ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

ObjectiveTo investigate the patterns of chronic disease comorbidity among permanent elderly residents in Xuhui District of Shanghai, and to analyze the impact of different comorbidity patterns on the elderly’s ability to perform activities of daily living. MethodsBased on data from the 2015 and 2021 Surveys on Health Status and Health Service Utilization among Permanent Residents in Xuhui District of Shanghai, the study included permanent residents who fully participated in both surveys, were aged 60 years or older at the 2015 survey, self-reported having a chronic disease, and reported no significant changes in their chronic disease status between the two surveys. A prospective cohort study design was adopted, using the 2015 data as the baseline and the 2021 survey data as follow-up data. Physical examinations and questionnaire surveys were conducted by the Shanghai Xuhui District Center for Disease Control and Prevention in the subdistricts and towns within the jurisdiction from April to July in both 2015 and 2021. Latent class analysis (LCA) was used to classify comorbidity patterns across 11 types of chronic diseases. The smaller the values of the Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the sample-corrected Bayesian information criterion (aBIC), the better the model fits. The Barthel index (BI) and the Lawton and Brody Instrumental Activities of Daily Living Scale (LB-IADL) were used to assess the participants’ activities of daily living (ADL) and instrumental activities of daily living (IADL). Multiple linear regression and multivariate logistic regression models were used to analyze the association between different comorbidity patterns and ADL and IADL. ResultsA total of 1 608 study participants were enrolled. Among them, 671 (41.73%) self-reported having no chronic diseases. The prevalence of 11 types of chronic diseases was as follows: hypertension in 743 participants (46.21%), heart disease in 148 participants (9.20%), cerebrovascular disease in 37 participants (2.30%), diabetes or abnormal blood glucose in 310 participants (19.28%), other endocrine system diseases (non-diabetic) in 39 participants (2.43%), malignant tumors in 37 participants (2.30%), chronic lung disease in 16 participants (1.00%), gout in 8 participants (0.50%), musculoskeletal disorders in 34 participants (2.11%), gastric or digestive system diseases in 27 participants (1.68%), and dyslipidemia in 15 participants (0.93%). LCA was used to classify comorbidity patterns of chronic diseases among older adults into 1 to 9 latent category combinations. Model 5 (i.e., 5 latent categories) had the lowest BIC (7 112.69) and aBIC (6 909.38), with a relatively low AIC (6 768.20), indicating the best model fit; thus, five latent categories represented the optimal combination in this study. The five latent categories (and their respective proportions of study participants) were the healthy control group (41.73%), the hypertension group (31.28%), the diabetes-hypertension group (19.28%), the severe illness group (5.29%), and the other metabolic diseases group (2.43%). According to multiple linear regression analyses, compared with the healthy control group, the diabetes-hypertension group had significantly lower BI-20 scores (b=-0.952, 95%CI: -1.317‒ -0.587, P<0.001) and lower IADL scores (b=-0.744, 95%CI: -0.999‒ -0.489, P<0.001); the severe illness group (b=-0.644, 95%CI: -1.072‒ -0.217, P=0.003) and the hypertension group (b=-0.344, 95%CI: -0.562‒ -0.125, P=0.002) had lower IADL scores. According to multivariate logistic regression analyses, compared with the healthy control group, older adults in the diabetes-hypertension group had a higher risk of disability (OR=2.835, 95%CI: 1.392‒5.774), impaired ADL function (OR=2.470, 95%CI: 1.637‒3.726), and impaired IADL function (OR=1.739, 95%CI: 1.264‒2.392); older adults in the severe illness group had a higher risk of impaired ADL function (OR=2.206, 95%CI: 1.171‒4.155). ConclusionAmong the elderly participating in the Survey on Health Status and Health Service Utilization of Permanent Residents in Xuhui District of Shanghai, diabetes-hypertension is one of the key chronic disease comorbidity combinations and has adverse effects on both ADL and IADL. Community health management should prioritize the elderly with diabetes-hypertension comorbidity, and strengthen early screening and comprehensive interventions to slow the decline in ADL and IADL.

ObjectiveTo investigate the application of central auditory testing combined with electroencephalographic features in the early screening of mild cognitive impairment due to Alzheimer's disease. MethodsA convenience sampling method was used to conduct a field survey in the Qixia District of Nanjing City, Jiangsu Province, from July to September, 2025. A total of 40 older adults diagnosed as mild cognitive impairment due to Alzheimer's disease and 23 cognitively normal older adults were recruited. Auditory N-back and dichotic listening paradigms were employed for assessment, while the scores of Montreal Cognitive Assessment Beijing Version (MoCA-BJ) and 32-channel electroencephalogram (EEG) data were simultaneously collected. Binary logistic regression analysis was applied to identify predictive indicators, receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated. ResultsThe total score of dichotic listening was positively correlated with overall cognitive function (r = 0.475, P < 0.01), while right-ear advantage showed negative correlations with overall cognition, visuospatial ability, abstract reasoning, and delayed recall (r < -0.276, P < 0.05). Task performance across all conditions of the N-back task was positively correlated with overall cognitive function (r > 0.249, P < 0.05). Regarding EEG features, δ and θ band power and power peaks were positively correlated with delayed recall (r > 0.258, P < 0.05), whereas (α+θ)/(α+β) and θ/(α+β) were positively correlated with naming ability and visuospatial executive function, respectively (r > 0.261, P < 0.05). The results of the binary logistic regression analysis showed that the total score of binaural dichotic listening, the accuracy of 1-back task, the average power of δ waves, and the ratio of θ/(α+β) were independent influencing factors for mild cognitive impairment due to Alzheimer's disease (P < 0.05). The ROC analysis indicated that the AUC for auditory task performance and EEG features were 0.845 and 0.735 respectively, and when combined, the AUC increased to 0.862. ConclusionThe screening model based on the integration of auditory task performance and EEG features can be used in the early identification of mild cognitive impairment due to Alzheimer's disease.

