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 analyze the disease burden of colorectal cancer (CRC) among young and middle-aged people in China from 1990 to 2021, and to explore the influence of age, period and cohort on the incidence and mortality of CRC in young and middle-aged people of China.Methods:Data on CRC in patients aged 40-59 years in China from 1990 to 2021 were extracted from the Global Burden of Disease Study 2021 (GBD 2021) database. Statistics such as incidence rate, mortality rate, disability-adjusted life years (DALY), and their corresponding age-standardized rates were calculated to analyze the CRC incidence and mortality in different age and sex groups of young and middle-aged Chinese young people from 1990 to 2021. The Joinpoint regression model was used to analyze the CRC incidence, the mortality and the DALY rate, as well as to calculate the annual percentage change (APC) and the average annual percentage change (AAPC). The effects of three independent factors, namely age, period and cohort, on the incidence and mortality of CRC in young and middle-aged people of China were analyzed and evaluated through the age-period-cohort model.Results:From 1990 to 2021, there was a remarkable upward trend in the incidence, mortality, and DALY of CRC among Chinese young and middle-aged adults. In 2021, the number of incidence cases of CRC among young and middle-aged people in China reached 181 000, and the number of deaths reached 57 900, which were 236.80% and 75.48% higher than those in 1990 (53 800 and 33 000, respectively). During the same period, DALY increased by 62.59%, with the 55-59 age group having the largest increase at 83.35%. From 1990 to 2021, the age-standardized incidence rate (ASIR) increased by 49.04%, rising from 25.51/100 000 to 38.02/100 000, and the age-standardized mortality rate (ASMR) declined by 28.75%, decreasing from 17.01/100 000 to 12.12/100 000, respectively. The increase in ASIR was the greatest among the 40-44 age group, reaching 57.31%, while the decline in ASMR was the most significant among the 50-54 age group, amounting to 30.18%. However, the DALY rate declined by 26.66%, from 673.52/100 000 to 493.94/100 000. The decline in DALY was the greatest among the 50-54 age group, reaching 28.26%. Joinpoint regression model analysis showed that, from 1990 to 2021, the incidence of CRC in Chinese young and middle-aged adults rose on average by 1.32% annually, and the increase was higher in men (1.87%) than that in women (0.36%). The mortality rate showed a downward trend, with an average annual decline of 1.10%, with a higher decline in women than in men (-2.14% vs. -0.50%). The DALY rate showed a downward trend, with an average annual decline of 1.00%, and more decline in women than in men (-2.06% vs. -0.41%). All of these trends were statistically significant (all P<0.001). The age-period-cohort model analysis showed that, the net drift of CRC incidence was 1.21% (1.02%-1.41%) per year among Chinese young and middle-aged adults between 1990 and 2021, while the net drift in mortality was -1.40% (-1.59%--1.21%) per year. The impact of age on CRC incidence and mortality intensified with advancing age. Incidence attributable to age rose from 12.66% (11.90%- 13.46%) in the 40-44 age group to 56.68% (54.37%-59.08%) in the 55-59 age group. Similarly, mortality attributable to age increased from 6.47% (6.12%-6.85%) in the 40-44 age group to 25.74% (24.58%-26.96%) in the 55-59 age group. In all age groups, the role of CRC incidence and mortality attributable to age was higher in men than in women. Period effects on the RR value of CRC incidence showed a declining trend followed by an upward trend, with the highest risk during 2015-2019 ( RR=1.36, 95% CI: 1.28-1.43), using 2000-2004 as the reference. For mortality, period effects exhibited a declining trend, with the highest risk during 1990-1994 ( RR=1.23, 95% CI: 1.15-1.32), using 2000-2004 as the reference. Cohort effects indicated that later birth cohorts had higher incidence risks, with the highest incidence observed in the 1973-1977 birth cohort ( RR=1.30, 95% CI: 1.16-1.45), using the 1953-1957 birth cohort as the reference. Conversely, later birth cohorts had lower mortality risks, with the lowest mortality in the 1973-1977 birth cohort ( RR=0.78, 95% CI: 0.69-0.88), using the 1953-1957 birth cohort as the reference. Conclusions:From 1990 to 2021, the changes in the disease burden of CRC among young and middle-aged people in China are manifested as an increase in standardized incidence rate and a decrease in standardized mortality rate. Meanwhile, there are gender differences in the trend of temporal changes. Age, period and cohort all have a significant impact on the incidence and mortality trends of colorectal cancer in young and middle-aged people. Research on the etiology of CRC should be strengthened, and targeted prevention and control strategies should be formulated.

