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:To propose an alarm method for ventilator fault and abnormality of machine signs based on convolutional neural network(CNN)model,which aimed at the problem of low detection rate of ventilator faults and abnormalities of machine sign,and to analyze its application value in patients with chronic obstructive pulmonary disease(COPD)in using non-invasive ventilator.Methods:This study established a identification model(CNN-SG)for ventilator fault based on stochastic gradient descent by mini-batch method that was introduced by CNN network,and a multi-task CNN identification model for abnormalities of machine signs of ventilator was established on the basis of CNN model.The respiratory waveform data of 60 patients with chronic obstructive pulmonary disease(COPD)who admitted to Wusong Hospital,Zhongshan Hospital Affiliated to Fudan University from January 2019 to January 2024 were collected.These data were divided into train set(42 cases)and validation set(18 cases)as ratio of 7 to 3.The training set was used in the learning process of model,while the validation set was used to assess the model's performance for unknown data.One-hot encoding was used to represent fault states,and to predict whether occurred abnormal data failures within specific time intervals.Two independent convolutional networks were employed respectively to detect and identify invalid inspiratory effort and double-triggering abnormalities in abnormal machine signs.Model performance was assessed by using accuracy,precision,recall rate,negative predictive value(NPV),and specificity.Chi-square test was used to compare the differences of various assessment indicators between different models.The F1-score was calculated to comprehensively assess the performance of model.Results:In the validation set,the accuracy(99.98%),precision(99.90%),recall rate(99.97%),NPV(98.68%),and specificity(98.24%)of CNN-SG model were higher than those of CNN model in identify the fault of ventilator.In detecting invalid inspiratory effort,the accuracy,sensitivity,specificity and F1-scores of CNN-MTL model were respectively 98.83%,98.81%,97.68%and 98.85.The accuracy,sensitivity,specificity and F1-scores of CNN-MTL model were respectively 98.70%,98.83%,97.62%,and 98.75 in identifying double-triggering positive features,as well as 98.80%,98.81%,98.88%and 98.99 for double-triggering negative features.All of the above indicators of CNN-SG were significantly better than those of the conventional CNN model.Conclusion:The established deep learning algorithm model based on CNN can effectively identify faults and abnormalities of machine signs of non-invasive ventilator.

Objective:Based on value orientation,it aimed to scientifically define the concept and connotation of accessibility to novel anticancer drugs,in order to deeply understand the nature and current status of the accessibility issues of novel anticancer drugs,and to provide a reference for the formulation and optimization of policies related to novel anticancer drugs.Methods:Data was collected through literature review and expert interviews,and the concept of drug accessibility was defined using the atomic diagram method.Results:The core images include"affordability","availability","high quality"and"patients".The concept of accessibility to novel anticancer drugs is defined as"the process of ensuring the sustainable supply,equitable access,affordability,and rational use of high-quality anticancer drugs to safeguard the realization of patient benefit goals."The connotation of the value orientation in policies on the accessibility of novel anticancer drugs is profoundly reflected in the multi-dimensional value-driven approach to ensure the ultimate benefit of patients,which includes quality,sustainability,equity,affordability,and rational use.Conclusion:The proposal of the concept and connotation of accessibility provides a theoretical basis for a deep understanding of the accessibility of novel anticancer drugs and offers valuable references for subsequent policy-making and practical operations.

Objective To explore the risk factors of nonalcoholic fatty liver disease(NAFLD)in obese children,and evaluate the diagnostic value of each index for NAFLD and establish a Nomogram prediction model.Methods A total of 207 obese children admitted at Department of Pediatrics the Second Hospital of Jiaxing from January 2022 to January 2025 were selected.These children were divided into two groups based on NAFLD diagnosis:non-NAFLD group(n=99)and NAFLD group(n=108).Differences in gender,age,body mass index(BMI),and related metabolic indicators were compared between two groups.Logistic regression was employed to analyze potential risk factors for NAFLD development,while receiver operating characteristic(ROC)curve and Nomograms were used to evaluate the predictive value of different factors for NAFLD.Results ROC curve analysis demonstrated diagnostic value for NAFLD in triglyceride-glucose index(TyG),triglyceride-to-cholesterol ratio,TyG-waist circumference,and TyG-BMI.Among these,the area under the curve(AUC)of TyG showed the highest value of 0.713,with an optimal cutoff of 8.189,sensitivity of 50.5％and specificity of 83.3％.Univariate Logistic regression analysis revealed multiple insulin resistance indicators associated with NAFLD development.Multivariate analysis identified homeostatic model assessment of insulin resistance(HOMA-IR)and TyG as independent risk factors,with TyG showing the best predictive value(OR=3.038 95％CI:1.089-8.475,P＜0.05).The constructed Nomogram prediction model demonstrated strong comprehensive discriminant capability(AUC=0.742).Conclusion The Nomogram model based on HOMA-IR,TyG and its derived indexes has certain clinical application value in the screening of NAFLD in children.

