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Metagenomics reveals the microbial community and functional metabolism variation in the partial nitritation-anammox process:From collapse to recovery

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Journal of Environmental Sciences 2024年第1期135卷 210-221页

作者： Hong Wang Hui Gong Xiaohu Dai Min Yang State key laboratory of Pollution control and Resource Reuse College of Environmental Science and EngineeringTongji UniversityShanghai 200092China BIOMATH Department of Data Analysis and Mathematical ModellingGhent UniversityGhent 9000Belgium

Mainstream partial nitritation-anammox(PNA)process easily suffers from performance instability and even reactor collapse in application.Thus,it is of great significance to unveil the characteristic of performance recovery,understand the intrinsic mechanism and then propose operational strategy.In this study,we combined long-term reactor operation,batch tests,and metagenomics to reveal the succession of microbial community and functional metabolism variation from system collapse to recovery.Proper aeration control(0.10-0.25mg O_(2)/L)was critical for performance recovery.It was also found that Candidatus Brocadia became the dominant flora and its abundance increased from 3.5%to 11.0%.Significant enhancements in carbon metabolism and phospholipid biosynthesis were observed during system recovery,and the genes abundance related to signal transduction was dramatically increased.The up-regulation of sdh and suc genes showed the processes of succinate dehydrogenation and succinyl-CoA synthesis might stimulate the production of amino acids and the synthesis of proteins,thereby possibly improving the activity and abundance of AnAOB,which was conducive to the performance recovery.Moreover,the increase in abundance of hzs and hdh genes suggested the enhancement of the anammox process.Changes in the abundance of key genes involved in nitrogen metabolism indicated that nitrogen removal pathway was more diverse after system recovery.The achievement of performance recovery was driven by anammox,nitrification and denitrification coupled with dissimilatory nitrate reduction to ammonium.These results provide deeper insights into the recovery mechanism of PNA system and also provide a potential regulation strategy for the stable operation of the mainstream PNA process.

关键词： Partial nitritation-anammox Metagenomics Microbial community Functional metabolism Recovery

A New Encrypted Traffic Identification Model Based on VAE-LSTM-DRN

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Computers, Materials & Continua 2024年第1期78卷 569-588页

作者： Haizhen Wang Jinying Yan Na Jia College of Computer and control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang key laboratory of big data Network Security Detection and analysis Qiqihar UniversityQiqiharChina

Encrypted traffic identification pertains to the precise acquisition and categorization of data from traffic datasets containing imbalanced and obscured content.The extraction of encrypted traffic attributes and their subsequent identification presents a formidable challenge.The existing models have predominantly relied on direct extraction of encrypted traffic data from imbalanced datasets,with the dataset’s imbalance significantly affecting the model’s performance.In the present study,a new model,referred to as UD-VLD(Unbalanced dataset-VAE-LSTM-DRN),was proposed to address above problem.The proposed model is an encrypted traffic identification model for handling unbalanced datasets.The encoder of the variational autoencoder(VAE)is combined with the decoder and Long-short term Memory(LSTM)in UD-VLD model to realize the data enhancement processing of the original unbalanced datasets.The enhanced data is processed by transforming the deep residual network(DRN)to address neural network gradient-related issues.Subsequently,the data is classified and recognized.The UD-VLD model integrates the related techniques of deep learning into the encrypted traffic recognition technique,thereby solving the processing problem for unbalanced datasets.The UD-VLD model was tested using the publicly available Tor dataset and VPN dataset.The UD-VLD model is evaluated against other comparative models in terms of accuracy,loss rate,precision,recall,F1-score,total time,and ROC curve.The results reveal that the UD-VLD model exhibits better performance in both binary and multi classification,being higher than other encrypted traffic recognition models that exist for unbalanced datasets.Furthermore,the evaluation performance indicates that the UD-VLD model effectivelymitigates the impact of unbalanced data on traffic classification.and can serve as a novel solution for encrypted traffic identification.

