OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To analyze the influencing factors of death in the elderly with coronavirus disease 2019(COVID-19).Methods The case data of death caused by COVID-19 in West China Fourth Hospital from January 1 to July 8,2023 were collected,and surviving cases from the West China Elderly Health Cohort infected with COVID-19 during the same period were selected as the control.LASSO-Logistic regression was adopted to analyze the data after propensity score matching and the validity of the model was verified by drawing the receiver operating characteristic curve.Results A total of 3 239 COVID-19 survivors and 142 deaths with COVID-19 were included.The results of LASSO-Logistic regression showed that smoking(OR=3.33,95%CI=1.46-7.59,P=0.004),stroke(OR=3.55,95%CI=1.15-10.30,P=0.022),malignant tumors(OR=19.93, 95%CI=8.52-49.23, P<0.001),coronary heart disease(OR=7.68, 95%CI=3.52-17.07, P<0.001),fever(OR=0.51, 95%CI=0.26-0.96, P=0.042),difficulty breathing or asthma symptoms(OR=21.48, 95%CI=9.44-51.95, P<0.001),and vomiting(OR=8.19,95%CI=2.87-23.58, P<0.001)increased the risk of death with COVID-19.The prediction model constructed based on the influencing factors achieved an area under the curve of 0.889 in the test set.Conclusions Smoking,stroke,malignant tumors,coronary heart disease,fever,breathing difficulty or asthma symptoms,and vomiting were identified as key factors influencing the death risk in COVID-19.
Humans ; COVID-19/mortality* ; Aged ; Propensity Score ; China/epidemiology* ; Risk Factors ; Logistic Models ; Smoking ; SARS-CoV-2 ; Male ; Female ; Stroke ; Neoplasms

This study was aimed at tracing the molecular typing and drug resistance characteristics of a suspected food poi-soning event caused by Clostridium perfringens in a district of Wuhan City.The FilmArray detection system and multiple fluo-rescence quantitative PCR methods were used to rapidly screen for pathogens in samples from the poisoning event.According to the initial screening results,bacteria were isolated,cultured,and identified by mass spectrometry.Fluorescence PCR was used to detect six virulence genes of the isolated Clostridium perfringens strains.On the basis of whole genome sequencing results,we conducted virulence genes,resistance genes,and whole genome single nucleotide polymorphism genetic evolution(wgSNPs)analyses.Antibiotic sensitivity testing was conducted with the agar dilution method.A total of ten strains of Clos-tridium perfringens were isolated,including eight strains from seven anal swab samples,one strain from fecal samples,and one strain from food samples.Food with suspected contamination had a Clostridium perfringens count of 7.8×106 CFU/g.The PLC(a)toxin gene was detected in all ten gas producing capsule isolation strains,but no other 5 tox-in genes such as CPE were detected,thus confirming that all were type A bacteria producing capsule Clostridium.All strains were 100％resistant to clindamycin and almost completely sensitive to antibiotics such as vancomycin,cefoxitin,and meropenem.Ten strains of Clos-tridium perfringens carried resistance genes such as tetB(P),tetA(P),and mprF,followed by ermQ(70％),ant(6)-Ⅰb(10％),and LnuP(10％).Genetic evolution analysis of wgSNPs indicated that the four outbreak strains clustered together and belonged to an independent subbranch with the suspected food sourcestrains,thus indicating close genetic relationships.In con-clusion,this food poisoning incident might have been be caused by hand torn chickens contaminated with Clostridium perfrin-gens,and the molecular types of the strains revealed high genetic diversity.No multiple drug resistance was observed,but all strains were resistant to clindamycin,an aspect requiring further clinical attention.

