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 evaluate the larvicidal effect of ultrasonic waves against Aedes albopictus larvae at various exposure parameters (distance and time), and to preliminarily investigate the effects of different containers (water volume and depth) and ultrasonic devices on the larvicidal efficacy, so as to provide experimental evidence for the application of ultrasound-based mosquito control technology. MethodsUnder controlled laboratory conditions, two commercially available ultrasonic devices [40 kHz/300 W and (50±5) kHz/70 W] were used to systematically examine the effects of exposure distance (20, 40, 60, 80, and 100 cm), exposure duration (1, 3, 6, 15 and 60 min), larval instar(Ⅰ‒Ⅱ and Ⅲ‒Ⅳ）, and container type on the immediate mortality of Aedes albopictus larvae collected from urban areas of Shanghai. Statistical analysis of the mortality rates of larvae among different experimental groups was performed using the chi-square test. ResultsUltrasonic exposure exerted a detectable larvicidal effect against Aedes albopictus larvae of all instars. For early-instar larvae, exposure time significantly affected mortality at all tested distances (20, 40, 60, 80 and 100 cm), with χ² values ranging from 25.57 to 32.74 ( all P<0.001). No significant distance effect was observed in the first and second instar larvae after short-term exposure (1 and 3 min; P>0.05). However, a distance-dependent effect emerged from 6 min onward (P<0.05). During short-term exposure (1 min and 3 min) at close range (20 cm and 40 cm), the immediate mortality of the third and fourth instar larvae was higher than that of the first and second instar larvae. Conversely, during prolonged exposure (15 min and 60 min), the first and second instar larvae exhibited significantly higher mortality than that of the third and fourth instar larvae. These results indicated that larval mortality was jointly influenced by exposure duration and distance. Preliminary experiments indicated that larvicidal efficacy in shallow water was lower than that in deep water. No significant difference in larvicidal effect was observed between the two ultrasonic devices with different frequencies and power outputs. ConclusionUnder laboratory conditions, ultrasound can effectively kill Aedes albopictus larvae, and the larvicidal effect is jointly influenced by larval instar, exposure distance, and aquatic environment. Compact ultrasonic devices show potential for field application in biological mosquito control.

To analyze the in vitro antibacterial effects of colistin (COL) or tigecycline (TGC) in combination with imipenem (IPM), amikacin (AMK), and cefoperazone-sulbactam (CSL) against carbapenem-resistant Acinetobacter baumannii(CRAB), so as to provide evidence for screening effective combination regimens for clinical microbial infections.

The shaoyang meridian is an important pivot between the internal organs and meridians system， with the functions of regulating qi and blood， balancing yin and yang， and coordinating the ascending and descending movement of qi. Dysfunction of the shaoyang pivot can lead to spleen and kidney deficiency， impaired liver and gallbladder qi regulation， and stagnation of qi and blood. It is believed that the onset and progression of Crohn's disease are closely related to shaoyang pivot dysfunction， with the core pathogenesis characterized by shaoyang disharmony， spleen deficiency， dampness retention， and blood stasis. Based on this understanding， the treatment principle centers on harmonizing the shaoyang pivot， supplemented by methods such as warming and nourishing the spleen and stomach， tonifying shaoyang， and soothing the liver and benefiting the gallbladder. Acupuncture is employed to target key acupoints along the shaoyang meridian to restore its regulatory functions， improve spleen and stomach transformation and transportation， facilitate liver and gallbladder qi flow， and promote the circulation of qi and blood. This provides a practical therapeutic approach for acupuncture-based treatment of Crohn's disease.

Objective To conduct a scoping review of research on the relationship between 24-hour movement behaviours and cognitive function in the elderly,so as to provide references for future research.Methods Totally 8 Chinese and English databases were systematically searched.The search period spanned from the establishment of databases until November 30,2024.According to the scoping review framework,2 researchers independently screened the studies,extracted the data of the included studies,and collaborated on the final analysis.Results A total of 12 papers were included,and the distribution of 24-hour movement behaviors in the elderly was as follows:3.0-5.4 h/d for light physical activity,0.6-1.5 h/d for moderate vigorous physical activity,8.9-12.3 h/d for sedentary behaviour and 6.7-8.4 h/d for sleep.Measures included objective,subjective and subject-objective measures.There are complex interactions among physical activity,sedentary behavior,sleep and cognitive function,which jointly affect cognitive function in the elderly.Conclusion Despite current differences in the measurement of 24-hour movement behaviours,the decreased physical activity,the increased sedentary time,and insufficient or excessive sleep are common problems among the elderly.By increasing physical activity,reducing sedentary behavior and ensuring adequate sleep,the overall cognitive function,executive function of the elderly can be improved.In the future,we should pay attention to the time allocation of 24-hour movement behaviours of the elderly,develop accurate and standardized measurement methods,and promote research in this field.

