Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks.

Machine learning methods are a novel way to predict and rank donors' willingness to donate blood and to achieve precision recruitment, which can improve the recruitment efficiency and meet the challenge of blood shortage. We collected information about experienced blood donors via short message service (SMS) recruitment and developed 7 machine learning-based recruitment models using PyCharm-Python Environment and 13 features which were described as a method for ranking and predicting donors' intentions to donate blood with a floating number between 0 and 1. Performance of the prediction models was assessed by the Area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score in the full dataset, and by the accuracy in the four sub-datasets. The developed models were applied to prospective validations of recruiting experienced blood donors during two COVID-19 pandemics, while the routine method was used as a control. Overall, a total of 95,476 recruitments via SMS and their donation results were enrolled in our modelling study. The strongest predictor features for the donation of experienced donors were blood donation interval, age, and donation frequency. Among the seven baseline models, the eXtreme Gradient Boosting (XGBoost) and Support vector machine models (SVM) achieved the best performance: mean (95%CI) with the highest AUC: 0.809 (0.806-0.811), accuracy: 0.815 (0.812-0.818), precision: 0.840 (0.835-0.845), and F1 score of XGBoost: 0.843 (0.840-0.845) and recall of SVM: 0.991 (0.988-0.994). The hit rate of the XGBoost model alone and the combined XGBoost and SVM models were 1.25 and 1.80 times higher than that of the conventional method as a control in 2 recruitments respectively, and the hit rate of the high willingness to donate group was 1.96 times higher than that of the low willingness to donate group. Our results suggested that the machine learning models could predict and determine the experienced donors with a strong willingness to donate blood by a ranking score based on personalized donation data and demographical details, significantly improve the recruitment rate of blood donors and help blood agencies to maintain the blood supply in emergencies.

Erythrocyte concentrates recovered from under-collected whole blood: experimental and clinical results.

BACKGROUND: Although periodic blood shortages are widespread in major Chinese cities, approximately 1 x 10(5) U of whole blood are discarded yearly because of under-collection. To reduce the wastage of acid citrate dextrose solution B (ACD-B) anticoagulated under-collected whole blood (UC-WB), this study was performed to elucidate the effect of extracellular pH and holding time on erythrocyte quality. Mannitol-adenine-phosphate (MAP) erythrocyte concentrates (UC-RBCs) were prepared with UC-WB to assess the safety and efficacy of this component. METHODS: The effect of the different extracellular pH levels and storage times on erythrocytes was assessed by fluorescent probes, SDS-PAGE electrophoresis, electron microscopy and spectroscopy. In vitro properties of 34 UC-RBCs that were prepared with UC-WB at different times after collection were analyzed and compared to normal RBCs during 35 days of storage. The results of transfusion with UC-RBCs and the incidence of adverse reactions in 49 patients were determined. RESULTS: 1) Low extracellular pH levels and long storage time induced increases in RBC fluorescence polarization and mean microviscosity, changes in membrane fluidity, band 1, 2 and 3 protein expression, and erythrocyte morphology. 2) During storage for 35 days, difference in between-subjects effects of K+, hemolysis and supernatant erythrocyte membrane protein (EMP) were statistically significant (P = 0.041, 0.007 and 0.002, respectively), while the differences between these parameters in the 4 h group and comparable controls were less significant. 3) Clinical data from 49 patients confirmed that transfusions with UC-RBCs were satisfactory with no adverse reactions. CONCLUSION: These results suggest that it is feasible to prepare RBCs with ACD-B anticoagulated UC-WB at a minimum of 66% volume of the labeled collection. It was effective and safe to transfuse the UC-RBCs prepared within 4 h after collection and stored within 7 days. The use of UC-WB would be a welcome addition to limited blood resources in China. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-TRC-13003967.

[Studies on flavonoids from stems and leaves of Calophyllum inophyllum].

OBJECTIVE: To study the chemical constituents from the stems and leaves of Calophyllum inophyllum. METHOD: The compounds were isolated by column chromatography on silica gel, Sephadex LH-20 and preparative TLC. Their structures were elucidated by chemical methods and NMR, MS spectroscopic data. RESULT: Nine compounds were identified as 2-hydroxyxanthone (1), 4-hydroxyxanthone (2), 1, 5-dihydroxyxanthone (3), 1, 7-dihydroxyxanthone (4), 1, 3, 5-trihydroxy-2-methoxyxanthone (5), 6-deoxyjacareubin (6), amentoflavone (7), kaempferol-3-O-alpha-L-rhamnoside (8) and quercetin-3-O-alpha-L-rhamnoside (9). CONCLUSION: Compounds 8 and 9 were isolated from the genus Calophyllum and compounds 1, 2, 4-6 were isolated from this plant for the first time.