ObjectiveTo investigate the role and mechanism of Lck/Yes-related novel protein tyrosine kinase （Lyn） on lipopolysaccharide （LPS）-induced M1-type polarization of macrophage. MethodsThe LentiCRISPR-V2 plasmid was digested with the restriction endonuclease BSMBI-V2， and the digested DNA fragments were recovered. The digested plasmid was ligated with Lyn-sgRNA using T4 ligase to generate the Lenti-Lyn-gRNA lentivirus. THP-1 cells were infected with the Lenti-Lyn-gRNA lentivirus to obtain a stable cell line with Lyn knockout， and a monoclonal THP-1 cell line with complete Lyn knockout （Lyn^⁻/⁻） was established subsequently. Wild-type Lyn （Lyn^WT） and Lyn^⁻/⁻ THP-1 cells were induced with 100 ng/mL phorbol myristate acetate （PMA） for 48 h to differentiate into M0 macrophages， which were further polarized into M1 macrophages by stimulation with 100 ng/mL LPS for 24 h. Quantitative real-time polymerase chain reaction （qPCR） was performed to detect the expression of M0 macrophage markers， including integrin αM （CD11b）， macrophage antigen （CD68）， and monocyte differentiation antigen （CD14）. The expression of Lyn in M1 macrophages differentiated from wild-type THP-1 cells （Lyn^WT-M1） was measured by qPCR， and the ratio of phosphorylated Lyn to total Lyn （P-Lyn/Lyn） in Lyn^WT-M1 cells was determined by Western blot. In M1 macrophages differentiated from Lyn-knockout THP-1 cells （Lyn^⁻/⁻-M1）， qPCR was used to detect the mRNA expression of inducible nitric oxide synthase （iNOS）， interleukin-6 （IL-6）， and chemokine （C-X-C motif） ligand 10 （CXCL-10）. Western blot was conducted to assess the protein expression of iNOS， as well as the protein levels of molecules related to the Janus kinase 1 （JAK1）-signal transducer and activator of transcription 1 （STAT1）signaling pathway， including JAK1， phosphorylated JAK1 （P-JAK1）， STAT1， and phosphorylated STAT1 （P-STAT1）. Additionally， the expression of the M1 macrophage marker cluster of differentiation 80 （CD80） was analyzed by flow cytometry. ResultsThe Lyn^-/- monoclonal cell line was successfully constructed. The expression of CD11b was significantly elevated in Lyn^-/- M0 macrophages， and the differentiation of M1 macrophages was successful. Knockdown of Lyn inhibited mRNA expression of iNOS， IL⁃6， CXCL⁃10， protein expression of iNOS and CD80 expression in M1 macrophages （P<0.05）. Western blot assay showed that Lyn knockdown inhibited protein expression of JAK1 and P-STAT1 （P<0.01）. ConclusionAfter CRISPR/Cas9-mediated Lyn knockout， the expression levels of JAK1 and P-STAT1， the key molecules in the JAK/STAT signaling pathway of M1 macrophages， are significantly downregulated； concomitantly， the expression of M1 macrophage-specific secretory factors （iNOS， IL⁃6， CXCL⁃10 mRNA） and CD80 is also downregulated， which may be achieved via targeted regulation of the JAK1/P-STAT1-mediated JAK/STAT signaling pathway.