This study aims to evaluate the therapeutic effect of Alpiniae Oxyphyllae Fructus-Saposhnikoviae Radix(AOF-SR) in a diabetic kidney disease(DKD) mouse model, explore its potential mechanism in regulating the NOD-like receptor protein 3(NLRP3) inflammasome via phosphoinositide 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target of rapamycin(mTOR) signaling pathway, and provide new theoretical support for traditional Chinese medicine(TCM) intervention in DKD. Using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), the active ingredients and potential targets of AOF-SR were screened and its molecular mechanisms were investigated through molecular docking, molecular dynamics simulations, and experimental validation. The db/db mice were randomly divided into four groups: model group, low-dose AOF-SR group, high-dose AOF-SR group, and canagliflozin group. The db/m mice served as normal group. After one week of acclimatization, the mice underwent drug intervention. Starting from one week after treatment, body weight, blood glucose levels, and 24-hour urinary protein(24hUP) were measured every two weeks. After 13 weeks of administration, tissue collection and indicator detection were performed. Blood glucose, 24hUP, urinary microalbumin(mAlb), serum creatinine(Scr), and blood urea nitrogen(BUN) levels were determined. Pathological changes in kidney tissue were observed using hematoxylin-eosin(HE) staining. Enzyme-linked immunosorbent assay(ELISA) was used to detect the levels of serum IL-1β, IL-18, and caspase-1, while RT-qPCR was employed to measure the mRNA expression levels of IL-1β, IL-18, caspase-1, and NLRP3. Western blot was used to assess the protein expression levels of NLRP3, PI3K, p-Akt, Akt, p-mTOR, and mTOR. Network pharmacology analysis indicated that wogonin, pinocembrin, hancinol, and kaempferol were the core compounds for drug treatment of the disease. Molecular docking and molecular dynamics simulations showed that core compounds, particularly wogonin, could specifically bind to PIK3R1, thereby regulating the PI3K/Akt/mTOR pathway. The experimental results indicated that both low and high doses of AOF-SR and canagliflozin significantly reduced blood glucose, 24hUP, mAlb, Scr, and BUN levels in db/db mice, while improving kidney pathological damage and inflammatory cell infiltration. Moreover, the treatments reduced the mRNA expression levels of caspase-1, IL-1β, and IL-18 in the kidneys of db/db mice, as well as the secretion of these factors in the serum. The drugs also inhibited the mRNA and protein expression levels of NLRP3 in the kidneys of db/db mice and decreased the protein levels of PI3K, p-Akt/Akt, and p-mTOR/mTOR. In conclusion, AOF-SR may improve kidney inflammation in DKD mice by regulating the PI3K/Akt/mTOR signaling pathway and inhibiting NLRP3 inflammasome activation.
Animals ; Mice ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Signal Transduction/drug effects* ; Phosphatidylinositol 3-Kinases/metabolism* ; Proto-Oncogene Proteins c-akt/metabolism* ; TOR Serine-Threonine Kinases/metabolism* ; Diabetic Nephropathies/metabolism* ; Inflammasomes/drug effects* ; Male ; Drugs, Chinese Herbal/chemistry* ; Humans ; Mice, Inbred C57BL

OBJECTIVES: To study the impact of family socioeconomic status on children's reading fluency and the chain mediation effect of family reading environment and children's living and learning styles in this relationship. METHODS: A total of 473 children from grades 2 to 6 in two primary schools in Nanjing were selected through stratified random sampling. The children's reading fluency was assessed, and a questionnaire was used to collect information on family socioeconomic status, family reading environment, and children's living and learning styles. The mediation model was established using the Process macro in SPSS, and the Bootstrap method was employed to test the significance of the mediation effects. RESULTS: Family socioeconomic status, family reading environment, and children's living and learning styles were significantly positively correlated with reading fluency (P<0.001). The family reading environment and children's living and learning styles mediated the relationship between family socioeconomic status and children's reading fluency. Specifically, the independent mediation effect of family reading environment accounted for 11.02% of the total effect, while the independent mediation effect of children's living and learning styles accounted for 10.79%. The chain mediation effect of family reading environment and children's living and learning styles accounted for 7.41% of the total effect. CONCLUSIONS Family socioeconomic status can affect children's reading fluency through three pathways: family reading environment, children's living and learning styles, and the chain mediation effect of family reading environment and children's living and learning styles.
Humans ; Child ; Male ; Female ; Reading ; Learning ; Social Class ; Family

