Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

ObjectiveTo establish a new noninvasive， simple， and convenient clinical predictive model by identifying independent predictive factors for rebleeding after endoscopic therapy in cirrhotic patients with esophagogastric variceal bleeding （EGVB）， and to provide a basis for individualized risk assessment and development of clinical intervention strategies. MethodsCirrhotic patients with EGVB who were diagnosed and treated in The First Affiliated Hospital of Xi’an Medical University from September 2018 to October 2023 were enrolled as subjects， and according to whether the patient experienced rebleeding within 1 year after endoscopic therapy， they were divided into rebleeding group with 93 patients and non-rebleeding group with 84 patients. Clinical data were collected and analyzed. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. A Logistic model was established based on the results of the univariate and multivariate analyses， and the receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the accuracy of the model. R software was used to visualize the model by plotting a nomogram， and the Bootstrap method was used for internal validation of the model. ResultsThe multivariate analysis showed that red blood cell count （RBC）， cholinesterase （ChE）， alkaline phosphatase （ALP）， albumin （Alb）， thrombin time （TT）， portal vein trunk diameter， sequential therapy， and primary prevention were independent predictive factors for rebleeding. Based on the results of the multivariate analysis， a logistic model was established as logit（P）=-0.805-1.978×（RBC）+0.001×（ChE）-0.020×（ALP）-0.314×（Alb）+0.567×（TT）+0.428×（portal vein trunk diameter）-2.303×［sequential therapy （yes=1， no=0）］-2.368×［primary prevention （yes=1， no=0）］. The logistic model （AUC=0.928， 95% confidence interval ［CI］： 0.893—0.964， P<0.001） had a better performance in predicting rebleeding than MELD score （AUC=0.603， 95%CI： 0.520—0.687， P=0.003）， Child-Pugh class （AUC=0.650， 95%CI： 0.578—0.722， P=0.001）， and FIB-4 index （AUC=0.587， 95%CI： 0.503—0.671， P=0.045）. The model had an optimal cut-off value of 0.607， a sensitivity of 0.817， and a specificity of 0.817. Internal validation confirmed that the model had good predictive performance and accuracy. ConclusionSequential therapy， implementation of primary prevention， an increase in RBC， and an increase in Alb are protective factors against rebleeding， while prolonged TT and widened main portal vein diameter are risk factors. The logistic model based on these independent predictive factors can predict rebleeding and thus holds promise for clinical application.

OBJECTIVE To establish a high-risk medication list and preventive and therapeutic measures for drug-induced hypofibrinogenemia， and to provide a reference for the prevention and treatment of this condition. METHODS By integrating domestic and international case reports， retrospective case-control studies， and spontaneous adverse drug reaction reporting databases， 19 domestically marketed high-risk drugs for drug-induced hypofibrinogenemia were identified. Based on the clinical characteristics and mechanisms of these drugs， relevant risk factors were systematically reviewed， and existing treatment options were summarized， leading to the preliminary development of recommended preventive and therapeutic measures. A two-round Delphi consultation was conducted to evaluate， revise， and ultimately reach consensus on the preliminary findings， using a mean importance score of ≥3.5 points for indicators and a coefficient of variation ＜0.3 as screening criteria. RESULTS The coefficient of expert authority for both rounds of expert consultation was 0.904. In the first round， the Kendall coordination coefficients （Kendall’s W ） for the high-risk medication list and the proposed preventive and therapeutic measures were 0.390 and 0.223 （ P ＜0.05）， respectively. In the second round， the Kendall’s W were 0.227 and 0.200 （ P ＜0.05）， respectively. After two rounds of expert consultation and discussion， 11 high-risk drugs for drug-induced hypofibrinogenemia， represented by hemocoagulase and certain anti-infective agents， were ultimately identified， along with 5 preventive and therapeutic measures spanning the entire process of “pre-medication assessment， intra-medication monitoring， and bleeding event management”. CONCLUSIONS This study has established a scientific and reliable high-risk medication list， and corresponding preventive and therapeutic measures for drug-induced hypofibrinogenemia， providing a theoretical basis and practical support for the early identification， stratified management， and precise intervention of this condition.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

