Background Fatigue among distribution network live-line workers in complex operational environments has become increasingly severe and requires widespread attention. Objective To investigate the positive rates of fatigue and associated influencing factors of live-line power distribution workers, and to make a reasonable strategy to reduce the fatigue of front-line workers. Methods Power supply companies in Guangdong, Guangxi, and Yunnan provinces were selected by cluster sampling in 2023, and all front-line live-line workers in the selected companies were recruited. The questionnaire used in this study consisted of two parts: one was the Fatigue Scale-14 (FS-14) for investigating fatigue status and the other was for associated influencing factors. A FS-14 score greater than 3 points was defined as fatigue. \begin{document}$ {\chi }^{2} $\end{document} test and logistic regression were employed to analyze the factors affecting fatigue. Results A total of 1341 questionnaires were distributed, and 1217 valid questionnaires were recovered, with a valid response rate of 90.75%. The average fatigue score of the participants was (6.84±3.79) points, and a total of 1054 participants scored over 3, resulting a fatigue positive rate of 86.6%. The logistic regression model showed that working under extreme weather (OR=2.03, 95%CI: 1.38, 2.98), overtime 2-3 times a week (OR=5.24, 95%CI: 1.28, 21.40), overtime everyday (OR=6.95, 95%CI: 1.71, 28.27), frequent wrist rotation (OR=1.95, 95%CI: 1.08, 3.51), and leaning back slightly (OR=2.94, 95%CI: 1.19, 7.28) associated with higher positive rates of fatigue. Conclusion The high positive rate of fatigue among live-line power distribution workers suggests severe fatigue issues. Extreme weather conditions, working overtime frequency, and maintaining wrist rotation and backward bending postures during work are main factors affecting their fatigue.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Acute pancreatitis （AP） often has an acute onset， and although most cases are self-limiting， there is still a risk of rapid deterioration， posing a serious threat to the lives of patients. Currently， traditional assessment tools such as clinical scoring systems and serum biomarkers are widely used to determine disease severity and prognosis. To enhance the accuracy of assessment， combined detection strategies integrating different scores and biomarkers are often used in clinical practice； however， there are still certain limitations such as insufficient specificity， limited early sensitivity， and a lack of consistent cut-off values. Therefore， current studies are actively exploring novel biomarkers with superior specificity and sensitivity and continuously optimizing their combined application strategies. This article summarizes the current application status of traditional assessment tools and reviews the research advances in novel biomarkers.

ObjectiveTo develop and preliminarily validate a prediction model for brace treatment failure risk in patients with adolescent idiopathic scoliosis (AIS), based on information obtained before brace treatment and during initial brace fitting. MethodsA total of 191 patients with AIS who initiated thoracolumbosacral orthosis treatment at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from March, 2015 to August, 2024 and had determinable outcomes were retrospectively included. Patients were divided according to a prespecified scheme into a training set (n = 133) and a validation set (n = 58). Brace treatment failure was defined as progression of the major-curve Cobb angle by ≥ 5° from baseline during follow-up or at brace weaning, or a final major-curve Cobb angle > 45°. Logistic regression, random forest, support vector machine with radial basis function kernel, and extreme gradient boosting (XGBoost) models were developed using routinely available clinical and radiographic variables before brace treatment and during initial brace fitting. Stratified five-fold cross-validation was used for hyperparameter tuning in the training set. Model performance was evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), Brier score, calibration curves, and decision curve analysis (DCA). SHapley Additive exPlanations (SHAP) was used to interpret the main explanatory model. ResultsIn cross-validation of the training set, both random forest and XGBoost showed good discriminative performance, with cross-validation-AUC values of 0.871 and 0.880, respectively. In the validation set, the AUC values of random forest and XGBoost were 0.888 and 0.899, the AUPRC values were 0.678 and 0.830, and the Brier scores were 0.086 and 0.076, respectively. Random forest was selected as the primary model for interpretation, with a calibration intercept of 0.091 and a calibration slope of 0.995. SHAP analysis indicated that the in-brace correction rate and the major-curve Cobb angle measured in the brace contributed most to the model predictions. ConclusionThe random forest model developed using routinely available pretreatment and initial-fitting variables shows preliminary predictive value for brace treatment failure risk in AIS, and may provide quantitative support for follow-up scheduling, brace-fit reassessment and early adherence-oriented management.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