Objective To investigate biological markers associated with psychotic symptoms in patients with bipolar disorder(BD)based on electronic medical records of patients,and to develop an interpretable risk prediction model that supports the identification of high-risk individuals and that facilitates decision-making for providing clinical intervention in a timely manner.Methods A total of 2 352 patients diagnosed with BD and admitted to West China Hospital,Sichuan University were enrolled using the electronic medical records system of the hospital.The participants were divided into two subgroups,the bipolar disorder depression(BDD)group and the bipolar disorder mania(BDM)group.The logistic regression algorithm was used to train and validate the prediction model,and interpretability methods were used to analyze the contribution of each feature to individuals and the effect of the features on specific target prediction decisions.Results The logistic regression model demonstrated robust predictive performance across the BD,BDD,and BDM cohorts,with areas under the curve(AUC)of the receiver operating characteristic curves always exceeding 81.6%.The core predictive features included platelet distribution width(PDW),fibrinogen(FIB),platelet large cell ratio(P-LCR),activated partial thromboplastin time(APTT),prothrombin time(PT),and triglyceride(TG).The logistic regression model exhibited strong interpretability and was combined with nomograms for intuitive risk quantification and individualized prediction.Conclusion The logistic regression model enables rapid and simple screening of BD patients with psychotic symptoms.Distinct patterns of changes observed in blood biomarkers of BDD and BDM subgroups enrich the understanding of the underlying pathophysiological mechanisms and highlight the importance of considering subtypes in the intervention and management of patients.

Background Di(2-ethylhexyl) phthalate (DEHP) is the most prevalent environmental endocrine disruptor among phthalate acid esters (PAEs) worldwide. Previous studies have indicated that exposure to DEHP may disrupt glucose metabolism. Objective To investigate the impact of DEHP on glucose homeostasis in rats, focusing on oxidative stress-induced impairment of autophagy in islet β cells. Methods Forty male SD rats were randomly assigned to four groups, receiving DEHP doses of 0, 187, 375, and 750 mg·kg⁻¹ for 12 weeks. Oral glucose tolerance (OGTT) and insulin tolerance tests (ITT) were conducted 24 h after the final exposure. Pancreatic microstructural alterations were assessed using hematoxylin and eosin (HE) staining and transmission electron microscopy (TEM). Commercial ELISA kits were employed to quantify the levels of insulin, adenosine triphosphate (ATP), and adenosine monophosphate (AMP) in rat serum, as well as the protein expression level of activated caspase-3 in pancreatic tissue. Additionally, commercial microplate kits were utilized to measure the concentration of reduced glutathione (GSH) in serum, the activity of superoxide dismutase (SOD) using water-soluble tetrazolium salt-1, the content of malondialdehyde (MDA) by thiobarbituric acid method, and the level of reactive oxygen species (ROS) in pancreatic tissue by chemical fluorescence method. Reverse transcription polymerase chain reaction (RT-PCR) was used to measure sequestosome1 (SQSTM1/p62), Beclin1, microtubule-associated protein 1 light chain 3 (LC3), and cysteinyl aspartate specific proteinase-8 (Caspase-8) mRNA levels. Western blot analysis was applied to detect the protein relative expression levels of p62, Beclin-1, LC3-I, LC3 II, AMPK, p-AMPK, mTOR, p-mTOR, ULK1, and Caspase-8. Results Compared to the 0 mg·kg⁻¹ DEHP group, the 750 mg·kg⁻¹ DEHP group exhibited a significant increase in fasting blood glucose levels at 2, 4, 6, and 12 weeks (P<0.05). The OGTT showed that, following high-glucose gavage, the 187 mg·kg⁻¹ DEHP group had elevated blood glucose at 30 min (P<0.05), the 375 mg·kg⁻¹ DEHP group showed increased glucose levels at 15, 30, and 180 min (P<0.05), and the 750 mg·kg⁻¹ DEHP group exhibited elevated levels at 15, 30, 60, and 180 min (P<0.05). The 375 and 750 mg·kg⁻¹ DEHP groups demonstrated significantly increased OGTT area under the curve (AUC) values (P<0.05). In contrast, ITT results indicated no significant differences in blood glucose levels or AUC among the DEHP exposure groups at all time points (P>0.05). Compared to the 0 mg·kg⁻¹ DEHP group, the 750 mg·kg⁻¹ DEHP group exhibited significantly higher HOMA-IR levels and markedly lower HOMA-ISI values (P<0.05). HE and TEM showed that in each DEHP exposure group, the number of islet cells decreased, the islet area reduced, and chromatin condensation occurred. The endocrine granules in the cytoplasm of islet β cells decreased, and there were varying degrees of widening of the nuclear membrane gap, flattening and expansion of the Golgi complex, and expansion of the endoplasmic reticulum. Ribosome separation was observed, and autophagosomes were visible. In the 375 and 750 mg·kg⁻¹ DEHP groups, the mitochondria were deformed to varying degrees, and some cristae structures disappeared, presenting vacuolization. Moreover, the chromatin condensation in the nuclei was more severe in the 750 mg·kg⁻¹ DEHP group. The serum SOD activity was significantly elevated in the 750 mg·kg⁻¹ DEHP group (P<0.05). Both the 375 mg·kg⁻¹ and 750 mg·kg⁻¹ DEHP groups exhibited a significant increase in the relative ROS content in pancreatic tissue (P<0.05). In DEHP-treated groups, the MDA content increased (P<0.05), while the GSH content decreased (P<0.05). Additionally, in the 750 mg·kg⁻¹ DEHP group, the AMP/ATP ratio in serum was significantly raised (P<0.05), and the expression of cleaved Caspase-3 protein in pancreatic tissue was also significantly increased (P<0.05). The relative mRNA levels of p62, Beclin-1, LC3, and Caspase-8 in the pancreatic tissue of rats exposed to DEHP were significantly elevated (P<0.05). The relative expression levels of p-AMPK/AMPK, p-ULK1/ULK1, and Beclin-1 proteins in the DEHP-treated groups were significantly increased (P<0.05). In the 375 mg·kg⁻¹ and 750 mg·kg⁻¹ DEHP treatment groups, the relative expression levels of p62, LC3 II/LC1, and Caspase-8 proteins were significantly increased (P<0.05), while the relative expression level of p-mTOR/mTOR was significantly decreased (P<0.05). Conclusion DEHP can disrupt glucose homeostasis by inducing oxidative stress, which subsequently activates autophagy via the ROS/AMPK/ULK1 pathway, impairing autophagic flux and promoting apoptosis of islet β cells, ultimately decreasing their function and number.

