Objective To quantitatively assess the exposure-response association between exposure to heatwave and sudden death, estimate the attributable excess deaths, and identify potential vulnerable subgroups. Methods A time-stratified case-crossover study was conducted among residents who died from sudden death in Jiangsu Province, China between 2015 and 2021. Heatwave events in Jiangsu Province, defined using varying relative temperature thresholds and durations, were identified using temperature data from the China Meteorological Administration Land Data Assimilation System (CLDAS V2.0). Individual heatwave exposure was assessed based on each subject's residential address. The exposure-response association between heatwave and sudden death was evaluated using conditional logistic regression model combined with a Distributed Lag Nonlinear Model(DLNM). Heatwave-attributable excess deaths were estimated. Stratified analyses by sex and age were performed to assess potential effect modifications. Results Under all definitions, exposure to heatwave was significantly associated with an increased risk of sudden death, and the risk increased with the intensity of heatwave. Using the P95_3d definition (temperature exceeding the 95th percentile for ≥3 consecutive days), heatwave was significantlyassociated with a 56% increased risk of sudden death (95% CI: 31%, 86%). The population-attributable fraction of sudden death due to heatwave exposure was 1.45% (95% CI: 0.97%, 1.90%). Stratified analyses indicated no statistically significant differences in the association between heatwave exposure and sudden death across age or sex subgroups. Conclusion Heatwave exposure was associated with an increased risk of sudden death. Reducing heatwave exposure during summer may help lower the occurrence of sudden death.

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.

BACKGROUND:The repair process of myocardial injury involves complex cellular and molecular mechanisms,especially mitochondrial calcium homeostasis,macrophage autophagy and pyroptosis pathways.Traditional Chinese medicine(TCM)has shown significant clinical efficacy in improving myocardial injury,but its mechanism of action needs to be thoroughly investigated. OBJECTIVE:To investigate the role of mitochondrial calcium homeostasis-mediated macrophage autophagy and pyroptosis pathways in myocardial injury,and to summarize the progress of TCM in this field. METHODS:A computerized search was performed for relevant literature from the database inception to March 2024 in the Web of Science,PubMed and CNKI.The search terms were"mitochondrial calcium homeostasis,macrophage autophagy,macrophage pyroptosis,traditional Chinese medicine,myocardial injury,myocardial injury reperfusion"in Chinese and English.Through literature review,we analyzed the relationship between mitochondrial calcium homeostasis and macrophage autophagy and pyroptosis,explored the mechanism of their roles in myocardial injury,and summarized the pathways of multi-targeted,multi-pathway effects of TCM. RESULTS AND CONCLUSION:The maintenance of mitochondrial calcium homeostasis has been found to be closely related to the normal function of cardiomyocytes.Macrophages can participate in the repair process of myocardial injury through autophagy and pyroptosis pathways.Autophagy contributes to cell clearance and regulation of inflammatory response,while pyroptosis affects myocardial repair by releasing inflammatory factors.TCM regulates mitochondrial calcium homeostasis and macrophage function through multiple mechanisms.For example,astragalosid regulates calcium homeostasis by lowering mitochondrial membrane potential and inhibiting cytochrome C,and epimedium glycoside plays a role in reducing β-amyloid deposition.In addition,herbal compounds and single drugs promote myocardial repair by activating or inhibiting specific signaling pathways,such as PI3K/AKT and nuclear factor-κB signaling pathways.Future studies should focus on the interactions between mitochondrial calcium homeostasis,autophagy and pyroptosis pathways,as well as how TCM can exert therapeutic effects through these pathways to provide new strategies and drugs for the treatment of myocardial injury.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

