Background Occupational health risk assessment is the foundation of safeguarding workers' occupational health. However, traditional assessment methods often fail to adequately account for health effects and enterprise-specific characteristics, limiting their comprehensive evaluation capabilities. Additionally, these methods suffer from inconsistent standards, narrow application scopes, insufficient hazard sub-categorization, and indicator systems that poorly support informatization and digital transformation. To address these gaps, this study proposes methodological innovations focusing on the assessment indicator system. Objective To construct a systematic, generalizable, and practical occupational health comprehensive risk assessment indicator system by leveraging occupational health practices and surveillance big data from Shanghai. Methods Initial system indicators were extrated through literature review. Subsequently, expert interviews and group discussions, combined with occupational health surveillance big data, were used to refine these indicators, forming a candidate pool covering two major dimensions: risk factor characteristics and enterprise characteristics. The Delphi method was applied to evaluate and screen the indicators, while the analytic hierarchy process (AHP) was used to construct a hierarchical model and determine indicator weights. Results A total of 76 articles were reviewed, identifying 25 candidate indicators. After two rounds of Delphi expert consultation, 8 primary indicators (e.g. hazard characteristics, exposure characteristics, health effects, industry characteristics, management characteristics, protective features, adverse events, and uncertainty) and 17 secondary indicators (hazard factor characteristics, exposure levels, number of people exposed, number of factor exposure, special physical exam indicators, suspected occupational diseases, occupational diseases, industry categories, organizational management, hazard reporting, occupational health training, hazard factor testing, occupational health exams, protective facilities, personal protective equipment, administrative penalties, and data quality) were finalized. The expert response rate was 100%, and the expert authority coefficient was 0.86. The Kendall's W coefficients for importance and accessibility scores across the two consultation rounds were 0.41, 0.40 and 0.41, 0.50. A hierarchical model targeting the comprehensive occupational health risk index was constructed, comprising two major elements and three levels of indicators. AHP was applied to calculate the weights, with all judgment matrices demonstrating satisfactory consistency (consistency ratio < 0.1). Conclusion By integrating risk factor profiles with enterprise-specific characteristics via the Delphi-AHP approach, a robust occupational health comprehensive risk assessment indicator system is established. This system provides a practical framework for digitized occupational health management, though further empirical validation in real-world settings is warranted.

OBJECTIVE To investigate the current status of informatization tools applied to antimicrobial stewardship in county hospitals in China， and to provide a reference for promoting the informatization development of antimicrobial stewardship in county hospitals.METHODS From August to September 2025， an online questionnaire survey was conducted among 1 007 county hospitals across 31 provinces（autonomous regions， and municipalities） in China. The survey focused on the application of four types of informatization tools：the real-time monitoring system for antimicrobial use， the pre-prescription review system， the irrational use warning system， and the electronic prescription evaluation system（hereinafter referred to as the “monitoring system”“review system”“warning system”“evaluation system”，respectively）. Correlation analysis and binary Logistic regression analysis were employed to explore the influencing factors.RESULTS Of the county hospitals， 80.83% were equipped with at least one type of informatization tool for antimicrobial stewardship， while 19.17% had no relevant tool. Only 18.87% of the hospitals were equipped with all four types of tools. The monitoring system exhibited the highest equipped rate （70.80%）， whereas the warning system was equipped in only 33.96% of the hospitals. Four types of tools are evenly and adequately deployed in the eastern region， the central and western regions have far lower deployment rates of intervention tools including review system and warning system， accompanied by prominent intra-provincial gaps. The total number of the health technicians， hospital grade， and prescription review rate of outpatient antibacterial drug were significantly and positively correlated with the deployment rates of the four informatization tools （ P ＜0.05）. The results of the Logistic regression model fitting indicated that the model of the review system was rated “excellent” [area under the receiver operating characteristic curve （AUC）＝0.81]， and the model of the warning system was rated “further improvement” （AUC＝0.67）. The total number of health technicians was significantly positively correlated with the deployment rates of all four types of informatization tools （all P ＜0.05）.CONCLUSIONS The informatization of antimicrobial stewardship in county hospitals in China remains in the initial stage of transitioning from “passive statistics” to “active prevention and control”， with challenges such as structural imbalance and regional disparities. In the future， differentiated support strategies should be implemented， the allocation of resources should be optimized， to enhance the level of refined antimicrobial stewardship.

BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surgical intervention remains the primary treatment option for early-stage lung cancer, and video-assisted thoracoscopic surgery (VATS) has become a common approach due to its minimal invasiveness and rapid recovery. However, post-discharge recovery remains incomplete, underscoring the importance of postoperative care. Traditional follow-up methods, lack standardization, consume significant medical resources, and increase the burden of the patients. Artificial intelligence (AI)-driven disease management platforms offer a novel solution to optimize postoperative follow-up. This study followed 463 lung cancer surgery patients using an AI-based platform, aiming to identify common postoperative issues, propose solutions, improve quality of life, reduce recurrence-related costs, and promote AI integration in healthcare. METHODS: Using the AI disease management platform, this study integrated educational videos, collaboration between healthcare teams and AI assistants, daily health logs, health assessment forms, and personalized interventions to monitor postoperative recovery. The postoperative rehabilitation status of the patients was assessed by the Leicester Cough Questionnaire (LCQ-MC). Two independent t-test and one-way ANOVA were used to analyze the causes of postoperative cough in lung cancer. RESULTS: Most issues occurred within 7 d post-discharge, significantly declined on 14 d post-discharge. Factors such as gender, smoking history, and surgical approaches were found to influence cough recovery. The incidence of cough on 7 d post-discharge in females was higher than that in males (P<0.01), while the incidence of cough on 14 d post-discharge in elderly patients was lower than that in young patients (P=0.03). The AI-based platform effectively addressed cough, pain, and sleep disturbances through phased interventions. CONCLUSIONS The AI-based platform significantly enhanced postoperative management efficiency and the self-care capabilities of the patients, particularly in phased cough management. Future integration with wearable devices could enable more precise and personalized postoperative care, further advancing the application of AI technology across multidisciplinary healthcare domains.
Humans ; Lung Neoplasms/rehabilitation* ; Male ; Female ; Middle Aged ; Aged ; Patient Discharge ; Artificial Intelligence ; Adult ; Postoperative Care ; Postoperative Period ; Disease Management ; Quality of Life

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.

Oral potentially malignant disorders (OPMD) refer to a group of diseases occurring on the oral mucosa that harbor the potential to progress into oral squamous cell carcinoma, including oral leukoplakia, oral erythroplakia, discoid lupus erythematosus of the oral mucosa, oral submucous fibrosis, oral lichen planus, actinic cheilitis, etc. Diabetes mellitus (DM) is one type of diseases characterized by chronic hyperglycemia, with a high incidence and mortality rate worldwide. Hyperglycemia is the characteristic metabolic change in DM patients and those in the pre-diabetic stage, playing a determinative role in many complications related to DM. A number of clinical studies had revealed an association between hyperglycemia and OPMD, as well as its malignant transformation. This article will review the potential regulatory effects and mechanisms of high glucose states, such as diabetes, on OPMD, and assess the correlation between hyperglycemia and the malignant transformation of OPMD.

Objective To analyze the risk factors for chronic mountain sickness(CMS)in young male migrants living in high-altitude areas and to construct a diagnostic model and evaluate its diagnostic efficacy.Methods From June 10 to December 29,2023,a cross-sectional study was conducted on young male migrants subjected with convenience sampling who had been living in high-altitude areas(4 500～5 000 m)for 6 months or longer.Their demographic data were collected and blood samples were collected for laboratory test.According to the Qinghai Score for Chronic Mountain Sickness,they were divided into CMS group and non-CMS group.Then the participants were randomly divided into a training set and a test set in a ratio of 8∶2.Independent risk factors for CMS occurrence were screened out,through random forest variable importance ranking,univariate and multivariable logistic regression analysis,and a diagnostic model was constructed based on these factors.Receiver operating characteristic(ROC)curve analysis,calibration curve analysis,clinical decision curve analysis,and influence curve analysis were used to comprehensively evaluate the diagnostic performance of the model.Results According to the inclusion and exclusion criteria,308 out of 376 participants were finally subjected,and 17.53%of them were diagnosed with CMS.The major clinical symptoms of the CMS patients were dyspnea or palpitations(79.63%)and sleep disorders(85.19%).Further analysis revealed that creatine kinase-MB/creatine kinase(CK-MB/CK,OR=2.17,95%CI:1.43～3.28),high-altitude residence time(OR=2.44,95%CI:1.08～5.54),and body mass index(BMI,OR=1.62,95%CI:1.05～2.50)were 3 major independent risk factors for CMS.The area under the curve(AUC)value of the CMS diagnostic model in the training set and test set was 0.821(95%CI:0.756～0.886)and 0.821(95%CI:0.700～0.944),the specificity was 66.30%and 73.90%,the sensitivity was 89.50%and 81.20%,respectively,indicating good discrimination ability.Hosmer-Lemeshow goodness-of-fit test showed consistency between predicted results and actual observations(χ2=10.029,P=0.263;χ2=4.477,P=0.812).Clinical decision curve analysis demonstrated that within the threshold probability range from 0.1 to 0.7,the net benefit of the model exceeded both full intervention and no intervention strategies.The influence curve analysis showed high consistency between the model predictions and actual incidence when the threshold probability exceeded 0.4.These two analyses together confirmed the clinical application value of the model.Conclusion CK-MB/CK,high-altitude residence time and BMI are independent risk factors for CMS,and their diagnostic model helps identify potential individuals at risk for CMS.Early intervention can prevent the harm of CMS to the health of young men migrating to high-altitude areas.

