Background Lead (Pb) is a highly toxic heavy metal that accumulates in the body, potentially leading to multi-systemic impairment. Compared with traditional statistical methods, machine learning techniques offer unique advantages, opening new avenues for occupational health risk assessment and the exploratory analysis of complex associations. Objective To examine the association between occupational lead exposure and multiple health indicators and to identify key risk factors for lead toxicity. Methods A cross-sectional study was conducted, integrating occupational hygiene investigation results from 16 lead-acid battery enterprises in Jiangsu Province with occupational health examination data from 1914 lead-exposed workers. Inter-group differences were analyzed using the χ² test or Fisher's exact test. Binary logistic regression and machine learning algorithms [CatBoost, Naive Bayes model (NBM), and random forest (RF)] were employed to evaluate the association between blood lead (PbB), urine lead (PbU), and health indicators including blood pressure (BP), red blood cell count (RBC), and alanine aminotransferase (ALT). Results The prevalence of abnormal PbB and PbU were 14.52% and 9.35%, respectively. The risks of abnormal BP, RBC, and ALT were significantly increased in the population with high lead levels (P<0.05). PbB abnormalities were closely associated with gender, environmental lead concentration, wearing masks, smoking, and alcohol consumption (P<0.05). Regarding occupational hazards, workers exposed to lead dust had a 1.98-fold risk of PbU abnormality compared to those exposed to lead fumes. The plate coating and acid leaching process posed the highest risk for both PbB (OR=8.81) and PbU (OR=5.46) abnormalities compared with assembly process. Furthermore, the risks of PbB and PbU abnormalities were significantly elevated among workers with abnormal BP, RBC or ALT (P<0.05). Among the models, CatBoost performed best in predicting RBC abnormality (accuracy: 95.8%; precision: 44.9%; F1 score: 0.952; AUC: 0.981). Feature importance analysis identified PbB and PbU as the core factors affecting abnormal RBC and ALT, while RBC and ALT abnormalities as key features for predicting the risk of PbB and PbU abnormalities. Conclusion By integrating traditional statistical methods with machine learning, this study reveals a complex bidirectional association between occupational lead exposure and multiple health indicators, and identifies gender, job category, and environmental Pb concentration as the key factors influencing PbB abnormalities. These findings provide a scientific foundation for the implementation of precision occupational health management models.

Background Lead (Pb) is a highly toxic heavy metal that accumulates in the body, potentially leading to multi-systemic impairment. Compared with traditional statistical methods, machine learning techniques offer unique advantages, opening new avenues for occupational health risk assessment and the exploratory analysis of complex associations. Objective To examine the association between occupational lead exposure and multiple health indicators and to identify key risk factors for lead toxicity. Methods A cross-sectional study was conducted, integrating occupational hygiene investigation results from 16 lead-acid battery enterprises in Jiangsu Province with occupational health examination data from 1914 lead-exposed workers. Inter-group differences were analyzed using the χ² test or Fisher's exact test. Binary logistic regression and machine learning algorithms [CatBoost, Naive Bayes model (NBM), and random forest (RF)] were employed to evaluate the association between blood lead (PbB), urine lead (PbU), and health indicators including blood pressure (BP), red blood cell count (RBC), and alanine aminotransferase (ALT). Results The prevalence of abnormal PbB and PbU were 14.52% and 9.35%, respectively. The risks of abnormal BP, RBC, and ALT were significantly increased in the population with high lead levels (P<0.05). PbB abnormalities were closely associated with gender, environmental lead concentration, wearing masks, smoking, and alcohol consumption (P<0.05). Regarding occupational hazards, workers exposed to lead dust had a 1.98-fold risk of PbU abnormality compared to those exposed to lead fumes. The plate coating and acid leaching process posed the highest risk for both PbB (OR=8.81) and PbU (OR=5.46) abnormalities compared with assembly process. Furthermore, the risks of PbB and PbU abnormalities were significantly elevated among workers with abnormal BP, RBC or ALT (P<0.05). Among the models, CatBoost performed best in predicting RBC abnormality (accuracy: 95.8%; precision: 44.9%; F1 score: 0.952; AUC: 0.981). Feature importance analysis identified PbB and PbU as the core factors affecting abnormal RBC and ALT, while RBC and ALT abnormalities as key features for predicting the risk of PbB and PbU abnormalities. Conclusion By integrating traditional statistical methods with machine learning, this study reveals a complex bidirectional association between occupational lead exposure and multiple health indicators, and identifies gender, job category, and environmental Pb concentration as the key factors influencing PbB abnormalities. These findings provide a scientific foundation for the implementation of precision occupational health management models.

