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 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.

Objective:To investigate the clinical application of ultrasound-guided cervical plexus block combined with superior laryngeal nerve block in tracheotomy for burn patients.Methods:A total of 88 burn patients who underwent tracheotomy from January 2022 to December 2022 were divided into observation group(44 cases)and matched group(44 cases).The matched group received conventional general anesthesia,while the observation group underwent ultrasound-guided cervical plexus block combined with superior laryngeal nerve block.The operation time,anesthetic effect,intraoperative hemodynamic parameters,postoperative complications,and patient satisfaction were compared.Results:The surgery time in the observation group was shorter than that in the matched group(P＜0.05).The anesthetic effect in the observation group was superior to that in the matched group,with more stable intraoperative hemodynamics,and smaller fluctuations in heart rate and mean arterial pressure(P＜0.05).The incidence of postoperative cough reflex,hoarseness,postoperative pain score,and respiratory complications in the observation group were lower than those in the matched group(P＜0.05).Patient satisfaction in the observation group was higher than that in the matched group(P＜0.05).Conclusion:Ultrasound-guided cervical plexus block combined with superior laryngeal nerve block for tracheotomy in burn patients can effectively improve anesthetic effect,reduce operation time,stabilize intraoperative hemodynamics,reduce postoperative complications,and improve patient satisfaction,which is worthy of clinical application.

Objective:To evaluate the effects of low level laser therapy(LLLT)on accelerating tooth movement and reducing pain during orthodontic treatment.Methods:26 patients with malocclusion of class Ⅱ,division 1 were included.Maxillary teeth on left and right sides were selected randomly as the experimental side and control side.Dental arches of experimental side received the irra-diation of LLLT with 7.5 J/cm2 for each point,10 points for each tooth,and the control side received placebo treatment,with the la-ser light off.The pain and the rate of teeth movement on experimental and control sides were compared.Results:The mean score of pain at the control side was significantly higher than that of the experimental side in the 7 days(P＜0.001).The average movement rate of the experimental group was higher than that of the control group(P＜0.05).Conclusion:LLLT is effective in accelerating tooth movement and reducing the related pain.

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 evaluate the preventive effects of transcutaneous electrical acupoint stimulation (TEAS) on chronic pain after lumbar spine surgery.Methods:This was a secondary analysis conducted on the studies assessing the effect of TEAS on gastrointestinal function in patients undergoing lumbar spinal surgery. Fifty lumbar spinal stenosis patients of either sex, aged 50-75 yr, with a body mass index of 18.5-28.0 kg/m 2, of American Society of Anesthesiologists Physical Status cassification Ⅰ or Ⅱ, with expected operation time≥3 h, undergoing lumbar spinal surgery under general anesthesia, were enrolled and assigned into 2 groups ( n=25 each) using a random number table method: control group (C group) and TEAS group. In group C, stimulating electrodes were placed at the non-acupoint parts of the limbs, but no electrical stimulation was applied. In group TEAS, the bilateral Neiguan (PC6), Hegu (L14), Zusanli (ST36), Shangjuxu (ST37) and Xiajuxu (ST39) were stimulated with disperse-dense waves at a frequency of 2/100 Hz. The intensity of stimulation was the maximum current that patients could tolerate. The intervention was performed once a day for 30 min per session at 30 min prior to anesthesia induction and on postoperative days 1-7. Telephone follow-ups were conducted at 3, 6 and 12 months after surgery to record the occurrence of postoperative moderate-to-severe lower back pain and leg pain (Numerical Rating Scale score ≥4), and the Oswestry Disability Index (ODI) value and four-item neuropathic pain questionnaire scores. The pain-related medical visits and usage of nonsteroidal anti-inflammatory drugs were also recorded after surgery. Results:Three patients in each group were lost to follow-up. Compared with group C, the incidence of chronic low back pain was significantly decreased at 6-12 months after surgery, the ODI value and four-item neuropathic pain questionnaire scores were decreased at 12 months after surgery ( P<0.05), ODI value difference reached the minimal clinically important difference, the proportion of patients requiring medical visits due to postoperative pain and usage rate of nonsteroidal anti-inflammatory drugs were decreased at 6-12 months after surgery ( P<0.05), and no significant change in the incidence of chronic moderate-to-severe leg pain was found at each time period after surgery in group TEAS( P>0.05). Conclusions:TEAS can prevent the occurrence of chronic lower back pain and improve functional impairment in patients undergoing lumbar spine surgery.

