ObjectiveTo investigate the infection characteristics of respiratory syncytial virus (RSV) in children with acute respiratory tract infection (ARI) in Pudong New Area, Shanghai, from 2013 to 2023, so as to provide an evidence for the prevention and control of RSV in Shanghai. MethodsChildren who sought medical care at sentinel healthcare facilities in Pudong New Area, Shanghai, between January 2013 and December 2023 and met the case definition of ARI were included in the study. Nasopharyngeal swab samples were collected and tested for viral pathogens using real-time fluorescene PCR, and the clinical information of whom was collected simultaneously. ResultsA total of 4 980 children were included in the ARI surveillance, among whom 231 tested positive for RSV, with an overall detection rate of 4.64%. Of these, 106 cases were type A and 125 were type B. From 2013 to 2023, the detection rate of RSV in children showed an overall trend of initial increase followed by a decline, with higher detection rates in autumn and winter and lower rates in spring and summer. The RSV detection rate gradually decreased with age, with the highest rate observed in children <1 year old, accounting for 16.33% (80/490) of RSV-detection cases. Cough was the most common clinical symptom. Among the RSV-positive cases, 36 involved co-infection with another virus, 6 co-infected with three viruses, and 1 with mixed infection of four viruses. The most frequent co-infection was RSV and human coronavirus. ConclusionChildren under 1 year of age are more susceptible to RSV infection, with cough being the predominant symptom. RSV infection in Pudong New Area, Shanghai, mainly occurs in winter. Targeted prevention and control measures should be taken for children under 1 year old during the winter season to reduce the risk of both RSV infection and co-infection with human coronavirus and influenza virus.

Objective To put forward relevant national legislative proposals for preventing workplace violence (WPV) in the healthcare industry by comparing the current legal practices of China and the United States. Methods The Workplace Violence Prevention for Health Care and Social Service Workers Act (hereinafter referred to as the "Act") of the United States was translated and analyzed. The relevant normative legal documents in China were systematically reviewed to compare the legislative differences in the prevention and control of WPV against health care workers. Results The Act aims to establish an employer-driven legal framework for WPV prevention and control. China has no specific legislation for WPV, but has established partial legislation for protecting healthcare workers from external violence through various legal practices. The "Act" regards WPV as an occupational hazard and adopts the priority control order to carry out the prevention and control of WPV. In contrast, China's legislation for WPV approach emphasizes public security and undermines occupational health, treating WPV merely as a work-related injury or accident with limited protection. This gap reveals divergent priorities for legal interests. Conclusion China should integrate WPV prevention and control into the occupational health legal framework through revising existing laws, advancing dedicated legislation, and ratifying relevant international conventions, to strengthen the occupational health legal system. All stakeholders should clarify the responsibilities for WPV prevention and control of healthcare workers, and ensure comprehensive legislative response.

Abnormal accumulation of collagen fibrils is a hallmark feature of oral submucous fibrosis (OSF). However, the precise characteristics and underlying mechanisms remain unclear, impeding the advancement of potential therapeutic approaches. Here, we observed that collagen I, the main component of the extracellular matrix, first accumulated in the lamina propria and subsequently in the submucosa of OSF specimens as the disease progressed. Using RNA-seq and Immunofluorescence in OSF specimens, we screened the cartilage oligomeric matrix protein (COMP) responsible for the abnormal collagen accumulation. Genetic COMP deficiency reduced arecoline-stimulated collagen I deposition significantly in vivo. In comparison, both COMP and collagen I were upregulated under arecoline stimulation in wild-type mice. Human oral buccal mucosal fibroblasts (hBMFs) also exhibited increased secretion of COMP and collagen I after stimulation in vitro. COMP knockdown in hBMFs downregulates arecoline-stimulated collagen I secretion. We further demonstrated that hBMFs present heterogeneous responses to arecoline stimulation, of which COMP-positive fibroblasts secrete more collagen I. Since COMP is a molecular bridge with Fibril-associated collagens with Interrupted Triple helices (FACIT) in the collagen network, we further screened and identified collagen XIV, a FACIT member, co-localizing with both COMP and collagen I. Collagen XIV expression increased under arecoline stimulation in wild-type mice, whereas it was hardly expressed in the Comp^-/- mice, even with under stimulation. In summary, we found that COMP may mediates abnormal collagen I deposition by functions with collagen XIV during the progression of OSF, suggesting its potential to be targeted in treating OSF.
Oral Submucous Fibrosis/pathology* ; Cartilage Oligomeric Matrix Protein/genetics* ; Animals ; Mice ; Humans ; Fibroblasts/metabolism* ; Collagen Type I/metabolism* ; Arecoline/pharmacology* ; Mouth Mucosa/metabolism* ; Cells, Cultured ; Fluorescent Antibody Technique

Objectives:To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods:Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation.Results:A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions:The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.Objectives To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation. Results A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.