BACKGROUND: Blood glucose and serum albumin have been associated with cardiovascular disease prognosis, but the impact of admission-blood-glucose-to-albumin ratio (AAR) on adverse outcomes in critical ill coronary artery disease (CAD) patients was not investigated. METHODS: Patients diagnosed with CAD were non-consecutively selected from the MIMIC-IV database and categorized into quartiles based on their AAR. The primary outcome was 1-year mortality, and secondary endpoints were in-hospital mortality, acute kidney injury (AKI), and renal replacement therapy (RRT). A restricted cubic splines model and Cox proportional hazard models assessed the association between AAR and adverse outcomes in CAD patients. Kaplan-Meier survival analysis determined differences in endpoints across subgroups. RESULTS: A total of 8360 patients were included. There were 726 patients (8.7%) died in the hospital and 1944 patients (23%) died at 1 year. The incidence of AKI and RRT was 63% and 4.3%, respectively. High AAR was markedly associated with in-hospital mortality (HR = 1.587, P = 0.003), 1-year mortality (HR = 1.502, P < 0.001), AKI incidence (HR = 1.579, P < 0.001), and RRT (HR = 1.640, P < 0.016) in CAD patients in the completely adjusted Cox proportional hazard model. Kaplan-Meier survival analysis noted substantial differences in all endpoints based on AAR quartiles. Stratified analysis and interaction test demonstrated stable correlations between AAR and outcomes. CONCLUSIONS The results highlight that AAR may be a potential indicator for assessing in-hospital mortality, 1-year mortality, and adverse renal prognosis in critical CAD patients.

OBJECTIVE: To evaluate the efficacy and safety of a hospital-made resuscitation pack, a Chinese medicinal herbal compound formula designed to enhance recovery in post-bronchoscopy patients. METHODS: In this randomized, single-blind, placebo-controlled clinical trial, eligible patients were randomly assigned 1:1 to either the treatment or control groups. The patients in the treatment group applied the resuscitation pack, which contained aromatic compounded Chinese herbs. The patients in the control group applied a hospital-made, single herb placebo pack. Packs were placed on the Tiantu (CV 22) acupuncture point for 4 h as soon as the bronchoscopy finished. Efficacy indicators, such as recovery time, patients' symptoms including nausea and dizziness, and adverse events (AEs) were observed and compared. The outcome indices were evaluated at baseline, 1 and 24 h after the bronchoscopy. Subgroup analysis was further performed by patients' age and depth of sedation. RESULTS: When applying generalized estimating equations (GEE) to evaluate the intensity of post-bronchoscopy nausea and vomiting, the intensity was lower in the treatment group (163 cases) compared with the control group (162 cases; 95% CI: 0.004, 0.099, P=0.03]. Also, significantly lower intensity of nausea was observed in the 60-70 years of age subgroup (95% CI: 0.029, 0.169, P=0.006) and deep sedation subgroup (95% CI: 0.002, 0.124; P=0.04). There was no significant difference in dizziness between two groups by GEE (95% CI: -0.134, 0.297; P=0.459). In addition, no serious AEs were observed in either group. CONCLUSIONS Our study found that the resuscitation pack markedly improved patients' symptoms by reducing nausea and vomiting after bronchoscopy without AEs, compared with placebo in the perioperative period. (Trial registration No. ChiCTR2000038299).
Humans ; Male ; Middle Aged ; Female ; Bronchoscopy/adverse effects* ; Single-Blind Method ; Aged ; Drugs, Chinese Herbal/adverse effects* ; Treatment Outcome ; Resuscitation ; Adult ; Medicine, Chinese Traditional

