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.

OBJECTIVE To investigate the antidepressant mechanism of Shugan hewei tang （SGHWT） based on the metabolomics of prefrontal cortex （PFC）-nucleus accumbens （NAc）-ventral tegmental area （VTA） neural circuit. METHODS Male SD rats were randomly divided into blank group， model group， SGHWT low-， medium- and high-dose groups [3.67， 7.34， 14.68 g/（kg·d）， by raw material]， and fluoxetine group [1.58 mg/（kg·d）， positive control]， with 12 rats in each group. Except for the blank group， the depression model was established by chronic unpredictable mild stress combined with individual cage housing in the remaining groups， and the corresponding drug solution or normal saline was administered via gavage during modeling， once a day， for 6 consecutive weeks. After the last administration， the body weight， sucrose preference rate， total moving distance， frequency into the center and immobility time of rats in each group were detected. Samples of PFC， NAc and VTA areas of rats in the blank group， model group， SGHWT medium-dose group and fluoxetine positive control groups were collected，and their histomorphological features were observed， and non-targeted metabolomics analysis （except for fluoxetine group）were performed and validated. RESULTS Compared with model group， the cytolysis， structural damage and other pathological damages in three brain regions of rats were significantly alleviated in each drug group， while their body weight， sucrose preference rate， total moving distance and frequency into the center were all significantly higher or longer （P＜0.05）， and immobility time was significantly shorter （P＜0.05）. The results of non-targeted metabolomics showed that a total of 78 endogenous differential metabolites were identified， with 40， 35 and 24 in the PFC， NAc and VTA regions respectively， mainly involved in amino acid， lipid and sphingolipid metabolism. The results of metabolic pathway enrichment analysis showed that SGHWT affected the neural circuits of depressed rats by regulating sphingolipid metabolism， alanine， aspartic acid and glutamic acid metabolism， saturated fatty acid biosynthesis， among which alanine， aspartic acid and glutamic acid metabolism was predominantly involved. Validation experiments showed that SGHWT significantly increased the phosphorylation levels of protein kinase B （Akt） and mammalian target of rapamycin （mTOR）， and decreased the protein expression of N-methyl-D-aspartic acid receptor 1 （NMDAR1） in the NAc region of rats. CONCLUSIONS SGHWT significantly improves the depression-like behavior and attenuates pathological damage of PFC-NAc-VTA neural circuit of model rats， the mechanism of which is associated with inhibiting NMDAR1 expression and activating the Akt/mTOR signaling pathway.

Objective: To explore the relationship of physical exercise behavior with mobile phone addiction and mental health of college students, so as to provide evidence for interventions to improve mobile phone addiction and mental health of college students. Methods: From October 8 to December 20 in 2024, 896 college students from 4 colleges in Beijing were selected using a combination of convenience sampling and stratified random cluster sampling method. Physical Activity Rating Scale (PARS-3), Mobile Phone Addiction Tendency Scale (MPATS), Adolescence Mental Health Diathesis Questionnaire (AMHDQ) and Symptom Checklist 90 (SCL-90) were used. The correlation of mobile phone addiction and mental health on physical exercise behavior of college students were analyzed by multivariable Logistic regression and linear regression. Results: Among the surveyed college students, 504 (56.25%) students had low exercise, 262 (29.24%) had moderate exercise, 130 (14.51%) had high exercise, and 392 (43.75%) had sufficient exercise. The total score of PARS-3 was 18.00 ( 15.00 , 33.00) points. Logistic regression analysis showed that the total score of MPATS ( OR=1.022, 95%CI =1.008-1.036), the total score of SCL-90 ( OR=1.010, 95%CI = 1.005 -1.015), the total AMHDQ score ( OR=0.995, 95%CI =0.992-0.998) were significantly associated with insufficient exercise among college students ( P <0.05). Linear regression analysis showed that the scores of MPATS, AMHDQS and SCL-90 were significantly correlated with physical exercise behavior ( B=-0.20, 0.04, -0.07, P <0.05). Conclusion The physical exercise behavior of college students is related to mobile phone addiction and mental health.

Congenital fibrosis of extraocular muscles (CFEOM) syndrome is a genetically determined congenital disorder characterized by non-progressive ophthalmoplegia, restrictive ocular fixation, and ptosis. Its estimated incidence is approximately 1 in 230 000 to 250 000. This paper reports a family with type 3 CFEOM diagnosed at the Second Xiangya Hospital of Central South University. The proband was a 10-year-old female who presented with right esotropia and right upper eyelid ptosis. Whole-exome sequencing revealed a heterozygous c.904G>A mutation in the TUBB3 gene. Genetic testing of family members identified that the proband's mother carried the same mutation and exhibited left eyelid ptosis. The child underwent strabismus correction followed by ptosis repair, both of which led to marked postoperative improvement. For children presenting with congenital extraocular movement restriction and ptosis, genetic testing plays a crucial role in confirming the diagnosis and guiding family analysis. Additionally, individualized surgical intervention can significantly improve both ocular function and cosmetic appearance.
Humans ; Female ; Child ; Ophthalmoplegia/congenital* ; Fibrosis/congenital* ; Blepharoptosis/surgery* ; Mutation ; Tubulin/genetics* ; Pedigree ; Male ; Esotropia/genetics* ; Congenital Cranial Dysinnervation Disorders

