Objective: To analyze the time-related factors influencing daily blood donation attendance at fixed donation sites in Nanjing and the heterogeneity among sites, and to provide evidence for optimizing site layout and operational management. Methods: Based on daily attendance data from 17 fixed donation sites in Nanjing for the full year of 2025, matched with contemporaneous meteorological and air quality data, a two-stage negative binomial generalized linear mixed model (NB-GLMM) was constructed. In the second stage, site-level static characteristics (number of scenic spots, daily operating hours, number of shopping malls, public transport stops, hospitals, universities, and residential buildings) were additionally incorporated. Model comparison was performed using Akaike information criterion (AIC). Significance of random effects was tested by likelihood ratio test, and site-specific random effects were extracted using empirical Bayes estimation. Robustness of the results was verified through residual diagnostics and multiple sensitivity analyses. Results: The first-stage model showed that rainfall was associated with lower attendance (IRR=0.943, P<0.001); holidays were associated with higher attendance (IRR=1.162, P<0.001); Saturdays and Sundays showed higher attendance than Mondays, with the strongest association on Sundays (IRR=1.195, P<0.001). Temperature exhibited a non-linear relationship (linear term P=0.051, quadratic term P=0.036). The joint results of the linear and quadratic terms for temperature suggested a nonlinear relationship between attendance and temperature. After introducing static characteristics in the second stage, the number of scenic spots (IRR=1.372, P=0.008) and daily operating hours (IRR=1.823, P<0.001) were found to be positively associated with attendance, while the numbers of shopping malls, public transport stops, hospitals, universities, and residential buildings showed no significant effects. Conclusion: Daily blood donation attendance at fixed sites in Nanjing is influenced by multiple factors including weather, day of the week, holidays, and site surroundings. Substantial heterogeneity exists among different sites; extended operating hours and more nearby scenic spots are associated with increased attendance.

Objective: To evaluate the feasibility of re-entry for blood donors deferred for single-reagent reactive anti-TP ELISA results, to assess the ability of ELISA S/CO values of different kits to discriminate true-from false-positive samples and to determine the optimal cutoff value for each kit, thereby providing a scientific basis for improving blood donor reentry strategies. Methods: Data of two donor cohorts were retrospectively collected: (1) a re-entry cohort of 106 donors who applied for re-entry at Jiangsu Province Blood Center from January 1, 2018 to December 31, 2025, all previously deferred for single-reagent reactive anti-TP ELISA results (58 reactive with the Xinchuang kit and 48 with the Kehua kit); (2) a routine screening confirmation cohort of 39 donors found to be single-reagent reactive in routine donation screening and additionally tested by TPPA between April 2024 and June 2026 (17 Xinchuang and 22 Kehua). Using TPPA results as the gold standard, the two cohorts were pooled (75 Xinchuang, 70 Kehua), and receiver operating characteristic (ROC) curves were constructed separately for each kit. The 95% confidence interval (CI) of the area under the curve (AUC) was estimated with 2 000 bootstrap replicates, and the optimal S/CO cutoff of each kit was determined by the maximum Youden index; sensitivity analysis was performed by cohort source. In addition, TPPA-confirmed positivity rates were compared between single-and dual-reagent reactive samples at re-entry testing. Results: Of the 106 donors in the re-entry cohort, 73 were successfully requalified and 33 failed. The mean S/CO value at deferral testing in successfully requalified donors was 1.930 (median 1.570), significantly lower than 3.487 (median 2.592) in failed donors (P<0.001). Among the 33 donors who failed requalification, 16 samples were TPPA positive; at re-entry testing, 7 were dual-reagent reactive (6 TPPA positive), 25 remained single-reagent reactive (9 TPPA positive), and 1 was ELISA non-reactive (TPPA positive). The TPPA positivity rate of dual-reagent reactive samples at re-entry testing was 85.7% (6/7), significantly higher than 36.0% (9/25) of single-reagent reactive samples (P=0.033); the agreement between the two kits at re-entry testing was poor (Kappa=0.231). ROC analysis of pooled samples showed that for the Xinchuang kit (n=75, 14 TPPA positive), the AUC was 0.837 (95%CI:0.731-0.929) with an optimal cutoff of 2.025, corresponding to a sensitivity of 92.9% (13/14), a specificity of 65.6% (40/61) and a negative predictive value of 97.6% (40/41); for the Kehua kit (n=70, 13 TPPA positive), the AUC was 0.787 (95%CI:0.649-0.900) with an optimal cutoff of 1.733, corresponding to a sensitivity of 92.3% (12/13), a specificity of 56.1% (32/57) and a negative predictive value of 97.0% (32/33). Sensitivity analysis by cohort showed that the AUCs calculated separately for the re-entry and screening cohorts were consistent in direction with the pooled analysis. Conclusion: S/CO values of both the Xinchuang and Kehua ELISA kits can discriminate TPPA-confirmed true from false positives, but their optimal cutoffs differ. Dual-reagent reactivity at re-entry testing strongly indicates TPPA-confirmed positivity; the TPPA positivity rate of single-reagent reactive samples increases in a gradient with rising S/CO values, and single-reagent reactive samples with low S/CO values are mostly false positives. Incorporating kit-specific stratified management based on quantitative S/CO thresholds into the re-entry mechanism may help establish a fast-track re-entry pathway for low-risk false-positive donors.

