ObjectiveTo investigate the correlation between neutrophil-to-lymphocyte ratio （NLR）， platelet-to-lymphocyte ratio （PLR）， systemic immune-inflammation index （SII） and the severity of intrauterine adhesions （IUA）. MethodsThe retrospective study included 380 patients who underwent transcervical resection of adhesions （TCRA） from December 2019 to March 2025. Based on the American Fertility Society （AFS） classification， patients were divided into mild （n=61）， moderate （n=225）， and severe （n=94） groups. NLR， PLR， and SII were calculated from preoperative blood tests. Statistical analyses included Kruskal-Wallis test and ordinal Logistic regression. ResultsNLR， PLR， and SII were significantly higher in the severe IUA group compared to the mild group （P<0.05）， with SII showing the strongest predictive ability （OR=1.004， P=0.001）. The number of intrauterine procedures was an independent risk factor （OR=1.27/level， P=0.016）. The predictive model ［Logit（P）=-0.676+0.241×operation times+0.004×SII］ effectively identified severe IUA cases. ConclusionInflammatory markers （particularly SII） are correlated with IUA severity and may serve as non-invasive tools for clinical assessment.

Objective To investigate the prevalence of work-related musculoskeletal disorders (WMSDs) in passenger drivers and its influencing factors. Methods A total of 951 passenger drivers in Guangdong Province were selected as the research subjects using the judgmental sampling method. A Musculoskeletal Injury Questionnaire was employed to assess the prevalence of WMSDs in the past year. Results The prevalence of WMSDs in passenger drivers was 41.11%. The result of multivariable logistic regression analysis showed that married drivers had a higher risk of WMSDs than single drivers (P<0.05). The lower the frequency of physical exercise, the longer the driving time per week, the longer the continuous driving time, the more restricted the driving working space, the poorer the foot comfort during driving, and the more affected the normal meal, the higher the risk of WMSDs (all P<0.05). The risk of WMSDs in drivers with sleep time ≤ 8.0 h/d was higher than that in drivers with sleep time > 8.0 h/d (P<0.01), and the risk of WMSDs in drivers with the same posture for a long time on the shoulder was higher than that in drivers without this poor working posture (P<0.01). Conclusion WMSDs were prevalent among passenger drivers, which was associated with demographic and adverse ergonomic factors. Intervention on lifestyle and adverse ergonomic factors could further reduce the risk of WMSDs of passenger drivers.

Objective To investigate the role and underlying mechanism of C1q-like protein 4 (C1ql4) in regulating the characteristics of breast cancer stem cells. Methods qRT-PCR was used to detect the expression of C1ql4 in breast cancer and normal breast epithelial cell lines, as well as to verify the transfection efficiency of C1ql4. Western blot analysis was employed to examine the phosphorylation levels of AKT, IKK, and IκB in different groups. An AKT activator was added to MDA-MB-231 cells with C1ql4 knockdown, whereas inhibitors targeting AKT, IKK, IκB, and NF-κB nuclear translocation were separately introduced to C1ql4-overexpressing MCF-7 cells. The nuclear translocation of NF-κB, expression levels of the target genes TNF-α and IL-1β, formation ability of tumorspheres, and proportion of CD44⁺/CD24^−/low stem-like subgroups were analyzed. Results C1ql4 expression in breast cancer cell lines was significantly upregulated compared with that in normal breast epithelial cells. Western blot analysis showed that p-AKT/AKT, p-IKK/IKK, and p-IκB/IκB ratios markedly reduced in C1ql4-knockdown MDA-MB-231 cells (all P<0.05) but significantly increased in C1ql4-overexpressing MCF-7 cells (all P<0.05). Rescue experiments demonstrated that the addition of an AKT activator to C1ql4-knockdown MDA-MB-231 cells resulted in the enhanced nuclear translocation of NF-κB, the increased nuclear/cytoplasmic NF-κB ratios, the elevated TNF-α and IL-1β expression levels, and significant recovery of tumorsphere formation ability and the proportion of CD44⁺/CD24^−/low stem-like subpopulations (all P<0.05). Conversely, in C1ql4-overexpressing MCF-7 cells, treatment with AKT, IKK, IκB, or NF-κB nuclear translocation inhibitors led to a reduction in NF-κB nuclear translocation, decreased nuclear/cytoplasmic NF-κB ratios, and declines in TNF-α and IL-1β expression levels, tumorsphere formation ability, and the CD44⁺/CD24^−/low subpopulation (all P<0.05). Conclusion C1ql4 promotes the translocation of NF-κB from the cytoplasm to the nucleus through the PI3K/AKT/NF-κB signaling pathway and enhances the expression of stemness in breast cancer cells.