BACKGROUND:At present,osteoarthritis has become a major disease affecting the quality of life of the elderly,and the therapeutic effect is poor,often focusing on preventing the disease process,and the pathogenesis of osteoarthritis is still not fully understood.Bioinformatics analysis was carried out to explore the main pathogenesis of osteoarthritis and related mechanisms of gene coding regulation. OBJECTIVE:To screen core differential genes with a major role in osteoarthritis by gene expression profiling. METHODS:Datasets were downloaded from the Gene Expression Omnibus(GEO):GSE114007,GSE117999,and GSE129147.Differential genes in the GSE114007 and GSE117999 data collections were screened using R software,performing differential genes to weighted gene co-expression network analysis.The module genes most relevant to osteoarthritis were selected to perform protein interaction analysis.Candidate core genes were selected using the cytocape software.The candidate core genes were subsequently subjected to least absolute shrinkage and selection operator regression and COX analysis to identify the core genes with a key role in osteoarthritis.The accuracy of the core genes was validated using an external dataset,GSE129147. RESULTS AND CONCLUSION:(1)A total of 477 differential genes were identified,265 differential genes associated with osteoarthritis were obtained by weighted gene co-expression network analysis,and 8 candidate core genes were identified.The least absolute shrinkage and selection operator regression analysis finally yielded a differential gene ASPM with core value that was externally validated.(2)It is concluded that abnormal gene ASPM expression screened by bioinformatics plays a key central role in osteoarthritis.

Objective To analyze the level of occupational health literacy (OHL) and mental health status in key populations in Jiangsu Province, and explore the impact of OHL on occupational stress, depressive symptoms, anxiety symptoms and insomnia symptoms. Methods A total of 11 181 workers from Jiangsu Province from April to December 2023 were selected as the research subjects using a combination of stratified cluster random sampling and probability proportional sampling method. The OHL levels of the workers, as well as their occupational stress, depression symptoms, anxiety symptoms and insomnia symptoms, were investigated using the Occupational Health Literacy Questionnaire of National Key Populations (including Occupational Health Literacy Scale, Core Occupational Stress Scale, Patient Health Questionaire-9, Generalized Anxiety Disorder 7-item Scale, and Self-Sleep Management Questionnaire). Results The OHL level of the research subjects was 41.7%, and the literacy levels of the four dimensions of occupational health legal knowledge, basic knowledge of occupational health protection, basic skills of occupational health protection, and healthy working style and behavior were 40.6%, 76.4%, 28.0% and 54.4%, respectively. The detection rates of occupational stress, depression symptoms, anxiety symptoms and insomnia symptoms were 21.8%, 17.7%, 26.4% and 29.6%, respectively. The result of multivariable logistic analysis showed that participants with adequate OHL had a lower risk of occupational stress, depressive symptoms, anxiety symptoms, and insomnia symptoms than those without adequate OHL (all P<0.01) after controlling individual and occupational confounding factors. The odds ratios and their 95% confidence intervals were 0.448(0.402-0.499), 0.664(0.593-0.742), 0.705(0.639-0.777) and 0.885(0.809-0.969), respectively. Conclusion OHL is an independent influencing factor for occupational stress, depressive symptoms, anxiety symptoms and insomnia symptoms in key populations from Jiangsu Province. Effective measures should be taken to improve the OHL level of workers, to reduce the risks of occupational stress, depressive symptoms, anxiety symptoms and insomnia symptoms.

