Objective: To statistically analyze the association between blood donation intervals and the incidence of adverse reactions to blood donation based on blood donor data from Shenzhen. Methods: Basic data and records of adverse reactions to blood donation among voluntary whole blood donors in Shenzhen from January 2017 to June 2025 were extracted. A total of 795 404 whole blood donations were recorded, including 502 743 from males and 292 661 from females, with 1 088 and 751 cases of adverse reactions, respectively. Analyses were performed using R software, including restricted cubic spline (RCS), binary logistic regression, and generalized estimating equations (GEE) to evaluate the correlation between donation intervals and adverse reactions. Results: A total of 1 839 cases of adverse reactions were recorded, accounting for 0.23% of the total donations. Both binary logistic regression analysis and the generalized estimating equations (GEE) model showed that there was no significant difference in the incidence of adverse reactions between male and female donors with an interval of ≥6 months compared to those with an interval of ≥3 months but<6 months. Furthermore, using the 3-5 month interval group as the reference, the analysis indicated that the incidence of adverse reactions significantly increased in males with a 9-12 month interval, while no statistically significant differences were observed across any of the female subgroups. Conclusion: There was no significant correlation between adverse reactions to blood donation and the donation interval. Compared with a donation interval of ≥6 months, an interval of<6 months does not lead to an increase in the incidence of adverse reactions among male or female donors. The findings of this study may help enhance the willingness of blood donors to participate.

Objective: To statistically analyze the association between blood donor age and the incidence of adverse reactions based on whole blood donor data from Shenzhen. Methods: Data on basic characteristics and records of adverse donation reactions among voluntary whole blood donors in Shenzhen from January 2017 to June 2025 were extracted. A total of 795 404 whole blood donations were recorded, including 502 743 from males and 292 661 from females, with 1 088 and 751 cases of adverse reactions, respectively. Analyses were performed using R software, including restricted cubic spline (RCS) analysis, binary logistic regression, and generalized estimating equations (GEE) to evaluate the correlation between donor age and adverse reactions. Results: A total of 1 839 cases of adverse reactions were recorded, accounting for 0.23% of the total donations. Both binary logistic regression and GEE model revealed that, compared with the≤55 years age group, the incidence of adverse reactions was reduced in both male and female donors in the >55 years age group, with the difference being statistically significant in males. Using the <23 years age group as a reference, the incidence of adverse reactions significantly decreased in both male and female donors across the 23-30, 31-40, 41-50, and 51-60 age groups, with the differences being statistically significant. Conclusion: There is a negative correlation between the rate of adverse donation reactions and age, with the incidence of such reactions among whole blood donors over 55 years old being no higher than that among donors aged 55 years or younger. These findings carry positive significance for safeguarding the donation rights of older donors and meeting clinical blood demand.

OBJECTIVE To construct a prediction model for tacrolimus trough concentration based on population pharmacokinetics （PPK） information and machine learning， evaluate its predictive performance in clinical therapeutic drug monitoring （TDM） data， and provide evidence-based support for individualized dose adjustment of tacrolimus after renal transplantation. METHODS A retrospective cohort study design was adopted， and consecutive TDM records of kidney transplant recipients treated in the First Affiliated Hospital of University of Science and Technology of China （Anhui Provincial Hospital） from January to June 2025 were included to construct the final analysis set. Based on 29 input variables including previous TDM concentration， previous concentration/dose （ C / D ） ratio， and individual predicted exposure （IPRE）， 13 commonly used regression algorithm models and 1 weighted ensemble model were systematically compared. The dataset was split into training set and test set in an 80∶20 ratio by patient. Five-fold cross-validation based on patient grouping was performed on the training set， and the model performance was evaluated on the obtained evaluation points using the coefficient of determination （ R 2 ）， mean absolute error （MAE）， root mean square error （RMSE）， Pearson correlation coefficient （Corr） and ±20%/±30% accuracy. The SHapley Additive exPlanations （SHAP） method was used for model interpretability analysis to identify core predictive features. RESULTS A total of 809 consecutive TDM records from 83 kidney transplant recipients were included， with 66 cases in the training set and 17 cases in the test set. The SVR model showed the best performance， with R 2 of 0.649 8， MAE of 1.126 0 ng/mL， RMSE of 1.478 6 ng/mL， Corr of 0.819 1， ±20% accuracy of 59.68%， and ±30% accuracy of 79.03%. The Weighted Ensemble model and Extra Trees model ranked second and third， respectively. SHAP interpretability analysis showed that the top 6 features contributing to the prediction were IPRE， previous TDM concentration， previous C/D ratio， dose-normalized concentration， hematocrit （HCT）， and concentration-dose coefficient （ θ cd ）， among which IPRE was the core predictive feature （SHAP mean value 0.915 4）. CONCLUSIONS The machine learning model incorporating PPK information demonstrates good predictive ability for tacrolimus concentration in the current TDM cohort. SVR is the optimal model， IPRE is the core predictive feature of the model， and a few core PK-derived features （IPRE， dose-normalized concentration， θ cd ） together with clinical features （previous TDM concentration， HCT， etc.） constitute the main information sources for model prediction.