Aim To explore the protective effects and underlying molecular mechanisms of periplogenin(Ppg)in preventing acetaminophen(APAP)-induced drug-induced liver injury(DILI).Methods An APAP-induced liver injury model was established in vi-vo and in vitro.Liver/spleen indices were recorded,and serum aspartate aminotransferase(AST)and ala-nine aminotransferase(ALT)levels were measured.The pathological changes in liver tissue were observed using hematoxylin-eosin(HE)staining.The influence of Ppg on inflammatory cytokines(IL-6,TNF-α,IL-1 β)and key proteins within the associated signaling pathways was examined using enzyme-linked immu-nosorbent assay(ELISA),quantitative polymerase chain reaction(qPCR),and Western blot.Additional-ly,glutathione(GSH),malondialdehyde(MDA),and superoxide dismutase(SOD)activity levels were meas-ured.The expression of markers related to the NF-κB signaling pathway was assessed using qPCR,Western blot,and immunofluorescence.Results In vivo exper-iments showed that Ppg improved the liver and spleen index of mice with drug-induced liver injury,and the levels of AST and ALT in the serum decreased signifi-cantly,reducing the pathological damage of liver tis-sue.In vitro experiments showed that Ppg significantly inhibited the expression of IL-6,TNF-α and IL-1 β,and decreased the levels of GSH and MDA and in-creased SOD activity in AML-12 cells.Additionally,the inhibition of the NF-κB signaling pathway using pyrrolidinedithiocarbamate ammonium(PDTC),an NF-κB signaling pathway inhibitor reduced inflammato-ry cytokine expression and significantly decreased p65 nuclear translocation,showing results comparable to those observed in the high-dose Ppg group.Conclu-sions Ppg alleviates APAP-induced liver injury,po-tentially by inhibiting the NF-κB signaling pathway in hepatocytes,thereby reducing the inflammatory re-sponse and protecting liver from APAP-induced dam-age.

This study was aimed at understanding the resistance status of dairy cow-derived Streptococcus strains in China,and providing scientific guidance for the rational use of antimicrobials and the development of new antimicrobials.Meta-analysis was used to explore the resistance of Streptococcus strains to 20 antimicrobials between 2000 and 2023.A total of 67 articles de-scribing 3 154 strains were included after a literature search,and a meta-analysis was conducted on the overall collection area according to time subgroups for 20 antimicrobials.Streptococci of dairy origin in China showed varying resistance rates(≥30％),as follows:penicillin(60％,95％CI=0.48-0.72),streptomycin(57％,95％CI=0.46-0.68),cotrimoxazole(56％,95％CI=0.28-0.82),lincomycin(51％,95％CI=0.26-0.76),tetracycline(49％,95％CI=0.40-0.59),doxycyc-line(42％,95％CI=0.24-0.60),clindamycin(41％,95％CI=0.28-0.54),ampicillin(39％,95％CI=0.27-0.52),e-rythromycin(37％,95％CI=0.28-0.45),kanamycin(36％,95％CI=0.20-0.54),and amoxicillin(30％,95％CI=0.10-0.53).On the basis of findings in the collection area,the resistance rates of dairy cow-derived Streptococcus to antimicrobials in Northeast China and Southwest China was generally high.The resistance rates of Streptococcus from dairy cattle to antimi-crobial drugs such as tetracycline,doxycycline,and lincomycin increased significantly over time.However,the resistance rates to antimicrobial drugs such as streptomycin,gentamicin,and enrofloxacin showed a significant decreasing trend.Dairy cow-de-rived Streptococcus had high resistance to some antimicrobials,and the resistance varied by region,because of differences in breeding and management.Monitoring of antimicrobial resistance rates,enhancing research on resistance mechanisms,and reg-ulating the use of antimicrobials remain necessary.

Objective This study aimed to explore the correlation between abnormal hand features and coronary atherosclerotic heart disease(CHD)to provide clinical data support for digitalized traditional Chinese medicine(TCM)hand diagnosis.Methods A palm key point prediction algorithm was used to automatically capture and collect detailed features of the palm and nails through image analysis and data mining using the hand diagnosis information collection technology based on the NVIDIA Jetson platform and Qt framework.A total of 438 cardiac patients who underwent coronary artery computed tomography angiography(CACTA)in the Department of Cardiology,Dongzhimen Hospital,Beijing University of Chinese Medicine,from December 2023 to April 2024 were included and divided into CHD(148 cases)and non-CHD groups(290 cases)based on the CACTA results.The hand features of the two groups were compared,and abnormal hand features associated with CHD were screened using random forest analysis as well as univariate and multivariate logistic regression analyses.Results Based on the results of univariate logistic regression and random forest analyses,a set of hand-related features associated with CHD were identified and subsequently included in the multivariate logistic regression analysis.These features included the morphology of the thenar eminence,the wrinkles of the thenar eminence,nail shape,nail texture,and the length of the blood vessel in the middle finger.Multivariate logistic regression analysis revealed that hypertrophic thenar eminence[odds ratio(OR):3.049,95%confidence interval(CI):1.430-6.503,P=0.004],presence of wrinkles on the thenar eminence(OR:2.206,95%CI:1.119-4.348,P=0.022),presence of gray-black vertical stripes on the nails(OR:1.981,95%CI:1.173-3.347,P=0.011),uneven nail surface(OR:3.130,95%CI:1.822-5.378,P<0.001),and inward-bending nail surface(OR:5.727,95%CI:1.812-18.102,P=0.003)were positively associated with CHD.In contrast,the blood vessel in the middle finger longer than 1/3 of the phalanx was negatively associated with CHD(OR:0.405,95%CI:0.234-0.702,P=0.001).Conclusion Certain hand features are significantly associated with CHD,providing the valuable clinical data to support for the digitalization of TCM hand diagnosis.