关键词： data enhancement LSTM deep residual network VAE

Relationship Between Climate Change and Marmot Plague of Marmota himalayana Plague Focus—the Altun Mountains of the Qinghai-Xizang Plateau,China,2000–2022

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China CDC weekly 2024年第4期6卷 69-74,I0006页

作者： Qun Duan Xiaojin Zheng Zhiqiang Gan Dongyue Lyu Hanyu Sha Xinmin Lu Xiaoling Zhao Asaiti Bukai Ran Duan Shuai Qin Li Wang Jinxiao Xi Di Wu Peng Zhang Deming Tang Zhaokai He Huaiqi Jing Biao Kan Xin Wang National Institute for Communicable disease control and prevention Chinese Center for Disease Control and PreventionBeijingChina Akesai Kazak Autonomous County Center for disease control and prevention Jiuquan CityGansu ProvinceChina Jiuquan Center for disease control and prevention Jiuquan CityGansu ProvinceChina Gansu Provincial Center for disease control and prevention Lanzhou CityGansu ProvinceChina

Introduction:Plague is a zoonotic disease that occurs naturally in specific geographic areas.Climate change can influence the populations of the plague host or vector,leading to variations in the occurrence and epidemiology of plague in animals.Methods:In this study,we collected meteorological and plague epidemiological data from the Marmota himalayana plague focus in the Altun Mountains of the Qinghai-Xizang Plateau.The data spanned from 2000 to 2022.We describe the climatic factors and plague epidemic conditions and we describe their analysis by Pearson’s correlation.Results:During the period from 2000 to 2022,the isolation rates of Yersinia pestis(Y.pestis)from marmots and fleas were 9.27%(451/4,864)and 7.17%(118/1,646),respectively.Additionally,we observed a positive rate of F1 antibody of 11.25%(443/3,937)in marmots and 18.16%(142/782)in dogs.With regards to climate,there was little variation,and a decreasing trend in blowing-sand days was observed.The temperature in the previous year showed a negative correlation with the Y.pestis isolation rate in marmots(r=−0.555,P=0.011)and the positive rate of F1 antibody in marmots(r=−0.552,P=0.012)in the current year.The average annual precipitation in the previous two years showed a positive correlation with marmot density(r=0.514,P=0.024),while blowingsand days showed a negative correlation with marmot density(r=−0.701,P=0.001).Furthermore,the average annual precipitation in the previous three years showed a positive correlation with the isolation rate of Y.pestis from marmots(r=0.666,P=0.003),and blowing-sand days showed a negative correlation with marmot density(r=−0.597,P=0.009).Conclusions:The findings of this study indicate that there is a hysteresis effect of climate change on the prevalence of plague.Therefore,monitoring climate conditions can offer significant insights for implementing timely preventive and control measures to combat plague epidemics.

关键词： Plague epidemiology Plateau

Characteristics of the HIV/AIDS Epidemic among People Aged≥50 Years in China during 2018–2021

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Biomedical and Environmental Sciences 2024年第4期37卷 399-405页

作者： HOU Yu Shan JIN Yi Chen CAI Chang TANG Hou Lin QIN Qian Qian LYU Fan National Center for AIDS/STD control and prevention Chinese Center for Disease Control and PreventionBeijing 102206China

Objective This study aimed to determine the current epidemiological status of PLWHA aged≥50 years in China from 2018 to 2021.It also aimed to recommend targeted interventions for the prevention and treatment of HIV/AIDS in elderly patients.Methods data on newly reported cases of PLWHA,aged≥50 years in China from 2018 to 2021,were collected using the CRIMS.Trend tests and spatial analyses were also conducted.Results Between 2018 and 2021,237,724 HIV/AIDS cases were reported among patients aged≥50 years in China.The main transmission route was heterosexual transmission(91.24%).Commercial heterosexual transmission(CHC)was the primary mode of transmission among males,while non-marital non-CHC([NMNCHC];60.59%)was the prevalent route in women.The proportion of patients with CHC decreased over time(Z=67.716,Panalysis indicated spatial clustering,and the high-high clustering areas were mainly distributed in the southwestern and central-southern provinces.Conclusion In China,PLWHA,aged≥50 years,were predominantly infected through heterosexual transmission.The primary modes of infection were CHC and NMNCHC.There were variations in the sex ratio among different age groups,infected through various sexual behaviors.HIV/AIDS cases exhibited spatial clustering.Based on these results,the expansion of HIV testing,treatment,and integrated behavioral interventions in high-risk populations is recommended to enhance disease detection in key regions.

