Background Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern, particularly among workers exposed to adverse ergonomic conditions. Manganese production involves heavy physical demands, yet research on WMSDs among manganese workers remains limited. Objective To investigate the prevalence and influencing factors of WMSDs among manganese workers in a manganese enterprise in Guangxi. Methods A cross-sectional survey was conducted from May to June 2024 on workers at a manganese factory in Guangxi. The Chinese Musculoskeletal Disorders Questionnaire was used to collect information on demographic characteristics, distribution of musculoskeletal symptoms, and work-related exposures. χ² test was applied to compare differences in positive WMSDs rates across groups, and logistic regression analysis was performed to identify associated factors. Results A total of 1476 workers were enrolled in the study after pre-determined inclusion and exclusion criteria. The overall prevalence of WMSDs was 34.15%. The most commonly affected body regions were the lower back (17.28%), neck (16.67%), and shoulders (13.82%). The results of logistic regression analysis indicated that female, older age, and education level of college or above were associated with a higher risk of WMSDs (P<0.05). Awkward working postures were significantly associated with WMSDs in corresponding body regions; in particular, awkward postures of the neck, upper limbs, trunk, and lower limbs were related to an increased risk of WMSDs in multiple body sites (P<0.05). In addition, poor lighting conditions, high workplace temperature, frequent or sustained arm support during work, and high job demands were associated with an increased risk of overall or site-specific WMSDs (P<0.05). Conclusion The high prevalence of WMSDs among manganese workers is closely associated with demographic characteristics, working postures, and work environment and organizational factors. Targeted ergonomic interventions focusing on high-risk body regions and key ergonomic exposures are warranted to reduce the risk of WMSDs among manganese workers.

ObjectiveTo investigate the expression changes of the Endophilin A1 （EPA1）-reactive oxygen species （ROS）-NLR family pyrin domain containing 1 （NLRP1） signaling pathway in chronic unpredictable mild stress （CUMS）-induced depression model mice. Methods50 C57BL/6 mice were randomly divided into control group and CUMS model group（n=25）. The model mice received 42 days of CUMS stress exposure， after which behavioral changes were assessed through monitoring body weight， sucrose preference test， forced swim test， tail suspension test， open field test， and elevated plus-maze test. Hematoxylin-Eosin and Nissl staining were used to observe neuronal damage in hippocampal CA1 and CA3 regions. Calcium ion （Ca²⁺） assay kit was used to detect Ca²⁺ levels in the hippocampus. Immunofluorescence was used to detect colocalization of EPA1 and NLRP1 as well as ROS changes in the hippocampus. Transmission electron microscopy was used to observe mitochondrial structure in hippocampal neurons. The expression levels of calcium-activated neutral protease 1 （Calpain-1）， nicotinamide adenine dinucleotide phosphate oxidase 2 （NOX2）， NLRP1 inflammasome， downstream inflammatory proteins， and synapse-associated proteins in the hippocampus of mice was detected by using Western blot. ResultsCompared with the control group， mice in the CUMS model group exhibited depressive-like behavior and hippocampal neuronal damage. The levels of NLRP1 and EPA1 significantly increased in the hippocampus， and both were co-expressed in the cytoplasm and membrane of hippocampal neurons in the CUMS group mice（P<0.01）. Ca²⁺ concentration was elevated（P<0.01）， and the protein levels of Calpain 1 and NOX2 were upregulated（P<0.01）. The average fluorescence intensity of ROS significantly increased， accompanied by structural damage to neuronal mitochondria（P<0.01）. The levels of NLRP1 and its downstream inflammatory proteins significantly increased （P<0.01）， while the expression levels of synapse-associated proteins significantly decreased （P<0.01）. ConclusionEPA1 exhibits abnormal expression changes in CUMS-induced depression model mice， which may be closely associated with ROS generation， NLRP1 inflammasome activation， and the regulation of synaptic protein expression.