Objective: To explore the micro associations and key bridge nodes between physical fitness indicators and anxiety/depressive symptoms among college students using network analysis, so as to provide a theoretical foundation for promoting physical and mental health of college students. Methods: From September to October 2025, a combination of purposive sampling and cluster sampling was employed to select 2 158 college students from three universities in Xuzhou City. Seven physical fitness indicators were measured and standardized according to the National Student Physical Health Standard. The Generalized Anxiety Disorder Scale-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9) were used to assess anxiety and depressive symptoms. Independent samples t-test was used for intergroup comparisons of physical fitness indicators and psychological symptom scores. A gaussian graphical model (GGM) was constructed to calculate node and bridge strength, followed by stability analyses. Results: The detection rates of anxiety and depressive symptoms among college students were 21.3% and 24.5%, respectively. Male participants demonstrated superior performance in physical fitness indicators such as vital capacity, 50 meter sprint, and standing long jump compared to female participants, whereas females exhibited better results in the sit and reach test ( t =48.35, -44.82 , 70.21, -16.51, all P <0.01). Regarding psychological indicators, female participants showed higher scores of anxiety and depressive symptoms than males ( t =-4.15, -4.46, both P <0.01). Physical fitness and psychological symptoms were predominantly negatively correlated. "feeling tired" and "not being able to stop or control worrying" were the symptoms with the highest centrality in the network of physical fitness and phychological symptoms among college students (standardized strengths were 2.15 and 1.98, respectively). Among the bridge indicators, the "1 000 m (male)/800 m (female) run" exhibited the highest strength (0.85), outperforming "vital capacity" (0.35); it was linked to the symptom cluster primarily by negatively predicting "feeling tired" (edge weight=-0.38). The network stability was excellent of physical fitness and phychological symptoms among college students (correlation stability coefficient= 0.60 ). Conclusions Endurance capacity serves as the most critical bridge connecting physical and mental health, and its decline is closely related to intensified feelings of fatigue. Colleges should prioritize endurance training as a core target for promoting college students mental health.

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Objective To explore the safety and effects of alpha-lipoic acid (ALA) in patients with ischemic heart failure (IHF). Methods A randomized, double-blind, placebo-controlled trial was designed (ClinicalTrial.gov registration number NCT03491969). From January 2019 to January 2023, 300 patients with IHF were enrolled in four medical centers in China, and were randomly assigned at a 1∶1 ratio to receive ALA (600 mg daily) or placebo on top of standard care for 24 months. The primary outcome was the composite outcome of hospitalization for heart failure (HF) or all-cause mortality events. The second outcome included non-fatal myocardial infarction (MI), non-fatal stroke, changes of left ventricular ejection fraction (LVEF) and 6-minute walking distance (6MWD) from baseline to 24 months after randomization. Results Finally, 138 patients of the ALA group and 139 patients of the placebo group attained the primary outcome. Hospitalization for HF or all-cause mortality events occurred in 32 patients (23.2%) of the ALA group and in 40 patients (28.8%) of the placebo group (HR＝0.753, 95%CI 0.473-1.198, P＝0.231; Figure 1A-1C). The absolute risk reduction (ARR) was 5.6%, the relative risk reduction (RRR) associated with ALA therapy was approximately 19.4% compared to placebo, corresponding to a number needed to treat (NNT) of 18 patients to prevent one event. In the secondary outcome analysis, the composite outcome of the major adverse cardiovascular events (MACE) including the hospitalization for HF, all-cause mortality events, non-fatal MI or non-fatal stroke occurred in 35 patients (25.4%) in the ALA group and 47 patients (33.8%) in the placebo group (HR＝0.685, 95%CI 0.442-1.062, P＝0.091; Figure 1D). Moreover, greater improvement in LVEF (β＝3.20, 95%CI 1.14-5.23, P＝0.002) and 6MWD (β＝31.7, 95%CI 8.3-54.7, P＝0.008) from baseline to 24 months after randomization were observed in the ALA group as compared to the placebo group. There were no differences in adverse events between the study groups. Conclusions These results show potential long-term beneficial effects of adding ALA to IHF patients. ALA could significantly improve LVEF and 6MWD compared to the placebo group in IHF patients.

