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.

Background Air pollution remains a critical public health issue, with persistent exposure to air pollutants continuing to pose significant health risks. Currently, research investigating the association between air pollution and myocardial infarction mortality in Shenzhen remains inadequate. Objective To quantitatively assess the association between air pollutants and myocardial infarction mortality in residents. Methods Based on the mortality surveillance system of Shenzhen Center for Disease Control and Prevention, we conducted a time-stratified case-crossover study of 10089 permanent residents who died from myocardial infarction in Shenzhen between 2013 and 2022. Using residential address information, we obtained individual-level exposure data for air pollutants from the China High Air Pollutants dataset and meteorological factors from the China Meteorological Administration Land Data Assimilation System. A time-stratified case-crossover study design was employed to construct a conditional logistic regression model to assess the association between short-term exposure to air pollutants and myocardial infarction mortality. The exposure-response relationship was visualized, and a comprehensive health risk assessment was performed. Results This study included a total of 10 089 cases of myocardial infarction deaths in Shenzhen. The median [interquartile range (IQR)] concentrations of fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃) in Shenzhen from 2013 to 2022 were 24.59 (20.19) μg·m⁻³, 42.85 (28.42) μg·m⁻³, 8.53 (3.39) μg·m⁻³, 29.47 (13.56) μg·m⁻³, 0.77 (0.27) mg·m⁻³, and 86.53 (51.39) μg·m⁻³, respectively. The moving average concentrations of PM_2.5 and PM₁₀ over the current day and the previous 2 days (lag02) showed the highest risk of myocardial infarction mortality, with an odds ratio (OR) and 95% confidence interval (95%CI) of 1.004 (1.001, 1.007) and 1.004 (1.002, 1.006), respectively. At lag05, SO₂ demonstrated the strongest association with the risk of myocardial infarction mortality, with an OR (95%CI) of 1.042 (1.019, 1.065). The exposure-response relationships of PM_2.5, PM₁₀, and SO₂ with myocardial infarction mortality were approximately linear, whereas NO₂ exhibited a nonlinear relationship. At lag05, the highest risk of myocardial infarction mortality associated with NO₂ exposure was observed when the NO₂ concentration was ≤21.92 μg·m⁻³, with an OR (95% CI) of 1.024 (1.003, 1.046). The health risk assessment indicated that, using the WHO Air Quality Guidelines as the reference, the local PM_2.5 and NO₂ exposure led to an excess mortality of 398 and 298 cases, respectively. The sensitivity analysis revealed that after adjusting for O₃ and restricting the study period to 2013—2019, the effect estimates for PM_2.5, PM₁₀, NO₂, and SO₂ on myocardial infarction mortality slightly increased. Conclusion Short-term exposure to air pollutants, including PM_2.5, PM₁₀, NO₂, and SO₂, could increase the risk of myocardial infarction mortality. This study provides important scientific evidence for environmental health risk assessment and environmental management in Shenzhen.

Aim To investigate the protective effect of Gualou Guizhi granules(GLGZG)on neuronal injury induced by LPS-activated microglia based on Notch signaling pathway.Methods LPS-activated microglia were co-cultured with neurons to construct neuron inju-ry models,and the cells were divided into the control group,model group,Notch inhibitor(DAPT)group,GLGZG(50,100,200 mg·L-1)group,DAPT+100 mg·L-1GLGZG group.After intervention,the activity of HT22 cells was detected by CCK-8 method,and rel-ative mRNA expression was detected by real-time PCR.The relative protein expression was detected by Western blot.Results Compared with the model group,after GLGZG intervention,the cell activity was significantly improved,GLGZG decreased IL-6,IL-12,Bax,Notch 1,caspase-3,Delta-1,NICD,RBPSUH,HES1 expression,and increased Bcl-2 expression(P＜0.05).Compared with the model group,the NICD,RBPSUH and HES1 mRNA and protein expressions significantly decreased after DAPT treatment(P＜0.05),and there was no superposition effect with GLG-ZG.Conclusion GLGZG may play a neuroprotective role by inhibiting inflammatory factors and apoptosis,and inhibiting Notch signaling pathway.