Large vessel occlusion due to intracranial atherosclerotic disease (ICAD-LVO) is one of the types of ischemic stroke with poor outcome. This article summarizes the relevant studies of ICAD-LVO in recent years, and reviews the imaging evaluation and treatment regimens to provide reference for clinical practice.

ObjectiveTo provide scientific support for the compilation of high-quality anti-nuclear， biological， and chemical （NBC） medical textbooks in China by retrieving books in the field of biological weapons defense in China， summarizing the publication time and distribution of publishing institutions， and categorizing content and key points of related books. MethodsRelevant subject terms in the field of biological weapons defense were searched through the official website of China National Digital Library and other websites， up until December 31， 2023， and were limited to books. Topic analysis was conducted on the introductions and contents of the books using the latent Dirichlet allocation （LDA） model. The number of topics was determined based on perplexity， and topics were identified according to the intertopic distance map， followed by a qualitative description of the core content of each topic. ResultsA total of 104 books were included in this study， among which four were identified as higher educational textbooks. The volume of publications increased during the periods 2002‒2004 and 2020‒2023. Research institutions accounted for the highest percentage of publishers （37.78%）， and 56.67% of the publishers were military institutions. The study identified six topics： "distribution， defense， and response to biological weapons"， "category， diagnosis， and treatment of biological warfare agents"， "response to biological public health emergencies"， "status of nuclear， biological， and chemical weapons internationally"， "biosafety risk management and prevention and control"， and "technologies and equipment related to biological hazard identification". ConclusionThere are few books in the field of biological weapons defense in China and the content is relatively outdated. In the future， the preparation of teaching materials should be aimed at practical emergency handling techniques for biological weapons， enhance the emphasis on biological weapons detection and biological warfare early warning， improve the fundamental theories at different training levels， and timely update the current research status in the field.

Objective:To develop a short-term prognostic model of spontaneous cerebral hemorrhage based on eXtreme Gradient Boosting (XGBoost) machine learning, and to compare its predictive performance with a Logistic regression model.Methods:Patients with sICH admitted to Department of Neurology, Second People's Hospital of Hefei from January 2018 to March 2022 were chosen; their general demographic characteristics, medical history, laboratory indices and cranial imaging data were retrospectively collected. The prognoses of patients 90 d after discharge were evaluated according to modified Rankin Scale (mRS) scores (good prognosis: mRS scores<3; poor prognosis: mRS scores≥3). XGboost and multiple Logistic regression models were used to screen out the factors for prognoses of patients 90 d after discharge, and area under receiver operating characteristic (ROC) curves, sensitivity, specificity and prediction accuracy of the 2 models were analyzed and compared.Results:A total of 413 patients with sICH were included; 180 patients(43.6 %) had poor prognosis and 233 (56.4%) had good prognosis 90 d after discharge. Multivariate Logistic regression results showed that age≥65 years, hemorrhage into the ventricle, hematoma volume of 20-40 mL, hematoma volume>40 mL and National Institutes of Health Stroke Scale (NIHSS) scores were independent influencing factors for short-term prognoses of sICH ( P<0.05). The variables in the XGBoost model were ranked in order of importance: NIHSS scores, systolic blood pressure at admission, Glasgow coma scale (GCS) scores, age≥65 years, hemorrhage into the ventricle, hematoma volume of 20-40 mL, and hematoma volume>40 mL. AUC of XGBoost model in predicting the prognosis was 0.895 (95% CI: 0.820-0.947), enjoying sensitivity of 68.89%, specificity of 94.83%, and prediction accuracy of 83.5%. AUC of Logistic regression model in predicting the prognosis was 0.894 (95% CI: 0.818-0.946), enjoying sensitivity of 93.33%, specificity of 70.69%, and prediction accuracy of 80.58%. Conclusion:The short-term prognostic model based on XGboost for sICH patients has high predictive efficacy, whose predictive accuracy is better than traditional Logistic regression.