Objective To explore the therapeutic effect of precise disconnection of pargastric varices guided by endoscopic ultrasound in the treatment of esophagogastric variceal bleeding.Method A retrospective analysis was conducted on 20 patients with cirrhosis esophagogastric variceal bleeding treated with endoscopic ultrasound-guided precise disconnection of pargastric varices from January 1,2024 to December 31,2024.The efficacy was analyzed.Result All 20 patients successfully completed the precise disconnection of pargastric varices under the guidance of endoscopic ultrasound.The injection of tissue gel combined with the placement of spring coils(14 cases)and the injection of tissue gel alone(4 cases)successfully blocked the pargastric varices.All patients did not experience perforation,esophageal and cardia stenosis,massive bleeding,septicemia,or ectopic embolization.One patient who received tissue gel alone had slight bleeding from the pargastric varices after surgery and improved after 3 days of treatment to reduce portal vein pressure.Another one patient who received tissue gel alone had a low-grade fever and normal body temperature after 3 days of anti-infection treatment.Conclusion Precise disconnection of pargastric varices under the guidance of endoscopic ultrasound has a good therapeutic effect on esophagogastric variceal bleeding,with fewer complications such as ectopic embolization,massive bleeding,infection,and perforation.However,close follow-up observation is still needed to address the issue of pargastric varices.

Objective To fabricate nanosilicate functionalized polycaprolactone(PCL/LAP)electrospun membrane and evaluate its role in bone marrow mesenchymal stem cells(BMSCs)-induced bone repairing.Methods The PCL/LAP electrospun membranes were fabricated via electrospinning technology and co-cultured with rat BMSCs.The cytocompatibility of the membranes was evaluated through cytoskeleton staining,live/dead cell staining and CCK-8 assay.The migration capacity of BMSCs was assessed using scratch assay,Transwell migration experiments and expression of migration-related genes(Pdgf and Tgfβ)was evaluated by qRT-PCR.The os-teogenic differentiation and pro-angiogenesis potential were determined by alkaline phosphatase(ALP)staining,alizarin red staining,expression levels of osteogenesis-related genes(Alp,Col1a1,Runx2,Bglap and Bmp2)and angiogenesis-related genes(Angpt1,Fgf2 and Vegfa)along with RUNX2 protein expression.PCL and PCL/LAP electrospun membranes conditioned medium was subsequently used to stimulate vascular endothelial cells(EAhy926).The expression of angiogenesis-associated genes(KDR,ENOS and HIF1A)was quantified by qRT-PCR.Results BMSCs adhered well to the surface of the PCL/LAP membranes,with no significant impact on cell viability(P＞0.05).PCL/LAP membranes not only promoted the proliferation(P＜0.05),migration(P＜0.05),but also enhanced ALP activity and mineralized nodule formation(P＜0.05),increased osteogenic differentiation gene and protein expression(P＜0.05)of BMSCs.Moreover,PCL/LAP promoted the expression of angiogenic genes of BMSCs(P＜0.05),to indirectly regulate angiogenesis-related gene expression in vascular endothelial cells(P＜0.05).Conclusion PCL/LAP electrospun membranes exhibit excellent biocompatibility and can promote proliferation,migration,osteogenic differentiation and BMSC-mediated angiogenic differentiation,showing great potential for bone defect repairing as barrier membrane.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

OBJECTIVE To optimize the molding process of Xiebai Granules(XG)using the Box-Behnken design-response surface method combined with the BP neural network method,and to evaluate the consistency of particle quality between different bat-ches by establishing physical fingerprint.METHODS Dry paste powder was used as the main drug,dry granulation was adopted,and the forming rate,dissolution rate,moisture absorption rate and angle of repose of the granules were used as evaluation indexes,the ex-cipients dextrin,maltodextrin and lactose of the particles,were screened by single factor test combined with simplex-lattice design and entropy weight method,and the optimal excipient ratio was selected.The entropy weight method combined with the Box-Behnken de-sign-response surface method and the BP neural network algorithm were used to optimize the process parameters,and the process veri-fication was carried out.The physical fingerprint was used to comprehensively characterize the bulk density(Da),hygroscopicity(H),moisture(HR),tap density(Dc),angle of repose(α),Hausner ratio(IH),relative uniformity index(Iθ),Carr index(IC),and in-terparticle pore number(Ie),and the consistency of particle quality in different batches was evaluated.RESULTS The optimal ratio of excipients was dextrin 15%,maltodextrin 48%,and lactose 37%.The optimal process parameters were conveying speed 95 r·min-1,pressure wheel speed 4 r·min-1 and hydraulic pressure 7 MPa.The similarity of the physical fingerprints of the five bat-ches of XG was greater than 0.98.CONCLUSION The optimized molding process of XG is stable and feasible,and the quality of different batches of XG is stable,which can provide a reference for the development and industrial scale-up production of XG.