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.

Objective To evaluate the effect of a multidisciplinary collaborative quality control management (hereinafter referred to as "QC management") on improving the performance of biological safety cabinets in hospital. Methods A total of 63 ClassⅡbiological safety cabinets in active use at Peking University Third Hospital were selected as the study subjects using the before-after study mode. Conventional management was implemented on the biological safety cabinets from 2018 to 2021. QC management was used in 2022. The compliance of biological safety cabinets management norm and performance differences under the two models were compared. Results The median and the 25th and 75th percentiles [M(P₂₅, P₇₅)] of the service life among these 63 biological safety cabinets were 3 (1,6) years. The overall performance pass rate and inflow velocity pass rate of biological safety cabinets were higher in the QC management than that in the conventional management (90.5% vs 65.1%, 96.8% vs 84.1%, both P<0.05). However, there was no significant difference in downflow velocity, high-efficiency particulate air filter integrity, cleanliness, airflow smoke pattern, noise, and illumination pass rates of biosafety cabinets before and after the implementation of QC management (79.4% vs 88.9%, 90.5% vs 100.0%, 96.8% vs 100.0%, 85.7% vs 100.0%, 100.0% vs 100.0%, and 85.7% vs 96.8%, respectively; all P>0.05). Conclusion sQC management improves the standardization of biological safety cabinet management and key performance indicators in hospital.

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 investigate cisplatin-induced cardiovascular toxicity and explore the protective effects and potential mechanism of curcumin co-treatment. METHODS: Forty adult male Sprague-Dawley rats were numbered and randomly divided into control group, cisplatin group (7.5 mg/kg, once a week, for 2 weeks), curcumin group (200 mg/kg per day, for 2 weeks) and cisplatin+curcumin group (cisplatin 7.5 mg/kg, once a week, and curcumin 200 mg/kg per day for 2 weeks) by a random number table method, with 10 rats in each group. Cardiac and vascular morphology and functions were assessed using hematoxylin-eosin and Masson's trichrome staining, serum indexes detection, echocardiography, electrocardiogram (ECG), blood pressure monitoring, vascular ring isometric tension measurement, and left ventricular pressure evaluation. The expressions of extracellular signal-regulated kinases (ERK) and phosphorylated-ERK (p-ERK) were analyzed by immunohistochemical staining. RESULTS: Cisplatin treatment induced notable cardiac alteration, as evidenced by changes in cardiac morphology, elevated serum enzymes (P<0.05), ECG abnormalities, and increased left ventricular end-diastolic pressure (P<0.05). Meanwhile, cisplatin significantly increased arterial pulse pressure (P<0.01), primarily due to a decrease in diastolic blood pressure. Severe fibrosis was also observed in the thoracic aorta wall. In vascular ring experiments, cisplatin treatment led to a significant reduction in phenylephrine-induced contraction (P<0.05) and acetylcholine-induced relaxation (P<0.01). Notably, Curcumin co-administration significantly alleviated cisplatin-induced cardiovascular damages, as demonstrated by improvement in these parameters. Furthermore, ERK expression in the myocardium and p-ERK expression in vascular smooth muscle cells were significantly upregulated following curcumin co-treatment. CONCLUSIONS Curcumin protects the heart and vasculature from cisplatin-induced damages, likely by upregulating ERK/p-ERK expression. These findings suggest that curcumin may serve as a promising therapeutic strategy for mitigating cisplatin-associated cardiovascular toxicity during tumor chemotherapy. In vitro cell culture experiments are needed to clarify the underlying mechanism.
Animals ; Curcumin/therapeutic use* ; Cisplatin/adverse effects* ; Rats, Sprague-Dawley ; Male ; Up-Regulation/drug effects* ; Extracellular Signal-Regulated MAP Kinases/metabolism* ; Phosphorylation/drug effects* ; Electrocardiography ; Blood Pressure/drug effects* ; Rats ; MAP Kinase Signaling System/drug effects*

