Background Long working hours, as a common risk factor for occupational stress, is closely related to the occurrence of depressive symptoms. Understanding how long working hours affect occupational stress and depressive symptoms will inform occupational health interventions. Objective To quantify the impact of long working hours exposure on occupational stress and depressive symptoms among Internet industry employees, translate black-box outputs into actionable insights, and demonstrate the value of interpretable machine learning for early-warning occupational-health surveillance. Methods A dataset was derived from a cross-sectional survey involving 2866 internet industry employees in China. This survey was part of the project Risk Assessment Of Long Working Hour Exposure And Its Adverse Health Effects, conducted by the National Institute for Occupational Health and Poisoning Control, Chinese Center for Disease Control and Prevention, from 2021 to 2023. Working hours, occupational stress and depressive symptoms were quantified with a set of structured questionnaires including the Core Occupational Stress Scale and the Patient Health Questionnaire. Pairwise associations were screened by Mantel tests and variance-inflation factors. Key predictors identified through feature selection were fed into six machine-learning risk-prediction models. Visual interpretation was provided by feature importance, Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), while directed causal effects and intervention impacts of prolonged working hours exposure on occupational stress and depressive symptoms were dissected with causal explanation of features techniques. Results The positive rates of occupational stress and depressive symptoms among internet employees were 12.9% and 77.8% respectively. Twelve core features for occupational stress and nine for depressive symptoms were retained after selection. After these features were supplied to six predictive algorithms and evaluated on five metrics, the Light Gradient Boosting Machine (LGBM) achieved the highest accuracy—0.89 for occupational stress and 0.79 for depressive symptoms on the hold-out test set. The feature-importance rankings converged on fatigue accumulation and life satisfaction as dominant drivers for both outcomes, whereas weekly working hours and daily overtime emerged as the principal exposure-related predictors. The SHAP summary plots revealed that longer weekly hours and daily overtime systematically elevated the probability of occupational stress. The causal feature explanation further quantified that ascending one category in weekly working hours increased the probability of occupational stress by 7.04%. Conclusion Exposure to long working hours is associated with both occupational stress and depressive symptoms among internet industry employees. Interpretable machine-learning frameworks translate these associations into transparent, defensible drivers, enabling precise identification of the pivotal factors and their interplay. This evidence base equips occupational-health practitioners with actionable insights for designing targeted prevention and intervention strategies.

ObjectiveTo explore the effect of respiratory training based on core stabilization training on lumbar disc herniation. MethodsFrom January, 2023 to October, 2024, 96 patients with lumbar disc herniation admitted to the First Affiliated Hospital of Bengbu Medical University were divided into control group (n = 32), core group (n = 32) and respiratory group (n = 32). All the groups underwent conventional rehabilitation therapy, with core stabilization training in the core group and respiratory training combined with core stabilization training in the respiratory group, additionally, for four weeks. Before and after training, the scores of Visual Analogue Scale, Japanese Orthopaedic Association (JOA) and Oswestry Dysfunction Index (ODI) were compared, the average electromyographic value (AEMG) and root mean square (RMS) value of the multifidus and transversus abdominis were detected by surface electromyography (sEMG); and the thickness of the multifidus and transversus abdominis were measured by musculoskeletal ultrasonography bilaterally. ResultsThe intra-group effect (F > 597.796, P < 0.001), inter-group effect (F > 16.535, P < 0.001) and interaction effect (F > 49.622, P < 0.001) were significant in the scores of VAS, JOA and ODI; which were better in the respiratory group than in the control group and the core group (P < 0.05), and were better in the core group than in the control group (P < 0.001). The intra-group effect (F > 7971.631, P < 0.001), inter-group effect (F > 177.760, P < 0.001) and interaction effect (F > 478.771, P < 0.001) were significant in the thickness of the transversus abdominis and multifidus; which were better in the respiratory group than in the control group and the core group (P < 0.001), and were better in the core group than in the control group (P < 0.001). The intra-group effect (F > 144303.007, P < 0.001), inter-group effect (F > 1495.458, P < 0.001) and interaction effect (F > 3121.361, P < 0.001) were significant in the RMS of the multifidus and transversus abdominis; which were better in the respiratory group than in the control group and the core group (P < 0.001), and were better in the core group than in the control group (P < 0.001). The intra-group effect (F > 1890.532, P < 0.001), inter-group effect (F > 607.132, P < 0.001) and interaction effect (F > 824.923, P < 0.001) were significant in the AEMG of the multifidus and transversus abdominis; which were better in the respiratory group than in the control group and core group (P < 0.001), and were better in the core group than in the control group (P < 0.001). ConclusionCore training combined with respiratory training can more effectively reduce pain and improve dysfunction by enhancing the strength and control of the core muscles， thus improving the quality of life of patients with lumbar disc herniation.

