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.

Obesity is a chronic low-grade inflammation and a risk factor for diseases such as diabetes， hypertension， dyslipidemia， and malignant tumors， demonstrating an increasingly grim development situation. The nuclear factor-kappa B （NF-κB） signaling pathway is a key signaling pathway involved in the immune response and inflammatory response. In obese individuals， the expression of NF-κB is overactivated， which leads to abnormal inflammatory responses in the body. Therefore， it is expected to alleviate inflammation and treat obesity by regulating the NF-κB signaling pathway， which has been proven effective by a large number of studies. The available studies on the NF-κB signaling pathway mostly focus on tumors， and there is no systematic review of the mechanism of this pathway in mediating obesity and the traditional Chinese medicine （TCM） treatment. We reviewed the research progress in the pathological and physiological processes of obesity mediated by NF-κB signaling pathway and TCM treatment， aiming to give insights into the clinical treatment of obesity with TCM and provide reference targets and research directions for exploring the biological foundations and the development of new TCM preparations.

[Objective] To explore the predictive value of HALP score for prognosis in patients with multiple myeloma (MM). [Methods] A retrospective analysis was conducted on laboratory indicators and related clinical data of newly diagnosed multiple myeloma (NDMM) patients, treated at the Affiliated Hospital of North Sichuan Medical College from January 2016 to October 2023, prior to their first treatment. The HALP score was calculated, and the optimal cutoff value for HALP was determined using X-tile software. Survival analysis was performed using Kaplan-Meier curves for high HALP and low HALP groups. Univariate and multivariate analyses were conducted using the Cox regression model, and a forest plot was generated using Graphpad Prism to illustrate factors that may impact patient prognosis. The predictive ability of HALP score combined with β2-microglobulin and ECOG score for prognosis in MM patients was evaluated using receiver operating characteristic curve (ROC) analysis. [Results] A total of 203 MM patients were included, with the optimal cutoff value for HALP score being 29.15 (P<0.05). Among them, 101 patients were in the low HALP score group, and 102 patients were in the high HALP score group. The results of univariate and multivariate analysis using the Cox regression model showed that a HALP score <29.15 was an independent risk factor for progression-free survival (PFS) and overall survival (OS) (P<0.05). ROC curve analysis indicated that the combination of HALP score with β2-microglobulin and ECOG score had a higher predictive value for prognosis in MM patients compared to using HALP score alone. [Conclusion] The HALP score is closely related to the prognosis of patients with NDMM. A low HALP score indicates a poorer prognosis, while the combination of HALP score with β2-microglobulin and ECOG score provides a higher predictive value when assessed together.

Objective: To compare the value of a body shape index (ABSI) and body roundness index (BRI) in predicting non-alcoholic fatty liver disease (NAFLD) among non-obese population, so as to provide a reference for the early identification of populations at high risk of NAFLD. Methods: Adults with a body mass index (BMI) of less than 28 kg/m2 who underwent health check-ups in Xiyuan Hospital of China Academy of Chinese Medical Sciences from 2022 to 2024 were selected as the study subjects. Demographic information, disease history, height, weight, waist circumference, blood pressure, and blood lipid indicators were collected, and ABSI and BRI were calculated. NAFLD was diagnosed using abdominal ultrasound. A multivariable logistic regression model was employed to analyze the relationships between ABSI, BRI and NAFLD among non-obese population. A generalized additive model combined with the penalized spline method was used to fit smooth curves to identify nonlinear relationships, and threshold effects were utilized to determine inflection points. The values of ABSI and BRI in predicting NAFLD among non-obese population were used the receiver operating characteristic (ROC) curve. Results: A total of 1 195 individuals were surveyed, including 345 males (28.87%) and 850 females (71.13%). A total of 348 cases of NAFLD were detected among the non-obese population, with a detection rate of 29.12%. The adjusted ABSI (sABSI) in the NAFLD group and non-NAFLD group were 7.95±0.33 and 8.08±0.34, while the BRI were 3.35±0.79 and 4.15±0.64, respectively, with statistically significant differences between the two groups (both P<0.05). Multivariable logistic regression analysis showed that, after adjusting for demographic information, disease history, blood pressure, and blood lipid indicators, both sABSI (OR=1.932, 95%CI: 1.184-3.158) and BRI (OR=1.594, 95%CI: 1.071-2.360) were significantly associated with NAFLD among non-obese population. Nonlinear positive correlations were observed between sABSI, BRI, and NAFLD among non-obese population. When sABSI≤8.46 and BRI≥2.72, both indices were positively associated with NAFLD. The area under the ROC curve for ABSI and BRI in predicting NAFLD risk among non-obese population were 0.619 and 0.782, respectively, with optimal cut-off values of 0.082 and 3.656, respectively. Conclusions ABSI and BRI show a non-linear relationship with NAFLD among non-obese population. BRI demonstrates relatively better performance in predicting NAFLD risk among this population and can serve as an auxiliary indicator for the early identification of NAFLD among non-obese population.

