OBJECTIVE To systematically evaluate the efficacy and safety of tislelizumab in the treatment of advanced non- small cell lung cancer （NSCLC）. METHODS Computerized searches were conducted in PubMed， Embase， the Cochrane Library， CNKI， Wanfang and other Chinese and English databases to collect randomized controlled trials （RCTs） on tislelizumab for advanced NSCLC. The search period was from the establishment of the databases to December 2024. After strictly screening the literature， extracting data and conducting quality evaluations in accordance with the inclusion and exclusion criteria， a meta-analysis was performed using RevMan 5.3 and Stata 16.0 software. RESULTS A total of 18 RCTs involving 2 337 patients were included， with 1 283 in the experimental group and 1 054 in the control group. The meta-analysis results showed that the objective response rate [RR＝1.61， 95%CI （1.48， 1.75）， P＜0.000 01]， disease control rate [RR＝1.21， 95%CI （1.13， 1.29）， P＜0.000 01]， progression free survival [HR＝0.55， 95%CI （0.45， 0.66）， P＜0.000 01]， and overall survival [HR＝0.78， 95%CI（0.62， 0.97）， P＝0.03] were significantly better in the experimental group than in the control group. There was no statistically significant difference in the incidence of adverse reactions between the two groups [RR＝1.00， 95%CI （0.73， 1.37）， P＝1.00]； among the common adverse reactions， only the incidence of liver function impairment was significantly higher in the experimental group than in the control group [RR＝1.30， 95%CI （1.10， 1.54）， P＜0.01]. CONCLUSIONS Tislelizumab in combination with chemotherapy or targeted drugs significantly improves the efficacy in patients with advanced NSCLC without increasing the risk of adverse reactions overall. However， liver function should be closely monitored during treatment.

To review the randomized controlled trials (RCTs) at home and abroad on digital intelligence (DI)-driven rehabilitation in patients of neuromuscular disease, compare the effects of DI-driven rehabilitation with traditional rehabilitation, summarize the special needs and challenges faced by patients in rehabilitation of rare neuromuscular diseases, and provide evidence for the development and quality improvement of rehabilitation for rare neuromuscular diseases.

To provide references to and give suggestions to the development and optimiza-tion of Digital Intelligence (DI) technology in management of non-hospitalized patients by systematical review the application of digital technology in non-hospital settings.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation and joint damage, accompanied by the accumulation of plasma cells, which contributes to its pathogenesis. Understanding the genetic alterations occurring during plasma cell differentiation in RA can deepen our comprehension of its pathogenesis and guide the development of targeted therapeutic interventions. Here, our study elucidates the intricate molecular mechanisms underlying plasma cell differentiation by demonstrating that PRDX1 interacts with DOK3 and modulates its degradation by the autophagy-lysosome pathway. This interaction results in the inhibition of plasma cell differentiation, thereby alleviating the progression of collagen-induced arthritis. Additionally, our investigation identifies Salvianolic acid B (SAB) as a potent small molecular glue-like compound that enhances the interaction between PRDX1 and DOK3, consequently impeding the progression of collagen-induced arthritis by inhibiting plasma cell differentiation. Collectively, these findings underscore the therapeutic potential of developing chemical stabilizers for the PRDX1-DOK3 complex in suppressing plasma cell differentiation for RA treatment and establish a theoretical basis for targeting PRDX1-protein interactions as specific therapeutic targets in various diseases.

Trophoblast cells serve as the foundation for placental development. We analyzed published multiomics sequencing data and found that trophoblast cells highly expressed RRS1 compared to primitive endoderm and epiblast. We used HTR-8/SVneo cells for further investigation, and Western blot and immunofluorescence staining confirmed that HTR-8/SVneo cells highly expressed RRS1. RRS1 was successfully knocked down in HTR-8/SVneo cells using siRNA. Using IncuCyte S3 live-cell analysis system based on continuous live-cell imaging and real-time data, we observed that proliferation, migration, and invasion abilities were all significantly decreased in RRS1-knockdown cells. RNA-seq revealed that knockdown of RRS1 affected the gene transcription, and upregulated pathways in extracellular matrix organization, DNA damage response, and intrinsic apoptotic signaling, downregulated pathways in embryo implantation, trophoblast cell migration, and wound healing. Differentially expressed genes were enriched in diseases related to placental development. Consistent with these findings, human chorionic villus samples collected from spontaneous abortion cases exhibited significantly reduced RRS1 expression compared to normal controls. Our results highlight the functional importance of RRS1 in human trophoblasts and suggest that its deficiency contributes to early pregnancy loss.
Humans ; Trophoblasts/physiology* ; Cell Movement/genetics* ; Cell Proliferation/genetics* ; Female ; Pregnancy ; Abortion, Spontaneous/metabolism* ; Cell Line ; Placentation/genetics*