Ischemic stroke is the main cause of death and disability in adults, and its incidence is increasing year by year. Obstructive sleep apnea (OSA) is the most common type of sleep-disordered breathing, which can increase the risk of ischemic stroke and affect the outcomes of patients. There is an increasing amount of research on the relationship between OSA and ischemic stroke. This article reviews the bidirectional relationship between OSA and ischemic stroke, the mechanism of OSA causing ischemic stroke, and the diagnosis and treatment of OSA in patients with ischemic stroke.

Objective:To investigate the impact of obstructive sleep apnea (OSA) on neurological function outcome in patients with acute ischemic stroke (AIS) at 90 days after onset.Methods:Patients with AIS admitted to Hefei Second People's Hospital from September 2022 to June 2023 were prospectively included. According to the modified Rankin Scale score at 90 days after onset, they were divided into a good outcome group (0-2) and a poor outcome group (>2). The demographic data, vascular risk factors, baseline laboratory tests, National Institutes of Health Stroke Scale (NIHSS) scores at admission, severity of obstructive sleep apnea (OSA), and apnea hypopnea index (AHI) were compared between the two groups. Multivariate logistic regression analysis was used to determine the independent risk factors for poor outcomes. Results:A total of 104 patients with AIS were enrolled, including 62 males (59.6%), with a median age of 65.5 years (interquartile range, 57.0-72.0 years). The median baseline NIHSS score was 3.00 (interquartile range, 2.00-4.00). The median AHI was 18.14/h (interquartile range, 11.34-27.88/h), 43 patients (41.35%) with no/mild OSA and 61 patients (58.65%) with moderate to severe OSA. Seventy-four patients (71.2%) had good outcome, and 30 patients (28.8%) had poor outcome. When introducing AHI as a categorical variable into the logistic regression model, the higher baseline NIHSS score (odds ratio [ OR] 3.041, 95% confidence interval [ CI] 1.797-5.145; P<0.001) and moderate to severe OSA ( OR 4.413, 95% CI 1.032-18.877; P=0.045) were independent risk factors for poor outcome; When introducing AHI as a continuous variable into the logistic regression model, higher baseline NIHSS score ( OR 3.176, 95% CI 1.844-5.472; P<0.001), age ( OR 1.093, 95% CI 1.014-1.177; P=0.020), and AHI ( OR 1.044, 95% CI 1.002-1.089; P=0.042) were independent risk factors for poor outcome. Conclusion:Moderate to severe OSA is an independent risk factor for poor functional outcome in patients with AIS at 90 days after onset, and a higher AHI indicates poor outcome in patients.

Background: Insulin regulates glucose homeostasis and has important effects on metabolism, cell growth, and differentiation. Depending on the cell type and physiological context, insulin signal has specific pathways and biological outcomes in different tissues and cells. For studying the signal pathway of insulin on glycolipid metabolism in porcine embryonic fibroblast (PEF), we used high-throughput sequencing to monitor gene expression patterns regulated by insulin. Objectives: The goal of our research was to see how insulin affected glucose and lipid metabolism in PEFs. Methods: We cultured the PEFs with the addition of insulin and sampled them at 0, 48, and 72 h for RNA-Seq analysis in triplicate for each time point. Results: At 48 and 72 h, 801 and 1,176 genes were differentially expressed, respectively. Of these, 272 up-regulated genes and 264 down-regulated genes were common to both time points. Gene Ontology analysis was used to annotate the functions of the differentially expressed genes (DEGs), the biological processes related to lipid metabolism and cell cycle were dominant. And the DEGs were significantly enriched in interleukin-17 signaling pathway, phosphatidylinositol-3-kinase-protein kinase B signaling pathway, pyruvate metabolism, and others pathways related to lipid metabolism by Kyoto Encyclopedia of Genes and Genomes enrichment analysis. Conclusions These results elucidate the transcriptomic response to insulin in PEF. The genes and pathways involved in the transcriptome mechanisms provide useful information for further research into the complicated molecular processes of insulin in PEF.