Reactive astrocytes, which exhibit a correlation with the degeneration of dopaminergic neurons, are present in a considerable number during the progression of Parkinson's disease (PD). However, the underlying factors shaping astrocyte reactivity and neuroinflammation in PD remain inadequately elucidated. Here, we demonstrate that fibroblast growth factor 7 (FGF7)/FGF receptor 2 (FGFR2) autocrine signaling intensifies astrocyte reactivity and inflammation. Genetic deletion of Arrb2, β-Arrestin2 encoding gene, led to escalated astrocyte reactivity in MPTP-treated mice, which was further substantiated in astrocyte-specific Arrb2 knockdown mice. RNA sequencing profiling of Arrb2 knockout astrocytes identified Fgf7 as a critical effector of astrocyte reactivity. Subsequently, conditional knockdown of Fgf7 and its receptor Fgfr2 in astrocytes elicited advantageous effects for MPTP-treated mice by restraining the inflammatory phenotypic transition of reactive astrocytes. Furthermore, deletion of astrocytic Fgf7 mitigated MPTP-induced pathology in Arrb2 knockout mice. Mechanistically, STAT1 was distinguished as the transcription factor suppressing Fgf7 expression, while β-Arrestin2 counteracted the proteasomal degradation of STAT1 by binding to RNF220, an E3 ubiquitin ligase for STAT1. More importantly, selectively engaging dopamine D2 receptor (Drd2)/β-Arrestin2-biased signaling using the agonist UNC9995 exhibited therapeutic potential in MPTP-treated mice via moderation of astrocytic FGF7 production, thereby restoring balance in astrocyte reactivity. Collectively, our study bridges a crucial knowledge gap by elucidating the novel functions of FGF family members within the central nervous system, particularly within the context of PD. The autocrine signaling of FGF7/FGFR2 represents a novel mechanism and a potential druggable target for modulating astrocyte-derived inflammation.

Inflammatory bowel disease (IBD) is an autoimmune disorder involving complex immune regulation, where balancing localized and systemic immunosuppression is a key challenge. This study aimed to enhance the therapeutic efficacy by engineering the probiotic Escherichia coli Nissle 1917 (EcN). We removed endogenous plasmids pMUT1 and pMUT2 from wild-type EcN and expressed the mPD-L1 (19‒238 aa)-mFc fusion protein on the bacterial surface using a cytolysin A (ClyA) fragment. This modification stabilized mPD-L1 (19‒238 aa) protein expression and promoted its recruitment to outer membrane vesicles (OMVs). The engineered strain, EcNΔ_pMUT1/2-ClyA-mPD-L1-mFc (EcN-ePD-L1-mFc), features conditional ePD-L1-mFc expression under the araBAD promoter, enhancing gut-targeted release and reducing systemic side effects. This strain improved treatment targeting and efficiency by enabling direct ePD-L1-mFc interaction with immune cells at inflammation sites. OMVs from this strain induced Treg proliferation, inhibited effector T cell proliferation in vitro, and significantly improved intestinal inflammation and colonic epithelial barrier repair in vivo. Additionally, the bacterium restored intestinal microbiota balance, increasing Lactobacillaceae and reducing Bacteroides. This study highlights the engineered bacterium's potential for targeted intestinal immune modulation and offers a novel local IBD treatment approach with promising clinical prospects.

OBJECTIVES: To explore the efficacy of low-intensity pulsed ultrasound (LIPUS) combined with nystatin for treatment of vaginal Candida albicans biofilm infection. METHODS: In vitro cultured Candida albicans biofilm were treated with LIPUS, nystatin, or both, and the minimum inhibitory concentration (MIC) of nystatin was determined. Crystal violet staining, confocal laser microscopy (CLSM) and scanning electron microscopy were used to quantify the biofilm and observe the activity and morphological changes of the biofilms; DCFH-DA was used to detect the changes in reactive oxygen species (ROS). Twenty female New Zealand White rabbits with vaginal inoculation of Candida albicans biofilm were randomized into 4 groups for treatment with normal saline, LIPUS, nystatin, or both LIPUS and nystatin. The changes in vulvar symptoms of the rabbits were observed, and the histopathological and ultrastructural changes of the vagina before and after treatment were observed using HE staining and transmission electron microscopy. RESULTS: In the combined treatment group, the MIC₅₀ and MIC₈₀ of nystatin in Candida albicans biofilms were both reduced by 50% compared with those in nystatin group, and the biofilm clearance rate increased by 26% and 68% compared with nystatin and LIPUS groups, respectively. Compared with nystatin and LIPUS treatment alone, the combined treatment produced stronger effects for inhibiting biofilm activity, causing structural disruption and promoting ROS production. In the rabbit models, the combined treatment more effectively improved vulvar symptoms and inflammatory infiltration, reduced residual vaginal hyphae/strains, and improved ultrastructure of the vaginal epithelium than LIPUS and nystatin treatment alone. CONCLUSIONS LIPUS combined with nystatin produces a significant synergistic antifungal effect against Candida albicans biofilm both in vitro and in vivo.
Animals ; Rabbits ; Female ; Biofilms/drug effects* ; Candida albicans/physiology* ; Nystatin/therapeutic use* ; Candidiasis, Vulvovaginal/microbiology* ; Ultrasonic Waves ; Antifungal Agents/therapeutic use* ; Vagina/microbiology* ; Ultrasonic Therapy ; Microbial Sensitivity Tests ; Combined Modality Therapy