Objective:To analyze the spatiotemporal correlation between the surveillance data of influenza in students reported by medical institutions and school absenteeism due to illness, and evaluate the application of Bayesian Structural Time Series model (BSTS) in the prediction of school influenza epidemic.Methods:A total of 13 schools in Dapeng new district of Shenzhen were selected. The incidence data of influenza in schools in Shenzhen from January 1, 2015 to December 31, 2019 were collected from China Disease Control and Prevention Information System and the illness related school absentence data during this period were collected from Shenzhen Student Health Surveillance System, and the spatiotemporal correlation between the data from two systems was analyzed and compared. BSTS was used to make long-term predictions of the monthly incidence of influenza in students in 2019 and short-term predictions of the weekly incidence of influenza in week 1-8 and week 45-52 of 2019 by using the data from two systems.Results:There was a temporal correlation between the data from China Disease Control and Prevention Information System and the data from Shenzhen Student Health Surveillance System ( r=0.93, P<0.001), and the lag of the former one was 1 day ( r=0.73, P<0.001). Influenza outbreaks were randomly distributed in different schools in Shenzhen, and there was no spatial correlation. The root mean square error ( RMSE) and mean absolute error ( MAE) were 0.35 and 0.28, respectively, in the long-term prediction, and the RMSE was 0.33 and 0.34, and the MAE was 0.26 and 0.28, respectively, in the short-term predictions of week 1-8 and week 45-52 of 2019, respectively, showing good prediction accuracy and fitting effect. Conclusion:By analyzing the data from China Disease Control and Prevention Information System and Shenzhen Student Health Surveillance System with BSTS, the dynamics of the school influenza epidemic can be accurately predicted, and effective technical support can be provided for the early warning and prevention and control of influenza epidemic.

Objective:To screen bile acid-related characteristic genes in IgA nephropathy (IgAN) based on the feature gene selection algorithm in the machine learning method, aiming to exploring the molecular biological mechanisms and biomarkers of IgAN.Methods:The gene expression data and sample grouping information of GSE93798, GSE116626 and GSE35487 were downloaded from the Gene Expression Omnibus (GEO). Bile acid-related gene sequences were obtained from the Molecular Signatures Database (MSigDB). R language was used to identify differentially expressed genes between IgAN samples and healthy control samples. Candidate genes were obtained by intersecting differentially expressed genes and bile acid-related genes. The least absolute shrinkage and selection operator (LASSO) algorithm in machine learning was used to screen the feature genes in the candidate genes as biomarkers, and the feature genes in the training set and validation set were analyzed by the rate of change index. Receiver operating characteristic curve (ROC) method was used to evaluate the diagnostic value of identified bile acid related characteristic genes for IgAN. Gene set enrichment analysis (GSEA) was used to analyze the Spearman correlation between the characteristic genes and all other genes and their related metabolic pathways. The expression of disease-characteristic genes in the kidney tissues of IgAN rats was validated by real-time PCR.Results:Gene expression information from kidney tissue samples of 20 IgAN cases and 22 healthy controls were obtained from GEO database. A total of 204 bile acid-related genes including 24 pathways were obtained from MSigDB. The results of gene differential expression analysis showed that 333 genes in the kidney tissues of IgAN patients were differentially expressed compared with those of healthy controls, including 102 up-regulated genes and 231 down-regulated genes, among which 12 differentially expressed genes were related to bile acid genes, as follows: NR1H4,SLC23A1, ALDH8A1, FABP1, ALB, SLC27A2, DIO1, CYP8B1, BBOX1, PIPOX, AKR1C1 and SLC10A2. Five characteristic genes ( NR1H4, SLC23A1, FABP1, ALB and AKR1C1) were screened by LASSO regression algorithm.ROC analysis results showed that in GSE93798 cohort genes, the AUC of NR1H4, SLC23A1, FABP1 and ALB genes with differential expression was >0.95 respectively in diagnosing IgAN, and that of AKR1C1 genes with differential expression was >0.85 in diagnosing IgAN. The gene expression data of SLC23A1 in GSE35487 cohort was missing. ROC analysis results of other four genes showed that the AUC of differential expression of ALB gene for IgAN was >0.95 respectively, that of NR1H4 gene was >0.70, and that of both FABP1 and AKR1C1 gene was >0.60. In the GSE116626 cohort genes, the AUC of five disease characteristic genes ( NR1H4, SLC23A1, FABP1, ALB, AKR1C1) for diagnosing IgAN was >0.60, respectively. These results suggested that 5 characteristic genes have certain distinguishing ability between IgAN group and control group. GSEA results were displayed that the characteristic genes were related to butyric acid metabolism, propionic acid metabolism, arginine and proline metabolism, valine leucine and isoleucine degradation, fatty acid metabolism, etc. These results suggested that five characteristic genes might be related to IgAN through the above metabolic mechanisms. The verification results of five bile acid characteristic genes in the rat model of IgAN in the kidney tissue showed that the expressions of four genes, NR1H4, SLC23A1, FABP1 and ALB, were higher than those of the control group, and there was no statistical significance in the expression of AKR1C1 gene between the two groups. Conclusions:The expression of bile acid-related characteristic genes is abnormal in the kidney tissue of IgAN patients. Four bile acid-related differentially expressed genes, NR1H4, SLC23A1, FABP1 and ALB, are expected to be biomarkers for non-invasive diagnosis and therapeutic targets .

