Background The prevalence of chronic diseases among the Chinese occupational population is rising steadily, with hypertension and diabetes becoming important health concerns. Occupational health examinations (OHE) provide stable population coverage, standardized protocols, and fixed follow-up intervals, offering a robust data foundation for risk assessment. However, most existing hypertension prediction studies rely on cross-sectional data and mainly focus on clinic onset, failing to capture the dynamic progression and cumulation of individual risk. Objective To construct a machine learning-based risk prediction model for blood pressure abnormality in occupational populations, providing a reference for health risk stratification and targeted health interventions. Methods Longitudinal data from 2020 to 2023 were extracted from the occupational health examination database of an institution in Shanghai. After excluding individuals with hypertension in any of the first three years, 3710 workers who participated 4 consecutive years of OHE were included. Six categories of blood pressure-related indicators from 2020 to 2022 were selected, including basic information, lifestyles, occupational exposures, cardiovascular indicators, routine blood tests, and biochemical markers, comprising 30 variables in total. For feature engineering, continuous variables were processed to reflect three-year dynamic characteristics: level (mean), variability (variance), and temporal trend (slope). Categorical variables were incorporated using 2022 values. Least absolute shrinkage and selection operator regression was applied to identify variables for inclusion in the machine learning models. Five models (decision tree, logistic regression, random forest, support vector machine, and XGBoost) were employed to predict blood pressure abnormality risk in 2023. And then sensitive analysis was conducted. The optimal model was selected based on the area under the curve (AUC) of receiver operating characteristic. Feature importance and SHAP analyses were applied to interpret the final model. Results Feature engineering transformed 17 continuous variables into 51 secondary variables, combined with 13 baseline variables, resulted in 24 variables screened out by LASSO regression. The logistic regression model achieved the best performance. Feature importance analysis indicated that the dynamic trajectory of blood pressure played a central role in the model, complemented by other biochemical and lifestyle indicators. SHAP analysis further showed that the model’s ability to not only identify risks of high-normal blood pressure and hypertension but also quantify the specific contribution of individual examination indicators to predicted risk, supporting risk-stratified population management in occupational health management. Conclusion Based on an existing occupational health examination database and routinely collected data, this study has developed a risk prediction model for blood pressure abnormalities in occupational populations. By incorporating dynamic change characteristics from longitudinal examinations, the study demonstrates the feasibility of using routine health data for early risk identification and stratified management. However, its applicability is limited by the availability of repeated examination data and the focus on specific occupational groups, requiring further validation across broader populations and diverse clinic scenarios.

ObjectiveTo investigate the epidemiological and clinical characteristics of human bocavirus (HBoV) in hospitalized children with acute lower respiratory tract infection (ALRTI) at a single-center children’s hospital in Shanghai, thereby providing evidence for the diagnosis, treatment, and prevention of HBoV infection. MethodsA retrospective study was conducted on 19 537 hospitalized children with ALRTI at Shanghai Children’s Hospital from January 2021 to December 2023. Multiplex polymerase chain reaction (PCR) combined with capillary electrophoresis was used to detect HBoV and 12 other common respiratory viruses /atypical pathogens. The positive detection rate, demographic characteristics (sex, age), temporal distribution (year, season) of HBoV, as well as the clinical characteristics of severe and non-severe pneumonia were analyzed. ResultsThe overall HBoV-positive rate was 2.57% (503/19 537), with 59.44% (299/503) being single infections and 40.56% (204/503) being co-infections. The positive detection rate was significantly higher in boys than that in girls (2.78% vs 2.33%, χ²=3.88, P=0.049). The highest infection rate was observed in toddlers, followed by infants (χ²=379.57, P<0.001). The positive rate peaked in 2021 and reached its lowest point in 2023 (χ²=45.49, P<0.001), with epidemics mainly prevalent in summer and autumn. The main clinical symptoms were cough (90.06%, 453/503), fever (75.94%, 382/503), and wheezing (39.96%, 201/503). Children with severe pneumonia showed a higher incidence of wheezing compared with the non-severe group (P<0.001), while underlying diseases and co-infections had no significant association with disease severity (P>0.05). ConclusionHBoV was an important pathogen of ALRTI in children, predominantly affecting infants and toddlers, with higher susceptibility in boys and seasonal peaks in autumn and summer. The main clinical manifestations included cough, fever, and wheezing, with wheezing being more prevalent in children with severe pneumonia.