Objective:To analyze the characteristics of cardiovascular and cerebrovascular diseases in patients with primary aldosteronism (PA) and compare them with age-, sex-, and blood pressure-matched patients with essential hypertension (EH).Methods:This cross-sectional study was conducted at the West China Hospital of Sichuan University. Patients with PA and EH between December 2018 and December 2021 were included. Demographic characteristics, stroke events, coronary artery diseases, peripheral vascular diseases, and cardiac structure and function indicators were analyzed. Propensity score matching (PSM) was used to balance non-study data. The t-test, chi-square test, and Wilcoxon signed-rank test were used for data comparison. The cardiovascular and cerebrovascular damage in the patients with unilateral and bilateral PA were also compared. Results:A total of 336 and 369 patients with PA and EH, respectively, were enrolled in this study. One hundred and ninety-eight patients from each group were included after PSM; no significant differences were found in terms of age, gender, and blood pressure. The prevalence of stroke in the PA group was considerably higher than that in the EH group [12.6% (25/198) vs. 5.6% (11/198), P=0.014], due to the significantly greater risk of ischemic stroke [10.0% (20/198) vs. 4.5% (9/198), P=0.029]. The prevalence of hemorrhagic stroke, coronary artery disease, peripheral arterial stenosis, aorta atherosclerosis, and aneurysm in the PA group were also higher than those in the EH group, but there was no statistical significance (all P>0.05). More patients with PA had concurrent left ventricular hypertrophy [22.2% (44/198) vs. 9.1% (18/198)], left atrial enlargement [40.4% (80/198) vs. 30.3% (60/198)], ventricular septal thickening [50.0% (99/198) vs. 36.9% (73/198)], and aortic widening [21.7% (43/198) vs. 13.1% (26/198)] than those with EH (all P<0.05). Compared with the bilateral PA group, the unilateral PA group had higher prevalence of left ventricular hypertrophy [28.3% (51/180) vs. 13.4% (11/82), P=0.013]. Conclusions:Compared with well-matched patients with EH, patients with PA have significantly higher risks of cardiovascular and cerebrovascular diseases, which are mainly manifested in increased prevalence of stroke and severe damage to the cardiac structure. Patients with unilateral PA may suffer more severe cardiac damage than those with bilateral PA.

Aim To explore the material basis and un-derlying mechanism of Qingre Huoxue Formula(QRHXF)in the treatment of non-small cell lung cancer(NSCLC)by applying network pharmacology,molecular docking technology and bioinformatics com-bined with animal experiments.Methods TCMSP,ECTM,and BATMAN databases were used to obtain active components and corresponding targets of QRHXF;GEO and DisGeNENT databases were con-ducted to acquire NSCLC-associated differential expres-sion genes.By intersecting them,the common targets were obtained.It was chosen to construct a herb-com-ponent-disease network and protein-protein interaction(PPI)network.Furthermore,DAVID database was used to perform gene ontology(GO)function and Kyo-to encyclopedia of genes and genomes(KEGG)path-way enrichment analyses.The molecular docking was presented by adopting Autodock Vina program to verify key targets.RNA-seq datawere downloaded from TC-GA database to obtain differential gene expression.Ka-planMeier(KM)analysis was performed to analyze the relationship between gene expression and overall sur-vival.Mouse subcutaneous tumor model of LLC was established.The effects of QRHXF on body weight,tumor volume and weight were monitored for pharmaco-dynamic analysis.Tumor tissues slides were stained with hematoxylin and eosin(HE)for histopathological examination.Immunohistochemistry(IHC)staining was employed for detecting Ki67 and EP300.Western blot was performed to measure the protein expression of TP53,CDK1 and NTRK1.Results The results of net-work pharmacology showed that a total of seven com-mon targets were screened from NSCLC and QRHXF,and the effect of QRHXF on anti-NSCLC may occur via multiple signaling pathways,including cell cycle.The results of molecular docking indicated that the main ac-tive components of QRHXF had low binding energy and stable docking conformation with the molecular target for treating NSCLC.According to bioinformatic analy-sis,there were significant differences in BRCA1,CDK1 and NTRK1 mRNA expression between tumor tissues and normal tissues,which were also prognostic factors for overall survival.Animal experimental research showed QRHXF inhibited subcutaneous tumor growth(P＜0.01)and improved the quality of life in mice with NSCLC.After QRHXF intervention,the density of tumor cells was significantly reduced,and necrotic are-as were increased.The expressions of Ki67 and EP300 were significantly decreased.Compared with the model group,Western blot showed up-regulation of TP53 and NTRKA(P＜0.05),whereas CDK1 were down-regu-lated(P＜0.05).Conclusion QRHXF exerted anti-NSCLC effects by regulating NTRK1,EP300,TP53,CDK1 and inducing cell cycle,cell cycle arrest and in-hibiting tumor growth,metastasis and angiogenesis.