The catalytic activity of 3-mercaptopyruvate (3MP) sulfurtransferase (MPST) converts 3MP to hydrogen sulfide (H₂S). However, the regulatory mechanisms governing MPST and its impact on the brain remain largely unexplored. Our study reveals the neuroprotective role of endothelial MPST-generated H₂S, regulated by protein phosphatase 2A (PP2A). Bioinformatics analysis and RNA sequencing demonstrated that endothelial PP2A is associated with neurodegenerative disease pathways. Cerebral ischemic mice exhibited significant inactivation of endothelial PP2A, evidenced by the reduction of PP2Acα in the brain endothelium. Mice with endothelium-specific null PP2A (PP2A^EC-cKO) exhibited neuronal loss, cognitive dysfunction, and long-term potentiation deficits. Postnatal inactivation of endothelial PP2A also contributes to cognitive dysfunction and neuronal loss. However, regaining endothelial PP2A activity by overexpressing Ppp2ca rescued neuronal dysfunction. Mechanistically, PP2A deficiency is intricately linked to the MPST-H₂S signaling pathway. A robust reduction in endothelial MPST-dependent H₂S production followed PP2A deficiency. Exogenous H₂S treatment and AAV-mediated overexpression of MPST in brain endothelial cells significantly mitigated neuronal dysfunction in PP2A^EC-cKO mice. Furthermore, PP2A deficiency promotes an increase in calcium influx and calpain2 phosphorylation, subsequently leading to MPST degradation. The PP2A activator (FTY720) and MPST activator (3MP sodium) both remarkably restored endothelial MPST-dependent H₂S production, subsequently rescuing ischemia-induced neurological deficits. In conclusion, our study demonstrates that endothelial PP2A deficiency leads to MPST degradation by activating calpain2, thus damaging neuronal function.

Abdominal aortic aneurysm (AAA) is a deadly condition of the aorta, carrying a significant risk of death upon rupture. Currently, there is a dearth of efficacious pharmaceutical interventions to impede the advancement of AAA and avert it from rupturing. Here, we investigated dihydromyricetin (DHM), one of the predominant bioactive flavonoids in Ampelopsis grossedentata (A. grossedentata), as a potential agent for inhibiting AAA. DHM effectively blocked the formation of AAA in angiotensin II-infused apolipoprotein E-deficient (ApoE^-/-) mice. A combination of network pharmacology and whole transcriptome sequencing analysis revealed that DHM's anti-AAA action is linked to heme oxygenase (HO)-1 (Hmox-1 for the rodent gene) and hypoxia-inducible factor (HIF)-1α in vascular smooth muscle cells (VSMCs). Remarkably, DHM caused a robust rise (∼10-fold) of HO-1 protein expression in VSMCs, thereby suppressing VSMC inflammation and oxidative stress and preserving the VSMC contractile phenotype. Intriguingly, the therapeutic effect of DHM on AAA was largely abrogated by VSMC-specific Hmox1 knockdown in mice. Mechanistically, on one hand, DHM increased the transcription of Hmox-1 by triggering the nuclear translocation and activation of HIF-1α, but not nuclear factor erythroid 2-related factor 2 (NRF2). On the other hand, molecular docking, combined with cellular thermal shift assay (CETSA), isothermal titration calorimetry (ITC), drug affinity responsive target stability (DARTS), co-immunoprecipitation (Co-IP), and site mutant experiments revealed that DHM bonded to HO-1 at Lys243 and prevented its degradation, thereby resulting in considerable HO-1 buildup. In summary, our findings suggest that naturally derived DHM has the capacity to markedly enhance HO-1 expression in VSMCs, which may hold promise as a therapeutic strategy for AAA.