Objective:To analyze the factors influencing the lung function of coal miners, identify the optimal combination of indicators for evaluating lung function, develop a risk assessment model using machine learning, and offer personalized risk assessment for workers.Methods:In June 2023, through cluster sampling, male underground workers who participated in occupational health examinations at a coal mine in North China from July to August 2018 were selected as the research subjects. Their health examination results and occupational environmental data were collected. A total of 3, 320 coal miners were included. Randomly divide the research subjects into a training set (2324 people) and a validation set (996 people) in a ratio of 7∶3, and the balance of the two sets was tested. Perform LASSO regression analysis using R 4.2.2 software to select relevant important variables, and determine the model's input variables by combining them with relevant literature. Utilize Python 3.8 to construct logistic regression, random forest, support vector machine, and XG Boost models, assess the models' discriminative ability using metrics like accuracy, sensitivity, specificity, F1 score, ROC curve, and AUC, evaluate the models' calibration using Brier score, Log loss score, and calibration curve, and further analyze the clinical performance of the developed models through DCA decision curve analysis.Results:Among the 3 320 coal miners, 856 had abnormal lung function (25.78%). The XG Boost model was identified as the optimal model, achieving a training set accuracy of 87.39%, sensitivity of 86.60%, specificity of 87.67%, F1 score of 0.779, AUC of 0.945, Brier score of 0.071, Log loss of 0.267 and demonstrated good calibration curve consistency.Conclusion:The XG Boost model exhibits superior predictive performance compared to other models, and the model has high application value. The Shapley Additive Explanation (SHAP) method is employed for interpretation, making it a reliable basis for preventing abnormal lung function in coal miners.

Objective To provide a reference basis for the establishment of ideal animal models of leukemia,the characteristics of animal models of leukemia was summarized.Methods The themes of"leukemia"and"animal"were searched in CNKI databases.The relevant literature on animal experiments of leukemia from January 2010 to August 2024 were screened.And a database by Excel 2017 tables was established by organizing their research animal strains,modeling methods and testing indexes to analyze the characteristics of leukemia animal models.Results After comparative analysis,it was found that the animal strains in modeling were BALB/C-nude mice(40 times,29.86%)and NOD/SCID mice(32 times,23.88%),respectively.The modeling method was transplanted cells(127 times,93.38%),and the detection indexes were pathological tissues(80 times,14.84%),blood smears(75 times.13.91%),general condition(73 times,13.54%),bone marrow smear(73 times,13.54%),flow cytometry(55 times,10.20%),blood routine(50 times,9.28%).Conclusion The existing animal models of leukemia are complex and diverse.

Objective:To investigate the impact of tumor origin (ventral pancreatic origin and dorsal pancreatic origin) on prognosis in patients with pancreatic head cancer.Methods:A retrospective analysis was performed on the clinical data of 150 patients with pancreatic head cancer who received surgical treatment at the First Affiliated Hospital of the Naval Medical University from October 2014 to December 2017. Among these patients, 92 were male and 58 were female, aged (61.2±8.8) years. The 150 patients were divided into two groups based on tumor origin: the ventral pancreatic cancer group ( n=72) and the dorsal pancreatic cancer group ( n=78). A comparative analysis of clinical, pathological, and imaging charac-teristics was conducted between the two groups. Univariate and multivariable Cox proportional hazards models were used to analyze the association between pancreatic head cancer origin and overall survival (OS). Results:Patients with pancreatic head carcinoma arising from the ventral and dorsal pancreas accounted for 48%(72/150) and 52%(78/150) of the study cohort, respectively. Pancreatic head carcinoma arising from the dorsal pancreas were more likely to show pathological features of pancreatic parenchymal atrophy [73.1%(57/78) vs. 47.2%(34/72), χ2=10.49, P=0.001] and pancreatitis [44.9%(35/78) vs. 29.2%(21/72), χ2=3.95, P=0.047]. In contrast, patients with pancreatic head carcinoma arising from the ventral pancreas was more frequently associated with contact with the superior mesenteric artery [25.0%(18/72) vs. 1.3%(1/78), χ2=19.04, P<0.001], perineural invasion [100%(72/72) vs. 88.5%(69/78), χ2=8.84, P=0.003], and positive surgical margins [15.3%(11/72) vs. 2.6%(2/78), χ2=7.65, P=0.006], with all differences statistically significant. The ventral pancreatic cancer group demonstrated cumulative survival rates of 33.2% and 0 at 1-year and 2-year postoperative intervals, respectively, while the dorsal pancreatic cancer group exhibited rates of 56.7% and 24.8% at the corresponding timepoints. Comparison of Kaplan-Meier survival curves between the two groups showed a statistically significant difference ( χ2=6.00, P=0.014). Multivariable Cox proportional hazards analysis identified dorsal pancreatic origin pancreatic head cancer as an independent predictor of increased mortality risk compared to ventral origin tumors ( HR=2.75, 95% CI: 1.52-4.98, P=0.001). Conclusion:The embryonic origin of pancreatic head cancer determines its clinical, pathological, and imaging heterogeneity, and pancreatic head cancer arising from the ventral pancreas demonstrates significantly worse prognostic outcomes compared to dorsal pancreatic origin.