Objective We aimed to evaluate the efficacy and safety of Shengxuebao Mixture in the treatment of cancer-related anemia(CRA)presenting with syndrome of deficiency of liver and kidney combined with syndrome of deficiency of both qi and blood.Methods A randomized,double-blind,placebo-controlled,multicenter clinical trial was conducted.Eligible patients with malignant tumors meeting the inclusion and exclusion criteria were enrolled from 26 hospitals,including Dongzhimen Hospital,Beijing University of Chinese Medicine,Xiaogan Central Hospital,and Yangzhou Hospital of Traditional Chinese Medicine,from June 1,2022,to September 30,2024.Patients were allocated 1:1 to either the experimental group receiving Shengxuebao Mixture or the control group receiving its simulator(placebo)using a block randomization method under double-blind conditions.Both groups received 15 mL orally three times daily for 28 consecutive days.The primary efficacy indicators included the hemoglobin(Hb)improvement rate(RHb)and the traditional Chinese medicine(TCM)syndrome improvement rate(RTCM)at week 4 of treatment.The secondary efficacy indicators encompassed Hb and red blood cell(RBC)count,Karnofsky Performance Status(KPS)score,TCM syndrome score,individual TCM symptom scores,and changes in each of these indicators compared to the baseline period at weeks 2,4,and 6 of treatment.Safety evaluations were conducted at week 4 of treatment.Results A total of 239 patients were enrolled,with 225 cases included in the Full Analysis Set(FAS)(109 in the experimental group vs.116 control group),163 in the Per Protocol Set(PPS)(77 vs.86),and 225 in the Safety Set(SS)(109 vs.116).Baseline characteristics between groups showed no significant differences.Significant differences were observed between the experimental and control groups in RHb at week 4(FAS:49.51%vs.35.24%,P<0.05;PPS:53.25%vs.36.05%,P<0.05)and RTCM at week 4(FAS:61.54%vs.39.62%,P<0.01;PPS:64.94%vs.40.70%,P<0.01).At weeks 2,4,and 6,the experimental group showed greater improvements in Hb and RBC counts than the control group.Additionally,the TCM syndrome scores were lower in the experimental group than in the control group at these time points.Except for week 2 in PPS,the KPS improvement was better in the experimental group than in the control group(P<0.05).The experimental group also demonstrated a greater reduction in scores for individual TCM symptoms such as spiritlessness and weakness,poor appetite and reduced food intake at weeks 4 and 6 compared to the control group(P<0.05,P<0.01).Furthermore,the reduction in vertigo score was more pronounced in the experimental group at week 6(P<0.01).For the score of pale and lusterless complexion,only in the PPS was the reduction from baseline more significant in the experimental group than in the control group at weeks 4 and 6(P<0.05).No significant differences were observed between the experimental and control groups in the incidence of all adverse events or drug-related adverse reactions.Conclusion Shengxuebao Mixture demonstrates significant efficacy in patients with CRA presenting syndrome of deficiency of liver and kidney combined with syndrome of deficiency of both qi and blood,effectively increasing Hb levels,ameliorating TCM syndromes,alleviating clinical symptoms,and enhancing functional status,with no significant difference in adverse drug reactions compared to the placebo.

Nowadays,the incidence of allergic diseases is increasing worldwide,which seriously affects the quality of human life.Recent studies have shown that sex hormones are closely related to the occurrence of allergic diseases.Sex hormones can directly affect the function and development of immune cells,as well as the susceptibility to autoimmune cell responses,resulting in different prevalence and clinical manifestations of allergic diseases in men and women.This article reviews the different roles and potential mechanisms of sex hormones in the occurrence and development of common allergic diseases.In atopic dermatitis,the amount of dehy-droepiandrosterone sulfate into dehydroepiandrosterone sulfate is higher in females than in males.Therefore,females are more suscep-tible to the influence of dehydroepiandrosterone,which inhibits the proliferation of Th2,resulting in a series of clinical symptoms.In allergic asthma,estrogen can aggravate type 2 airway inflammation and androgens can reduce type 2 airway inflammation.Studies have found that there are estrogen and progesterone receptors in the nasal mucosa.When the estrogen concentration increases,the two re-ceptors are also up-regulated,resulting in clinical manifestations such as increased nasal secretions and nasal mucosal swelling.

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.