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.

Objective: To explore the prospective association between multidimensional sleep indicators and the risk of newlyonset dental caries, providing a reference for childrens oral healthrelated sleep intervention. Methods: In October 2021, 1 417 students in grades 1 to 4 (aged 6 to 11) from two elementary schools in Bengbu, Anhui Province, were selected by cluster sampling method. Surveys and followup visits were conducted at baseline (T1), November 2022 (T2), May 2023 (T3), and November 2023 (T4), respectively, including parental questionnaires, oral health and physical examination. Bedtime, sleep duration, sleep midpoint, social jet lag, weekend catchup sleep, and sleep habits were collected and calculated. A multifactorial Cox proportional risk regression model was used to analyze the association between multidimensional sleep indicators and newlyonset caries in schoolaged children after 2 years. Results: The prevalence of dental caries in children was 65.1% at baseline, and the prevalence was 59.0% at the end of the 2year followup. Cox proportional risk regression model showed that for every 1point increase in the childrens bedtime resistance, nocturnal awakenings, parasomnias, and daytime sleepiness scores, the risk of newlyonset caries increased by 12% (HR=1.12, 95%CI=1.08-1.15), 22% (HR=1.22, 95%CI=1.15-1.29), 12% (HR=1.12, 95%CI=1.08-1.17), and 15% (HR=1.15, 95%CI=1.12-1.19), respectively; the risk of newlyonset caries increased by 23% for each 1 h increase in the length of weekend catchup sleep (HR=1.23, 95%CI=1.14 -1.33); compared with children who went to bed before 21:00 on school days, those who went to bed later than 22:00 had a 57% higher risk of newlyonset caries (HR=1.57, 95%CI=1.22-2.03). Compared to children who slept adequately (≥9 h/d), those with insufficient sleep had a 67% higher risk of new caries (HR=1.67, 95%CI=1.43-1.95) (P<0.01). Conclusions These findings suggest a significant association between sleep patterns/sleep disorders and the development of childhood dental caries. Incorporating sleep behavior optimization and sleep quality improvement into comprehensive caries prevention and oral health management protocols may represent a promising intervention strategy to enhance childrens oral health outcomes.

Objective To analyze the clinical characteristics and prognostic risk factors of patients with atrial fibrillation(AF)related to septic shock admitted to the intensive care unit(ICU).Methods This retrospective cohort study included 152 patients with septic shock who were admitted to the ICU between January 2020 and December 2023.Patients were categorized into AF(n=48)and non-AF(n=104)groups based on the occurrence of AF.Clinical parameters were compared between the two groups,and variables with statistically significant differences(P<0.05)were entered into a multivariate logistic regression analysis to identify clinical features associated with AF.Patients were also stratified into survival(n=103)and death(n=49)groups based on 28-day outcomes.Variables showing signifi-cant intergroup differences(P<0.05)were further included in a multivariate model to identify independent risk factors for mortality.Kaplan-Meier survival analysis was performed using AF as a binary variable,and log-rank tests were applied to compare survival curves.Results The incidence of AF was 31.58%among patients with septic shock.Compared with the non-AF group,the AF group was older,received higher cumulative doses of vasoactive agents,and had elevated levels of lactate(Lac),N-terminal brain natriuretic peptide precursor(NT-proBNP),troponin I(cTnI),tumor necrosis factorα(TNF-α),and C-reactive protein(CRP).The AF group also had higher E/e'ratios,left ventricular ejection fraction(LVEF),Acute Physiology and Chronic Health Evaluation-Ⅱ(APACHEⅡ)scores,Sequen-tial Organ Failure Assessment(SOFA)scores,and 28-day mortality rates(all P<0.05).Multivariate logistic regression identified age(odds ratio[OR]=1.060,P=0.015),SOFA score(OR=1.525,P=0.001),TNF-α(OR=1.009,P=0.026),CRP(OR=1.008,P=0.002),and E/e'(OR=1.363,P=0.023)as independent risk factors for AF.The 28-day mortality rate was 32.24%.Compared with survivors,non-survivors had significantly higher Lac,cTnI,E/e',LVEF,and TNF-α levels,higher APACHEⅡand SOFA scores,longer ICU stays,and a higher incidence of AF(all P<0.05).Multivariate analysis identified SOFA score,cTnI,E/e',and AF as independent predictors of 28-day mortality.Kaplan-Meier analysis revealed significantly poorer survival in patients with AF(χ2=6.747,P=0.009).Conclusion AF is common in ICU patients with septic shock.Advanced age,greater organ dysfunction,elevated inflammatory markers,and diastolic dysfunction are associated with AF occurrence.Organ dysfunction,myocardial injury,diastolic dysfunction,and AF are inde-pendent predictors of mortality in this population.Greater clinical attention is warranted in patients with AF and septic shock due to their elevated risk of poor outcomes.

The xylitol dehydrogenase(XDH)is a crucial enzyme involved in the xylose utilization in pentose-catabolizing yeasts and fungi.In addition to producing xylulose,XDH can also be employed to develop a biosensor for monitoring xylitol concentration.In this study,the gene encoding the thermophilic fungus Talaromyces emersonii XDH(TeXDH)was heterologously expressed in Escherichia coli BL21(DE3)at 16 ℃ in the soluble form.Recombinant TeXDH with high purity was purified by using a Ni-NTA affinity column.Size-exclusion chromatography and SDS-PAGE analysis demonstrated that the puri-fied recombinant TeXDH exists as a native trimer with a molecular mass of approximately 116 kD,and is composed of three identical subunits,each with a molecular weight of around 39 kD.The TeXDH strictly preferred NAD+as a coenzyme to NADP+.The optimal temperature and pH of the TeXDH were 40 ℃and 10.0,respectively.After EDTA treatment,the enzyme activity of TeXDH decreased to 43.26％of the initial enzyme activity,while the divalent metal ions Mg2+or Ca2+could recover the enzyme activity of TeXDH,reaching 103.32％and 110.69％of the initial enzyme activity,respectively,making them the optimal divalent metal ion cofactors for TeXDH enzyme.However,the divalent metal ions of Mn2+,Ni2+,Cu2+,Zn2+,Co2+,and Cd2+significantly inhibited the activity of TeXDH.ICP-MS and molecular doc-king studies revealed that 1 mol/L of TeXDH bound 2 mol/L Zn2+ions and 1 mol/L Mg2+ion.Further-more,TeXDH exhibited a high specificity for xylitol,laying the foundation for the development of future xylitol biosensors.

T cell exhaustion plays an immunosuppressive role in malignant tumors. Continuous tumor antigen stimulation, the presence of suppressive immune cells and cytokines in the tumor microenvironment, the up regulation of inhibitory receptor expression on the surface of T cells, changes in T cell related transcription factors, and metabolites in the tumor microenvironment may lead to T cell exhaustion. Reversing the exhaustion of T cells in tumor patients is a promising strategy for tumor immunotherapy. This article will review the latest research progress on T cell exhaustion status, pathogenesis, reversal methods, and clinical applications in hematological tumors.
Humans ; Hematologic Neoplasms/immunology* ; T-Lymphocytes/immunology* ; Tumor Microenvironment ; Immunotherapy ; T-Cell Exhaustion

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

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.