Background The quality of occupational health technical services is directly linked to the protection of workers' health rights and the efficacy of occupational disease prevention and control. However, the industry still faces critical challenges: sporadic instances of institutional non-compliance and persistent irregularities in professional practice continue to undermine overall service performance. Objective To assess the current quality status of occupational health technical services in Zhejiang Province and propose countermeasures for quality improvement, providing a scientific basis for policy optimization and service delivery quality enhancement. Methods A total of 69 occupational health technical service institutions in Zhejiang Province that obtained formal accreditation as of April 30, 2024, were sampled, including 3 public institutions and 66 private institutions (comprising 3 formerly Class-A, 28 formerly Class-B, 11 formerly Class-C, and 24 newly certified institutions). Following the Technical Protocol for Quality Monitoring of Occupational Health Technical Service in Zhejiang Province and the Technical Protocol for Proficiency Testing of Occupational Health Detection in Zhejiang Province, a quality assessment task force comprising national and provincial experts was established. Evaluation was conducted across four dimensions: qualification maintenance and compliance, standardization of technical services, authenticity of technical services, and proficiency testing, utilizing a combination of document review, on-site inspections, and technical skill assessments. Results The occupational health technical service institutions in Zhejiang Province were predominantly private entities (82.5%), with significant disparities in overall service quality. The pass rates for qualification maintenance and compliance, technical service standardization, technical service authenticity, and the excellence rate for laboratory proficiency testing were 81.5%, 80.7%, 97.3%, and 90.4%, respectively. Regarding qualification maintenance, the pass rates for "environmental conditions" (49.8%, 56.7%) and "instrumentation and equipment" (58.2%、65.6%) were significantly lower for formerly Class-C and newly certified institutions compared to other categories. In terms of technical standardization, "standardized on-site inspections" recorded the lowest pass rate (67.4%), with newly certified institutions at only 48.0%. Regarding technical service authenticity, formerly Class-C institutions exhibited issues such as missing raw chromatograms for blank samples (85.7% pass rate). In laboratory proficiency testing, public and formerly Class-A institutions achieved 100% excellence rates, but the performance of formerly Class-C and newly certified institutions was comparatively weak; specifically, the failure rate for organic analysis in formerly Class-C institutions reached 20%; the failure rate for dust testing items in newly certified institutions was 10.3%. Conclusion The overall quality of occupational health technical services in Zhejiang Province still requires significant improvement, particularly in basic institutional conditions, the standardization of on-site inspections, and laboratory proficiency in organic and dust analysis. Formerly Class-C and newly certified institutions should be the primary focus of quality management efforts. Differentiated regulatory strategies are recommended, alongside strengthening interim and ex-post supervision to gradually enhance the quality of occupational health technical services across all institutions.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

Objective To explore the clinical features, diagnosis, treatment and prognosis of testicular Ewing sarcoma(ES), so as to enhance the understanding and differential diagnosis of this disease. Methods A retrospective analysis was conducted on the clinical manifestations, auxiliary examinations and pathological findings of a case of left-sided ES treated at our hospital, supplemented by a review of relevant literature. Results A 24-year-old male patient presented with left testicular enlargement with pain. Magnetic resonance imaging suggested a neoplastic lesion, with a high likelihood of testicular germ cell tumor. A radical left orchiectomy was performed. Postoperative pathology revealed testicular ES. The patient subsequently completed 8 cycles of VDC/IE chemotherapy and showed no evidence of recurrence at 10 months of follow-up. Analysis of literature on 5 previously reported cases of testicular ES had testicular enlargement as the primary presentation. All patients underwent surgery and 4 received adjuvant therapy. Follow-up revealed 1 death at 9 months postoperatively, with no recurrence or progression seen in the remainder. Conclusion ES occurring in the testis is extremely rare.Testicular ES is a poorly differentiated small round-cell malignant tumor that primarily presents as testicular enlargement. Current treatment mainly surgical resection combined with adjuvant chemotherapy.

Morinda officinalis is one of the “Four Great Southern Medicines” and is commonly used in clinical practice to treat erectile dysfunction and nocturnal emissions caused by kidney yang deficiency， uterine cold infertility， menstrual disorders， low abdominal pain， rheumatism， and muscle and bone weakness. Based on the principle of “treating raw and cooked differently”， this article summarizes the effects of different processing methods on the chemical constituents and pharmacological effects of M. officinalis . Research has found that processing can affect the content and structure of sugars， iridoids， and anthraquinones in M. officinalis ， thereby regulating its pharmacological effects such as anti-osteoporosis， immune regulation， anti-fatigue， and anti-depression. Among them， salt M. officinalis shows outstanding performance in anti-osteoporosis and enhancing immunity. Although previous studies have preliminarily elucidated the major chemical constituents of M. officinalis and their pharmacological characteristics， the dynamic transformation paths of constituents during the processing remain to be further clarified， especially the es tablishment of a quality marker system associated with the processing technology， to achieve the precision and intelligent development of the processing.