ObjectiveTo explore the effect of Shenge Bushen Capsules （SBC） on sexual development in normal 3-week-old mice. MethodsThe experiment consisted of two parts. In the first part， mice were divided into four groups： The control group and the low， medium， and high-dose SBC groups （234.7， 469.4， 938.7 mg·kg^-1， respectively）. In the second part， mice were divided into four groups： Control group， Pseudostellariae Radix polysaccharide （PRP） group， total flavonoids group， and SBC group， all receiving a dose of 469.4 mg·kg^-1. After 7 days of administration， the vaginal opening of female mice and the descent of testes and scrotum in male mice， as well as the ovarian and testicular organ indices， were observed. After 4 weeks of administration， female and male mice were housed together for 2 days， and the pregnancy rate of females was monitored. After delivery， the pregnant female mice continued receiving the treatment for 4 weeks， and the sexual development of their offspring， including vaginal opening， testicular descent， and organ indices of ovaries and testes， was observed. Serum sex hormones were measured by enzyme-linked immunosorbent assay （ELISA）， and the expression of gonadotropin-releasing hormone （GnRH） and growth hormone （GH） proteins in the hypothalamus was assessed by Western blot. ResultsCompared with the control group， there was no significant effect on the vaginal opening of female mice or the descent of testes in male mice after 7 days of SBC administration. After 4 weeks of administration， the pregnancy rate in the low-dose group was significantly reduced （P<0.05）， but no significant effects were observed in the other groups. The three doses of SBC did not significantly affect the ovarian or testicular organ indices， and there was no significant upregulation in the expression of GnRH or GH in the hypothalamus. The primary component of SBC， Pseudostellariae Radix polysaccharide， significantly reduced the vaginal opening in female mice after 7 days of administration （P<0.05）. After 4 weeks， the serum estradiol levels of non-pregnant female mice were decreased （P<0.05）， but there was no significant effect on the expression of GnRH or GH proteins in the hypothalamus of either male or female mice. Additionally， there were no significant effects on precocious puberty indicators， such as vaginal opening and testicular descent， in the offspring mice. ConclusionSBC does not significantly promote precocious puberty in young mice， and it does not have any noticeable effects on the pregnancy rate of adult mice or the sexual development of their offspring.

Objective To establish an animal model of hand,foot,and mouth disease(HFMD)in Syrian hamsters coinfected with coxsackievirus A6(CVA6)and coxsackievirus B1(CVB1).Methods 42 Syrian hamsters were divided into a CVA6 infection group,CVB1 infection group,CVA6 and CVB1 coinfection group and control group.A HFMD model was established by nasal instillation of virus solution and phosphate-buffered saline.Clinical and physiological indicators and detoxification status were monitored and recorded for 15 d,and animals were selected on day 7(D7)after infection for histopathology and viral antigen and nucleic acid testing.Results Hamsters in the single-infection and coinfection groups showed clinical symptoms similar to human HFMD.White blood cell,neutrophil,and lymphocyte result were characteristic of viral infection.Both viral nucleic acids were detected in throat swabs,feces,blood,and tissues and both viruses were isolated from fecal samples.Pathological damage and positive co-localization of CVA6 and CVB1 viral antigen proteins and nucleic acids were found in brain and other tissues.Conclusions Nasal instillation of a CVA6 and CVB1 mixture can successfully coinfect Syrian hamsters,replicate herpes infection similar to human HFMD,and cause pathological viral myocarditis and encephalitis damage.The result showed that the coinfection group was more seriously affected than the single-infection group,with worse clinical symptoms,increased viral replication,and obvious tissue pathological damage.This study provides a reference for further basic and clinical research into human enterovirus coinfection.