Aim To explore the mechanism of Con-grong Shujing granule(CSGs)in the treatment of Par-kinson's disease(PD)by network pharmacology,mo-lecular docking and parallel reaction monitoring(PRM)technology.Methods The active components of CSGs and the target genes of Parkinson's disease were obtained through the database.The intersection targets of drugs and diseases were selected to construct the"drug-active ingredient-target"and protein interac-tion network.The intersection target genes were impor-ted into David database for GO and KEGG enrichment analysis,and the main components were docked with key targets.27 SD rats were randomly divided into the normal group(n=9),model group(n=9)and treat-ment group(n=9).On day 1,7 and 14 of treatment,PRM analysis was used to detect the changes in the specific peptides of key target proteins in the substantia nigra of rats.Results The main components of CSGs wereTanshialdehyde,Baicalein,Quercetin and Kaempferol.The most important targets for the treat-ment of PD were TP53,AKT1,EGFR,HSP90 AA1 and STAT3.KEGG analysis mainly enriched MAPK,PI3K-Akt and neurotrophic factor signaling pathway.The molecular docking between core components and core targets showed that the binding of drugs and targets had good activity.PRM analysis of key proteins found that the target peptide expression levels of ASK1,JNK1 and JNK3 were different among groups(P＜0.05).Con-clusion CSGs can alleviate ERS,inhibit apoptosis and play a neural protective role through the ASK1-JNK pathway.

Gene editing technology has become an important tool for biomedical research because of its high efficiency and precision in target gene localization and cleavage.The technology not only facilitates basic research on gene function,but also provides new strategies for gene therapy of hereditary diseases and genetic improvement of crops.With the integration of artificial intelligence(AI)technology,espe-cially the application of machine learning algorithms,the design and execution of gene editing have be-come more intelligent.AI technology optimizes the design of sgRNAs through predictive analysis and pat-tern recognition,improving the specificity and efficiency of editing while reducing the risk of off-target effects.In addition,AI plays a key role in the parsing of large-scale genomic data,providing new per-spectives for understanding complex biological processes and disease mechanisms.This paper reviews the research progress of data-driven gene editing technology in target precision,safety enhancement and per-sonalized therapy,aiming to provide reference and inspiration for researchers in the field of gene editing technology and to promote the application and development of AI in gene editing technology.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]

Gene editing technology has become an important tool for biomedical research because of its high efficiency and precision in target gene localization and cleavage.The technology not only facilitates basic research on gene function,but also provides new strategies for gene therapy of hereditary diseases and genetic improvement of crops.With the integration of artificial intelligence(AI)technology,espe-cially the application of machine learning algorithms,the design and execution of gene editing have be-come more intelligent.AI technology optimizes the design of sgRNAs through predictive analysis and pat-tern recognition,improving the specificity and efficiency of editing while reducing the risk of off-target effects.In addition,AI plays a key role in the parsing of large-scale genomic data,providing new per-spectives for understanding complex biological processes and disease mechanisms.This paper reviews the research progress of data-driven gene editing technology in target precision,safety enhancement and per-sonalized therapy,aiming to provide reference and inspiration for researchers in the field of gene editing technology and to promote the application and development of AI in gene editing technology.

Objective:To investigate the efficacy of 3D-printed navigation guided pudendal lead implantation on nervous regula-tion of lower urinary tract symptoms(LUTS)in male patients.Methods:Twenty-eight male patients who underwent perineal nervous regulation treatment for LUTS in Gongli Hospital of Pudong New Area from October 2021 to October 2023 were randomly divided into observation group and control group.The technology assisted with 3D-printed navigation to regulate the genital nerves was used in ob-servation group.And the patients in control group were treated with regulation of the genital nerves by routine puncture.Operation time of puncture,number of surgical punctures,and stimulator debugging time compared between the two groups.The improvement of post-operative symptoms and surgical complications of patients in the observation group were recorded as well.Result:A total of 12 male LUTS patients were included in the observation group,with an average age of 36.5±6.5 years,including 7 cases of frequent micturi-tion,3 cases of perineal pain,and 2 cases of dysuria.Four patients showed no significant improvement in symptoms,including two pa-tients with pain and two cases of frequent micturition who did not undergo secondary surgery.While the other eight patients showed sig-nificant improvement in symptoms.The average time for successful puncture in control group was(21.13±4.53)minutes,which was longer than that of the 3D-printed navigation group([10.32±3.42]min)significantly(P＜0.05).The average number of punctures in the ordinary puncture group was 5.62±1.43,which was significantly higher than that in the 3 D-printed navigation group(1.5±0.56).There was no statistically significant difference in the average time for stimulator debugging between the two groups of patients.The conversion rate of the 3D-printed navigation group in the second phase was 66.7％,which was higher than that(37.5％)significantly(P＜0.05).Conclusion:3D printing navigation of pudendal nerve electrode wire implantation can improve the accuracy of electrode implantation and the conversion rate to a certain extent,which has the advantages of reducing the difficulty of surgery.