Triple-negative breast cancer (TNBC) remains a refractory subtype of breast cancer due to its resistance to various therapeutic strategies. In this study, we introduce a "brake-release and accelerator-pressing" approach to engineer a microneedle patch embedded with copper-doped Prussian blue nanoparticles (Cu-PB) and the ferroptosis inducer sorafenib (SRF) for raised chemodynamic (CDT)/photothermal (PTT) combination therapy against TNBC. Upon transdermal insertion, the dissolving microneedles swiftly disintegrate and facilitate the release of SRF. Under gentle external light exposure, copper ions (Cu²⁺) and iron ions (Fe³⁺) were liberated from Cu-PB. The direct chelation of Cu²⁺ and the indirect suppression by SRF, collectively attenuate glutathione peroxidase 4 (GPX4) enzymatic function, destabilizing the cellular redox equilibrium (referred to as the "brake-release" strategy). The release of Cu²⁺ and Fe³⁺ ions instigates a Fenton/Fenton-like reaction within tumor cells, further yielding hydroxyl radicals and elevating reactive oxygen species (ROS) concentrations (referred to as the "accelerator-pressing" strategy). This overwhelming ROS accumulation, coupled with the impaired clearance of resultant lipid peroxides (LPO), ultimately triggers a robust ferroptosis cell death response. In summary, this study presents an innovative combinatorial therapeutic strategy based on dual-ferroptosis induction for TNBC, implying a promising therapeutic platform for developing ferroptosis-centered treatments for this aggressive breast cancer subtype.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

A novel analytical method was developed in this study by combining online solid phase extraction with ultra performance liquid chromatography-tandem mass spectrometry(Online SPE-UPLC-MS/MS)for simultaneous determination of 50 kinds of steroid hormones in surface water.Specifically,after high-speed centrifugation of 4 mL water samples,the supernatant was directly injected into an Oasis HLB online SPE column for enrichment and purification.Subsequently,the target compounds were transferred to the analytical column via valve switching for separation and analysis.The chromatographic separation was performed on a Thermo Acclaim RSLC C18 column(100 mm×2.1 mm,2.2 μm),using a mobile phase composed of 5 mmol/L ammonium fluoride aqueous solution and acetonitrile.Mass spectrometric detection was conducted in positive ion mode,utilizing multiple reaction monitoring(MRM)with quantification achieved by the internal standard method.The method validation demonstrated that the limits of detection(LOD)for the 50 kinds of steroid hormones ranged from 0.02 to 0.50 ng/L,while the limits of quantification(LOQ)were between 0.08 and 1.67 ng/L.The average recoveries in surface water samples at spiked concentrations of 5,20 and 200 ng/L were between 74.1％and 119％,with relative standard deviations(RSDs)of 0.2％to 9.9％.This method was applied to analyze 11 surface water samples collected from sites surrounding a pharmaceutical and chemical industrial park.A total of 44 kinds of steroid hormones were detected,with concentrations ranging from 0.11 to 88.6 ng/L,revealing the presence of hormone contamination in the environmental waters surrounding industrial areas.Compared with the traditional offline SPE methods,the proposed online SPE technique significantly reduced sample volume requirements and pretreatment time,while minimizing the loss of target compounds during the pretreatment process.Moreover,compared to reported online SPE techniques,this method achieved high-throughput analysis of multiple classes of steroid hormones,with lower detection limits and higher recoveries.Overall,this method provided rapid sample preparation,high sensitivity,and excellent stability,making it suitable for the direct analysis of trace steroid hormones in surface water.