Objective:To explore the relationship between obesity indicators and DNA methylation clocks acceleration,and to analyze their temporal sequence.Methods:Data were obtained from two sur-veys conducted in 2013 and 2017-2018 by the Chinese National Twin Registry.Peripheral blood DNA methylation data were measured using the Illumina Infinium Human Methylation 450K BeadChip and EPIC BeadChip.DNA methylation clocks/acceleration metrics(GrimAA,PCGrimAA and Dunedin-PACE)were calculated using the DNA methylation online tool(https://dnamage.genetics.ucla.edu/)or R code provided by researchers.Obesity indicators included weight,body mass index(BMI),waist circumference,waist-hip ratio,and waist-height ratio.A total of 1 070 twin individuals were included in the cross-sectional analysis,comprising 378 monozygotic(MZ)twin pairs and 155 dizygotic(DZ)twin pairs for within-pair analysis.Mixed-effects models were used to examine the associations between obesity indicators and DNA methylation clocks,as well as their acceleration measures.The longitudinal analysis included 314 twin individuals,comprising 95 MZ twin pairs and 62 DZ twin pairs for within-pair analy-sis.Cross-lagged panel models were applied to further explore the temporal relationships between obesity and DNA methylation clock indicators.All analyses were conducted both in the full twin sample and separately within MZ and DZ twin pairs.Results:In the cross-sectional analysis population,monozygotic twins accounted for 71.0％,males for 68.0％,and the mean chronological age was(49.9±12.1)years.In the longitudinal analysis population,monozygotic twins accounted for 60.5％,males for 60.8％,with a mean baseline chronological age of(50.4±10.2)years and a mean follow-up duration of(4.6±0.6)years.Except for the waist-to-hip ratio,which was significantly higher at follow-up com-pared with baseline,no statistically significant differences were observed in the means of other obesity in-dicators between baseline and follow-up.Correlation analysis revealed that weight,BMI,waist circumfe-rence,waist-hip ratio(WHR),and waist-height ratio(WHtR)were positively correlated with Dunedin-PACE in all the twins,with WHtR showing the strongest association(β=0.21,95％CI:0.11 to 0.31).Weight and BMI were negatively associated with GrimAA(β=-0.03,95％CI:-0.05 to-0.01;β=-0.07,95％CI:-0.12 to-0.02),while weight was negatively associated with PCGrim-AA(β=-0.02,95％CI:-0.03 to 0.00).However,within-twin-pair analyses showed no statistically significant correlations.Cross-lagged panel model analysis indicated that higher baseline weight might lead to increased GrimAA at follow-up,while elevated baseline weight,BMI,and waist circumference might increase PCGrimAA.Higher baseline WHR was associated with increased DunedinPACE at follow-up.Conclusion:Obesity indicators correlate with DNA methylation clock acceleration metrics.Baseline obesity may influence changes in certain DNA methylation clock indicators over time,suggesting that obesity could exert long-term health effects by accelerating DNA methylation aging.However,these associations may be confounded by shared genetic or environmental factors among the twins.

Traditional Chinese medicine(TCM)has been used for the control and prevention of infectious diseases for thousands of years.Due to its characteristics of multiple components and multiple targets,it shows promising therapeutic prospects in the field of anti-infection.Here,we provide a detailed introduction to the current application of various omics technologies,such as metabolomics,proteomics,genomics,and transcriptomics in the study of TCM's anti-infective properties.The application of omics technologies can help explore the active components and their targets in TCM that contribute to its anti-infective effects;elucidate the biosynthetic pathways of active components,aiding in the discovery of new active ingredients;and investigate the mechanisms by which TCM affects pathogenic microorganisms,as well as interpret the mechanisms of TCM's synergy with antibiotics.As more research findings are produced and validated,the role of TCM in addressing the global challenge of antimicrobial resistance will become increasingly prominent through the integration of multi-omics and multidisciplinary research methods in the future.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

When the epidemiology of infectious diseases is more complex, it is often difficult for disease prediction studies based on a single model to capture the multidimensional nature of disease transmission. In recent years, combining different models to improve infectious disease prediction has gradually become a research trend and hotspot. Existing studies have shown that combined models usually have higher prediction performance and better generalization ability. The current combined models mainly combine machine learning and other models, including time-series models, dynamic models, etcetera. In addition, integrated learning that combines diverse machine learning techniques also holds significant importance across various research domains. This paper reviews the progress of applying combined models around machine learning in infectious disease prediction to promote the innovation and practice of combined models for infectious diseases and help to build smarter and more efficient infectious disease early warning and prediction methods and systems.

Methods such as compartmental models, agent-based models, time series models, and machine learning can be used for the prediction of infectious disease incidence. When disease epidemics are complex, it is often difficult to use a single model to comprehensively and accurately capture the multi dimensional nature of the disease. Exploring the combined application of different models has gradually become a research trend and hotspot in recent years, and the prediction performance of combined models is often better than that of single ones. Current research related to combined models mainly focus on machine learning or compartmental models. In this review, we focus on the combination of compartmental models and other models, and summarize their combination principles, application progress, and advantages or disadvantages for the purpose of promoting the innovation and application of combined models for infectious disease incidence prediction, and establishing a more intelligent and efficient early warning and prediction method or systems for the prevention and control of infectious disease.