Objective To investigate the mechanism by which suppressor of cytokine signaling 3(SOCS3)regulates microglial inflammation through nuclear factor-kappaB(NF-κB),providing novel mechanistic insights into microglial involvement in Parkinson's disease(PD)pathogenesis.Methods ① Ten male C57BL/6 mice(12 weeks old,weighing 20～25 g)were subjected to intraperitoneal injection of 15 mg/kg MPTP to establish a PD model.Rotarod test was used to assess motor function.Western blotting was employed to detect the protein expression of tyrosine hydroxylase(TH)and ionized calcium-binding adapter molecule 1(IBA-1)in the substantia nigra.RT-qPCR was utilized to measure the mRNA level of SOCS3 in the substantia nigra.Immunohistochemistry was performed to assess NF-κB p65 subunit expression.The expression of SOCS3,NF-κB and p-NF-κB was measured with Western blotting.② Microglial cell line BV2 was stimulated with 1 000 ng/mL lipopolysaccharide(LPS)for 6 h to establish an inflammatory model.Subsequently,SOCS3 was knocked down.NF-κB inhibitor BAY 11-7082 was used to treat the cells.RT-qPCR and Western blotting were used to measure the expression of SOCS3 at mRNA and protein levels.Western blotting was also applied to detect the expression of NF-κB and p-NF-κB,and ELISA was conducted to measure TNF-α and IL-1β levels in the culture supernatant.Immunofluorescence assay was carried out to localize NF-κB(nuclear vs cytoplasmic).③ A co-culture system of BV2 microglia and N2a neuroblastoma cells was established to investigate the regulatory effects of microglia on neuronal cells.MTT assay and TUNEL staining were used respectively to determine cell viability and apoptosis of N2a cells.Results ① Compared to the control mice,the PD mouse model exhibited reduced rotarod fall latency,down-regulation in TH and SOCS3(P<0.01),up-regulation in IBA-1 and increased p-NF-κB/NF-κB ratio(P<0.01).② In BV2 cells,LPS stimulation increased TNF-α,IL-1β,and p-NF-κB/NF-κB ratio(P<0.01),while down-regulated SOCS3 expression(P<0.01).SOCS3 knockdown in LPS-stimulated BV2 cells further increased the p-NF-κB/NF-κB ratio(P<0.01),increased nuclear localization of NF-κB,and elevated TNF-α and IL-1β levels(P<0.01).BAY 11-7082 treatment in these SOCS3-knockdown,LPS-stimulated cells resulted in reduced p-NF-κB/NF-κB ratio,TNF-α,and IL-1β(P<0.01),and decreased NF-κB nuclear distribution.③ LPS-stimulated BV2 cells reduced cell viability and increased cell apoptosis in N2a cells(P<0.01).SOCS3 knockdown in BV2 cells exacerbated the reduction in N2a cell viability(P<0.01)and the increase in cell apoptosis in N2a cells(P<0.01).BAY 11-7082 treatment of these SOCS3-knockdown BV2 microglia attenuated the reduction in N2a cell viability and decreased apoptosis in N2a cells(P<0.01).Conclusion SOCS3 inhibits microglia inflammatory response through down-regulation of NF-kB activity,and in turn attenuates neuronal cell death and ameliorates PD nerve injury.