Objective:To propose an alarm method for ventilator fault and abnormality of machine signs based on convolutional neural network(CNN)model,which aimed at the problem of low detection rate of ventilator faults and abnormalities of machine sign,and to analyze its application value in patients with chronic obstructive pulmonary disease(COPD)in using non-invasive ventilator.Methods:This study established a identification model(CNN-SG)for ventilator fault based on stochastic gradient descent by mini-batch method that was introduced by CNN network,and a multi-task CNN identification model for abnormalities of machine signs of ventilator was established on the basis of CNN model.The respiratory waveform data of 60 patients with chronic obstructive pulmonary disease(COPD)who admitted to Wusong Hospital,Zhongshan Hospital Affiliated to Fudan University from January 2019 to January 2024 were collected.These data were divided into train set(42 cases)and validation set(18 cases)as ratio of 7 to 3.The training set was used in the learning process of model,while the validation set was used to assess the model's performance for unknown data.One-hot encoding was used to represent fault states,and to predict whether occurred abnormal data failures within specific time intervals.Two independent convolutional networks were employed respectively to detect and identify invalid inspiratory effort and double-triggering abnormalities in abnormal machine signs.Model performance was assessed by using accuracy,precision,recall rate,negative predictive value(NPV),and specificity.Chi-square test was used to compare the differences of various assessment indicators between different models.The F1-score was calculated to comprehensively assess the performance of model.Results:In the validation set,the accuracy(99.98%),precision(99.90%),recall rate(99.97%),NPV(98.68%),and specificity(98.24%)of CNN-SG model were higher than those of CNN model in identify the fault of ventilator.In detecting invalid inspiratory effort,the accuracy,sensitivity,specificity and F1-scores of CNN-MTL model were respectively 98.83%,98.81%,97.68%and 98.85.The accuracy,sensitivity,specificity and F1-scores of CNN-MTL model were respectively 98.70%,98.83%,97.62%,and 98.75 in identifying double-triggering positive features,as well as 98.80%,98.81%,98.88%and 98.99 for double-triggering negative features.All of the above indicators of CNN-SG were significantly better than those of the conventional CNN model.Conclusion:The established deep learning algorithm model based on CNN can effectively identify faults and abnormalities of machine signs of non-invasive ventilator.

Objective:Based on value orientation,it aimed to scientifically define the concept and connotation of accessibility to novel anticancer drugs,in order to deeply understand the nature and current status of the accessibility issues of novel anticancer drugs,and to provide a reference for the formulation and optimization of policies related to novel anticancer drugs.Methods:Data was collected through literature review and expert interviews,and the concept of drug accessibility was defined using the atomic diagram method.Results:The core images include"affordability","availability","high quality"and"patients".The concept of accessibility to novel anticancer drugs is defined as"the process of ensuring the sustainable supply,equitable access,affordability,and rational use of high-quality anticancer drugs to safeguard the realization of patient benefit goals."The connotation of the value orientation in policies on the accessibility of novel anticancer drugs is profoundly reflected in the multi-dimensional value-driven approach to ensure the ultimate benefit of patients,which includes quality,sustainability,equity,affordability,and rational use.Conclusion:The proposal of the concept and connotation of accessibility provides a theoretical basis for a deep understanding of the accessibility of novel anticancer drugs and offers valuable references for subsequent policy-making and practical operations.