Objective To explore the association of diabetes status with the development of tuberculosis (TB) among the community population in Shanghai, and to provide evidence for the formulation of tuberculosis prevention and control strategies. Methods This population-based cohort study was based on Shanghai Suburban Adult Cohort and Biobank (SSACB) in China. The baseline data were acquired by questionnaires, physical examinations and blood biochemistry tests. TB incidence was obtained by matching with TB management information system data. A Cox proportional risk model was established to assess the risk of tuberculosis. Results A total of 36 014 research subjects were included, with an average age of 56.3±11.3 years, of which 14 587 (40.5%) were male. Over 6 years of follow-up, 47 individuals progressed to tuberculosis (incidence rate: 19.8 per 100 000 person-year, 95% CI: 14.6 -26.4). An increased risk of TB was observed in participants with newly diagnosed diabetes compared with those without diabetes (adjusted hazard ratio [aHR], 2.73; 95% CI, 1.19 - 6.28). Conclusion The risk of tuberculosis in newly diagnosed diabetic patients is significantly increased, and strengthening tuberculosis screening for this population should be considered in practical work.

AIM To study the chemical constituents from ethyl acetate fraction of Balanophora harlandii Hook.f.and their tyrosinase inhibitory activity.METHODS Separation and purification were performed using silica gel,MCI,ODS,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The monophenolase inhibitory activity was determined by the tyrosinase-catalyzed oxidation of L-tyrosine.RESULTS Twenty-four compounds were isolated and identified as sesamin(1),methyl caffeate(2),quercetin(3),5,7-dihydroxychromanone(4),methyl 3,4-dihydroxybenzoate(5),esculetin(6),kaempferol(7),naringenin(8),pyrogallic acid(9),pinosylvin(10),methyl propionate(11),caffeic acid(12),saccharinol(13),ferulic acid(14),trans-p-hydroxycinnamic acid(15),cinnamic acid(16),vanillic acid(17),vanillin(18),4-hydroxyacetophenone(19),4-hydroxybenzaldehyde(20),apigenin(21),(-)-isolariciresinol(22),(-)-secoisolariciresinol(23)and meso-2,3-di(3′,4′-methylenedioxybenzyl)butane-1,4-diol(24).The IC50 values of compounds 3,5,7,8,19,and 20 ranged from(0.246 5±0.028 3)to(1.278 2±0.021 3)mmol/L.CONCLUSION Compounds 1-9、11、15、17-21、24 are isolated from this plant for the first time,and 1,6,9,17-19,24 are first isolated from genus Balanophora.Compounds 3、5、7、8、19 and 20 have tyrosinase inhibitory activity.

