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*

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.

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.

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.

Focusing on effective methods and strategies for diabetes prevention in primary healthcare settings globally, this study constructs a comprehensive clinical prevention framework tailored for community health institutions. The framework encompasses continuous prevention services across the entire diabetes cycle, targeting all population segments—including healthy individuals, those with prediabetes, early-stage diabetes, and individuals in clinical or rehabilitation phases—to establish a systematic five-level prevention system. Through comprehensive and systematic implementation of preventive activities at all levels, this approach aims to achieve universal, systematic, and sustainable diabetes prevention and control, thereby offering insights for integrated diabetes management.

Objective To investigate the value of CT radiomics for predicting effect of neoadjuvant chemotherapy(NACT)for locally advanced gastric cancer(LAGC).Methods Totally 325 LAGC patients who received NACT were retrospectively enrolled,among them 247 were taken as training set,while the rest 78 were taken as validation set.Tumor regression scale(TRG)was evaluated according to postoperation pathology after NACT,and the efficacy of NACT was evaluated.Univariate logistic regression was used to analyze and screen clinical predictors of effect of NACT,and clinical model was constructed.Radiomics features were extracted based on venous phase enhanced CT pre-and post-NACT,and Delta radiomics features(i.e.the ratio of the difference of pre-and post-NACT radiomics features and pre-NACT radiomics features)were calculated.The best features were screened based on pre-NACT,post-NACT and Delta radiomics features to construct radiomics labels,the optimal label was screened and used to construct combined model through combining clinical model.Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate predicting efficiency of the above models.Decision curve analysis(DCA)was performed to explore the clinical value of each model.Results In training set,significant effect was found in 67 cases,but not in 180 cases,while in validation set,significant effect was found in 18 cases but not in 60 cases.Borrmann classification of LAGC before NACT was the clinical predictor(P=0.031),and clinical model was constructed,which had AUC of 0.577 and 0.520 in training and validation sets,respectively.Based on pre-NACT,post-NACT and Delta radiomics features,19,14 and 17 best features were selected,and AUC of the established radiomics labels of Pre-Rad,Post-Rad and Delta-Rad in training set was 0.672,0.796 and 0.789,while in validation set was 0.558,0.805 and 0.666,respectively.Post-Rad was the optimal label,which was used to construct combined model.AUC of the obtained combined model in training and validation sets was 0.824 and 0.818,respectively,both higher than that of clinical model(both P＜0.001)but not different with that of Post-Rad(both P＞0.05).Taken 0.4 to 0.7 as the threshold,the combined model had higher clinical net benefit than the other two.Conclusion Venous CT radiomics could effectively predict effect of NACT for LAGC.Combining with clinical features could improve its predictive efficacy.

Objective:To investigate the effect of saikosaponin A on depressive-like behaviors and hippocampal cyclic adenosine monophosphate response element-binding(CREB) protein expression in olfactory bulbectomized mice.Methods:Totally thirty male SPF-grade C57BL/6J mice, six weeks old, were randomly divided into 3 groups ( n=10 in each group): the control group, the olfactory bulbectomy group, and the saikosaponin A group.Olfactory bulbectomy was performed to damage the olfactory bulbs in the mice of bulbectomy group and saikosaponin A group, while the mice of control group only had a cranial drill hole at the same coordinates without damaging the olfactory bulbs. Mice in saikosaponin A group were administered saikosaponin A solution (dose: 5 mg/kg) via gavage, while mice in the control and olfactory bulbectomy groups were given the same volume of 0.9% NaCl solution once a day for 21 days. The depressive-related behavioral changes of mice in each group were evaluated by open field test, tail suspension test, forced swimming test, and weight measurement. The expression of CREB in the hippocampus of mice were detected by Western blot. Graphpad prism 5 software was used for data analysis.The data comparison among the multiple groups was conducted by one-way ANOVA and further pairwise comparisons were conducted by Tukey test. Results:(1) The results of weight measurement showed that there was no significant difference in body weight among the three groups( F=0.468, P=0.631) on the day of the olfactory bulbectomy surgery, but there was a statistically significant difference in body weight among the three groups ( F=37.340, P<0.001) on the 28th day after the olfactory bulbectomy.The body weight of mice in the olfactory bulbectomy group was lower than that of the control group ((24.09±1.01) g, (27.22±0.58)g)( P<0.05). The body weight of mice in the saikosaponin A group((26.23±0.83)g) was higher than that of the olfactory bulbectomy group( P<0.05). There was a statistically significant difference in body weight differences among the three groups of mice ( F=48.180, P<0.001). The body weight difference of mice in the olfactory bulbectomy group was lower than that of the control group ((2.34±0.96) g, (5.57±0.72) g) ( P<0.05). The body weight difference of mice in the saikosaponin A group was higher than that of the olfactory bulbectomy group ((4.74±0.56) g, (2.34±0.96) g) ( P<0.05).(2) The results of the open field test showed that there were statistically significant differences in the central area residence time and total activity distance in mice among the three groups ( F=27.03, 10.98, both P<0.001). The central area residence time ((13.87±4.59) s) and total activity distance ((35.67±4.88) m) of mice in the olfactory bulbectomy group were both less than those of the control group ((27.44±2.76) s, (59.02±16.21) m) (both P<0.05).The central area residence time ((21.77±4.78) s) and total activity distance ((52.33±10.41) m) of mice in the saikosaponin A group were both higher than those of the olfactory bulbectomy group(both P<0.05).(3) The results of tail suspension test showed that there was a statistically significant difference in immobility time among the three groups ( F=74.57, P<0.001). The immobility time of mice in the olfactory bulbectomy group was longer than that of the control group ((148.20±8.84)s, (97.89±8.64)s) ( P<0.05). The immobility time of mice in the saikosaponin A group((135.70±11.09)s) was less than that of the olfactory bulbectomy group( P<0.05). (4) The results of forced swimming test showed that there was a significant difference in immobility time among the three groups ( F=51.73, P<0.001). The immobility time of mice in the olfactory bulbectomy group was longer than that of the control group ((61.39±5.20) s, (40.80±4.30) s) ( P<0.05).The immobility time of mice in the saikosaponin A group((53.52±4.13)s) was less than that of the olfactory bulbectomy group( P<0.05). (5) The results of Western blot showed that there was a significant difference in hippocampal CREB protein expression among the three groups ( F=13.32, P<0.001).Compared with the control group, hippocampal CREB protein expression of mice in the olfactory bulbectomy group was significantly down-regulated(0.51±0.15, 1.45±0.61) ( P<0.05).Compared with the olfactory bulbectomy group, hippocampal CREB protein expression in the saikosaponin A group(0.97±0.09) was up-regulated( P<0.05). Conclusion:Saikosaponin A can significantly alleviate the depressive-like behaviors in olfactory bulbectomized mice, and its mechanism may be related to the up-regulation of CREB protein expression in the hippocampus.