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

ObjectiveTo understand the current status of Cronobacter sakazakii (Cronobacter spp.) infection and its molecular epidemiological characteristics among patients with diarrhea, so as to provide evidence for the prevention and control of diarrhea disease caused by infection with Cronobacter spp. in Changping District, Beijing. Methods760 stool samples were collected from the diarrhea patients in a sentinel hospital in 2019, for the detection of Cronobacter spp., Salmonella, diarrheogenic Escherichia coli (DEC), and Vibrio Parahaemolyticus. Meanwhile, drug sensitivity experiment and pulsed-field gel electrophoresis (PFGE) typing analysis were conducted on the Cronobacter spp. strains isolated. ResultsA total of 20 Cronobacter spp. strains (2.63%) were isolated, with a lower detection rate than that of Salmonella and Vibrio Parahaemolyticus (χ²=9.052, P=0.011). However, there were no statistically significant differences between the detection rates in Cronobacter spp. and DEC (χ²=1.076, P=0.300). Seasonal characterization analysis showed that Cronobacter spp. could be detected in spring (1.00%), summer (4.17%), autumn (3.00%) and winter (1.67%), and the differences were statistically significant (χ²=662.700, P<0.001). The PFGE analysis showed that 20 PFGE banding patterns were found in 20 Cronobacter spp. strains, with a similarity coefficient ranging from 56.30% to 90.09% and a diverse PFGE banding pattern. The drug sensitivity experiment results showed that 18 (90.00%) strains were resistant to cefazolin, and2 (10.00%) strains were intermediate. While, as for cefoxitin, 2 (10.00%) strains were resistant to it, and 5 (25.00%) strains were intermediate. All the 20 strains were 100.00% sensitive to the other 11 antibiotics. ConclusionIn the study, Cronobacter spp. is detected in all seasons through the year, with a high resistance rate to cefazolin, no multi-drug resistant bacteria appeared, and diverse PFGE banding patterns.

To summarize the clinical experience of Professor WANG Jie in treating palpitation using the method of tonifying the kidneys and invigorating blood. It is believed that kidney yang deficiency and heart vessel stasis are the key pathogenesis of palpitation， and it is advocated to treat palpitation by tonifying the kidney and invigorating the blood. Meanwhile，the methods of draining water， dissolving phlegm， and fortifying the spleen to supplement the blood should be applied. For palpitation with kidney yang deficiency and heart vessel stasis with upward water， the treatment could use self-prescribed Bushen Huoxue Lishui Formula （补肾活血利水方）； for palpitation with phlegm obstruction in blood vessel， the treatment could use self-prescribed Bushen Huoxue Huatan Formula （补肾活血化痰方）； for palpitation with spleen yang deficiency， the treatment could use self-prescribed Bushen Huoxue Jianpi Formula （补肾活血健脾方）.

This study aims to understand the biological characteristics of Streptococcus dysgalacti-ae of yak origin.Bacterial isolation and identification,drug susceptibility test,virulence gene test and pathogenicity test were carried out on milk samples of yaks from Naqu City to evaluate the bi-ological characteristics of the isolated strains.Meanwhile,molecular biological information such as virulence factors and drug resistance genes were analyzed by whole genome sequencing,and viru-lence genes were verified by PCR.The results showed that a strain of Streptococcus dysgalactiae was isolated from the milk of yak,and its colony morphology was pinpoint size,smooth edge and milky white.This strain is sensitive to many antibiotics(penicillin G,cephalosporin,ciprofloxacin,tetracycline,erythromycin,etc.).Virulence gene test results showed that the strain carries six key virulence genes(cyl,eno,scpB,bca,bac and napr),which may be closely related to its pathoge-nicity.In the pathogenicity test,the mice were listless and less active after infection,but no death occurred during the observation period.The pathological changes of spleen,kidney,liver and lung tissue were found,suggesting that the strain had certain pathogenic potential but not high lethali-ty.Whole genome sequencing data showed that the gene length of this strain was 4 079 280 bp,the GC content was 39.41％,3 964 coding genes were predicted,604 of which were annotated as viru-lence factors,and another 28 gene mutations may enhance its pathogenic ability.Through annota-tion of CARD database,two Pat A resistance genes and two lmrp resistance genes were found,re-vealing their potential resistance mechanism.Through whole genome sequencing technology and bioinformatics analysis method,this study revealed the genomic characteristics,drug resistance and pathogenicity mechanism of Streptococcus dysgalactiae of yak origin.The findings provide impor-tant scientific evidence for further exploration of the pathogenicity,drug resistance mechanisms,and molecular evolution of yak-derived Streptococcus agalactiae.

Mitochondria are organelles in eukaryotic cells that play a crucial role in cellular energy me-tabolism,oxidative stress,heat production,and signal transduction.Mitochondrial transplantation(MT)is currently one of the most advanced techniques for treating mitochondrial dysfunction and anti-aging re-search.This study aimed to explore the feasibility and effectiveness of xenogeneic MT by transplanting mitochondria from yak(Bos grunniens),domestic cattle(Bos taurus),and horse(Equus caballus)into mice(Mus musculus).The results demonstrated that mitochondria from yak,domestic cattle,and horse could be successfully transplanted into mice and maintained in various tissues and organs of the mice for at least 14 days,as confirmed by confocal imaging,digital PCR,and DNA sequencing.MT mice exhibi-ted positive biological effects,including increased ATP content and mitochondrial DNA copy number(P＜0.05),with the maximum effect observed on day 7,which was sustained until day 14.Reactive oxygen species(ROS)levels in MT mice significantly increased at 2 hours post-injection(P＜0.05),then grad-ually decreased towards baseline levels by day 7 and day 14(P＞0.05).These findings support the effec-tiveness of xenogeneic MT and suggest that the effects can be maintained for up to 14 days.This study provides scientific evidence for future clinical applications.