BACKGROUND: T cell dysfunction, which includes exhaustion, anergy, and senescence, is a distinct T cell differentiation state that occurs after antigen exposure. Although T cell dysfunction has been a cornerstone of cancer immunotherapy, its potential in transplant research, while not yet as extensively explored, is attracting growing interest. Interferon regulatory factor 4 (IRF4) has been shown to play a pivotal role in inducing T cell dysfunction. METHODS: A novel ultra-low-dose combination of Trametinib and Rapamycin, targeting IRF4 inhibition, was employed to investigate T cell proliferation, apoptosis, cytokine secretion, expression of T-cell dysfunction-associated molecules, effects of mitogen-activated protein kinase (MAPK) and mammalian target of rapamycin (mTOR) signaling pathways, and allograft survival in both in vitro and BALB/c to C57BL/6 mouse cardiac transplantation models. RESULTS: In vitro , blockade of IRF4 in T cells effectively inhibited T cell proliferation, increased apoptosis, and significantly upregulated the expression of programmed cell death protein 1 (PD-1), Helios, CD160, and cytotoxic T lymphocyte-associated antigen (CTLA-4), markers of T cell dysfunction. Furthermore, it suppressed the secretion of pro-inflammatory cytokines interferon (IFN)-γ and interleukin (IL)-17. Combining ultra-low-dose Trametinib (0.1 mg·kg -1 ·day -1 ) and Rapamycin (0.1 mg·kg -1 ·day -1 ) demonstrably extended graft survival, with 4 out of 5 mice exceeding 100 days post-transplantation. Moreover, analysis of grafts at day 7 confirmed sustained IFN regulatory factor 4 (IRF4) inhibition, enhanced PD-1 expression, and suppressed IFN-γ secretion, reinforcing the in vivo efficacy of this IRF4-targeting approach. The combination of Trametinib and Rapamycin synergistically inhibited the MAPK and mTOR signaling network, leading to a more pronounced suppression of IRF4 expression. CONCLUSIONS Targeting IRF4, a key regulator of T cell dysfunction, presents a promising avenue for inducing transplant immune tolerance. In this study, we demonstrate that a novel ultra-low-dose combination of Trametinib and Rapamycin synergistically suppresses the MAPK and mTOR signaling network, leading to profound IRF4 inhibition, promoting allograft acceptance, and offering a potential new therapeutic strategy for improved transplant outcomes. However, further research is necessary to elucidate the underlying pharmacological mechanisms and facilitate translation to clinical practice.
Animals ; Mice ; Mice, Inbred BALB C ; Mice, Inbred C57BL ; Interferon Regulatory Factors/metabolism* ; Heart Transplantation/methods* ; T-Lymphocytes/immunology* ; Sirolimus/therapeutic use* ; Pyridones/therapeutic use* ; Graft Survival/drug effects* ; Pyrimidinones/therapeutic use* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Male ; Signal Transduction/drug effects*

With the increasing abuse of antibiotics,the development of rapid,accurate and sensitive methods for antibiotic detection has become critical.Nucleic acid sensors as new biosensors have shown great potential in the field of antibiotic detection due to their high selectivity,high sensitivity and real-time monitoring ability.This paper reviews the research progress in antibiotic detection based on nucleic acid sensors,including colorimetric,optical and electrochemical nucleic acid sensors,in the hope of providing a reference for the research and development of new types of antibiotic detection technologies based on nucleic acid sensors.