OBJECTIVE: To observe the clinical symptoms and MRI outcomes of patients with ruptured lumbar disc herniation(LDH) through a multicenter randomized controlled study, and to evaluate the clinical efficacy and safety of Yiqi Huoxue formula() in the treatment of this disease. METHODS: A total of 160 outpatients and inpatients with ruptured LDH admitted to 4 medical centers from January 2023 to June 2023 were selected and randomly divided into the Yiqi Huoxue formula group and the control group, with 80 patients in each group. In the Yiqi Huoxue formula group, there were 43 males and 37 females, with an age of (41.03±9.56) years and a disease duration of (10.45±25.37) days, and the patients were treated with Yiqi Huoxue formula. In the control group, there were 34 males and 46 females, with an age of (42.14±8.73) years and a disease duration of (11.31±21.14) days;during the acute phase, patients in this group could take celecoxib capsules orally, and methylcobalamin orally at the same time. The Japanese Orthopaedic Association (JOA) score, Oswestry disability index (ODI), changes in the volume of herniated disc tissue on MRI, herniation rate, and absorption rate were recorded at the time of enrollment and during follow-ups at the 3rd, 6th, and 12th month after treatment. RESULTS: A total of 156 patients completed the clinical follow-up, and 4 patients withdrew midway. The clinical symptoms of all patients who completed the study were relieved to varying degrees, and reabsorption of herniated disc tissue was observed in all patients in the Yiqi Huoxue formula group after treatment. For the JOA score:in the Yiqi Huoxue formula group, it was (10.73±2.76) points before treatment and (24.65±2.19) points at the 12th month after treatment;in the control group, it was (11.01±1.20) points before treatment and (17.07±3.26) points at the 12th month after treatment. For the ODI score:in the Yiqi Huoxue formula group, it was (26.21±3.55) points before treatment and (5.65±2.19) points at the 12th month after treatment;in the control group, it was (27.92±2.51) points before treatment and (9.09±2.15) points at the 12th month after treatment. At the 12th month after treatment, the JOA and ODI scores of both groups were better than those before treatment, and the scores of the Yiqi Huoxue formula group were better than those of the control group, with statistically significant differences (P<0.05). In terms of the herniated disc volume and herniation rate on MRI, the Yiqi Huoxue formula group was superior to the control group, with statistically significant differences(P<0.05). Reabsorption occurred in 56.96%(45/79) of patients in the Yiqi Huoxue formula group, which was significantly higher than the 37.66%(29/77) in the control group. CONCLUSION After treatment with Yiqi Huoxue formula, patients with ruptured LDH show significant improvement in clinical symptoms and a marked reduction in the volume of herniated discs. During the follow-up period, no obvious adverse drug reactions are observed in patients, and no recurrence of symptoms is found at the last follow-up, indicating that the formula has safe and reliable efficacy.
Humans ; Male ; Female ; Intervertebral Disc Displacement/drug therapy* ; Adult ; Drugs, Chinese Herbal/adverse effects* ; Middle Aged ; Lumbar Vertebrae

Objective:To systematically evaluate the current financing status of Beijing's urban and rural residents'basic medical insurance,analyze equity disparities among different groups under the existing flat-rate financing policy.By simulating the equity changes of various financing schemes with different contribution rates,this study aims to provide foundations for advancing medical insurance financing system reform.Methods:Based on the per capita disposable income and number of insured residents in Beijing's 16 districts from 2018 to 2023,we separately calculated the Gini coefficient,concentration index,and Kakwani index,along with their changes before and after financing adjustments,to assess the funding burden among different insured groups.Using the geometric mean method,we projected per capita disposable income and insured populations for each district in Beijing from 2024 to 2035,simulating various financing schemes under different premium rate systems.Results:From 2018 to 2023,the Gini coefficient of net income after financing consistently exceeded that of original income before financing.The concentration index remained positive and showed an upward trend,while the Kakwani index was negative for all periods.The Gini coefficient after financing slightly decreased for the elderly and working populations with fiscal subsidy support,whereas it remained higher than that for students and children.Under the simulated differentiated rate system,the post-funding Gini coefficient for 2024-2035 was lower than the original value,and the Kakwani index was positive.Conclusions:The current fixed-amount financing mechanism for urban and rural residents'basic medical insurance exhibits regressive characteristics and insufficient fairness,with disparities in equity among different insured groups.It is necessary to establish differentiated financing standards based on differential rates,particularly implementing a financing mechanism with dynamic adjustments according to regional and group income levels,to enhance the fairness of financing for urban and rural residents'basic medical insurance.