关键词： HIV/AIDS Aged≥50 years China

Geographically and Temporally Weighted Regression in Assessing Dengue Fever Spread Factors in Yunnan Border Regions

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Biomedical and Environmental Sciences 2024年第5期37卷 511-520页

作者： ZHU Xiao Xiang WANG Song Wang LI Yan Fei ZHANG Ye Wu SU Xue Mei ZHAO Xiao Tao National key laboratory of Intelligent Tracking and Forecasting for Infectious diseases Chinese Center for Disease Control and PreventionBeijing 102211China Yunnan Institute of Parasitic diseases Pu’er 665000YunnanChina

Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-temporal variability of these factors in border regions.Methods We conducted a descriptive analysis of dengue fever’s temporal-spatial distribution in Yunnan border areas.Utilizing annual data from 2013 to 2019,with each county in the Yunnan border serving as a spatial unit,we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region.Results The GTWR model,proving more effective than Ordinary Least Squares(OLS)analysis,identified significant spatial and temporal heterogeneity in factors influencing dengue fever’s spread along the Yunnan border.Notably,the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence,meteorological variables,and imported cases across different counties.Conclusion In the Yunnan border areas,local dengue incidence is affected by temperature,humidity,precipitation,wind speed,and imported cases,with these factors’influence exhibiting notable spatial and temporal variation.

关键词： Dengue fever Meteorological factor Geographically and temporally weighted regression

Efficacy of substances containing 3 types of active ingredients-saponins, flavones, and alkaloids in regulation of cytokines in autoimmune diseases a systematic review and Meta-analysis based on animal studies

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Journal of Traditional Chinese Medicine 2024年第3期44卷 417-426页

作者： ZHU Ruifang ZHANG Jun LYU Yaru CHEN Yulu HAN Shifan WANG Hongwei key laboratory for Molecular Diagnosis and Treatment of Hematologic diseases Second Hospital of Shanxi Medical University Editorial Office First Hospital of Shanxi Medical University School of Nursing Shanxi Medical University

OBJECTIVE: To investigate the efficacy of substances containing 3 types of active ingredients-saponins,flavones, and alkaloids on experimental animals with autoimmune diseases(AIDs).METHODS: The protocol for this systematic review and Meta-analysis was prospectively registered with PROSPERO(CRD42023395741). Searches were conducted in the China National Knowledge Infrastructure, Wanfang, Chinese Science and Technology Journals, China Biomedical, Pub Med,Cochrane Library, and Embase databases to screen for animal studies investigating the therapeutic effects of saponins, flavones, or alkaloids on autoimmune diseases;consequently, corresponding data extraction tables were prepared. Systematic Review Centre for laboratory Animal Experimentation was used to assess the risk of methodological bias in the included literature. RevMan 5.4 was used for the Meta-analysis on the 8 serum cytokines.RESULTS: A total of 31 studies were included, all of which were randomized controlled studies. Meta-analysis indicated that substances rich in saponins, flavones, and alkaloids reduced serum levels of interleukin(IL)-1β[standardized mean difference(SMD) =-1.94, 95%confidence interval(CI)(-2.99,-0.90), P = 0.0003], IL-6 [SMD =-1.65, 95% CI(-2.33,-0.97,) P control autoimmune diseases in the future.

