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 address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

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.

Heat stroke is a heat-related illness caused by an imbalance between the body's heat production and heat dissipation,which could lead to multiple organ dysfunction syndrome with a high mortality rate.Rapid and effective reduction of core body temperature is key to successful treatment.This article reviews recent progress in the treatment of heat stroke,including new understandings of organ injury mechanisms,the timing,velocity and goals of cooling treatment,evaluation and selection of traditional cooling techniques(such as cold water immersion),and scientific evaluation of new cooling technologies(such as blood purification technology and intravascular heat exchange cooling technology),aiming to promote understanding and treatment of heat stroke.

Objective:To investigate the impact of early invasive arterial blood pressure (IBP) monitoring on survival and neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients undergoing extracorporeal cardiopulmonary resuscitation (ECPR).Methods:This retrospective cohort study analyzed 44 OHCA patients receiving ECPR between January 2021 and January 2023. Patients were divided into: Early intervention group : IBP established within 3 min of ECMO initiation; Late intervention group : IBP established after ICU admission. Baseline characteristics, ECMO parameters, and clinical outcomes were compared. Multivariable logistic regression (adjusted for age, initial rhythm, etc.) and Spearman's correlation were used.Results:This study included a total of 44 patients treated with OHCA and ECPR, divided into an early intervention group of 23 cases and a late intervention group of 21 cases. The early intervention group showed significantly higher: Survival to discharge (43.5% vs. 9.5%, P<0.05), Good neurological recovery (CPC 1-2: 34.8% vs. 9.5%, P<0.05).Early intervention independently predicted survival (adjusted OR=18.84, 95% CI:1.97-179.98, P=0.01). Stratified analysis by pH (cutoff 7.0) demonstrated consistent benefits in both pH>7.0 ( aOR=0.392, 95% CI:0.106-0.678) and pH≤7.0 subgroups ( aOR=0.385, 95% CI: 0.075-0.695; interaction P=0.183). Early IBP positively correlated with CPC scores ( ρ=0.40, P=0.007). Conclusions:Early IBP monitoring significantly improves survival and neurological outcomes in OHCA-ECPR patients, supporting its integration into standardized protocols.