ObjectiveTo enhance the genetic diagnostic yield for fetal short femur length （FL） and to evaluate the integration of whole exome sequencing （WES） with chromosomal abnormality detection in prenatal diagnosis. MethodsA total of 27 mid-to-late trimester fetuses diagnosed with short FL ［FL < 5th percentile for gestational age or < -2 SD （Standard Deviation）］ at the Prenatal Diagnosis And Medical Genetics Center，Shenshan Medical Center，Memorial Hospital of Sun Yat-Sen University between November 2023 and May 2025 were included. Amniotic fluid or umbilical cord blood samples were collected and subjected to chromosomal karyotyping （19cases）， chromosomal microarray analysis （CMA） or low-coverage whole genome copy number variation（CNV-Seq） （27 cases）， and trio-based whole exome sequencing （trio-WES） （27 cases）. The pathogenicity of genetic variants were interpreted according to the American College of Medical Genetics and Genomics （ACMG） guidelines. ResultsTwenty-six genomic variants were detected in 17 of the 26 fetuses， including numerical chromosomal abnormalities （mosaic type）， copy number variations （CNVs）， single nucleotide variants （SNVs） and insertions-deletions （INDELs）. Genomic variants detected in 11 cases could explain the short femur phenotype.The overall diagnostic rate was 11/27， with pathogenic/likely pathogenic variants explaining 9 cases and variants of uncertain significance （VUS） accounting for 1 cases. In addition Chromosomal karyotype analysis revealed chromosome mosaicism explaining 1 case. The diagnostic rate of CNV detection （CMA/CNV-seq） was 2/27， while WES achieved a diagnostic rate of 10/27， with an incremental yield of 8/27 in cases with negative or inconclusive CNV results. Pathogenic mutations involved genes such as FGFR3， SHOX， DUOX2， CLCN5， and HBA1/HBA2. ConclusionTrio-WES significantly improves the genetic diagnostic rate for fetal short femur length， particularly in cases where chromosomal analysis fails to identify a cause. Karyotyping remains valuable for detecting low-level mosaicism in large-scale chromosomal abnormalities， thereby complementing WES and CNV detection. A stepwise or parallel genetic testing strategy is recommended in prenatal diagnosis to optimize diagnostic efficiency and support clinical decision-making.

It is believed that there is a pathogenesis of yang deficiency in polycystic ovary syndrome （PCOS） infertility， and it is concluded that warm-yang method has a better effect in improving endometrial abnormality， enhancing the quality of follicles， correcting endocrine disorders， and resolving or alleviating clinical symptoms in PCOS infertility. Based on Yanghe Decoction （阳和汤）， a representative traditional Chinese medicine decoction for warming yang， Yanghe Xiaonang Decoction （阳和消囊汤） was formulated， combining with warm medicinals according to symptoms， and aerobic exercise was also advocated to help generate and develop yang qi， in order to provide ideas for clinical treatments.

