosil hydrolase family. They catalyze the hydrolysis of 1,4-glycosidic linkages between xylose residues in the backbone of xylans . Since xA. awamori. In conical flasks, the maximum activity of xylanase was reached between the fourth and eighth day of fermentation (about 100 IU/gds), while in the plate-type SSF reactor, the maximum activity was reached on the fifth day of fermentation (195.92 ± 11.0 IU/gds).Tomato pomace is a waste available in large quantities, and its chemical composition contains proteins, lipids, carbohydrates, amino acids, carotenoids, and minerals. Umsza-Guez et al.  used thiBacillus sp. and B. halodurans FNP135) producing xylanase and laccase. They used wheat bran as substrate. Under optimized conditions , a significant increase in the production of xylanase (1685 IU/g) and laccase (2270 IU/g) was obtained. The mixed enzyme preparation was found to be effective in bio-bleaching of craft pulp.Some studies have shown that co-cultivation of compatible microorganisms can enhance enzyme biosynthesis. Gupta et al.  studied Bacillus nealsonii under SSF conditions on wheat bran as substrate. The protease was purified by standard protein purification procedures that include methods such as ammonium sulfate precipitation, gel filtration chromatography, and ion exchange chromatography. Each step was performed at 4 °C, and enzyme volume, protease activity, and protein content were determined after each step. The combination of mannanase and protease from B. nealsonii was found to be effective in removing various stains when used as detergent additive.Some researchers are concerned with the purification and characterization of the enzymes produced, as this is an important step that provides insight into enzyme properties and helps determine potential applications. David et al.  optimizeAFIRs are rich in nutrients and bioactive compounds. Therefore, these residues have potential applications in SSF processes for the obtainment of beneficial compounds such as phenolic compounds, organic acids, flavor, and aroma compounds , which pPhenolic compounds represent the important group of bioactive compounds from plant material. They are the most abundant antioxidants in the human diet. Their structure consists of an aromatic ring, containing one or more hydroxyl substituents. The number and position of the hydroxyl groups, and the nature of substituents on the aromatic rings, affect the physiological properties of phenolic compounds. These compounds show a broad spectrum of physiological properties, such as anti-allergenic, anti-artherogenic, anti-inflammatory, anti-microbial, antioxidant, anti-thrombotic, cardioprotective, and vasodilatory effects . Generalp-coumaric, syringic, vanillic, and p-hydroxybenzoic [Lignin fraction of AFIRs contains various phenolic compounds, mainly phenolic acids such as ferulic, ybenzoic . Simple ybenzoic . On the ybenzoic   was 20.12 μgdb of sample for apple pomace and 12.24 μgdb of sample for fermented apple pomace. Bucić-Kojić et al. [T. versicolor. According to obtained results, increments in extraction yield of caffeic acid, vanillic acid, p-hydroxybenzoic acid, and syringic acid were observed in fermented grape pomace . Pomegranate peel and creosote bush leaves were successfully used as a substrate for ellagic and gallic acid production by A. niger GH1 [A. niger and R. oligosporus and its influence on the content of phenolic compounds, antioxidant activity, and lipid composition were investigated by Dulf et al. [Lentinus edodes resulted in an increase in the ellagic acid content [Ajila et al.  studied traction . They coć et al.  investige pomace . Furtheriger GH1 . In the f et al. . They co content .A. niger ARNU-4 using tea waste as substrate.Organic acids are used as preservatives in food and beverage production since they can prevent spoilage and prolong the shelf life of food. Sharma et al.  have shoM. purpureus was cultivated on corn meal, peanut meal, and coconut residue and soybean meal for the purpose of red pigment production.In the research conducted by Nimnoi and Lumyong , fungus Ceratocystis fimbriata under SSF conditions, using a coffee husk as a substrate, was tested by Soares et al. [Kluyveromyces marxianus proved to be suitable for producing value-added aroma compounds by SSF using a sugarcane bagasse and sugar beet molasses [Fungi and bacteria have been reported as microorganisms with great ability to produce flavor and aroma compounds during SSF. Production of fruity flavors by fungi s et al. . Kluyvermolasses . Applicamolasses ,112,118.Due to the increasing trend towards the production of biofuels as a substitute for fossil fuels, environmentally friendly methods for their production are being developed. The first-generation biofuels are usually produced from crops , but from a sustainability point of view, the main limitation of production of first-generation