Objective:To investigate the occurrence of work-related musculoskeletal disorders (WMSDs) among underground coal mine workers, identify the risk factors for WMSDs, and provide a scientific evidence for the prevention and treatment of WMSDs.Methods:In March 2024, through cluster sampling, the on-the-job workers who underwent questionnaire surveys and health examinations at a certain coal mine from July to August 2018 were selected as the research subjects. Basic information of employees, ergonomics-related characteristics, and the occurrence status of WMSDs in each part were collected, and multivariate logistic regression was used for analysis.Results:The incidence rate of WMSDs in at least one site among underground coal mine workers within the past year was 62.22% (219/352). The top three sites in sequence were the lower back (44.32%, 156/352), neck (26.14%, 92/352), and knee (26.14%, 92/352). Multivariate logistic regression analysis showed that frequently exerting great force with arms or hands during work ( OR=2.223, 95% CI: 1.022-4.836), prolonged static forward bending ( OR=1.544, 95% CI: 1.305-1.972), and frequently exerting great effort to operate tools or machines ( OR=2.206, 95% CI: 1.011-4.813), absence of external support systems ( OR=1.589, 95% CI: 1.349-1.996), and repetitive full-body twisting ( OR=1.523, 95% CI: 1.298-1.916) were all risk factors for the occurrence of WMSDs in the lower back ( P<0.05). Both night shift work ( OR=1.564, 95% CI: 1.339-1.939) and frequent forward neck flexion ( OR=1.532, 95% CI: 1.312-1.907) were all risk factors for the occurrence of WMSDs in the neck ( P<0.05). Lifting heavy objects above the shoulder ( OR=1.333, 95% CI: 1.142-1.782), uncomfortable posture and inability to exert force ( OR=1.873, 95% CI: 1.104-2.712), the use of vibration tools ( OR=2.958, 95% CI: 1.255-6.972), and length of service >10 years ( OR=1.525, 95% CI: 1.105-1.967) were all risk factors for the occurrence of WMSDs in the knee ( P<0.05) . Conclusion:The incidence of WMSDs among underground coal miners is relatively high, mainly concentrated in the lower back, neck and knee, and is related to factors such as poor working postures, and work organization. Coal mining enterprises should strengthen work organization, provide appropriate working equipment, and ensure reasonable distribution of workloads.

Objective:To identify risk factors influencing the incidence of hypertension among steelworkers (Homo sapiens) and establish an effective and easily implementable hypertension prediction model.Methods:In September 2023, 2214 steelworkers (Homo sapiens) were selected as study subjects. Basic demographic information, lifestyle, and occupational exposure data were collected, along with physiological measurements such as height, weight, and blood pressure. Multivariate unconditional logistic regression analysis was employed based on relevant literature to determine influencing factors for hypertension among steelworkers (Homo sapiens). Python 3.9 software was used to construct and compare logistic regression, support vector machine (SVM), random forest, extreme gradient boosting tree (XGBoost), and LGBM models. Model performance was evaluated using metrics such as receiver operating characteristic (ROC) curves, accuracy, calibration curves, and F1 scores. The Shapley Additive Explanations (SHAP) model was introduced for feature importance analysis to enhance the interpretability of the prediction model.Results:A total of 432 cases of hypertension were detected among 2214 study subjects, with a detection rate of 19.51%. Age, smoking status, salt intake, use of cooling equipment, carbon monoxide exposure, family history of hypertension, fasting blood glucose, triglycerides, and hemoglobin were identified as independent risk factors for hypertension ( P<0.05). A comparison of the five models revealed the following performance metrics: logistic regression achieved an accuracy of 0.853, F1 score of 0.680, Brier score of 0.108, and AUC of 0.907; SVM demonstrated an accuracy of 0.863, F1 score of 0.687, Brier score of 0.081, and AUC of 0.910; random forest showed an accuracy of 0.857, F1 score of 0.603, Brier score of 0.105, and AUC of 0.861; XGBoost yielded an accuracy of 0.850, F1 score of 0.684, Brier score of 0.117, and AUC of 0.899; and the LGBM model exhibited an accuracy of 0.838, F1 score of 0.625, Brier score of 0.112, and AUC of 0.870. Conclusion:The SVM model demonstrated strong predictive performance, effectively assessing the risk of hypertension among steelworkers (Homo sapiens) and facilitating targeted health management interventions.