Objective To compare the node strength in white matter networks between depressive disorder and bipolar depression patients,analyze structural connectivity impairments across brain regions,and assess their diagnostic utility.Methods This longitudinal study initially enrolled 91 patients with a baseline diagnosis of depressive episode.All subjects underwent diffusion tensor imaging at recruitment and white matter structural weighted networks were constructed using deterministic fiber tracking.After≥9 years of naturalistic follow-up,23 patients who maintained a diagnosis of major depressive disorder(MDD group)and 18 patients who maintained a diagnosis of bipolar disorder(BD group),while 30 demographically matched healthy controls(HC group)were included for comparison.The differences in nodal connection strength within the brain white matter networks among the three groups were compared.Furthermore,the receiver operator characteristic(ROC)curve was utilized to evaluate the diagnostic value of the differential brain regions in distinguishing between MDD and BD.Results In the left anterior cingulate gyrus,the node strength was lower in the BD than in the MDD group(3.89±0.76 vs.4.74±0.60).However,the node strength in the right caudate nucleus(4.94±1.26 vs.3.46±0.99)and right globus pallidus(1.98±0.67 vs.1.25±0.29)was higher in the BD than in the MDD group(P<0.01,FWE-corrected).The combined connectivity strengths of three brain regions—the left anterior cingulate gyrus,right caudate nucleus and right globus pallidus—were used to differentiate between MDD and BD,and an ROC curve was plotted,with an area under the curve(AUC)of 0.95(95%CI:0.91～0.99;P<0.001).The sensitivity and the specificity were 0.89 and 0.87,respectively.Conclusion The differences in node strength between patient groups may serve as a potential neuroimaging biomarker.Integration of node connectivity strengths from these differential brain regions can achieve superior discrimination accuracy.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Psoriasis is an incurable chronic inflammatory disease that requires new interventions. Here, we found that fibroblasts exacerbate psoriasis progression by promoting macrophage recruitment via CCL2 secretion by single-cell multi-omics analysis. The natural small molecule celastrol was screened to interfere with the secretion of CCL2 by fibroblasts and improve the psoriasis-like symptoms in both murine and cynomolgus monkey models. Mechanistically, celastrol directly bound to the low-density lipoprotein receptor-related protein 1 (LRP1) β-chain and abolished its binding to the transcription factor c-Jun in the nucleus, which in turn inhibited CCL2 production by skin fibroblasts, blocked fibroblast-macrophage crosstalk, and ameliorated psoriasis progression. Notably, fibroblast-specific LRP1 knockout mice exhibited a significant reduction in psoriasis like inflammation. Taken together, from clinical samples and combined with various mouse models, we revealed the pathogenesis of psoriasis from the perspective of fibroblast-macrophage crosstalk, and provided a foundation for LRP1 as a novel potential target for psoriasis treatment.

The coinfection of respiratory viruses and bacteria is a major cause of morbidity and mortality worldwide, despite the development of vaccines and powerful antibiotics. As a macromolecule that is difficult to absorb in the gastrointestinal tract, a homogeneous polysaccharide from Houttuynia cordata (HCPM) has been reported to exhibit anti-complement properties and alleviate influenza A virus (H1N1)-induced lung injury; however, the effects of HCPM without in vitro antiviral and antibacterial activities on more complicated pulmonary diseases resulting from viral-bacterial coinfection remains unclear. This study established a representative coinfection murine pneumonia model infected with H1N1 (0.2 LD₅₀) and methicillin-resistant Staphylococcus aureus (MRSA, 10⁷ CFU). HCPM significantly improved survival rate and weight loss, and ameliorated gut-lung damage and inflammatory cytokine production. Interestingly, the therapeutic effect of HCPM on intestinal damage preceded that in the lungs. Mechanistically, HCPM inhibited the overactivation of the intestinal complement (C3a and C5a) and suppressed the activation of the NLR family pyrin domain-containing 3 (NLRP3) pathway, which contributes to the regulation of the Treg/Th17 cell balance in the gut-lung axis. The results indicate the beneficial effects of an anti-complement polysaccharide against viral-bacterial coinfection pneumonia by modulating crosstalk between multiple immune regulatory networks.

Objective To analyze the virus subtypes, molecular evolutional and molecular transmission network features of the first confirmed mpox case in Huai’an City, Jiangsu Province, so as to provide insights into understanding of the transmission and evolution dynamics of mpox virus and formulation of the mpox control strategy in the city. Methods Genomic DNA was extracted from swabs of the first confirmed mpox case’s skin lesions in Huai’an City, and the amplicon sequencing library was constructed using the hypersensitive mpox virus whole-genome capture kit. High-throughput sequencing was performed using the GridION X5 nanopore sequencer on the Nanopore sequencing platform, and single nucleotide polymorphism (SNP) analysis of mpox virus genome sequences was performed following sequence assembly. In addition, phylogenetic analysis, genetic genealogy and molecular traceability analysis were performed. Results The virus whole genome sequence of the first confirmed mpox case was successfully obtained by high-throughput sequencing, with a full length of 197 182 bp, and was named hMpxV/China/JS-HA01/2023, which belonged to the clade IIb (West African clade) lineage B.1.3. Compared with the mpox virus reference sequence MPXV-M5312_HM12_Rivers-001 (GenBank accession number: NC_063383), the genome sequence of the Huai’an virus isolate carried 86 SNPs, including 40 SNPs in the coding region as non-synonymous mutations and 73 SNPs as nucleotide mutations caused by APOBEC3 (APOBEC3). Of the 97 mpox virus gene sequences, 79 sequences were included in the molecular network (81.44%), and the threshold of the genetic distance accessed to the network was 0.35/10⁵. There were two large molecular transmission clusters and one scattered cluster in the molecular transmission network of the mpox virus, andthehMpxV/China/JS-HA01/2023 sequence was located in the large cluster. The 97 gene sequences formed 92 haplotypes, including three shared haplotypes Hap_4, Hap_6 and Hap_38, and an exclusive haplotype Hap_1 of hMpxV/China/JS-HA01/2023 generated from mutation of the exclusive haplotype Hap_43, while the exclusive haplotype Hap_43 was generated from mutation of the shared haplotype Hap_38. Conclusions The whole genome sequence of the mpox virus isolated from the first confirmed mpox case in Huai’an City has been successfully obtained, and the molecular evolutionary and molecular transmission network characteristics of the virus have been preliminarily understood.