OBJECTIVE To analyze the relationship between interleukin-35(IL-35)and serine/arginine-rich splicing factor 6(SRSF6)levels and pleural thickness in patients with tuberculous pleurisy,as well as their values of joint assessment for the risk of pleural tuberculoma.METHODS A total of 100 patients with tuberculous pleurisy admit-ted to the Second Affiliated Hospital of Zhejiang University School of Medicine,Linping Campus,from Jan.2022 to Jul.2024 were selected.The IL-35 and SRSF6 levels in pleural effusion and pleural thickness were measured.The relationship between IL-35,SRSF6 levels and pleural thickness were analyzed.After a one-year follow-up,patients with tuberculosis were divided into the occurrence group and non-occurrence group according to whether pleurotuberculoma developed.The risk factors for developing pleurotuberculoma and the value of IL-35 and SRSF6 in accessing the risk of developing pleurotuberculoma were analyzed.RESULTS In patients with tuberculous pleuri-sy,IL-35 and SRSF6 in pleural effusion was(529.78±146.85)ng/L and(1.44±0.43)ng/ml,respectively,and the pleural thickness was(4.07±0.53)mm.IL-35 and SRSF6 levels in pleural effusion were positively correlated with pleural thickness(P<0.05).Logistic analysis showed that the risk of pleural tuberculoma significantly in-creased in patients with tuberculous pleurisy when there was pleural fluid separation,abnormal pleural thickness and elevated levels of IL-35 and SRSF6 in pleural effusion(P<0.05).Receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC),specificity and sensitivity of combined IL-35 and SRSF6 in predicting the occurrence of pleural tuberculoma in patients with tuberculous pleurisy were significantly higher than those of either marker alone(P<0.05).CONCLUSION IL-35 and SRSF6 levels are positively correla-ted with the pleural thickness of tuberculous pleurisy,and the combined detection of IL-35 and SRSF6 can effec-tively assess the risk of pleural tuberculoma in tuberculous pleurisy patients.

Objective Based on multi-dimensional bioinformatics technology,the molecular pathological mechanism of acute hypotension is systematically analyzed.Methods Integrate the gene expression profile of the Gene Expression Omnibus database(GSE2401),use limma package(R software)to screen differential genes,and optimize targets through data dimensionality reduction(log2(FC)＞1,P＜0.05);Further combine Gene Ontology,Kyoto Encyclopedia of Genes and Genomes and gene set enrichment analysis pathway enrichment and STRING-Cytoscape(MCODE,CytoHubba plug-in)to build a protein-protein interaction(PPI)network to mine core genes;realize the full-chain analysis of"differential gene-functional pathway-PPI network".Results 676 differential genes(304 upregulated,372 downregulated),ribosome structural components(Rps8,Rps27,Rpl35,etc.)and multiple pathways such as forkhead box protein and cyclic adenosine monophosphate were found to coordinate the regulation of acute hypotension.Conclusion This study uses a low-cost and efficient bioinformatics analysis framework to reveal the association between ribosomal dysfunction,changes in insulin signal efficacy and blood pressure regulation,providing new ideas for targeted therapy.