Liver ischemia-reperfusion injury (LIRI) is a pathological process involving multiple injury factors and cell types, with different stages. Currently, protective drugs targeting a single condition are limited in efficacy, and interventions on immune cells will also be accompanied by a series of side effects. In the current bottleneck research stage, the multi-target and obvious clinical efficacy of Chinese medicine (CM) is expected to become a breakthrough point in the research and development of new drugs. In this review, we summarize the roles of reactive oxygen species (ROS) and reactive nitrogen species (RNS) in various stages of hepatic ischemia-reperfusion and on various types of cells. Combined with the current research progress in reducing ROS/RNS with CM, new therapies and mechanisms for the treatment of hepatic ischemia-reperfusion are discussed.
Reperfusion Injury/drug therapy* ; Reactive Oxygen Species/metabolism* ; Reactive Nitrogen Species/metabolism* ; Humans ; Liver/drug effects* ; Animals ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*

OBJECTIVE: To investigate the anti-inflammatory effect of rutaecarpine (RUT) on monosodium urate crystal (MSU)-induced murine peritonitis in mice and further explored the underlying mechanism of RUT in lipopolysaccharide (LPS)/MSU-induced gout model in vitro. METHODS: In MSU-induced mice, 36 male C57BL/6 mice were randomly divided into 6 groups of 8 mice each group, including the control group, model group, RUT low-, medium-, and high-doses groups, and prednisone acetate group. The mice in each group were orally administered the corresponding drugs or vehicle once a day for 7 consecutive days. The gout inflammation model was established by intraperitoneal injection of MSU to evaluate the anti-gout inflammatory effects of RUT. Then the proinflammatory cytokines were measured by enzyme-linked immunosorbent assay (ELISA) and the proportions of infiltrating neutrophils cytokines were detected by flow cytometry. In LPS/MSU-treated or untreated THP-1 macrophages, cell viability was observed by cell counting kit 8 and proinflammatory cytokines were measured by ELISA. The percentage of pyroptotic cells were detected by flow cytometry. Respectively, the mRNA and protein levels were measured by real-time quantitative polymerase chain reaction (qRT-PCR) and Western blot, the nuclear translocation of nuclear factor κB (NF-κB) p65 was observed by laser confocal imaging. Additionally, surface plasmon resonance (SPR) and molecular docking were applied to validate the binding ability of RUT components to tumor necrosis factor α (TNF-α) targets. RESULTS: RUT reduced the levels of infiltrating neutrophils and monocytes and decreased the levels of the proinflammatory cytokines interleukin 1β (IL-1β) and interleukin 6 (IL-6, all P<0.01). In vitro, RUT reduced the production of IL-1β, IL-6 and TNF-α. In addition, RT-PCR revealed the inhibitory effects of RUT on the mRNA levels of IL-1β, IL-6, cyclooxygenase-2 and TNF-α (P<0.05 or P<0.01). Mechanistically, RUT markedly reduced protein expressions of tumor necrosis factor receptor (TNFR), phospho-mitogen-activated protein kinase (p-MAPK), phospho-extracellular signal-regulated kinase, phospho-c-Jun N-terminal kinase, phospho-NF-κB, phospho-kinase α/β, NOD-like receptor thermal protein domain associated protein 3 (NLRPS), cleaved-cysteinyl aspartate specific proteinase-1 and cleaved-gasdermin D in macrophages (P<0.05 or P<0.01). Molecularly, SPR revealed that RUT bound to TNF-α with a calculated equilibrium dissociation constant of 31.7 µmol/L. Molecular docking further confirmed that RUT could interact directly with the TNF-α protein via hydrogen bonding, van der Waals interactions, and carbon-hydrogen bonding. CONCLUSION RUT alleviated MSU-induced peritonitis and inhibited the TNFR1-MAPK/NF-κB and NLRP3 inflammasome signaling pathway to attenuate gouty inflammation induced by LPS/MSU in THP-1 macrophages, suggesting that RUT could be a potential therapeutic candidate for gout.
Animals ; NF-kappa B/metabolism* ; Male ; Indole Alkaloids/therapeutic use* ; Signal Transduction/drug effects* ; Mice, Inbred C57BL ; Inflammation/complications* ; Uric Acid ; Quinazolines/therapeutic use* ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Humans ; Gout/chemically induced* ; Inflammasomes/metabolism* ; Cytokines/metabolism* ; THP-1 Cells ; Mitogen-Activated Protein Kinases/metabolism* ; Mice ; Molecular Docking Simulation ; Lipopolysaccharides ; Quinazolinones