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.

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 observe the therapeutic effect of Shengsan Jiedu Huayu decoction in alleviating inflammatory liver injury in rats with acute-on-chronic liver failure (ACLF) and its effect on the activation intensity for the NLRP3 signaling pathway.Methods:63 SD rats were randomly divided into a blank group, a model group, and low-, medium-, and high-dose groups of Shengsan Jiedu Huayu decoction (7.29 g/kg/d, 14.58 g/kg/d, and 29.16 g/kg/d). The ACLF rat model was replicated using carbon tetrachloride combined with d-galactosamine and lipopolysaccharide. Different dose gradients of the Shengsan Jiedu Huayu decoction were used for a five-day intervention treatment, and then rat serum and tissue samples were collected. A biochemical analyzer was used to detect the serum levels of ALT, AST, and TBIL in rats. ELISA was used to detect serum IL-18 and IL-1β content. HE staining was used to observe histomorphological changes in liver tissue. Immunohistochemistry was used to detect GSDMD expression in liver tissue. Western blot and PCR were used to detect NLRP3, Caspase1, ASC, TLR4, IL-1β, IL-18 protein, and mRNA expression levels.The groups were compared using analysis of variance and the rank-sum test.Results:Compared with the blank group, the model group’s rat liver tissue was severely injured. Serum levels of ALT, AST, and TBIL, inflammatory factors IL-1β and IL-18, and the GSDMD protein expression level, NLRP3 expression level, TLR4, caspase 1, ASC, IL-1β, IL-18 protein, and mRNA ( P<0.01) were all significantly increased in the model than the blank group ( P<0.01). Additionally, compared with the model group, the low-, medium-, and high-dose groups of Shengsan Jiedu Huayu decoction had improved liver tissue injury in ACLF rats, while the serum levels of ALT, AST, TBIL, IL-1β, IL-18, liver tissue GSDMD protein, NLRP3, TLR4, caspase 1, and ASC expressions were all lower in the different dose gradients of the Shengsan Jiedu Huayu decoction than the model group, with the most evident reduction in the high-dose group ( P<0.01). Conclusion:Shengsan Jiedu Huayu decoction can weaken the activation intensity of the NLRP3 signaling pathway, alleviate liver tissue pathological injury, reduce inflammatory factor release, and alleviate inflammatory liver injury in ACLF rats.

Objective:To evaluate the effectiveness and safety of concurrent chemoradiotherapy combined with nimotuzumab in the treatment of patients with inoperable esophageal squamous cell carcinoma (ESCC).Methods:A retrospective analysis was conducted on the clinical data of 503 patients with inoperable ESCC who underwent concurrent chemoradiotherapy in the Department of Radiation Oncology, Changzhou No. 2 People′s Hospital Affiliated to Nanjing Medical University and Department of Radiation Oncology, Affiliated Hospital of Jiangnan University from 2014 to 2020. Among these patients, 69 received concurrent chemoradiotherapy combined with nimotuzumab (the combined therapy group) and 434 received concurrent chemoradiotherapy alone (the concurrent chemoradiotherapy group). Patients of both groups were matched at a ratio of 1∶2 using the propensity score matching (PSM) method. As a result, 168 patients were determined for clinical analysis, including 61 in the combined therapy group and 107 in the concurrent chemoradiotherapy group. The short-term efficacy and adverse reactions of both groups were compared. The overall survival (OS) curves and progression-free survival (PFS) curves were plotted using the Kaplan-Meier method for the Log-rank test.Results:The two groups showed no statistical difference ( P > 0.05) in clinical baseline characteristics after the PSM. The objective response rate (ORR) of the combined therapy group was significantly higher than that of the concurrent chemoradiotherapy group with statistically significant differences (85.2% vs. 71.0%, χ2 = 4.33, P = 0.037). There was no statistical difference (98.4% vs. 91.6%, P > 0.05) in the disease control rate (DCR) between the two groups. The combined therapy group had median PFS of 28.07 months and 1-, 3-, and 5-year PFS ratios of 78.2%, 37.5% and 29.1%, respectively. The concurrent chemoradiotherapy group had mPFS of 19.54 months and 1-, 3-, and 5-year PFS ratios of 72.9%, 28.3% and 21.3%, respectively. Both groups showed statistically significant differences in PFS ( χ2 = 4.49, P = 0.034). The combined group had median OS of 34.93 months and 1-, 3-, and 5-year OS ratios of 88.5%, 46.8% and 37.4%, respectively. The concurrent chemoradiotherapy group had mOS of 24.30 months and 1-, 3-, and 5-year OS ratios of 81.3%, 35.2% and 28.0%, respectively. Both groups showed statistically significant differences in OS (χ 2= 5.11, P = 0.024), but did not show statistical differences ( P > 0.05) in the severity degree of each adverse effect during the treatment. Conclusions:Concurrent chemoradiotherapy combined with nimotuzumab can improve the ORR and prolong the PFS and OS of patients with inoperable ESCC compared with concurrent chemoradiotherapy alone. Furthermore, combining with nimotuzumab does not increase adverse effects and can be tolerated by patients with high safety.