Objective To demonstrate that neferine(Nef)alleviates Parkinson's disease(PD)by inhibiting microglial pyroptosis mediated through the reactive oxygen species(ROS)/NOD-like receptor protein 3(NLRP3)/Caspase-1 pathway.Methods BV2 microglial cells were divided into:control group,lipopolysaccharides(LPS)-adenosine triphosphate(ATP)group,and LPS-ATP+Nef group.Pyroptosis was induced by 1 μg/mL LPS+5 mmol/L ATP,with 2 mmol/L Nef pretreatment.Eighteen 10-12-week-old male C57BL/6 mice(22～25 g)were randomly assigned to:control(n=6),1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)(n=6),and MPTP+Nef(n=6)groups.Detection methods included:flow cytometry for pyroptosis,Cell Counting Kit-8(CCK-8)for viability,2',7'-dichlorodihydrofluorescein diacetate(DCFH-DA)for ROS,commercial kits for malondialdehyde(MDA),superoxide dismutase(SOD),glutathione(GSH),ELISA/Western blot for interleukin-1β(IL-1β)/IL-18,immunofluorescence/immunohistochemistry for NLRP3/Caspase-1,tyrosine hydroxylase(TH)immunohistochemistry,hematoxylin-eosin staining for neuropathology,and modified neurological severity score(mNSS).Results Versus control,LPS-ATP group showed decreased viability(P=0.002),increased pyroptosis(P<0.001),elevated ROS(P<0.001)/MDA(P<0.001)/IL-1β(P<0.001)/IL-18(P<0.001),upregulated NLRP3(P<0.001)/Caspase-1(P<0.001),and reduced GSH(P<0.001)/SOD(P<0.001).Nef treatment reversed these effects(all P<0.05).According to the results of murine studies,compared with the control group,the MPTP group had increased mNSS(P<0.001)/tissue ROS(P<0.001),downregulated TH(P<0.001),upregulated NLRP3(P<0.001)/Caspase-1(P<0.001).Nef treatment significantly attenuated the MPTP-induced deleterious effects(P<0.05).Histopathological analysis revealed that control group exhibited uniformly distributed hippocampal neurons with distinct nuclear morphology;MPTP group showed neuronal swelling,interstitial edema,and nuclear atrophy;MPTP+Nef group demonstrated ameliorated neuronal damage.Conclusion Nef inhibits microglial pyroptosis via ROS/NLRP3/Caspase-1 axis,ameliorating PD neuroinflammation and pathology.

Objective To establish a human luminal breast cancer stem cell(BCSC)model and investigate the inhibitory effects of astragaloside Ⅳ(AS-Ⅳ)on BCSC growth.Methods MCF-7 breast cancer cells were cultured in stem cell-specific medium to induce BCSC formation.The BCSCs were then divided into a blank control group and an AS-Ⅳ treatment group,both groups were given PBS or AS-Ⅳ treatment.Morphological changes were observed after intervention.The therapeutic efficacy of AS-Ⅳ was evaluated using 3D spheroid formation and cell viability assays.Transcriptomic profiling and gene expression analysis were performed to elucidate the underlying mechanisms.Results Compared with the MCF7 breast cancer cells,MCF7 breast cancer stem cell mammospheres exhibited accelerated growth(P＜0.01)and significantly increased expression of the stemness marker ALDH1A1(P＜0.01).Further comparison with the blank control group revealed that astragaloside Ⅳ(AS-Ⅳ)treatment significantly inhibited MCF7 breast cancer stem cell proliferation(P＜0.001)and slowed mammosphere growth(P＜0.01).Transcriptomic analysis demonstrated that differentially expressed genes(DEGs)induced by stem cell modeling and AS-Ⅳ intervention were enriched in the cellular senescence signaling pathway.AS-Ⅳ intervention substantially increased the number of SA-β-gal-positive cells(P＜0.01).RT-PCR analysis confirmed that AS-Ⅳsignificantly upregulated mRNA expression of IL-1α(P＜0.01),P21(P＜0.001),and P53(P＜0.05)in MCF7 breast cancer stem cells.Conclusion Astragaloside Ⅳ suppresses the growth of human luminal breast cancer stem cells by inducing cellular senescence.