A throat swab sample from a pediatric case in Tongzhou District, Beijing was identified as enterovirus; the patient was a 1-year-and-8-month-old male sporadic case. Whole-genome sequencing revealed a viral genome length of 7 436 bp. BLAST alignment confirmed the serotype as EV-D68. Phylogenetic analysis of the whole genome indicated that this strain belongs to the B3 clade, showing closer genetic proximity to the 2018 Shanghai strain MW697453 with 99.53% whole-genome nucleotide homology. Genetic and amino acid variation analysis demonstrated that the B3 subclade to which this strain belongs exhibits a nucleotide deletion at positions 718–726, differing from deletion sites observed in other B3 clade strains. A key neuropathogenic amino acid site, T650A, was found to have undergone mutation. Recombination analysis confirmed no cross-clade recombination events in this strain. This study conducted genetic characterization of the strain's evolutionary relationship with EV-D68 strains from different regions and years in China, providing data support for formulating prevention and control measures against EV-D68 infection.

Idiopathic pulmonary fibrosis(IPF)is a chronic progressive disease with a short survival time after diagnosis.Current treatments using western medicines have shown poor efficacy and lung transplantation is costly,highlighting the need to find new,safe,and effective treatments.Animal experiments are important for investigating the mechanisms of drug action,and suitable animal models of IPF are required for experimental research.Bleomycin is commonly used to induce IPF models.Traditional Chinese medicine(TCM)has the advantages of multiple therapeutic targets and few adverse reactions,and is gradually gaining attention for the treatment of IPF.Ongoing experimental research is being carried out to verify the specific targets and mechanisms of TCM in the treatment of IPF,utilizing animal models of IPF.This review considers the selection of animal models of IPF,the method used to induce,establish,and evaluate the models,and the interventional effects of TCM.We also summarize the best modeling method for animal models of IPF and the current status of TCM treatments to provide a basis for further scientific research and the clinical treatment of IPF.

Objective:To establish a three-dimensional culture and stress-loaded model of human periodontal ligament cells(hP-DLCs)in vitro and to determine the effect of static pressure on autophagy.Methods:Periodontal tissue was scraped from fresh ex-tracted tooth surfaces for culture and hPDLCs were obtained.Type Ⅰ rat tail collagen was extracted to prepare collagen-sodium algi-nate composite hydrogel,in which third-generation hPDLCs were embedded.After 72 h of culture,gene expression of autophagy-related proteins LC3,Atg-5 and Beclin-1 was detected by quantitative real-time polymerase chain reaction(qRT-PCR),and the expression of Atg-5,Beclin-1 and LC3 was detected by Western blotting.Results:Cells grew well in collagen-alginate hydrogels.After 15 min of compressive stress loading,the level of autophagy of hPDLCs increased significantly and then gradually decreased to the baseline level.Conclusion:Collagen-alginate hydrogel has good biocompatibility and safety,and can be used as an excellent scaffold for three-dimensional cell culture in vitro.Static compressive stress can accelevate autophagy,and this acceleration is rapid and short-lived.