OBJECTIVE To build a Tibetan-language medication service platform based on “internet+” and evaluate its effect on improving medication compliance and safety of Tibetan patients with chronic disease. METHODS Medication guidance contents of commonly used drugs in the outpatient department were summarized， translated and recorded in Tibetan-language or video to form a “text-audio-video” multi-dimensional “internet+ ” Tibetan-language medication service platform. A total of 387 Tibetan outpatients with chronic disease in our hospital after the implementation of “internet+” Tibetan-language medication service platform （from January 2024 to June 2024） in our hospital were selected as the intervention group， and 387 Tibetan outpatients before the implementation （from January 2023 to June 2023） were selected as the control group. Patients in the control group received conventional window-based Chinese-language medication services， while patients in the intervention group received both conventional window-based Chinese-language medication service and “internet+ ” Tibetan-language medication service. The medication compliance of patients was evaluated using the 12-item Medication Compliance Scale. A six-level causality assessment was conducted as the principles for analyzing adverse drug reactions （ADR） set by the National Center for ADR Monitoring. Additionally， statistics were compiled on the occurrence of ADR that were assessed as “definite”“probable” or “possible” in the causality assessment. RESULTS The proportion （31.0%） of patients with good medication compliance and compliance scores [39.0 （37.0，42.0）] of patients in the intervention group were significantly better than control group [7.0%， 21.0（19.0， 23.0）]（ P＜0.05）. There were no statistically significant differences in the incidence of various types of ADR or the overall incidence between the two groups （P＞0.05）. CONCLUSIONS The “internet+” Tibetan-language medication service platform is constructed successfully； the service can effectively improve the medication compliance of Tibetan-language patients， but its effect on improving the medication safety of patients is limited.

Background Enhancing the sense of honor and belonging among medical staff is a key component of establishing a modern hospital management system. Compared to medical staff at general hospitals, medical staff at oncology hospitals are more prone to job burnout, yet few studies in China have focused on job burnout among employees in oncology hospitals. Objective To propose a hypothetical model in which job well-being moderates the relationship between stressors and occupational burnout, to explore how stressors influence burnout and potential moderating role of job well-being, and to provide better understanding of job burnout and motivate employees based on the double-edge sword effect of stressors. Methods A cross-sectional survey was conducted in May 2022 at a tertiary oncology specialty hospital in Chongqing, China. A total of 1 898 medical staff were recruited. Data were collectedthrough four scales including a general information questionnaire, Maslach Burnout Inventory-Human Service Survey, Work Stressor Scale, and Occupational Well-being Scale for Medical Staff. Independent sample t-tests and one-way ANOVA were used for univariate comparisons of job burnout. Pearson correlation analysis was employed to examine the relationships between job burnout, stressors, and job well-being. Hierarchical linear regression was conducted to identify factors influencing job burnout and to examine potential moderating role of job well-being in the relationship between stressors and job burnout. Results A total of 2 123 questionnaires were distributed, with 1 898 valid responses, yielding an effective response rate of 89.4%. The prevalence of job burnout was 60.1%. The correlation coefficient was 0.717 (P<0.001) between stressors and burnout, −0.784 (P<0.05) between job well-being and burnout, and −0.744 (P<0.001) between stressors and job well-being. The quadratic stressors showed a statistically significant effect on burnout (β=0.404, P<0.01). Job well-being positively moderated the relationship between the linear stressors and burnout (β=1.289, P<0.001) and negatively moderated the relationship between the quadratic stressors and job burnout (β=−0.571, P<0.01), explaining 7.1% of the variance. Conclusion Job burnout prevalence is relatively high among employees in oncology hospitals. There is a curvilinear relationship between stressors and job burnout, with job well-being moderating this relationship. From a practical perspective, it is recommended to establish a tiered stress alert system to monitor employees’ stress levels and prevent prolonged exposure to high-pressure conditions. Additionally, improving employees’ job well-being through institutional incentives and developmental support can enhance its moderating role in mitigating the adverse effects of stressors on job burnout. Meanwhile, fostering coordinated responses between organizations and individuals is crucial for strengthening mental health management systems, thereby supporting a healthy, stable, and sustainable development of the healthcare workforce.