Objective To observe the value of CT angiography(CTA)radiomics for evaluating the risk of basilar tip aneurysm(BTA)rupture.Methods Totally 133 BTA patients were retrospectively enrolled and divided into ruptured group(n=39)and unruptured group(n=94)based on BT A ruptured or not,also divided into training set(n=93)and test set(n=40)at the ratio of 7∶3.CTA radiomics features of BTA were extracted,the best radiomics features were screened,and the radiomics score(Radscore)was calculated.Then machine learning(ML)models were established with logistic regression(LR),random forest(RF),decision tree(DT)and K-nearest neighbor(KNN)algorithms,respectively.Radscore model was also established,and finally a combined model was constructed based on clinical data,routine imaging findings and Radscore.The efficacy of the above models for evaluating the risk of BTA rupture were comparatively analyzed.Results Finally 4 radiomics features of BTA were obtained.The area under the curve(AUC)of LR,RF,DT and KNN radiomics models for differentiating ruptured and unruptured BTA in training set was 0.770,0.816,0.817 and 0.795,respectively,while that in test set was 0.795,0.793,0.786 and 0.824,respectively,both being not significant different(both P＞0.05).Patient's gender,alcohol consumption history,BTA morphology and Radscore were all independent impact factors of BT A rupture(all P＜0.05),which were used to establish a clinical-routine imaging model.For all 133 cases,AUC of the combination model for differentiating ruptured and unruptured BTA was 0.877,of Radscore model was 0.775,while that of clinical-routine imaging model was 0.677,of the former was significantly higher than of the last two(both P＜0.05).Conclusion CTA radiomics was helpful for evaluating the risk of BTA rupture.Combining with clinical data and routine imaging findings could further improve the value of CTA radiomics.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To preliminarily explore whether sirtuin1 (SIRT1) activation can inhibit neuronal ferroptosis in rats after traumatic brain injury (TBI) by regulating hypoxia-inducible factor-1α (HIF-1α)-mediated glycolysis.Methods:(1) Six SD rats were randomly divided into sham-operated group and TBI group, with 3 rats in each group; TBI model in the TBI group was established by hydraulic impact method, and rats in the sham-operated group underwent same surgery without impact. Cortical tissues of the two groups were sent for tandem mass tag (TMT) labeled quantitative proteomics detection to analyze the differential expression proteome; Kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA) were used to detect pathway enrichment of the screened differential proteins. (2) Twelve SD rats were randomly divided into sham-operated group and 1-day, 3-day and 7-day post-TBI groups, with 3 rats in each group. Treatment methods were the same as above; Western blotting was used to detect SIRT1 protein expression. (3) Forty-eight rats were randomly divided into sham-operated group, TBI group, TBI+vehicle group and TBI+SIRT1 agonist group, with 12 rats in each group; rats in the sham-operated group and TBI group accepted treatment as above; rats in the TBI+SIRT1 agonist group were intraperitoneally injected with SRT1720 (dissolved in ≤ 5% dimethyl sulfoxide, at a dose of 20 mg/kg) within 30 minutes after modeling, twice a day (with an interval of 12 hours); and rats in the TBI+vehicle group were injected with same dose of dimethyl sulfoxide at the same time. One d after modeling, neurological deficit was assessed using modified Neurological severity score (mNSS), brain water content was measured by dry-wet weight method, histopathological changes in the cortical lesions were observed by HE staining, mitochondrial ultrastructure was examined by transmission electron microscopy, malondialdehyde (MDA) content and superoxide dismutase (SOD) activity in the brain tissues were detected by colorimetry, and protein expressions of SIRT1, HIF-1α (key protein in the glycolytic pathway), glutathione peroxidase 4 (GPX4, key protein in the ferroptosis pathway), and acyl-CoA synthetase long-chain family member 4 (ACSL4, key protein in the ferroptosis pathway) were evaluated by Western blotting.Results:(1) KEGG analysis revealed that the glycolysis pathway and HIF-1 signaling pathway were obviously enriched in the cortical tissues of rats in the TBI group compared with the sham-operated group; GSEA showed that the HIF-1 signaling pathway (mmu04066) and ferroptosis pathway (mmu04216) gene sets in the cortical tissues of rats in the TBI group exhibited enrichment trends compared with those in the sham-operated group. (2) Compared with the sham-operated group, the 1-day, 3-day, and 7-day post-TBI groups had significantly decreased SIRT1 protein expression ( P<0.05), with the most prominent decline in 1-day post-TBI group. (3) Compared with the TBI+vehicle group, rats in the TBI+SIRT1 agonist group showed significantly reduced mNSS score and brain tissue water content (9.83±1.17 vs. 7.66±1.21; [83.62±0.91]% vs. [80.09±0.68]%, P<0.05). HE staining indicated clearer structure of the cortical area at the injury sites, and improved neuron morphology in the TBI+SIRT1 agonist group compared with those in the TBI+vehicle group; and transmission electron microscopy showed reduced mitochondrial shrinkage and partial restoration of cristae structures in the TBI+SIRT1 agonist group compared with those in the TBI+vehicle group. Compared with the TBI+vehicle group, the TBI+SIRT1 agonist group exhibited significantly decreased MDA content ([62.72±9.20] nmol/g vs. [39.34±3.48] nmol/g), increased SOD activity ([1.95±0.23] U/mg vs. [2.48±0.14] U/mg), elevated GPX4 protein expression (0.37±0.04 vs. 0.46±0.03), and decreased HIF-1α and ACSL4 protein expressions (1.16±0.15 vs. 0.81±0.12; 1.14±0.06 vs. 1.29±0.04), with significant differences ( P<0.05). Conclusion:SIRT1 activation can exert neuroprotective effect by inhibiting HIF-1α-mediated glycolysis and reducing neuronal ferroptosis after TBI.

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.