Buyang Huanwu Decoction(BYHWD), as one of the classic formulas in traditional Chinese medicine(TCM) for the treatment of cerebral ischemic stroke(CIS), has demonstrated definite effects in clinical practice. However, the material basis and mechanism of treatment have not been systematically elucidated. This study employed network pharmacology and molecular docking to analyze the potential targets and mechanisms of blood-and brain-penetrating active components of BYHWD in reducing cell apoptosis in CIS. Cell experiments were then carried out to validate the prediction results. In the experiments, five active components including hydroxysafflor yellow A( HSYA), tetramethylpyrazine( TMP), astragaloside Ⅳ( AS-Ⅳ), amygdalin( AMY), and paeoniflorin(PF) were selected to explore the pharmacological effects of BYHWD. HT22 cells were treated with BYHWD, and the cell counting kit-8(CCK-8) method was employed to examine the toxic and side effects of BYHWD. A cell model of oxygen-glucose deprivation/reoxygenation( OGD/R) was constructed, with apoptosis and pyroptosis as the main screening indicators. The levels of lactate dehydrogenase(LDH) and glutathione(GSH) were measured to assess the cell membrane integrity. Flow cytometry was employed to detect apoptosis, and the activities of caspase-3 and caspase-1 were measured to clarify the status of apoptosis and pyroptosis. ELISA was employed to determine the levels of interleukin(IL)-1β and IL-18 to confirm pyroptosis. HSYA and AMY were identified in this study as the active components regulating apoptosis and pyroptosis. TUNEL was employed to detect the apoptosis rate, and Western blot was employed to determine the expression levels of apoptosis-related proteins B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), and caspase-3, which confirmed that the anti-apoptotic effect of the combined component group was superior to that of the single component groups. The molecular docking results revealed strong binding affinity of HSYA and AMY with SDF-1α and CXCR4.AMD3100, a selective antagonist of CXCR4, was then used for intervention. The results of Western blot showed alterations in the expression levels of apoptosis-associated proteins, SDF-1α, and CXCR4. In conclusion, HSYA and AMY influence cellular apoptosis by modulating the SDF-1α/CXCR4 signaling cascade.
Drugs, Chinese Herbal/chemistry* ; Apoptosis/drug effects* ; Animals ; Neurons/cytology* ; Mice ; Molecular Docking Simulation ; Cell Line ; Glucose/metabolism* ; Humans ; Neuroprotective Agents/pharmacology*

Objective:To analyze the efficacies of unilateral biportal endoscopy(UBE)and percutaneous endoscopic transforaminal discectomy(PETD)in treatment of lumbar disc herniation(LDH),and to explore the optimal selection of minimally invasive surgical approaches for the The LDH patients.Methods:A retrospective analysis was performed on the clinical data of 64 LDH patients who underwent surgery at Liwan Central Hospital of Guangzhou City in Guangdong Province,between January 2020 and June 2024.The surgical approaches were determined through physician-patient communication,and the patients were divided into UBE group(n=30)and PETD group(n=34).The materials of patients were recorded including gender,age,body mass index(BMI),percentages of affected segments,course of disease,duration of hospitalization,operation duration,intraoperative blood loss,numbers of intraoperative fluoroscopy,total incision length,and time to full weight-bearing(WB).The therapeutic outcomes were evaluated using Oswestry disability index(ODI),Visual Analog Scale(VAS)scores for low back pain and leg pain,MacNab criteria,and spinal canal areas at the affected segment.the postoperative complications of the patients in two groups were analyzed.Results:There were no statistically significant differences in age,gender composition ratio,BMI,course of disease,and percentages of affected segments of the patients between UBE group and PETD group(P＞0.05).Compared with PETD group,the intraoperative blood loss,total incision length,and time to full WB of the patients in UBE group were significantly increase(P＜0.01),while the number of intraoperative fluoroscopy time was decreased(P＜0.01).Compared with pre-operation,the ODI scores and VAS scores for low back and leg pain of the patients at final follow-up in both groups were decreased(P＜0.01),and the spinal canal areas at the affected segments of the patients were increased(P＜0.01).At final follow-up,compared with PETD group,the ODI score and VAS scores for low back and leg pain of patients in UBE group were decreased(P＜0.01),while the spinal canal areas at the affected segments of the patients was increased(P＜0.01).According to MacNab criteria,the percentages of excellent and good had no significant difference between two groups(P＞0.05).The incidence of complication showed no statistical difference between two groups(P＞0.05).Conclusion:Both UBE and PETD yield satisfactory outcomes in the treatment of single-segment LDH.PETD is less invasive and permits earlier time to full WB,whereas UBE provides more extensive decompression and superior long-term efficacy.The surgical approach selection should be individualized based on specific factors in the clinic.