Objective: To assess the impact of long-term antiretroviral therapy (ART) on human immunodeficiency virus (HIV) blood screening outcomes in post-exposure prophylaxis (PEP) failure cases through a longitudinal analysis of blood screening results over a 7-year period in a patient with HIV PEP failure. Methods: This study conducted 13 follow-up assessments for a high-risk individual who initiated ART shortly after exposure. The effectiveness of various blood screening methods, including immunological assays and nucleic acid testing (NAT), was analyzed. Blood samples were also tested with HIV RNA quantification testing, Western blot (WB) confirmation testing, chemiluminescence immunoassay (CLIA), and HIV rapid tests utilizing gold and selenium labels. A comprehensive analysis was performed to evaluate the changes in diagnostic capabilities of different testing methods for HIV biomarkers over an extended period following PEP failure. Results: The patient had two high-risk exposures: one day before ART initiation (BA1) and seven days preceding treatment (BA7). On the first day after the ART treatment (AA1), the HIV RNA concentration (viral load) was 9.07×10 copies/mL; by day five (AA5), the viral load decreased to 1.04×10 copies/mL. At day eleven (AA11), NAT and ELISA tests were both positive, with the WB result remaining indeterminate (gp160+). At day 48 (AA48), the S/CO value of the fourth generation ELISA reagent was 1.07, while results from a 6-sample pool and quantitative NAT were negative. However, a single sample NAT returned a positive result and WB tests indicated positivity for p17, p24, and gp160. At AA74, the quantitative NAT rebounded to 2.83×10 copies/mL, with positive NAT results for single and 6-sample pool NAT tests. The S/CO values of the imported and domestic ELISA reagents were 3.39 and 23.44, respectively. At AA201, 6-sample pool and quantitative NAT were negative again, while single sample NAT remained positive. From AA319 to AA2221, all NAT results have remained consistently below the minimum detection limit. At AA2221, S/CO values of the imported and domestic ELISA reagents were 3.47 and 23.44, respectively. Conclusion: The findings indicate that patients experiencing PEP failure after high-risk HIV exposure are at a higher risk of being missed by mixed-sample NAT pools and individual serological tests. Nonetheless, anti-HIV antibody levels are sustained at elevated values for an extended duration, underscoring antibody testing as an effective measure for blood screening.

Objective: To construct a 5G unmanned aerial vehicle (UAV) airport platform for blood transportation and explore its feasibility and advantages within the blood emergency support system. Methods: Based on 5G high-speed network transmission technology, a UAV management system was designed to achieve a closed-loop management of the entire transportation process, including blood distribution, route information, flight status, emergency dispatch, hospital reception, real-time temperature monitoring, and video surveillance. Integrated with an open UAV airport, the first "5G UAV Blood Transportation Intelligent Airport Platform" was established. Results: At present, the platform has settled in 2 sets of UAV systems, established 17 routes, and carried out regular UAV blood transportation services for 15 hospitals. From January 1, 2024 to June 30, 2025, a total of 12 134 sorties were completed, with a total transported blood weight of 7 692.38 kg, including 25 500 units of red blood cells, 3 824.5 units of platelets, 1 350 370 mL of plasma, and 10 810 units of cryoprecipitate. Compared to land transportation, UAV delivery saved an average of 46.8 minutes during rush hours (maximum: 89.3 minutes) and an average of 32.3 minutes during non-rush hours (maximum: 59.1 minutes). In terms of the quality of UAV blood transportation, the temperature of suspended red blood cells was between 4 and 8℃, that of platelets was between 20 and 24℃, and that of plasma was below 0℃. No damage has occurred so far. Conclusion: The UAV blood transportation platform can stably provide blood delivery services during both routine and emergency conditions, ensuring timely blood delivery and stable blood quality.

OBJECTIVE To report a case of hepatitis B virus （HBV） reactivation induced by iparomlimab and tuvonralimab， summarize the clinical characteristics and potential mechanisms of such adverse reactions induced by immune-checkpoint inhibitors （ICIs）， and provide references for clinical application. METHODS From the perspective of a clinical pharmacist， a retrospective analysis was conducted on the treatment course of a patient with metastatic cervical cancer who experienced HBV reactivation after receiving iparomlimab and tuvonralimab. Additionally， an analysis of the correlation with adverse reactions was performed， and the clinical characteristics， risk factors， potential mechanisms， key points of treatment approaches and pharmaceutical care associated with HBV reactivation induced by ICIs were summarized. RESULTS & CONCLUSIONS The patient developed HBV reactivation and severe liver injury after using iparomlimab and tuvonralimab. The condition improved following drug discontinuation， and symptomatic treatment such as glucocorticoids. According to Naranjo’s Assessment Scale and China’s Measures for the Reporting and Monitoring of Adverse Drug Reactions， the association between iparomlimab and tuvonralimab and HBV reactivation was judged as “highly probable”， and it was identified as a new adverse reaction； the correlation between iparomlimab and tuvonralimab， paclitaxel and liver injury was “highly probable”. HBV reactivation in hepatitis B patients receiving standardized antiviral therapy is very rare after ICIs treatment； HBV reactivation is related to the overactivation of the immune system and disruption of immune balance induced by ICIs. For such patients， glucocorticoids should be administered for treatment， accompanied by pharmaceutical care， including pre- medication risk assessment and monitoring of relevant indicators during treatment.