Morinda officinalis is one of the “Four Great Southern Medicines” and is commonly used in clinical practice to treat erectile dysfunction and nocturnal emissions caused by kidney yang deficiency， uterine cold infertility， menstrual disorders， low abdominal pain， rheumatism， and muscle and bone weakness. Based on the principle of “treating raw and cooked differently”， this article summarizes the effects of different processing methods on the chemical constituents and pharmacological effects of M. officinalis . Research has found that processing can affect the content and structure of sugars， iridoids， and anthraquinones in M. officinalis ， thereby regulating its pharmacological effects such as anti-osteoporosis， immune regulation， anti-fatigue， and anti-depression. Among them， salt M. officinalis shows outstanding performance in anti-osteoporosis and enhancing immunity. Although previous studies have preliminarily elucidated the major chemical constituents of M. officinalis and their pharmacological characteristics， the dynamic transformation paths of constituents during the processing remain to be further clarified， especially the es tablishment of a quality marker system associated with the processing technology， to achieve the precision and intelligent development of the processing.

OBJECTIVE To study the mechanism of action of Rehmannia glutinosa-medicated serum （RG） in regulating lipopolysaccharide （LPS）-induced polarization of BV2 microglia to interfere with neuroinflammation. METHODS An in vitro neuroinflammation model of BV2 cells induced by LPS was established. Cells were divided into control group， LPS group， 10%RG group， 20%RG group， BAY 11-7082 [nuclear factor kappa B （NF-κB） inhibitor] group， and 20%RG+BAY 11-7082 group. Except for the control group， cells in all other groups were pretreated with corresponding drugs for 12 h and then stimulated with LPS for 24 h. The morphology of cells in each group was observed， and the fluorescence intensity of ionized calcium binding adaptor molecule 1 （Iba-1）， inducible nitric oxide synthase （iNOS）， CD206， the mRNA expression of tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， IL-1β， iNOS， IL-4， IL-10， transforming growth factor-β （TGF-β）， arginase-1 （Arg-1）， and the Toll-like receptor 4 （TLR4）/NF-κB/NOD-like receptor thermal protein domain associated protein 3 （NLRP3） signaling pathway-related protein expression were detected. RESULTS Compared with the control group， the LPS group showed significant changes in cell morphology， exhibiting a typical M1 activated morphology. The fluorescence intensity of Iba-1 and iNOS， the relative expression levels of TNF-α， IL-6， IL-1β， iNOS mRNA， the relative expression levels of TLR4， NLRP3， caspase-1 p20， IL-1β p17 protein， and the phosphorylation levels of NF-κB p65 and inhibitor of nuclear factor kappa B α were significantly increased （P＜0.05）. The fluorescence intensity of CD206 and the relative expression levels of IL-4， IL-10， TGF-β， and Arg-1 mRNA were significantly reduced （P＜0.05）. Compared with the LPS group， the changes in the above indicators in the cells of the 10%RG group， 20%RG group， BAY 11-7082 group， and 20%RG+BAY 11-7082 group were significantly reversed （P＜0.05）， and there was no statistically significant difference in the comparison of the last three groups （P＞0.05）. CONCLUSIONS RG can effectively inhibit the overall activation of microglia and correct their M1/M2 polarization imbalance， and its mechanism may be closely related to the inhibition of excessive activation of the TLR4/NF-κB/NLRP3 signaling pathway.

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.