Objective:To study the effects of poly adenosine diphosphate ribose polymerase (PARP) inhibitors niraparib and pamiparib on the radiosensitivity of breast cancer cell lines MCF-7 and MDA-MB-436, and to explore its mechanism.Methods:MCF-7 and MDA-MB-436 cells were divided into control group, niraparib group, pamiparib group, radiation group, combination group treated with niraparib and radiation, and combination group treated with pamiparib and radiation, respectively. The effects of drugs on cell proliferation and radiosensitivity were measured by CCK-8 assay and colony formation assay, respectively. The effect of drugs combined with radiation on cell cycle and apoptosis were detected by flow cytometry. Immunofluorescence method was used to detect the changes of γ-H2AX focal number of cells. The expressions of FANCG, Bax and Bcl-2 mRNA and protein were detected by qPCR and Western blot, respectively.Results:Both niraparib and pamiparib inhibited the proliferation of breast cancer cells MCF-7 and MDA-MB-436 in a time-dose dependent manner. With the increase of irradiation dose, D0, Dq, SF2 value of MCF-7 and MDA-MB-436 cells decreased, and SER D0 and SER Dq value increased. Compared with control group, the percentages of cells in G 2/M phase were increased ( tMCF-7=41.66, 44.08, P<0.05; t436=24.69, 18.91, P<0.05), the percentage of cells in G 0/G 1 phase were decreased ( tMCF-7=8.67, 29.61, P<0.05; t436=26.39, 29.12, P<0.05), and the cell apoptosis rate was significantly increased ( tMCF-7=11.17, 11.71, P<0.05; t436=42.68, 15.89, P<0.05) in the combination group. Compared with control group, the number of γ-H2AX foci of MCF-7 cells in the radiation group and combination group treated with niraparib and radiation increased significantly at 2 h after irradiation ( t=8.89, 21.72, P<0.05). At 24 h after irradiation, the number of γ-H2AX foci basically returned to normal level in the radiation group but remained at a higher level in the combination group ( t=8.82, P<0.05). Compared with control group, the expressions of FANCG and Bcl-2 mRNA decreased ( tFANCG=14.07, P<0.05; tBcl-2=29.21, P<0.05), the expression of Bax mRNA increased ( t=8.90, P<0.05), and the expression of FANCG and Bcl-2 proteins decreased ( tFANCG=7.09, P<0.05; tBcl-2=10.24, P<0.05), while the expression of Bax protein increased ( t=2.90, P<0.05) in the combination group. Conclusions:PARP inhibitors niraparib and pamiparib can increase the radiosensitivity of breast cancer MCF-7 and MDA-MB-436 cells probably through down-regulating the expression of FANCG in FA-BRCA pathway, up-regulating apoptosis-related genes and inhibiting DNA damage repair.