As a primary approach to safeguarding workers' occupational health in China, the work-related injury insurance still has insufficient preventive measures for occupational groups. By reviewing the preventive measures embedded in Germany’s statutory accident insurance (Gesetzliche Unfallversicherung) and Japan’s workers’ accident compensation insurance, this study summarized their best practices and then proposed the following policy directions based on China’s specific context: strengthening the prevention-oriented institutional framework, increasing financial investment in occupational injury prevention, improving the incentive mechanisms of floating premium rate, and promoting data integration and intelligent applications in occupational health management. These measures are expected to shift China’s work-related injury insurance system from a compensation-oriented model to one that emphasizes comprehensive prevention and health promotion, thereby providing useful insights for better safeguarding the health of Chinese workers.

ObjectiveTo investigate the mechanisms by which Shangxia Liangji pills improve cognitive function in Alzheimer's disease （AD） mice based on the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） pathway， aiming to provide experimental evidence for its clinical use in AD treatment. MethodsFifty APP/PS1 double-transgenic mice were randomly divided into a model group， Shangxia Liangji pills low-dose group， medium-dose group， high-dose group， and donepezil hydrochloride group， with 10 mice in each group. Additionally， 10 C57BL/6 mice of the same genetic background were assigned to the normal group. Cognitive function was assessed using the Morris water maze and novel object recognition tests. Hippocampal pathological changes were observed using transmission electron microscopy and Nissl staining. Neuroinflammation in hippocampal tissue was detected by enzyme-linked immunosorbent assay （ELISA）. Protein expression levels of PI3K/Akt pathway-related proteins， postsynaptic density protein 95 （PSD95）， and amyloid precursor protein （APP） in hippocampal tissue were measured by Western blot. ResultsCompared with the normal group， the model group exhibited significantly increased total swimming distance and escape latency， significantly reduced number of platform crossings （P<0.01）， and a decreased recognition index （P<0.01）. Marked neuronal apoptosis was observed in the hippocampal region， with a marked reduction in the number of neurons in the CA3 region （P<0.01）. Levels of interleukin-6 （IL-6）， interleukin-1β （IL-1β）， and tumor necrosis factor-α （TNF-α） in hippocampal tissue were significantly elevated （P<0.01）. APP expression in hippocampal tissue was markedly upregulated （P<0.01）， while PSD95， p-PI3K/PI3K， and p-Akt/Akt protein expression were significantly downregulated （P<0.01）. Compared with the model group， the Shangxia Liangji pills high-dose group showed significantly reduced total swimming distance and escape latency， significantly increased number of platform crossings （P<0.01）， and an elevated recognition index （P<0.01）. Hippocampal neuronal apoptosis was alleviated， with a significant increase in the number of neurons in the CA3 region （P<0.01）. Levels of IL-6， IL-1β， and TNF-α were significantly decreased （P<0.01）. APP expression was downregulated （P<0.05）， while PSD95， p-PI3K/PI3K， and p-Akt/Akt protein expression were significantly upregulated （P<0.01）. ConclusionShangxia Liangji pills may improve cognitive function in AD mice by modulating the PI3K/Akt pathway， thereby reducing neuroinflammation and alleviating neuronal and synaptic injury.