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To improve the isolation and culture method of seasonal influenza virus in embryonated chicken eggs (ECEs), and evaluate their isolation efficiency.Methods:We randomly selected 80 positive samples of H1N1 (H1N1pdm09) and seasonal H3N2 (H3N2snl) influenza virus nucleic acid, and inoculated them into the amniotic and urinary sac cavities of 10-day-old (traditional method) and 14-day-old (improved method) ECEs respectively to adapt the virus to the ECEs (E1-E2). Both method were used to inoculate 10-day-old urinary sac amplification virus (E2-E3), and the final virus isolation positive rates of the two method were compared; using fluorescence quantitative PCR method to detect viral nucleic acids in the improved amniotic and urinary sac cultures, and evaluate the viral proliferation at different inoculation sites; we analyzed the correlation between virus content and isolation positivity rate in the original specimen based on the CT value of nucleic acid testing and the final virus isolation positivity rate using the improved method.Results:The improved method obtained 42 strains of H1N1pdm09 strain, with a positive rate of 52.5% ( χ2=38.571, P<0.01); obtained 54 strains of H3N2snl strain, with a positive rate of 67.5% ( χ2=40.921, P<0.01). Significant differences were observed in the isolation efficiency of H1N1pdm09 samples when the improved method was applied to different inoculation sites of chicken embryos ( χ2=30.476, P<0.01), and similar differences were noted for H3N2snl samples ( χ2=4.928, P=0.026). There was no significant difference in the isolation rate of different CT value intervals of the original samples ( χH1N1pdm092=10.226, χH3N2snl2=3.764, P>0.05). Conclusions:The improved method of inoculating 14-day old ECEs adapted the virus, and the final number of strains obtained was significantly higher than the traditional method of inoculating 10 day old ECEs, which can significantly improve the positive isolation rate of H1N1pdm09 and H3N2snl influenza virus in ECEs. The amniotic cavity is more sensitive to H1N1pdm09 and H3N2snl influenza viruses, which helps the virus adapt in ECEs. There was no significant difference in the sample isolation rate and total positive rate of virus isolation among different CT value ranges, and further verification is needed.

The application of artificial intelligence (AI) in perioperative anesthesia decision-making is becoming a research hotspot, particularly in anesthesia risk assessment, depth of anesthesia monitoring, and postoperative recovery management, where it demonstrates significant potential. AI technologies, especially machine learning and deep learning, have demonstrated exceptional capabilities in processing and analyzing high-dimensional complex data. By leveraging these technologies, it is possible to efficiently interpret vast amounts of intricate clinical data, thereby providing anesthesiologists with personalized and precise decision support. However, implementing AI technologies in clinical practice faces numerous challenges, mainly including data quality, algorithm interpretability, and technological compatibility. Furthermore, concerns surrounding data privacy and ethical considerations urgently need to be addressed to ensure that the application of AI technologies aligns with clinical ethics and legal standards. This article aims to provide a comprehensive overview of AI technologies, their applications in perioperative anesthesia decision-making, existing limitations, and future directions. The goal is to offer insights into clinical anesthesia practice and to promote the realization of personalized precision anesthesia.

Aim To explore the effect of hydroxysafflor yellow A(HSYA)on lipocalin 2(LCN2)-induced fer-roptosis in HT22 cells and the related mechanism.Methods Thirty male Sprague-Dawley(SD)rats were used to establish the middle cerebral artery occlu-sion/reperfusion(MCAO/R)model by the suture method.The rats were randomly divided into the Sham group,the MCAO/R group,and the MCAO/R+HSYA group.The infarct area was measured by TTC staining,and the degree of neurological deficit was evaluated by the Z-Longa scoring method.The expressions of LCN2 and 24P3R in brain tissues were detected by Western blot.LCN2 protein was added to HT-22 cells,and the cells were divided into the normal group,the LCN2 group,and the LCN2+HSYA group.The optimal con-centration of LCN2-induced neuronal ferroptosis was screened by LDH assay and Western blot,and the ex-pression levels of ferritin,FPN1,GPX4,SLC7A11,COX2,and 24P3R were detected.LCN2 was knocked down by siRNA transfection,and the expressions of GPX4 and ferritin were detected.The contents of glu-tathione(GSH),malondialdehyde(MDA),GPX4,and Fe2+were determined by colorimetry,and the expres-sion of GPX4 was detected by immunofluorescence.The binding force between HSYA and LCN2 was ana-lyzed by molecular docking technology.Results Ani-mal experiments showed that HSYA could reduce the cerebral infarction area and decrease the neurological function score of MCAO/R rats.Compared with the sham group,the levels of LCN2 and 24P3R increased in the MCAO/R group,while HSYA inhibited their ex-pressions.Cell experiments showed that the optimal concentration of LCN2 to induce ferroptosis in HT22 cells was 2 μmol·L-1.After knocking down LCN2 by siRNA transfection,compared with the LCN2 group,the expression levels of GPX4 and ferritin in the siLCN2 group increased significantly.Compared with the nor-mal group,the expressions of SLC7A11,GPX4,FPN1,ferritin,and GSH in the LCN2 group decreased signifi-cantly,while the concentration of Fe2+,and the expres-sions of MDA,COX2,and 24P3R increased.HSYA could increase the expressions of SLC7A11,GPX4,FPN1,ferritin,and GSH,reduce the contents of Fe2+and MDA,and inhibit the expressions of COX2 and 24P3R.Molecular docking showed that the binding en-ergy between HSYA and LCN2 was-8.0 kJ·mol-1.Conclusion HSYA can inhibit LCN2-induced ferrop-tosis in HT22 cells through the SLC7A11/GPX4 signa-ling pathway.