Objective To employ three dimensional high-resolution vessel wall magnetic resonance imaging(3D hr-VW-MRI)for analyzing the imaging characteristics of posterior circulation non-stenotic intracranial atherosclerotic plaque and to discuss its diagnostic value in identifying culprit plaques.Methods Ninety-three patients(age[62.94±9.70]years old,67 males,26 females)with non-stenotic atherosclerosis in our hospital from Jan.2019 to Jan.2021 were retrospectively recruited.The imaging features of plaques,including luminal area,maximum wall thickness and minimum wall thickness at the most stenotic site,stenosis rate,plaque burden,remodeling index,eccentricity index,enhancement ratio at the most stenotic site,and intraplaque hemorrhage,were measured based on T1-weighted imaging(T1WI)and contrast-enhanced T1WI.The culprit plaque was defined as a lesion arising from the responsible vascular supply area to a fresh infarction on the diffusion weighted imaging(DWI)and T2 fluid attenuated inversion recovery(T2-FLAIR)images with accompanying ischemic stroke/transient ischemic attack(TIA).A plaque was considered to be a nonculprit plaque when it occurred in patients with presumed ischemic stroke/TIA,but without an infarct on DWI and T2-FLAIR.Results Sixty-one culprit plaques and 32 non-culprit plaques were analyzed.The proportions of patients with hyperlipidemia,National Institutes of Health stroke scale(NIHSS)score,narrowest plaque enhancement rate,and incidence of intraplaque hemorrhage in the culprit plaque group were significantly higher than those in the non-culprit plaque group(all P＜0.05).Multivariate logistic regression analyses showed that NIHSS score(odds ratio[OR]=1.799,95％confidence interval[CI]1.303-2.484,P＜0.001),enhancement ratio(OR=1.076,95％CI 1.027-1.128,P=0.002)and intraplaque hemorrhage(OR=30.708,95％CI 2.563-367.925,P=0.007)were associated with plaque type.Conclusion NIHSS score,enhancement ratio at the most stenotic site,and intraplaque hemorrhage are independent risk factors for culprit plaques in patients with posterior circulation non-stenotic intracranial atherosclerotic disease.These indicators may help identify such culprit plaques and could be used to screen individuals with plaques having these characteristics,thereby providing a basis for early preventive interventions.

Objective To analyze the basic characteristics of patients with acute myocardial infarction in a tertiary hospi-tal from 2014 to 2023,and provide references for the prevention,treatment,management,and quality control of this disease.Methods Based on the data from the medical records of patients with acute myocardial infarction admitted to a tertiary hospital from January 1,2014,to December 31,2023,the basic characteristics of hospitalized patients and trends in hospitalization costs were analyzed to summarize the development patterns.Results Over the past decade,the number of hospitalized patients with a-cute myocardial infarction has been increasing,while the average length of hospital stay,average cost per hospitalization,and mortality rate have been decreasing.Among the 19 937 patients,there were 16 037 male patients(80.44％)and 3 900 female patients(19.56％),with a male-to-female ratio of 4.11∶1.The median age for male patients was 60 years,while for female patients it was 68 years,indicating that males tend to develop the disease approximately 10 years earlier than females.Among pa-tients aged 60 and above,the mortality rate is positively correlated with age,while among patients below 60,the mortality rate is negatively correlated with age.The decision to undergo surgery has a significant impact on hospitalization costs.From the per-spective of cost structure,the proportion of consumables has decreased from 69.81％to 54.60％in the past decade but remains relatively high.Conclusion With the advancement of hospital management and medical insurance policies,the diagnosis,treat-ment,and quality of care for acute myocardial infarction have significantly improved.However,consumables management remains a key focus.Men and individuals aged 50 and above should be given special attention.During the diagnosis and treatment process,greater attention should also be given to younger or older patients and female patients to reduce the mortality rate.

This study examines the progress and application of Artificial Intelligence (AI) in the prevention and control of infectious diseases within Chinese healthcare institutions. It analyzes the difficulties and challenges encountered during implementation to promote the intelligent transformation and upgrading of infectious disease prevention and control. The results indicate that AI technology has made progress in areas such as infectious disease surveillance and early warning, risk assessment and emergency response, screening and detection, image-based diagnosis and analysis, and health management. Nevertheless, significant challenges remain, including limited application depth and breadth, issues with data quality and privacy protection, insufficient technological maturity and interpretability, potential legal risks, and a shortage of interdisciplinary professionals. To advance the application of AI technology in infectious disease prevention and control and support the modernization of China′s relevant systems, recommendations include strengthening policy support, establishing data standards and robust privacy protection mechanisms, increasing R&D investment, refining laws and regulations, and enhancing the training of interdisciplinary talent.