Objective:To characterize the epidemiology, antimicrobial susceptibility, and molecular mechanisms of carbapenem-resistant Enterobacterales (CRE) carrying multiple carbapenemase genes in China, and to provide evidence for infection control and antibiotic stewardship.Methods:From 2016 to 2023, 115 CRE isolates harboring at least two carbapenemase genes were collected from 41 hospitals in 18 provinces across China. Species identification, antimicrobial susceptibility testing, and whole-genome sequencing were performed. Multilocus sequence typing (MLST) and capsular typing were conducted using Kleborate, plasmid replicon types were identified with PlasmidFinder, and a core genome phylogenetic tree was constructed.Results:The majority of isolates belonged to Klebsiella spp. (80.0%, 92/115), followed by E. cloacae (8.7%, 10/115) and E. coli (6.1%, 7/115). The isolates were mainly from Hebei, Beijing, Shandong, and Hunan (60.9%, 70/115), and sputum was the predominant specimen (43.5%, 50/115). The most common genotype was bla KPC+bla NDM (73.0%, 84/115), primarily in Klebsiella spp. (79.8%, 67/84), followed by bla NDM+bla IMP (15.7%, 18/115). The prevalent plasmid replicon types were IncFII (77.5%, 86/111), IncFIB (68.5%, 76/111), IncR (51.4%, 57/111), and IncX3 (20.7%, 23/111). Notably, 88.6% (31/35) of ST11-KL64 K. pneumoniae strains co-harbored IncFII, IncFIB, and IncR plasmids simultaneously. Between 2016 and 2022, the dominant subtype among Klebsiella spp. isolates was bla KPC-2+bla NDM-1 (56.2%, 36/64). In 2023, the bla KPC-2+bla NDM-13 subtype (29.5%, 19/64) emerged and exhibited clonal transmission (single nucleotide polymorphism 2?74 bp) in Hebei, Beijing, and Jilin. Susceptibility testing showed widespread resistance to β-lactams (90.2%-100%). Aztreonam-avibactam, tigecycline, and colistin retained high activity, with susceptibility rates of 90.16%-98.36%. Conclusions:In China, the majority of clinical Enterobacteriaceae strains that harbor multiple carbapenemases are Klebsiella spp. co-producing KPC and NDM enzymes. Dissemination is driven by both clonal expansion of ST11-KL64 and horizontal transfer of IncFII, IncFIB, and IncR plasmids. The recent emergence and regional clonal spread of the bla KPC-2+bla NDM-13 genotype underscore the urgent need for strengthened surveillance and containment measures.

Objective To explore the correlation between thyroid autoimmunity(TAI)and gestational diabetes mellitus(GDM)in Chinese euthyroid women.Methods A total of 508 euthyroid women were enrolled in the cross-sectional study,who performed their entire clinical/biological workup and oral glucose tolerance test(OGTT)from the department of Gynecology and Endocrinology of the Beijing Obstetrics and Gynecology Hospital,Capital Medical University from June 2023 to June 2024.At median 8(6-10)weeks of gestation,thyroid-stimulating hormone(TSH),free thyroxine(fT4),and thyroid peroxidase antibodies(TPOAb)were measured,baseline characteristics were recorded,and an OGTT was performed between 24 and 28 weeks of pregnancy.According to the OGTT results,they were divided into GDM group(n=169)and non GDM group(n=339).Thyroid parameters,the demographic and obstetric parameters,and the prevalence of TAI were compared with two groups.The factors associated with GDM were analyzed with multivariate Logistic regression analysis.Results The age,body mass index(BMI),and proportion of obese women before pregnancy in the GDM group were all significantly higher than those in the non-GDM group,with statistically significant differences(P<0.001).The proportion of pregnant women over 30 years old in the GDM group was significantly higher than that in the non-GDM group(59.17%vs 6.79%,χ2=168.667,P<0.001).The proportion of obese mothers(BMI≥28 kg/m2)before pregnancy in the GDM group was 24.26%,which was significantly higher than that in the non-GDM group(8.26%)(χ2=24.599,P<0.001).The incidence of TAI in the GDM group was 54.44%,while it was 15.93%in the non-GDM group.The difference between the two groups was statistically significant(χ2=81.659,P<0.001).The results of Logistic regression analysis showed that maternal age over 30 years and pre-pregnancy obesity increased the risk of GDM occurrence in TAI women by 6.08 times(OR=6.08,95%CI 3.61-10.25,P<.001).Conclusion Among early pregnancy women with normal thyroid function,as age increases during follow-up(especially over 30 years old),pre-pregnancy BMI increases(especially in obese individuals),and those with pre-pregnancy TAI,the risk of developing GDM during pregnancy significantly increases.It is necessary to explore preventive strategies for GDM in euthyroid TAI women,with a view to improving adverse pregnancy outcomes.