Objective To investigate the effectiveness of continuous improvement projects based on FOCUS-PDCA on the pathogen sample submission rate before antimicrobial therapy for inpatients.Methods FOCUS-PDCA was used to improve the pathogen sample submission rate in Affiliated Hospital of Nantong University from Jun.to Jul.2023.The inpatients from Jan.to May 2023(before improvement)were enrolled as control group,and the inpatients from Aug.to Dec.2023(after improvement)were enrolled as improvement group.The utilization rate of antibiotics,the submission rate of pathogen samples,the submission rate of clinical microbial samples and the detection rate of multidrug-resistant organisms were compared between the 2 groups.Results The utilization rate of therapeutic antimicrobial agents(32.18％vs 32.93％,P=0.003)and antimicrobial consumption intensity(39.99 defined daily dose[DDD]/100 patient-days vs 44.19 DDD/100 patient-days)in the improvement group were significantly lower than those in the control group.The pathogen sample submission rates before antimicrobial therapy and key antimicrobial combination therapy in the improvement group were significantly higher than those in the control group(52.01％vs 23.64％,87.74％vs 77.71％;both P＜0.001).The qualified rate of microbial specimens in the improvement group was significantly higher than that in the control group(88.77％vs 80.11％,P＜0.001).The detection rates of multidrug-resistant organisms and carbapenem-resistant Klebella pneumoniae in the improvement group were significantly lower than those in the control group(40.45％vs 48.42％,29.65％vs 43.17％;both P＜0.001).Conclusion The continuous improvement projects based on FOCUS-PDCA can improve the pathogen sample submission rate,reduce the detection rate of multidrug-resistant organisms,and promote standardized hospital infection quality management.

Objective:To investigate the diagnostic and prognostic value of systemic immune inflammatory index (SII) for severe traumatic brain injury secondary to acute lung injury (sTBI-ALI).Methods:A retrospective study was conducted on patients with severe traumatic brain injury admitted to the trauma center of the First Affiliated Hospital of Soochow University from January 2021 to November 2023. Patients received standard treatments including hemostasis and intracranial pressure management. Vital signs and blood routine data were collected upon admission. Patients were categorized into sTBI group and sTBI-ALI group based on established clinical diagnostic criteria for ALI to evaluate the diagnostic utility of SII. Subsequently, within the sTBI-ALI group, patients were stratified into survival and non-survival groups based on their 30-day outcomes to assess the prognostic value of SII.Results:A total of 260 sTBI patients were enrolled, of whom 113 developed ALI. Among the sTBI-ALI patients, 73 survived at 30 days. Compared to the sTBI group, the sTBI-ALI group exhibited significantly higher respiratory rates, heart rates, white blood cell counts, neutrophil counts, platelet counts, and SII levels (all P<0.05). Multivariate logistic regression analysis showed that SII index ( OR=1.003, 95% CI: 1.002-1.004, P<0.001) was an independent risk factor for ALI development in sTBI patients. The combined predictive model incorporating SII and heart rate yielded an AUC of 0.801 (95% CI: 0.740-0.862). The non-survival group had significantly higher neutrophil counts and SII levels, and significantly lower Glasgow Coma Scale scores than the survival group (all P<0.05). Multifactorial regression analysis indicated that SII index ( OR=1.002, P=0.004, 95% CI: 1.000-1.003) served as an independent risk factor for 30-day mortality in sTBI-ALI patients. The combined predictive model of SII and GCS achieved an AUC of 0.904 (95% CI: 0.848-0.960). Conclusions:SII demonstrates potential as a biomarker for predicting the development of ALI following sTBI. Furthermore, incorporating SII into predictive models significantly enhances the ability to forecast mortality risk in sTBI-ALI patients.

Metastasis is the leading cause of death from cutaneous melanoma. Identifying metastasis-related targets and developing corresponding therapeutic strategies are major areas of focus. While functional genomics strategies provide powerful tools for target discovery, investigations at the protein level can directly decode the bioactive epitopes on functional proteins. Aptamers present a promising avenue as they can explore membrane proteomes and have the potential to interfere with cell function. Herein, we developed a target and epitope discovery platform, termed functional aptamer evolution-enabled target identification (FAETI), by integrating affinity aptamer acquisition with phenotype screening and target protein identification. Utilizing the aptamer XH3C, which was screened for its migration-inhibitory function, we identified the Chondroitin Sulfate Proteoglycan 4 (CSPG4), as a potential target involved in melanoma migration. Further evidence demonstrated that XH3C induces cytoskeletal rearrangement by blocking the interaction between the bioactive epitope of CSPG4 and integrin α4. Taken together, our study demonstrates the robustness of aptamer-based molecular tools for target and epitope discovery. Additionally, XH3C is an affinity and functional molecule that selectively binds to a unique epitope on CSPG4, enabling the development of innovative therapeutic strategies.