ObjectiveTo investigate the risk factors for rebleeding after endoscopic therapy for esophageal and gastric varices in liver cirrhosis patients， to construct a clinical predictive model， and to provide a reference for predicting rebleeding in the early stage， reducing the incidence rate of rebleeding， and improving the clinical outcome of patients. MethodsA retrospective analysis was performed for the clinical data of 194 liver cirrhosis patients with gastroesophageal variceal bleeding who received initial endoscopic therapy at Department of Gastroenterology， The Second People’s Hospital of Lanzhou， from January 1， 2021 to May 31， 2025. According to whether rebleeding occurred within 1 year after endoscopic therapy， the patients were divided into rebleeding group and non-rebleeding group. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The patients enrolled were randomly divided into a training set and a validation set at a ratio of 7∶3. In the training set， the Lasso regression analysis was used to obtain optimal predictive variables， and the factors that might affect prognosis were included in the univariate and multivariate Logistic regression analyses to identify independent predictive factors for rebleeding after endoscopic therapy for esophageal and gastric varices in liver cirrhosis patients， which were used to construct a nomogram model. In both the training set and the validation set， the receiver operating characteristic （ROC） curve and the calibration curve were used to assess the discriminatory ability and calibration of the model， and decision curve analysis and the clinical impact curve were used to assess the clinical practicability of the model. ResultsAmong the 194 liver cirrhosis patients with esophageal and gastric varices， 116 （59.79%） experienced rebleeding within 1 year after endoscopic therapy， with 76 patients in the training set and 40 patients in the validation set. In the training set， the Lasso regression analysis and the univariate and multivariate Logistic regression analyses showed that etiology of liver cirrhosis （odds ratio ［OR］=3.540， 95% confidence interval ［CI］： 1.520 — 7.150， P<0.001）， Child-Pugh class （OR=3.560， 95%CI： 1.380 — 9.500， P=0.019）， severity of esophageal and gastric varices （OR=8.190， 95%CI： 3.568 — 17.850， P=0.026）， and main portal vein diameter （OR=2.954， 95%CI： 1.349 — 15.030， P=0.044） were independent predictive factors for rebleeding of esophageal and gastric varices in liver cirrhosis patients. A nomogram model was constructed based on the above independent predictive factors. The ROC curve analysis showed that this model had an area under the ROC curve of 0.845 （95%CI： 0.778 — 0.912） in the training set and 0.801 （95%CI： 0.798 — 0.868） in the validation set. The model had an index of concordance of 0.832 in the training set and 0.820 in the validation set， suggesting that the model had a good discriminatory ability. The Hosmer-Lemeshow test showed P values of 0.320 and 0.550 in the training set and validation set， respectively， the calibration curve indicated that the predicted probabilities of the nomogram model were in good concordance with the actual observed probabilities， suggesting that the model had good calibration. The decision curve analysis and the clinical impact curve showed that the model had good clinical utility. ConclusionThe nomogram model based on etiology of liver cirrhosis， Child-Pugh class， severity of esophageal and gastric varices， and main portal vein diameter has a certain clinical value in predicting the risk of rebleeding from esophageal and gastric varices in liver cirrhosis.

ObjectiveTo evaluate pharmacological effects of Shengmai injection（SMI）on cerebral ischemia and study its neuroprotective mechanism. MethodsMale specific pathogen-free （SPF） Sprague-Dawley （SD） rats were randomly divided into a sham group， a model group， a low-dose SMI group（3 mL·kg^-1）， a middle-dose SMI group（6 mL·kg^-1）， a high-dose SMI group（12 mL·kg^-1）， and a Ginaton group（4 mL·kg^-1）according to the random number table method， with 12 rats in each group. The rat model of cerebral ischemia-reperfusion（MCAO/R）was prepared via the suture method. The administration groups were intraperitoneally injected with corresponding concentrations of SMI or Ginaton injection after reperfusion， which was conducted for 3 consecutive days. The sham group and model group were administered the equivalent volume of physiological saline. The pharmacological effects of SMI on brain injury in MCAO/R rats were evaluated by neurological function scores， cerebral infarction area， hematoxylin-eosin （HE） staining， Nissl staining， terminal deoxynucleotidyl transferase dUTP nick-end labeling （TUNEL） staining， and Western blot. The dominant link and key protein of SMI treating cerebral injury were explored using proteomic analysis. The related mechanisms of SMI were further validated using enzyme-linked immunosorbent assay （ELISA）， Western blot， and chloride ion fluorescence probe with oxygen-glucose deprivation/reoxygenation（OGD/R）-treated PC12 cells and MCAO/R rats. ResultsCompared with the sham group， the model group showed significantly increased neurological function scores， cerebral infarction area， neuronal apoptosis rate， and expression levels of apoptosis related proteins （P<0.05， P<0.01）and significantly decreased density of Nissl bodies and neurons（P<0.01）. Compared with the model group， the SMI groups exhibited significantly decreased neurological function scores， cerebral infarction area， neuronal apoptosis rate， and expression levels of apoptosis related proteins （P<0.05， P<0.01）and significantly increased density of Nissl bodies and neurons （P<0.05）. The proteomic analysis results showed that oxidative stress and inflammatory response were important processes of SMI intervening in MCAO/R injury， and the chloride intracellular channel protein 1 （CLIC1） was one of key proteins in its action network. The levels of representative indicators of oxidative stress and inflammatory response in the MCAO/R rats of the SMI groups were significantly reduced， compared with those in the model group（P<0.05， P<0.01）， and the expression levels of CLIC1 and downstream NOD-like receptor protein 3 （NLRP3） decreased （P<0.01）. In addition， the experimental results based on the OGD/R PC12 cells showed that SMI significantly increased the cell survival rate（P<0.01） and significantly decreased the intracellular chloride ion concentration（P<0.05）. ConclusionSMI has neuroprotective effects. Oxidative stress and inflammatory response are key processes of SMI intervening in MCAO/R injury. The potential mechanism is closely related to the regulation of CLIC1.