This study aims to establish BHK-21 stable cell lines expressing APN from four species(human,pig,dog,and cat),the APN fragments were amplified from pEGFP-C1-APN plasmids of the four species stored in the laboratory to generate the recombinant plasmids pcDNA4.0-APN.Af-ter the recombinant plasmids were transfected into BHK-21 cells,the stable BHK-21 cell lines ex-pressing the APNs were selected by two rounds of limited dilution.The constructed BHK-21 cell lines were identified by indirect immunofluorescence assay(IFA),and their susceptibility to PD-CoV and TGEV was tested for these four cell lines.Virus infection experiments revealed that PD-CoV infected cells expressing human,pig,and dog APNs,while it did not infect cells expressing cat APN.Simultaneously,TGEV infected cells expressing pig,dog,and cat APNs,but did not infect cells expressing human APN.The results suggest that the risk of cross-species infection for different coronaviruses and the established cell line can be used effectively to evaluate the virus in-fection.The findings also revealed that PDCoV has the potential risk of cross-species infection of human and dog,and TGEV has the potential risk of cross-species infection of dog and cat.These results provide a basis for the prevention and control strategy of coronaviruses.

Objective To investigate the expressions of cyclin B2(CCNB2)and cyclin E1(Cyclin E1)in hepatocellular carcinoma(HCC)and their significance for the prognosis of HCC.Methods Sixty HCC patients were admitted and treated from October 2013 to October 2016.The expressions of CCNB2 and Cyclin E1 in 60 HCC tissues and adjacent normal tissues were detected by immunohistochemistry,and the relationship between the two and the clinicopathological characteristics of HCC patients was analyzed;Spearman method was performed to analyze the correlation of CCNB2 and Cyclin E1 expression;Kaplan-Meier was performed to analyze the relationship between CCNB2,Cyclin E1 expression and clinical prognosis;and univariate and multivariate Cox regression were performed to analyze the influencing factors of clinical prognosis of HCC patients.Results The positive expression rates of CCNB2 and Cyclin E1 in HCC(61.67％,56.67％)were significantly higher than those in adjacent normal tissues(20.00％,13.33％,P＜0.05);the positive expressions of CCNB2 and Cyclin E1 were positively correlated with serum AFP level,liver cirrhosis status,tumor thrombus and recurrence(P＜0.05).The expressions of CCNB2 and Cyclin E1 in HCC tissues were positively correlated(r=0.487,P=0.000).The positive expressions of CCNB2 and Cyclin E1 in HCC tissues predicted a lower survival time(x2=7.104,7.140,P=0.008,0.008).In addition,the positive expressions of CCNB2 and Cyclin E1 were independent factors affecting the prognosis of HCC patients(P＜0.05).Conclusion CCNB2 and Cyclin E1 are highly expressed in HCC and are associated with serum AFP level,cirrhosis status,tumor thrombus and recurrence,and can be used as independent prognostic markers.

Objective:To evaluate the predictive performance of machine learning methods for predicting the risk of death in traumatic hemorrhage, and address the low prediction accuracy of traditional trauma scores, provide a reference for developing a more robust prediction method for severe trauma patients.Methods:Clinical data of severe trauma patients from the National Trauma Medical Center between April 1, 2023, and March 31, 2024 were collected. ElasticNet, Recursive Feature Elimination, and Mutual Information-based feature selection methods were used to screen variables and compared with traditional hypothesis testing methods. Built the prediction models for mortality risk in traumatic hemorrhage using Logistic Regression, ElasticNet, and Support Vector Machine (SVM) and compared the predictive performance.Results:The study included 5,601 trauma patients, the results of the variable screening and importance ranking were consistent with three feature selection methods. The classification accuracy and AUC values for the three models were as follows: Overall accuracy was 83.2%, survival accuracy was 84.0%, death accuracy was 76.3%, and an AUC was 0.86 in logistic regression; Overall accuracy was 78.9%, survival accuracy was 78.5%, death accuracy was 81.7%, and an AUC was 0.88 in ElasticNet; Overall accuracy was 84.7%, survival accuracy was 86.1%, death accuracy was 72.4%, and an AUC was 0.86 in SVM. The prediction performance of three models is quite little.Conclusion:Machine learning methods can effectively improve the prediction of death risk for traumatic hemorrhage,and has wide applications.