Objective To explore the application values of different detection methods in monitoring the decline pattern of syphilis-spe-cific antibody in the non-congenital syphilis children.Methods A total of 80 non-congenital syphilis children were included in the study.The serum specimens were collected after birth,and the syphilis-specific antibodies were detected using electrochemilumines-cence immunoassay(ECLIA),western blotting(WB),treponema pallidum particle agglutination assay(TPPA),enzyme-linked im-munosorbent assay(ELISA),and toluidine red unheated serum test(TRUST).Follow-up was conducted every three months until the positive results of ELISA and TRUST turned to negative.Results The results of ECLIA showed that the syphilis-specific antibody lev-els in the non-congenital syphilis children declined to 25％of the level at birth within 2 to 3 months,and the rate of decline was inde-pendent of the initial concentration.WB analysis indicated that the specific IgG bands in non-congenital syphilis children at birth were consistent with those of their mother,and the sequence of specific antibodies decline was as follows:TPN47,TPN15,TPN45,and TPN17.Due to methodological limitations,the absorbance values of ELISA showed no significant change during the first three months after birth when high concentrations of antibodies were present in the samples,but it showed high sensitivity in the detection for the samples with low-concentration of syphilis antibodies.The detection rates of ECLIA,TPPA,and WB were compared by using ELISA as the reference method.At birth,the detection rates of syphilis antibodies were 100％,100％,and 90％,respectively.In 3 months after birth,the detection rates were 100％,100％,and 75％.In 6 months after birth,,they were 100％,46％,and 15％.In 9 months after birth,they were 83％,33％,and 0％.The positive rate of TRUST was 17.5％at birth.and turned to negative in 3 month of follow-up.Conclusion Syphilis specific IgG antibodies may fully transferred to the fetus and decline in a predictable pattern after birth.The comprehensive analysis for the results of the four methods suggested that dynamic detection using ECLIA method could be used to pre-dict the risk of non-congenital syphilis or terminate the follow-up at 3 months,while the seroconversion detected by WB was earlier than that by TPPA,while ELISA required the longest follow-up period.

Neurogenic bladder(NB)is one of the most challenging urinary system disorders,with spinal cord injury(SCI)being an important etiological factor.Animal models provide crucial tools for investigating the pathogenesis,therapeutic strategies,and novel drug screening for NB subsequent to SCI.We reviewed and synthesized recent literature on NB animal models after SCI from both domestic and international sources.This review summarizes and analyzes research advancements using these models in terms of animal species,SCI segments,modeling techniques,and evaluation indicators,with the aim of offering insights and guidance for future experimental research based on animal models of NB following SCI.

This paper conducts a systematic literature review to analyze and summarize the current status, admission standards, practical scope, competency requirements, and talent cultivation of public health nursing teams both domestically and internationally, in order to provide reference for the development of public health nursing in China and assist in the improvement of the public health talent team.

Neurogenic bladder(NB)is one of the most challenging urinary system disorders,with spinal cord injury(SCI)being an important etiological factor.Animal models provide crucial tools for investigating the pathogenesis,therapeutic strategies,and novel drug screening for NB subsequent to SCI.We reviewed and synthesized recent literature on NB animal models after SCI from both domestic and international sources.This review summarizes and analyzes research advancements using these models in terms of animal species,SCI segments,modeling techniques,and evaluation indicators,with the aim of offering insights and guidance for future experimental research based on animal models of NB following SCI.