Objective:To describe the distribution characteristics of alcohol consumption in adult twins in the Chinese National Twin Registry (CNTR), and further explore the influence of genetic factors on alcohol consumption in adult twins.Methods:The subjects of the study were twins registered by CNTR in 11 project areas across China from 2010 to 2018. A total of 56 966 twins (28 483 pairs) aged 18 years and above who answered questions about drinking behavior were included, and the random effect model was used to describe the population and regional distribution characteristics of alcohol consumption. Intra-pair analysis was performed to calculate the concordance rate and heritability of their alcohol consumption.Results:The age of all subjects was (36.6±12.0) years, and current drinkers accounted for 16.6% (9 461/56 966) of all subjects. In men, those aged 50-59 years, those in northern China, those living in rural area, those with low education level and those with high BMI, the proportions of current drinkers were higher. After excluding 468 pairs of twins who had stopped alcohol use and 21 764 pairs of twins who had no drink or had small amount drink, an intra-pair analysis was conducted in 4 929 pairs of same-sex twins, and found that the concordance rate of alcohol consumption was 64.0% (2 059/3 215) in monozygotic twins, and 52.6% (902/1 714) in dizygotic twins, the difference was significant ( P<0.001), and the heritability of alcohol consumption was 24.1% (95% CI: 18.9%- 29.3%). The further stratified analysis found that in southern men, the heritability was highest in those aged 40-49 years (36.1%, 95% CI: 21.6%-50.7%), while in northern men, the heritability was highest in those aged 50-59 years (34.2%, 95% CI: 18.1%-50.3%). Conclusions:In adult twins in China, there were population and regional differences in the distribution of alcohol consumption behavior, and alcohol consumption was influenced by genetic factors, and gender, age and region had potential modifying effects.

Objective:To compare the consistency of microarray chemiluminescent protein chip and immunoblotting in the autoantibody spectrum of patients and the diagnostic efficacy of systemic lupus erythematosus(SLE), and to explore the correlation between the detection results of protein microarray and clinical indicators and lymphocyte subsets.Methods:Serum autoantibodies in 649 samples collected between December 2023 and December 2024 in Nanjing Drum Tower Hospital were analyzed using the microarray chemiluminescent protein chip method, with 401 samples simultaneously tested by immunoblotting. Kappa coefficient assessed inter-method consistency. Diagnostic performance was compared via ROC curves. Spearman correlation analysis evaluated relationships between autoantibody levels and SLEDAI-2000 scores, clinical parameters, and lymphocyte subsets.Results:The two methods demonstrated good consistency across 14 antinuclear antibodies, with optimal agreement for anti-SSA/Ro ( Kappa=0.845, P<0.001), anti-SSB ( Kappa=0.825, P<0.001), and anti-CENP B ( Kappa=0.851, P<0.001). The protein chip method significantly improved SLE diagnostic efficacy, particularly for anti-dsDNA (AUC difference=0.291, P<0.001) and anti-Sm antibodies (AUC difference=0.295, P<0.001). Combined detection of anti-SSA/Ro and anti-nRNP/Sm antibodies achieved superior diagnostic performance (AUC=0.927). Anti-dsDNA, anti-histone, and anti-nucleosome antibodies positively correlated with SLEDAI-2000 ( r=0.408, 0410, 0.384, all P<0.001), complement ( P<0.001), and 24-hour urinary protein ( r=0.374, 0.387, 0.301, all P<0.001). Immunological analysis showed that the proportion of NK cells was generally negatively correlated with antinuclear antibodies such as anti-dsDNA ( r=-0.352, P<0.001) and anti-Sm ( r=-0.328, P<0.001) antibodies. Meanwhile, the proportion of CD8 + T cells was positively correlated with anti-nRNP/Sm ( r=0.229, P=0.002) and anti-Sm antibodies ( r=0.211, P=0.005). The proportion of CD4 + T cells was negatively correlated with anti-SSA/Ro ( r=-0.239, P<0.001), while the proportion of B cells was positively correlated with anti-dSDNA antibody ( r=0.300, P<0.001). Conclusion:The protein chip method showed strong consistency with immunoblotting for detecting 14 autoantibodies but demonstrated superior SLE diagnostic efficacy. The combined use of multiple detection methods can enhance the reliability of clinical diagnosis.