OBJECTIVE: To elucidate how spinal manipulative therapy (SMT) exerts its analgesic effects through regulating brain function in lumbar disc herniation (LDH) patients by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: From September 2021 to September 2023, we enrolled LDH patients (LDH group, n=31) and age- and sex-matched healthy controls (HCs, n=28). LDH group underwent rs-fMRI at 2 distinct time points (TPs): prior to the initiation of SMT (TP1) and subsequent to the completion of the SMT sessions (TP2). SMT was administered once every other day for 30 min per session, totally 14 treatment sessions over a span of 4 weeks. HCs did not receive SMT treatment and underwent only one fMRI scan. Additionally, participants in LDH group completed clinical questionnaires on pain using the Visual Analog Scale (VAS) and the Japanese Orthopedic Association (JOA) score, whereas HCs did not undergo clinical scale assessments. The effects on the brain were jointly characterized using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Correlation analyses were conducted between specific brain regions and clinical scales. RESULTS: Following SMT treatment, pain symptoms in LDH patients were notably alleviated and accompanied by evident activation of effects in the brain. In comparison to TP1, TP2 exhibited the most significant increase in ALFF values for Temporal_Sup_R and the most notable decrease in ALFF values for Paracentral_Lobule_L (voxelwise P<0.005; clusters >30; FDR correction). Additionally, the most substantial enhancement in ReHo values was observed for the Cuneus_R, while the most prominent reduction was noted for the Olfactory_R (voxelwise P<0.005; clusters >30; FDR correction). Moreover, a comparative analysis revealed that, in contrast to HCs, LDH patients at TP1 exhibited the most significant increase in ALFF values for Temporal_Pole_Sup_L and the most notable decrease in ALFF values for Frontal_Mid_L (voxelwise P<0.005; clusters >30; FDR correction). Furthermore, the most significant enhancement in ReHo values was observed for Postcentral_L, while the most prominent reduction was identified for ParaHippocampal_L (voxelwise P<0.005; clusters >30; FDR correction). Notably, correlation analysis with clinical scales revealed a robust positive correlation between the Cuneus_R score and the rate of change in the VAS score (r=0.9333, P<0.0001). CONCLUSIONS Long-term chronic lower back pain in patients with LDH manifests significant activation of the "AUN-DMN-S1-SAN" neural circuitry. The visual network, represented by the Cuneus_R, is highly likely to be a key brain network in which the analgesic efficacy of SMT becomes effective in treating LDH patients. (Trial registration No. NCT06277739).
Humans ; Magnetic Resonance Imaging ; Intervertebral Disc Displacement/diagnostic imaging* ; Male ; Female ; Brain/diagnostic imaging* ; Adult ; Manipulation, Spinal/methods* ; Middle Aged ; Lumbar Vertebrae/physiopathology* ; Pain Management ; Rest ; Case-Control Studies

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique