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.

BACKGROUND: Alpha-glucosidase inhibitors or dipeptidyl peptidase-4 inhibitors are both hypoglycemia agents that specifically impact on postprandial hyperglycemia. We compared the effects of acarbose and sitagliptin add on to metformin on time in range (TIR) and glycemic variability (GV) in Chinese patients with type 2 diabetes mellitus through continuous glucose monitoring (CGM). METHODS: This study was a randomized, open-label, active-con-trolled, parallel-group trial conducted at 15 centers in China from January 2020 to August 2022. We recruited patients with type 2 diabetes aged 18-65 years with body mass index (BMI) within 19-40 kg/m 2 and hemoglobin A1c (HbA1c) between 6.5% and 9.0%. Eligible patients were randomized to receive either metformin combined with acarbose 100 mg three times daily or metformin combined with sitagliptin 100 mg once daily for 28 days. After the first 14-day treatment period, patients wore CGM and entered another 14-day treatment period. The primary outcome was the level of TIR after treatment between groups. We also performed time series decomposition, dimensionality reduction, and clustering using the CGM data. RESULTS: A total of 701 participants received either acarbose or sitagliptin treatment in combination with metformin. There was no statistically significant difference in TIR between the two groups. Time below range (TBR) and coefficient of variation (CV) levels in acarbose users were significantly lower than those in sitagliptin users. Median (25th percentile, 75th percentile) of TBR below target level <3.9 mmol/L (TBR 3.9 ): Acarbose: 0.45% (0, 2.13%) vs . Sitagliptin: 0.78% (0, 3.12%), P = 0.042; Median (25th percentile, 75th percentile) of TBR below target level <3.0 mmol/L (TBR 3.0 ): Acarbose: 0 (0, 0.22%) vs . Sitagliptin: 0 (0, 0.63%), P = 0.033; CV: Acarbose: 22.44 ± 5.08% vs . Sitagliptin: 23.96 ± 5.19%, P <0.001. By using time series analysis and clustering, we distinguished three groups of patients with representative metabolism characteristics, especially in GV (group with small wave, moderate wave and big wave). No significant difference was found in the complexity of glucose time series index (CGI) between acarbose users and sitagliptin users. By using time series analysis and clustering, we distinguished three groups of patients with representative metabolism characteristics, especially in GV. CONCLUSIONS: Acarbose had slight advantages over sitagliptin in improving GV and reducing the risk of hypoglycemia. Time series analysis of CGM data may predict GV and the risk of hypoglycemia. TRIAL REGISTRATION Chinese Clinical Trial Registry: ChiCTR2000039424.
Humans ; Metformin/therapeutic use* ; Sitagliptin Phosphate/therapeutic use* ; Acarbose/therapeutic use* ; Diabetes Mellitus, Type 2/blood* ; Middle Aged ; Male ; Female ; Adult ; Blood Glucose/drug effects* ; Hypoglycemic Agents/therapeutic use* ; Aged ; Glycated Hemoglobin/metabolism* ; Adolescent ; Young Adult ; China ; East Asian People

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 investigate the distribution of IgM anti-A/B titers among group O whole blood donors in Jiangsu, establish a low-titer threshold, and analyze the demographic characteristics of low-titer donors, so as to provide data for recruiting low-titer group O whole blood (LTOWB) donors. Methods: Plasma samples from 1 009 group O whole blood donors were tested for IgM anti-A and anti-B titers using the microplate technique. The distribution of antibody titers was analyzed to establish a low-titer threshold. The distribution trends of titers across different demographic groups were also analyzed. Results: The peak titer for anti-A, anti-B were 64 (31.5%), 4 (23.8%), respectively, The proportion of donors with both anti-A and anti-B titers below 64 was 97.3% (982/1 009). The mean anti-A titer was higher than anti-B titer. Anti-A titers were higher in female donors than in male donors (P<0.05). The anti-A titers differed significantly among different age groups (P<0.05). However, no significant difference in titers was observed based on the number of donations (P>0.05). Conclusion: A titer of 64 can be used as the reference threshold of LTOWB in Jiangsu. Male donors of appropriate age are more suitable than female donors for establishing an emergency panel of LTOWB mobile donors.

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.