Objective To analyze the coverage of chronic disease-related indicators and the distribution of positive detection rates in occupational medical examinations (OME). Methods A total of 872 862 currently employed workers who underwent OME from 2015 to 2023 were selected as the study participants using a convenience sampling method. According to the year of OME, the study period was divided into three periods: 2015-2017, 2018-2020, and 2021-2023. The examination rates and positive detection rates of five chronic disease-related indicators, including obesity, high blood pressure, hyperglycemia, dyslipidemia, and hyperuricemia, were analyzed. Results Regarding the routine medical examination indicators in OME, the examination rates for systolic and diastolic blood pressure were both 97.4%, while those for body height and weight were both 6.8%. Among the mandatory or optional examination items for specific occupational groups in OMEs, the examination rates of fasting blood glucose, triglycerides, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol were 35.2%, 18.5%, 18.5%, 7.8%, and 7.9%, respectively. Regarding items not included in OMEs, the examination rates of glycated hemoglobin and uric acid were 0.2% and 19.2%, respectively. The examination rates for systolic and diastolic blood pressure consistently exceeded 95.0%, the examination rates for fasting blood glucose, triglycerides, and uric acid ranged from 32.9% to 37.0%, 16.8% to 21.4%, and 16.9% to 24.1%, respectively, while the rates for body height and weight remained below 10.0% across these three periods. Among workers who completed corresponding OME items, dyslipidemia and hyperuricemia showed relatively higher positive detection rates, with rates of 23.2% and 23.0%, respectively. The positive detection rates of obesity, high blood pressure, and hyperglycemia were relatively lower, at 9.6%, 3.5%, and 1.4%, respectively. Across the three periods, the positive detection rates of dyslipidemia, hyperuricemia, obesity, high blood pressure, and hyperglycemia ranged from 18.0% to 33.7%, 7.0% to 28.5%, 7.8% to 10.9%, 3.3% to 3.9%, and 1.4% to 1.5%, respectively, all showing increasing trends with advancing OME periods (all P<0.01). Conclusion Current OME practices show a mismatch between the coverage of chronic disease-related indicators and the actual health risks among occupational worker populations. Although blood pressure monitoring is well implemented, basic physical indicators (body height and body weight) and key metabolic indicators (blood glucose, blood lipids, and uric acid) are insufficiently covered, limiting comprehensive assessment of occupational health risks. Optimization of monitoring strategies is urgently needed to improve data completeness.

Objectives: . Head and neck squamous cell carcinoma (HNSCC) exhibits high recurrence rates, particularly in cases of radioresistant HNSCC (RR-HNSCC). Non-thermal plasma (NTP) therapy effectively suppresses the progression of HNSCC. However, the therapeutic mechanisms of NTP therapy in treating RR-HNSCC are not well understood. In this study, we explored the regulatory role of NTP in the RR-HNSCC signaling pathway and identified its signature genes. Methods: . After constructing two RR-HNSCC cell lines, we prepared cell lysates from cells treated or not treated with NTP-activated media (NTPAM) and performed RNA sequencing to determine their mRNA expression profiles. Based on the RNA sequencing results, we identified differentially expressed genes (DEGs), followed by a bioinformatics analysis to identify candidate molecules potentially associated with NTPAM therapy for RR-HNSCC. Results: . NTPAM reduced RR-HNSCC cell viability in vitro. RNA sequencing results indicated that NTPAM treatment activated the reactive oxygen species (ROS) pathway and induced ferroptosis in RR-HNSCC cell lines. Among the 1,924 genes correlated with radiation treatment, eight showed statistical significance in both the cell lines and The Cancer Genome Atlas (TCGA) cohort. Only five genes—ABCC3, DUSP16, PDGFB, RAF1, and THBS1—showed consistent results between the NTPAM data sequencing and TCGA data. LASSO regression analysis revealed that five genes were associated with cancer prognosis, with a hazard ratio of 2.26. In RR-HNSCC cells, NTPAM affected DUSP16, PDGFB, and THBS1 as activated markers within 6 hours, and this effect persisted for 12 hours. Furthermore, enrichment analysis indicated that these three DEGs were associated with the extracellular matrix, transforming growth factor-beta, phosphoinositide 3-kinase/protein kinase B, and mesenchymal-epithelial transition factor pathways. Conclusion . NTPAM therapy exerts cytotoxic effects in RR-HNSCC cell lines by inducing specific ROS-mediated ferroptosis. DUSP16, PDGFB, and THBS1 were identified as crucial targets for reversing the radiation resistance induced by NTPAM therapy, providing insights into the mechanisms and clinical applications of NTPAM treatment in RR-HNSCC.

In cases where a tracheal injury exceeds half the length of the adult trachea or one-third of the length of the child trachea, it becomes difficult to perform end-to-end anastomosis after tracheal resection due to excessive tension at the anastomosis site. In such cases, tracheal replacement therapy is required. Advances in tissue engineering technology have led to the development of tissue engineering tracheal substitutes, which have promising applications. Hydrogels, which are highly hydrated and possess a good three-dimensional network structure, biocompatibility, low immunogenicity, biodegradability, and modifiability, have had wide applications in the field of tissue engineering. This article provides a review of the characteristics, advantages, disadvantages, and effects of various hydrogels commonly used in tissue engineering trachea in recent years. Additionally, the article discusses and offers prospects for the future application of hydrogels in the field of tissue engineering trachea.