Objective To analyze the policy texts related to pediatric medications in China over the past decade,to explore the deficiencies in existing policy formulation from the perspective of stakeholders,and to propose reasonable optimization suggestions based on the current situation.Methods Collecting national-level policies related to pediatric drugs in China from 2013 to 2023,a two-dimensional policy analysis framework of"Policy tools-Stakeholder"were established.And the content analysis method was used to code,categorize,and statistically analyze the policy texts.Results A total of 54 pediatric drug policies were included in the analysis.In terms of policy tools,a total of 197 policy codes were formed,with environmental tools being the most prevalent with 92 codes(46.70％),primarily consisting of regulatory management tools(28 codes,30.43％).This was followed by supply-oriented tools with 53 codes(26.90％),mainly focused on the issuance of technical guidelines(21 codes,39.62％).Demand-oriented tools accounted for the least with 52 codes(26.40％),with inter-departmental collaboration tools having the highest proportion(17 codes,32.69％).In the dimension of stakeholders,a total of 223 policy codes were formed,with the government having the highest number of codes at 133(59.64％),followed by medical institutions with 56 codes(25.11％).The proportions for medical personnel,pharmaceutical companies,and patients were similar,with 14 codes(6.28％),11 codes(4.93％),and 9 codes(4.04％),respectively.Conclusions Pediatric drugs face challenges with policy tools where supply-oriented tools,particularly those providing financial support,suffer from insufficient policy depth and customization.The demand-oriented tools have a low proportion,leading to structural imbalance and underutilized effectiveness;the environment-oriented tools focus more on regulation than incentives,restricting the accessibility of pediatric drugs;the potential of multiple stakeholders is not fully activated,and there is a lack of policies centered around pediatric patients.To address these issues,supply-oriented policy tools need to establish a diversified financial support model and clearly define the scope of coverage.Demand-oriented policy tools require further adjustments to the catalog,procurement upgrades,and international collaborative research to reshape the pediatric drug security system.Environmental policy tools should enhance economic support,strengthen intellectual property rights,and implement targeted education to build a development ecosystem for pediatric drugs.Regarding stakeholders,it is essential to strengthen multi-stakeholder collaboration and optimize pediatric drug policy tools with a patient-centered approach.

Objective To analyze the policy texts related to pediatric medications in China over the past decade,to explore the deficiencies in existing policy formulation from the perspective of stakeholders,and to propose reasonable optimization suggestions based on the current situation.Methods Collecting national-level policies related to pediatric drugs in China from 2013 to 2023,a two-dimensional policy analysis framework of"Policy tools-Stakeholder"were established.And the content analysis method was used to code,categorize,and statistically analyze the policy texts.Results A total of 54 pediatric drug policies were included in the analysis.In terms of policy tools,a total of 197 policy codes were formed,with environmental tools being the most prevalent with 92 codes(46.70％),primarily consisting of regulatory management tools(28 codes,30.43％).This was followed by supply-oriented tools with 53 codes(26.90％),mainly focused on the issuance of technical guidelines(21 codes,39.62％).Demand-oriented tools accounted for the least with 52 codes(26.40％),with inter-departmental collaboration tools having the highest proportion(17 codes,32.69％).In the dimension of stakeholders,a total of 223 policy codes were formed,with the government having the highest number of codes at 133(59.64％),followed by medical institutions with 56 codes(25.11％).The proportions for medical personnel,pharmaceutical companies,and patients were similar,with 14 codes(6.28％),11 codes(4.93％),and 9 codes(4.04％),respectively.Conclusions Pediatric drugs face challenges with policy tools where supply-oriented tools,particularly those providing financial support,suffer from insufficient policy depth and customization.The demand-oriented tools have a low proportion,leading to structural imbalance and underutilized effectiveness;the environment-oriented tools focus more on regulation than incentives,restricting the accessibility of pediatric drugs;the potential of multiple stakeholders is not fully activated,and there is a lack of policies centered around pediatric patients.To address these issues,supply-oriented policy tools need to establish a diversified financial support model and clearly define the scope of coverage.Demand-oriented policy tools require further adjustments to the catalog,procurement upgrades,and international collaborative research to reshape the pediatric drug security system.Environmental policy tools should enhance economic support,strengthen intellectual property rights,and implement targeted education to build a development ecosystem for pediatric drugs.Regarding stakeholders,it is essential to strengthen multi-stakeholder collaboration and optimize pediatric drug policy tools with a patient-centered approach.