Objective To explore the application values of different detection methods in monitoring the decline pattern of syphilis-spe-cific antibody in the non-congenital syphilis children.Methods A total of 80 non-congenital syphilis children were included in the study.The serum specimens were collected after birth,and the syphilis-specific antibodies were detected using electrochemilumines-cence immunoassay(ECLIA),western blotting(WB),treponema pallidum particle agglutination assay(TPPA),enzyme-linked im-munosorbent assay(ELISA),and toluidine red unheated serum test(TRUST).Follow-up was conducted every three months until the positive results of ELISA and TRUST turned to negative.Results The results of ECLIA showed that the syphilis-specific antibody lev-els in the non-congenital syphilis children declined to 25％of the level at birth within 2 to 3 months,and the rate of decline was inde-pendent of the initial concentration.WB analysis indicated that the specific IgG bands in non-congenital syphilis children at birth were consistent with those of their mother,and the sequence of specific antibodies decline was as follows:TPN47,TPN15,TPN45,and TPN17.Due to methodological limitations,the absorbance values of ELISA showed no significant change during the first three months after birth when high concentrations of antibodies were present in the samples,but it showed high sensitivity in the detection for the samples with low-concentration of syphilis antibodies.The detection rates of ECLIA,TPPA,and WB were compared by using ELISA as the reference method.At birth,the detection rates of syphilis antibodies were 100％,100％,and 90％,respectively.In 3 months after birth,the detection rates were 100％,100％,and 75％.In 6 months after birth,,they were 100％,46％,and 15％.In 9 months after birth,they were 83％,33％,and 0％.The positive rate of TRUST was 17.5％at birth.and turned to negative in 3 month of follow-up.Conclusion Syphilis specific IgG antibodies may fully transferred to the fetus and decline in a predictable pattern after birth.The comprehensive analysis for the results of the four methods suggested that dynamic detection using ECLIA method could be used to pre-dict the risk of non-congenital syphilis or terminate the follow-up at 3 months,while the seroconversion detected by WB was earlier than that by TPPA,while ELISA required the longest follow-up period.

This paper conducts a systematic literature review to analyze and summarize the current status, admission standards, practical scope, competency requirements, and talent cultivation of public health nursing teams both domestically and internationally, in order to provide reference for the development of public health nursing in China and assist in the improvement of the public health talent team.

Abstract: Inflammatory bowel disease (IBD), whose pathogenesis remains elusive, is a group of autoimmune diseases characterized by chronic, progressive, and lifelong inflammation of the digestive tract. The pathogenesis of IBD remains elusive. Although a number of drugs have been developed to treat IBD, their effects are merely anti-inflammatory. In addition, current treatments for IBD are easily susceptible to resistance in clinical practice. Mesenchymal stem cells (MSCs) have been reported to have the ability to migrate to the site of inflammation, with potent immunoregulatory effects, and to rebalance the immune microenvironment and restore the integrity of the epithelial barrier with significant value of application, particularly for patients who are refractory to classic medicines. In this paper, we reviewed the clinical applications, mechanisms and engineerable properties of MSC products and their exosomes to provide some reference for the use of MSCs and their exosomes in the treatment of IBD.

Centralized monitoring is a risk-based remote monitoring mode that can effectively improve monitoring efficiency and quality. From July to September 2023, this study developed a centralized monitoring scheme for investigator initiated trials(IIT). This scheme utilized electronic data collection system and clinical research document management system, using programming techniques to compare the consistency of key project processes and data, monitor data filling, distribution trends, logical relationships, as well as documents such as informed consent forms, protocol violation records, and adverse event reports. It could timely identify problems in clinical trials and develop targeted response measures. From October to December 2023, 6 experts conducted centralized monitoring for 153 IIT projects using this scheme and found common issues in program execution(86 projects), ethical approvals(68 projects), and informed consent forms(67 projects), and so on. At the scome time, corresponding measures were developed. The process took a total of 20 days, with an average time of 6.27 hours per project. Compared with traditional on-site monitoring, the centralized monitoring scheme developed in this study had shown certain advantages in terms of timeliness, which could help guide the efficient implementation of on-site monitoring work and provide references for tertiary public hospitals to improve the quality of clinical trials.