Objective:To explore the trend of hearing changes in infants with GJB2 gene p.V37I mutation at different months. Methods:The subjects were 54 children（108 ears） with p.V37I homozygous or compound heterozygous mutation in GJB2 gene. All the subjects underwent auditory brainstem response, auditory steady-state response, acoustic immittance and other audiological tests. Children were divided into three groups according to their age, 26 cases in group A were ≤3 months old, 17 cases in group B were>3~≤6 months old, and 11 cases in group C were>6 months old. Statistical analysis was performed on the three groups of ABR response threshold, hearing degree, the ASSR average response threshold of four frequencies and the ASSR response thresholds for each frequency of 500, 1 000, 2 000 and 4 000 Hz. Results:Among the 54 cases, 35 were male and 19 were female, with an age rang of 2-27 months and a median age of 4 months. The ABR response threshold of the three groups were ranked from low to high as group A, group B and group C, and the difference was statistically significant（P<0.05）. The ABR response thresholds of the three groups were ranked from low to high as group A, group B, and group C. The comparison between groups showed that the ABR response thresholds of group C was higher than that of group A（P=0.006）. The proportion of confirmed hearing loss in the three groups was 34.61%, 50.00% and 63.64%, respectively, and the difference of hearing level among the three groups was statistically significant（P<0.05）. The comparison between groups showed that the difference between group A and group C was statistically significant（P=0.012）, normal hearing accounted for the highest proportion in group A（65.39%）, while mild hearing loss accounted for the highest proportion in group C（45.46%）. The ASSR average response thresholds of the four frequencies in the three groups were ranked from low to high as group A, group B and group C, and the difference is statistically significant（P<0.05）. The comparison between groups showed that response ASSR thresholds of group C was higher than that of group A（P=0.002）. Response thresholds of ASSR in each frequency in the three groups were all ranked from low to high as in group A, group B and group C, and the differences were statistically significant（P<0.05）. Compared with each other between groups, response ASSR thresholds of group C was higher than those of group A（P=0.003） and group B（P=0.015） at 500 Hz, while response ASSR thresholds of group C was higher than group A at 1 000 Hz（P=0.010） and 2 000 Hz（P<0.001）, and there was no statistical difference at 4 000 Hz. Conclusion:The incidence of hearing loss in GJB2 gene p.V37I mutation increased with age, and the degree of hearing loss increased, the hearing progression was mainly 500, 1 000 and 2 000 Hz suggesting regular follow-up and alert to hearing changes.
Humans ; Connexin 26 ; Male ; Female ; Infant ; Child, Preschool ; Mutation ; Evoked Potentials, Auditory, Brain Stem ; Connexins/genetics* ; Auditory Threshold ; Hearing/genetics* ; Hearing Loss/genetics*

This article reviews the role of different types of T lymphocyte subpopulations in pathological cardiac fibrosis remodeling. T helper 17 (Th17) cells are implicated in promoting the development of pathological cardiac fibrosis remodeling, while regulatory T (Treg) cells exert an immunosuppressive functions as negative regulators, attributing to their interleukin-10 (IL-10) secretion and functional phenotype. Th1 and Th2 cells are involved in different stages of the inflammatory response in pathological cardiac fibrosis remodeling, and their influence varies according to the pathological mechanisms of different cardiac diseases. In addition, CD8⁺ T cells regulate the activation and polarization of macrophages, promote the secretion of granzyme B, induce cardiomyocyte apoptosis, and aggravate cardiac fibrosis post-myocardial infarction. Considering the limitation of cytokine modulation in clinical therapy of heart failure, targeting T-cell co-stimulatory molecules emerges as a promising strategy for treating pathologic cardiac remodeling. Future research will explore chimeric antigen receptor modified T cells (CAR-T cells) technology and targeted regulation of Treg cells quantity and phenotype, for both of which have the potential to become effective methods for treating heart disease.
Humans ; Fibrosis ; T-Lymphocytes, Regulatory/immunology* ; Ventricular Remodeling/immunology* ; Myocardium/immunology* ; Animals ; Th17 Cells/immunology* ; Interleukin-10/metabolism* ; Th1 Cells/immunology* ; Th2 Cells/immunology*