关键词： Meta-analysis alkaloids autoimmune diseases flavones saponins system evaluation

On convergence of covariance matrix of empirical Bayes hyper-parameter estimator

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control Theory and Technology 2024年第2期22卷 149-162页

作者： Yue Ju Biqiang Mu Tianshi Chen School of data Science and Shenzhen Research Institute of big data The Chinese University of Hong KongShenzhenShenzhen518172GuangdongChina Division of Decision and control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technology10044StockholmSweden key laboratory of Systems and control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of SciencesBeijing100190China

Regularized system identification has become the research frontier of system identification in the past decade.One related core subject is to study the convergence properties of various hyper-parameter estimators as the sample size goes to infinity.In this paper,we consider one commonly used hyper-parameter estimator,the empirical Bayes(EB).Its convergence in distribution has been studied,and the explicit expression of the covariance matrix of its limiting distribution has been given.However,what we are truly interested in are factors contained in the covariance matrix of the EB hyper-parameter estimator,and then,the convergence of its covariance matrix to that of its limiting distribution is required.In general,the convergence in distribution of a sequence of random variables does not necessarily guarantee the convergence of its covariance matrix.Thus,the derivation of such convergence is a necessary complement to our theoretical analysis about factors that influence the convergence properties of the EB hyper-parameter estimator.In this paper,we consider the regularized finite impulse response(FIR)model estimation with deterministic inputs,and show that the covariance matrix of the EB hyper-parameter estimator converges to that of its limiting distribution.Moreover,we run numerical simulations to demonstrate the efficacy of ourtheoretical results.

关键词： Regularized system identification Hyper-parameter estimator Empirical Bayes Convergence of covariance matrix

Improving Federated Learning through Abnormal Client Detection and Incentive

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 383-403页

作者： Hongle Guo Yingchi Mao Xiaoming He Benteng Zhang Tianfu Pang Ping Ping College of Computer and Information Hohai UniversityNanjing211100China key laboratory ofWater big data Technology of Ministry ofWater Resources Hohai UniversityNanjing211100China

data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness.

关键词： Federated learning abnormal clients incentive credit score abnormal score detection

Causal relationship between circulating vitamin C and 25-hydroxyvitamin D concentrations and common mental disorders-a Mendelian randomization study

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Food Science and Human Wellness 2024年第4期13卷 1877-1885页

作者： Yuanyuan Wang Lirong Dong Meng Zhao Shiyu Yin Pan Da Dengfeng Xu Yifei Lu Jiayue Xia Niannian Wang Shaokang Wang Guiju Sun key laboratory of Environmental Medicine and Engineering of Ministry of Education and Department of Nutrition and Food HygieneSchool of Public HealthSoutheast UniversityNanjing 210009China Department of Integrated Service and Management Jiangsu Provincial Center for Disease Control and PreventionNanjing 210009China

Mental disorders seriously affect people’s health and social stability.This Mendelian randomization(MR)study was designed to investigate the causal relationship between circulating vitamin C(VC)or 25-hydroxyvitamin D(25(OH)D)levels and mental disorders.The data used for the MR analysis were derived from the summary genome-wide association studies(GWAS)database for VC and 25(OH)D and from the Finn Gen consortium for fourteen mental disorders.Based on the inverse variance weighted(IVW)method,we found a potential causal association between circulating VC and anxiety disorders(IVW:OR=1.139,95%CI:1.023-1.269,P=0.018).However,no causal association was found between VC or 25(OH)D and other mental disorders(P>0.05).In the reverse MR analysis,individuals with Alzheimer’s disease was causally associated with higher concentrations of circulating VC(P=0.012),while individuals with anxiety disorders had a negative association between the concentrations of 25(OH)D(P=0.012).However,the current evidence does not support a causal relationship between VC or 25(OH)D and other mental disorders.In addition,there was no causal association between circulating VC and 25(OH)D(P>0.05).Future studies are needed to confirm these findings and to elucidate the mechanisms of potential causality.

关键词： Circulating vitamin C 25-Hydroxyvitamin D Mental disorder Mendelian randomization