As the prevalence of chronic diseases increases among occupational populations in China, the focus of occupational health management has shifted from ″occupational disease prevention and control″ to ″occupational disease and chronic disease prevention and control″. At present, occupational medical examinations (OME) are mainly focused on occupational disease prevention and control, and generally lack of chronic disease indicators such as blood lipids and blood glucose, limiting the role of OME in life-cycle health management of workers. To address this gap, it is necessary to incorporate chronic disease screening indicators into OME. Integrating OME and chronic disease screening faces bottlenecks, including concerns about increased operating costs in small- and medium-sized enterprises, and the risk of employment discrimination caused by the leakage of employee health privacy. A tiered strategy is recommended. Incorporating low-cost indicators such as blood lipids, waist circumference into routine examinations, and customizing advanced screening for elder or high-risk position workers. The prioritization of screening indicators can be determined by expert consultation and employer-employee discussions. Meanwhile, the results of chronic disease screening indicators should not be included in occupational health surveillance records to protect workers′ privacy. In summary, expanding OME to cover more chronic disease indicators provides valuable economic and social benefits. In the long run, common chronic disease screening indicators should be included in the regular medical examination indicators of OME, thereby reducing the burden of chronic diseases on occupational populations and promoting the health management of occupational populations.

Objectives: . Head and neck squamous cell carcinoma (HNSCC) exhibits high recurrence rates, particularly in cases of radioresistant HNSCC (RR-HNSCC). Non-thermal plasma (NTP) therapy effectively suppresses the progression of HNSCC. However, the therapeutic mechanisms of NTP therapy in treating RR-HNSCC are not well understood. In this study, we explored the regulatory role of NTP in the RR-HNSCC signaling pathway and identified its signature genes. Methods: . After constructing two RR-HNSCC cell lines, we prepared cell lysates from cells treated or not treated with NTP-activated media (NTPAM) and performed RNA sequencing to determine their mRNA expression profiles. Based on the RNA sequencing results, we identified differentially expressed genes (DEGs), followed by a bioinformatics analysis to identify candidate molecules potentially associated with NTPAM therapy for RR-HNSCC. Results: . NTPAM reduced RR-HNSCC cell viability in vitro. RNA sequencing results indicated that NTPAM treatment activated the reactive oxygen species (ROS) pathway and induced ferroptosis in RR-HNSCC cell lines. Among the 1,924 genes correlated with radiation treatment, eight showed statistical significance in both the cell lines and The Cancer Genome Atlas (TCGA) cohort. Only five genes—ABCC3, DUSP16, PDGFB, RAF1, and THBS1—showed consistent results between the NTPAM data sequencing and TCGA data. LASSO regression analysis revealed that five genes were associated with cancer prognosis, with a hazard ratio of 2.26. In RR-HNSCC cells, NTPAM affected DUSP16, PDGFB, and THBS1 as activated markers within 6 hours, and this effect persisted for 12 hours. Furthermore, enrichment analysis indicated that these three DEGs were associated with the extracellular matrix, transforming growth factor-beta, phosphoinositide 3-kinase/protein kinase B, and mesenchymal-epithelial transition factor pathways. Conclusion . NTPAM therapy exerts cytotoxic effects in RR-HNSCC cell lines by inducing specific ROS-mediated ferroptosis. DUSP16, PDGFB, and THBS1 were identified as crucial targets for reversing the radiation resistance induced by NTPAM therapy, providing insights into the mechanisms and clinical applications of NTPAM treatment in RR-HNSCC.

Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a staggered herringbone micromixer (SHM) chip. Our findings reveal that most investigated variables significantly influence liposomal size, often interrelating in complex ways. We evaluated the predictive performance of several widely-used ML algorithms, including ensemble methods, through cross-validation (CV) for both liposome size and polydispersity index (PDI). A standalone dataset was experimentally validated to assess the accuracy of the ML predictions, with results indicating that ensemble algorithms provided the most reliable predictions. Specifically, gradient boosting was selected for size prediction, while random forest was employed for PDI prediction. We successfully produced uniform large (600 nm) and small (100 nm) liposomes using the optimised experimental conditions derived from the ML models. In conclusion, this study presents a robust methodology that enables precise control over liposome size distribution, offering valuable insights for medicinal research applications.