Objective:To summarize the medication law and academic experience of Professor Yuan Jinsheng in the treatment of angina pectoris (AP) of coronary heart disease (CHD) through R language data mining technique.Methods:The effective outpatient medical records of Professor Yuan Jinsheng in the treatment of AP of CHD from January 1, 2016 to September 30, 2023 were selected, and the R 4.2.3 was used for frequency statistics, association rule analysis, systematic clustering analysis and correlation analysis of prescription drugs.Results:A total of 292 prescriptions were included, including 268 patients, involving 204 kinds of Chinese materia medica, and the total frequency of Chinese materia medica was 4 253 times. The main properties were warm and neutral, the main tastes were bitter, pungent and sweet, and the main meridians were spleen, lung and liver meridians. The analysis of association rules obtained 125 core TCM combinations, and the commonly used drug pair was Trichosanthis Fructus-Aurantii Fructus Immaturus. The core prescription composed of Aurantii Fructus Immaturus, Chuanxiong Rhizoma, Trichosanthis Fructus, Citri Reticulatae Pericarpium and Salviea Miltiorrhizae Radix et Rhizoma. Seven TCM groups of were obtained by systematic clustering analysis. Correlation analysis showed that the drug pairs with phi coefficient greater than 0.6 were in 8 groups.Conclusions:Studies suggest that AP of CHD is located in the heart, which is related to lung, spleen, liver and kidney, deficiency in root and excess in superficiality, phlegm, blood stasis and qi stagnation are important pathological factors. The treatment is based on the basic principles of tonifying qi, promoting yang, relieving rheumatism, resolving phlegm, activating blood circulation, and promoting qi circulation. It embodies Professor Yuan's academic thoughts and principles of differentiation and treatments of "taking fluency as the main point, regulating the five internal organs and weighing the root and superficiality".

Whole blood transfusion for the resuscitation of trauma patients is not a new concept, with its history dating back to World War I. Due to the significant survival benefits of early intervention with whole blood, an increasing number of countries and regions are using whole blood for pre-hospital resuscitation of patients with traumatic haemorrhage. Whole blood containing low-titer anti-A and anti-B antibodies is known as low-titer group O whole blood. The safety of transfusion of low-titer group O whole blood has been proven in military and local trauma centers in some countries. The use of low-titer group O whole blood for pre-hospital trauma care in China will pose new challenges to blood stations that provide whole blood. This paper reviews the selection of group O donors, the setting of anti-A and anti-B titers threshold and their detection, as well as the collection, preparation and storage of whole blood.

Objective Based on Network pharmacology to explore the mechanism of Compound Danshen Dripping Pills in treating Psycho-cardiological disease.Methods To obtain the validated targets of the complete formulation of Compound Danshen Dripping Pills,data were sourced from databases including China National Knowledge Infrastructure,Wanfang,VIP,and PubMed.Additionally,genes associated with Psycho-cardiological disease were retrieved from the Genecards database.Utilizing the Digital Intelligence Traditional Chinese Medicine Innovation Platform,network proximity was calculated for the obtained targets and genes.The potential targets of Compound Danshen Dripping Pills in the treatment of Psycho-cardiological disease conduct enrichment analysis,trace the source of medicinal materials and effective components absorbed into the blood.Results Obtained 192 targets for the Compound Danshen Dripping Pills,1137 genes for Psycho-cardiological disease,and the network proximity calculation showed a significant correlation between the two(Z-score=-6.5282).The enrichment analysis of the 95 potential targets predominantly reveals their association with several key pathways,including AGE-RAGE signaling in diabetic complications,Lipid and atherosclerosis,fluid shear stress and atherosclerosis,the HIF-1 signaling pathway,TNF signaling.The traceability analysis indicates that 80 targets are associated with three distinct medicinal materials,10 targets are linked to two medicinal materials,and 5 targets are connected to a single medicinal material.95 targets are mainly related to 17 effective blood components such as salvianolic acid B,tanshinone ⅡA,and salvianolic acid A.The top 16 key genes were obtained by sorting the targets based on the Betweenness values corresponding to the blood components.The enrichment analysis of the key gene indicated that the treatment of Psycho-cardiological disease with Compound Danshen Dripping Pills is associated with the positive regulation of smooth muscle cell proliferation and the hypoxia response.Additionally,it is linked to the AGE-RAGE signaling pathway in diabetic complications,fluid shear stress and atherosclerosis,the relaxin signaling pathway,lipid and atherosclerosis,and the TNF signaling pathway,etc.Conclusion The Compound Danshen Dripping Pills may improve Psycho-cardiological disease by regulating inflammatory response,oxidative stress,myocardial ischemia,neuroprotection,and neurotoxicity inhibition through components such as salvianolic acid B,tanshinone ⅡA,tanshinone Ⅰ,salvianolic acid A,protocatechuic acid,etc.

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.