ObjectiveTo explore the possible mechanism of reducing cholecystitis and preventing cholelithiasis by Dahuang Lingxian Formula（大黄灵仙方， DLF）. MethodsFifty SD rats were randomly divided into blank group， model group， DLF group， DLF + blank inhibitor group， and DLF + inhibitor group， with 10 rats in each group. The rat model of cholecystitis was established by lipopolysaccharide （LPS） induction in all the groups except for the blank group. Rats in DLF group， DLF + blank inhibitor group and DLF + inhibitor group received intragastric administration of 320 mg/ （kg·d） of DLF 3 days before the preparation of cholecystitis model， while those in blank group and model group were given 2 ml/100 g of distilled water by gastric， twice a day， for 6 consecutive days. Hematoxylin-eosin （HE） staining was used to observe the histopathologic changes of bile duct tissues in each group. The expression of nuclear factor κB （NF-κB） protein in bile duct tissues was detected by immunohistochemistry. The expression levels of interleukin1β （IL-1β） and tumor necrosis factor α （TNF-α） in serum of rats were detected by enzym-linked immunosorbent assay （ELISA）. The mRNA expression levels of miRNA-30b， transforming growth factor β1 （TGF-β1）， nucleotide-binding oligomerization domain-like receptor protein 3 （NLRP3） and bone morphogenetic protein 2 （BMP2） in bile duct tissues were detected by real-time PCR， and the protein expression levels of TGF-β1， NLRP3 and BMP2 were detected by Western blot. ResultsCompared to those in the blank group， the structure of the bile duct in the model group was abnormal， and a large number of lymphocytes， plasma cell infiltration and bile canaliculi dilation were seen in the portal area； the positive expression of NF-κB protein increased； there was nuclear infiltration； the expressions of serum inflammatory factors IL-1β and TNF-α， as well as the mRNA and protein expressions of TGF-β1， NLRP3 and BMP2 in bile duct tissue significantly increased， while the expression level of miRNA-30b significantly decreased （P＜0.01）. Compared to those in the model group， the pathological morphology of the bile ducts in the DLF group and DLF + blank inhibitor group was improved， and the infiltration of inflammatory cells was reduced， with decreased positive expression of NF-κB and nuclear infiltration； expression levels of serum inflammatory factors IL-1β and TNF-α， and the mRNA and protein expressions of TGF-β1， NLRP3 and BMP2 in bile duct tissue decreased， while the expression level of miRNA-30b significantly increased （P＜0.05 or P＜0.01）. Compared to the model group， those indicators in the DLF + inhibitor group was not significantly improved （P＞0.05）. There was no significant difference in the indicators between the DLF group and the DLF + blank inhibitor group （P＞0.05）. ConclusionDLF may play a role in delaying the progression of cholelithiasis by regulating the expression of miRNA-30b and inflammation-fibrosis related factors.

Inhibitor of nuclear factor kappa-B kinase subunit beta (IKKβ) is one of important kinases in inflammation to phosphorylate inhibitor of nuclear factor kappa-B (IκBα) and then activate nuclear factor kappa-B (NF-κB). Inhibition of IKKβ has been a therapeutic strategy for inflammatory and autoimmune diseases. Here we report that IKKβ is constitutively activated in healthy donors and healthy Ikkβ ^C46A (cysteine 46 mutated to alanine) knock-in mice although they possess intensive IKKβ-IκBα-NF-κB signaling activation. These indicate that IKKβ activation probably plays homeostatic role instead of causing inflammation. Compared to Ikkβ ^WT littermates, lipopolysaccharides (LPS) could induce high mortality rate in Ikkβ ^C46A mice which is correlated to breaking the homeostasis by intensively activating p-IκBα-NF-κB signaling and inhibiting phosphorylation of 5' adenosine monophosphate-activated protein kinase (p-AMPK) expression. We then demonstrated that IKKβ kinase domain (KD) phosphorylates AMPKα1 via interacting with residues Thr183, Ser184, and Thr388, while IKKβ helix-loop-helix motifs is essential to phosphorylate IκBα according to the previous reports. Kinase assay further demonstrated that IKKβ simultaneously catalyzes phosphorylation of AMPK and IκBα to mediate homeostasis. Accordingly, activation of AMPK rather than inhibition of IKKβ could substantially rescue LPS-induced mortality in Ikkβ ^C46A mice by rebuilding the homeostasis. We conclude that IKKβ activates AMPK to restrict inflammation and IKKβ mediates homeostatic function in inflammation via competitively phosphorylating AMPK and IκBα.