Objective:To investigate the effects of two anastomosis methods on perioperative and pathological outcomes during totally laparoscopic right hemicolectomy (TLRH).Methods:In a national multicenter snapshot study, 1,854 patients who underwent laparoscopic right hemicolectomy were enrolled from 52 tertiary hospitals across China. The post-hoc analysis based on this study compared the data of 303 patients who underwent TLRH. Patients were divided into the antiperistaltic group (33 cases) and the isoperistaltic group (270 cases) according to type of anastomosis. Due to the significant difference in sample size between the two groups, propensity score matching (PSM) was performed to eliminate the influence of baseline characteristic discrepancies. The matching was based on the following known confounding factors: age, gender, body mass index (BMI), history of abdominal surgery, and history of diabetes, with a caliper value of 0.2. Perioperative and pathological outcomes were compared between the two groups.Results:After PSM, 33 patients were included in the antiperistaltic group and 65 patients in the isoperistaltic group. There were no statistically significant differences in baseline data between the two groups (all P>0.05). No significant differences were observed between the two groups in terms of operation time, blood loss, time to first defecation, time to first oral intake, or the incidence and grading of complications either (all P>0.05). However, length of postoperative hospital stay in the isoperistaltic group was significantly shorter than that in the antiperistaltic group, however (7.0 [6.0, 9.0] days vs. 8.0 [7.0, 10.5] days, P=0.049). In terms of pathological outcomes, there were also no statistically significant differences between the two groups in the number of harvested lymph nodes or the number of positive lymph nodes (all P>0.05). Conclusions:The two digestive tract reconstruction modalities, antiperistaltic and isoperistaltic anastomosis, have comparable perioperative safety and efficacy in TLRH. The isoperistaltic group had better outcomes in terms of postoperative hospital stay.

BACKGROUND:The extracellular-regulated protein kinase 5(ERK5)signaling protein is essential for the survival of organisms,and resveratrol can promote osteoblast proliferation through various pathways.However,whether resveratrol can regulate osteoblast function through the ERK5 signaling protein needs further verification. OBJECTIVE:To explore the regulatory effect of ERK5 on the proliferation of MC3T3-E1 cells and related secreted proteins,and to further verify whether resveratrol can complete the above process by activating ERK5. METHODS:Mouse MC3T3-E1 preosteoblasts were treated with complete culture medium,XMD8-92(an ERK5 inhibitor),epidermal growth factor(an ERK5 activator),resveratrol alone,XMD8-92+EGF,and resveratrol+XMD8-92,respectively.Western blot assay was used to detect the expression of ERK5 and p-ERK5 proteins,proliferation-related proteins Cyclin D1,CDK4 and PCNA,and osteoblast-secreted proteins osteoprotegerin and receptor activator of nuclear factor-κB ligand in MC3T3-E1 cells of each group.The fluorescence intensity of ERK5,osteoprotegerin and receptor activator of nuclear factor-κB ligand in each group was detected by cell immunofluorescence staining,and cell proliferation was detected by EdU staining,respectively.The appropriate concentration and time of resveratrol intervention in MC3T3-E1 cells were determined by cell morphology observation and cell counting kit-8 assay. RESULTS AND CONCLUSION:The activation of ERK5 signaling protein could effectively promote the proliferation of MC3T3-E1 cells,up-regulate the osteoprotegerin/receptor activator of nuclear factor-κB ligand ratio.The appropriate concentration and time for resveratrol intervention in MC3T3-E1 cells was 5 μmol/L and 24 hours,respectively.Resveratrol could activate ERK5 signaling protein,thereby promoting osteoblast proliferation and up-regulating the osteoprotegerin/RANKL ratio.All these results indicate that resveratrol can promote the proliferation of MC3T3-E1 cells and up-regulate the osteoprotegerin/RANKL ratio by activating the ERK5 signaling protein.