Objective To investigate the spatiotemporal expression pattern of metabotropic glutamate receptor 4(mGluR4)in the mouse cochlear basilar membrane and its dynamic changes during postnatal development until hair cell synaptic maturation.Methods Ten healthy 3-month-old C57BL/6L wild-type mice(5 males,5 females,25～35 g)were bred to obtain offspring.Cochlear samples from postnatal days 1～30(P1～P30)were analyzed.Frequency-specific auditory brainstem response(ABR)thresholds were measured at 45.2,32.0,22.6,16.0,11.3,8.0,5.6,and 4.0 kHz in P12,P14,P16,P21,and P30 mice.Immunofluorescence assay combined with confocal laser scanning microscopy was used to scan cochlear whole-mount preparations.Spatiotemporal co-localization profiling of mGluR4 and synaptic markers Ctbp2 and Snap25 was observed,and quantitative comparisons of fluorescent puncta density were performed.Results ABR testing revealed undifferentiated waveforms in all P12 mice,while 70%of P14 mice exhibited well-defined Wave I.In P14,P16,P21 and P30,mice undergoing ABR testing,50%failed to exhibit ABR waveforms when stimulated by 45.2 kHz tones,and 87.5%showed no response to 32.0 kHz stimuli.Auditory response thresholds for other frequencies progressively decreased with increasing postnatal age.Immunolocalization demonstrated stronger mGluR4 expression in inner hair cells(IHCs)versus outer hair cells(OHCs).Distinct mGluR4 puncta were observed at IHC presynaptic active zones(co-localized with Snap25)as early as P11,but showed minimal overlap with CtBP2-labeled ribbons.Quantitative analysis revealed significantly higher mGluR4 puncta density at P30 compared to P14 synapses(P<0.05).Conclusion Postnatal upregulation of mGluR4 at IHC synaptic regions correlates with functional maturation.These findings suggest mGluR4 may modulate vesicular exocytosis regulation and exert pharmacological inhibition on glutamate release,potentially influencing synaptic plasticity during auditory pathway refinement.

Curcumin is a natural yellow pigment， a natural phenolic antioxidant extracted from the rhizomes of Curcuma longa and Curcumae Rhizoma of the ginger family， with anti-inflammatory， anti-tumor and antioxidant properties. In recent years， it has been found that curcumin also has good antidepressant properties， and it is considered a safe and effective antidepressant potential drug. The mechanism of curcumin’s antidepressant efficacy mainly includes regulating neurotransmitters， modulating the hypothalamic-pituitary-adrenal axis， regulating brain-derived neurotrophic factor， inhibiting neuroinflammation， inhibiting oxidative stress， and regulating gut microbiota， etc.， and there is an overlapping and synergistic therapeutic effect of the above mechanisms. At present， the antidepressant mechanism of curcumin is still not fully understood， and will be combined with multi-omics technology， new formulation technology， and clinical trials to obtain further breakthroughs in the future.

BACKGROUND: High temperatures are known to be associated with an increased risk of self-harm, but the influence of demographic changes and country-level indicators on the burden of heat-related self-harm remains unclear. This study examined the key factors driving changes in self-harm mortality linked to high temperatures and explored their impact at the country level. METHODS: This is an ecological study that analyzes data from the 2021 Global Burden of Disease (GBD) study, the World Bank, and the Climate Research Unit (CRU) were analyzed. Decomposition analyses were used to identify key factors driving changes in high temperature-related self-harm mortality between 1990 and 2021. A panel data model assessed the impact of national indicators on heat-related self-harm mortality. RESULTS: In 2021, 14,885 deaths globally were attributed to heat-related self-harm, a 41.94% increase from 1990, with low-middle SDI regions accounting for 47.84% of these deaths. While the global death rate from heat-related self-harm declined slightly over this period, South Asia and low-middle SDI regions contributed most to the decline. However, population aging exacerbated mortality rates. Demographic and meteorological factors were also linked to heat-related self-harm. CONCLUSION The global decline in heat-related self-harm mortality is largely driven by reductions in females, low-middle SDI regions, and South Asia. However, population aging and growth in these regions have added to the mortality burden, slowing the overall decline. Factors such as population density are also associated with heat-related self-harm. Targeted measures are needed to mitigate heat-induced self-harm more effectively in future.
Humans ; Self-Injurious Behavior/etiology* ; Hot Temperature/adverse effects* ; Global Health/statistics & numerical data* ; Female ; Male ; Adult ; Middle Aged ; Aged ; Young Adult ; Adolescent