Aim To explore the protective effect of the isochroman compound Asperisochroman B(AB)on oxygen-glucose deprivation/reoxygenation(OGD/R)injury of neurons based on the PI3K/AKT/Foxo1 path-way and to reveal the related mechanism.Methods Primary neurons were cultured and the OGD/R model was constructed.The primary neurons were divided in-to the blank control group,OGD/R group,and AB low,medium,and high concentration(3,10,30 μmol·L-1)groups.The effects of AB on primary neurons were determined by CCK-8 assay,lactate dehydrogen-ase(LDH)release assay,and Hoechst 33342 stai-ning.The expression levels of PI3K,AKT,and Foxo1-related proteins were detected by Western blot.After intervention with the PI3K inhibitor(LY294002)and re-modeling and intervention with high concentra-tion of AB(30 μmol·L-1),the expression of PI3K/Foxo1 pathway-related proteins was detected by West-ern blot.Results Compared with the OGD/R group,AB could significantly increase the cell survival rate of primary neurons and reduce the release of LDH.The results of Hoechst 33342 and immunofluorescence stai-ning showed that AB reduced apoptosis after OGD/R injury.Western blot results showed that compared with the OGD/R group,after AB intervention,the expres-sion levels of Bcl-2 and NeuN proteins in neurons sig-nificantly increased(P＜0.01),and the expression level of Bax protein significantly decreased(P＜0.01).At the same time,it upregulated the expres-sion levels of p-AKT and PI3K proteins,promoted Foxo1 phosphorylation,and downregulated the expres-sion of Foxo1.Compared with the high-dose AB group,LY294002 could inhibit the changes of the a-bove indicators and reverse the protective effect of AB on OGD/R-injured primary neurons.Conclusions AB can alleviate oxygen-glucose deprivation/reoxygen-ation-induced neuronal injury,and its mechanism may be related to the activation of the PI3K/AKT/Foxo1 signaling pathway.

Objective:To analyze the spatiotemporal correlation between the surveillance data of influenza in students reported by medical institutions and school absenteeism due to illness, and evaluate the application of Bayesian Structural Time Series model (BSTS) in the prediction of school influenza epidemic.Methods:A total of 13 schools in Dapeng new district of Shenzhen were selected. The incidence data of influenza in schools in Shenzhen from January 1, 2015 to December 31, 2019 were collected from China Disease Control and Prevention Information System and the illness related school absentence data during this period were collected from Shenzhen Student Health Surveillance System, and the spatiotemporal correlation between the data from two systems was analyzed and compared. BSTS was used to make long-term predictions of the monthly incidence of influenza in students in 2019 and short-term predictions of the weekly incidence of influenza in week 1-8 and week 45-52 of 2019 by using the data from two systems.Results:There was a temporal correlation between the data from China Disease Control and Prevention Information System and the data from Shenzhen Student Health Surveillance System ( r=0.93, P<0.001), and the lag of the former one was 1 day ( r=0.73, P<0.001). Influenza outbreaks were randomly distributed in different schools in Shenzhen, and there was no spatial correlation. The root mean square error ( RMSE) and mean absolute error ( MAE) were 0.35 and 0.28, respectively, in the long-term prediction, and the RMSE was 0.33 and 0.34, and the MAE was 0.26 and 0.28, respectively, in the short-term predictions of week 1-8 and week 45-52 of 2019, respectively, showing good prediction accuracy and fitting effect. Conclusion:By analyzing the data from China Disease Control and Prevention Information System and Shenzhen Student Health Surveillance System with BSTS, the dynamics of the school influenza epidemic can be accurately predicted, and effective technical support can be provided for the early warning and prevention and control of influenza epidemic.