biofuels is food and energy competition . TherefoT. versicolor increase biogas productivity. Jain et al. [C. phytofermentans may represent an alternative to SmF in the production of reducing sugars that are metabolized to ethanol and acetate. Clostridium phytofermentans is considered a suitable anaerobic mesophilic bacterium for biological treatment of lignocellulosic biomass because it produces numerous enzymes that participate in degradation of complex carbohydrates to simple sugars.Complex chemical structure of biomass  requires the pretreatment of such lignocellulosic material, which is a pivotal step before being involved in the hydrolysis and fermentation process. Delignification and detoxification are two main targets of ligninolytic enzymes in biofuel production. Delignification presents reduction of lignin content in biomass, while detoxification means reduction of toxic components present in biomass hydrolysate . Tišma en et al.  found thThe quality of feed is an imperative of modern livestock agriculture. There is a great increase of need for feed as a consequence of world population growth and the need for food of animal origin.Phanerochaete chrysosporium, Pleurotus sp., L. edodes, Coriolus versicolor, Phlebia sp., Ceriporiopsis subvermispora, and Ganoderma sp. have been applied for SSF of various AFIRs  to produce animal feed of better quality through improved digestibility, enhanced palatability, and availability of fermentable energy to ruminal microbes [Therefore, many researchers focus on manipulation with unconventional feed sources, such as lignocellulosic biomass with microorganisms. AFIRs remaining after cereal  processing possess binding properties because of starch they contain. However, due to the low nitrogen and mineral content, as well as the reduced digestibility associated with high lignin, cellulose, and hemicellulose content, direct utilization of AFIRs for ruminant feeding is limited . To imprmicrobes . The culmicrobes . The commicrobes . In addimicrobes .The problems in modern livestock agriculture are that animal feed and feed materials can be contaminated with undesirable substances , which may originate from the environment and/or the production process. When production animals consume such contaminated feed, the contaminants may transfer to food of animal origin, such as liver, meat, and milk. In the European Union (and most of the rest of the world), legislation is in place to manage the feed and feed material contamination. Official limits and guidelines indicate safe levels of each contaminant, often per feed  group. Moreover, procedures for control of the presence of the contaminant are prescribed, e.g., the number of samples to be taken for which contaminants. Within the European Union (EU), Regulation (EC) No. 882/2004 provides rules for the official controls that have to be performed to ensure the verification of compliance with feed and food law, animal health, and animal welfare rules .T. versicolor culture filtrate, which was shown to be a very promising tool for aflatoxin B1 reduction of contaminated maize in animal feed. Studies on the use of T. versicolor in the animal nutrition indicate its highly relevance in the term of sustainable feed production [The possible solution to remove mycotoxins is the use of selected white-rot fungi, such as, e.g., oduction .AFIRs are rich natural sources of various nutrients and bioactive compounds. Although these residues can cause serious economic and environmental problems due to unacceptable disposal, large quantities of residues are considered as potential for reuse and as energy sources. Their availability and low cost could lead to more economical industrial scale processes. SSF is an environmentally friendly bioprocess that does not use expensive AFIRs as substrates and can offer significant advantages in economic terms for the production of valuable compounds . It is also an alternative to the pretreatment process for the low-cost production of sustainable biofuels, which poses a challenge for the commercialization of the production process. The main drawback of this technology is that the hydrolysis of lignocellulosic components in some feedstocks is too slow, which prevents this method as a potential pretreatment method at industrial level. To speed up the process and make it more efficient, it is possible to use a combination of another pretreatment method  with the biological pretreatment. However, the development and establishment of combined methods still requires a large amount of research and work to reach full efficiency. Numerous studies have led to great progress in the development of SSF processes from laboratory scale to scale-up and bioreactor application. With the increasing competition in the industry, optimization of the process and bioreactor design are important factors in the field of future research.