Objective: To explore the association between the HLA antibody positivity rate in female blood donors and pregnancy history, number of pregnancies, interval from the last pregnancy to blood donation, and age, to identify associated variables using a univariate generalized additive model (GAM), and to further analyze the predictive role of characteristic variables for HLA antibody positivity using a random forest model. Methods: HLA antibody detection was performed on 391 female blood donors using the Luminex immunomagnetic bead method. The correlation between pregnancy-related factors and HLA antibodies was analyzed using the Chi-square test. Based on R software, a univariate GAM was first constructed to analyze the association types between characteristic variables and the HLA antibody positivity rate, followed by the construction of a random forest model to evaluate the predictive value of the variables. Results: Among the 391 female blood donors without a transfusion history, the overall HLA antibody positivity rate was 26.34%. The positivity rate in donors with a pregnancy history was significantly higher than that in those without (30.09% vs 9.72%, P<0.05), and HLA antibody positivity rate increased linearly with the number of pregnancies (P<0.05). In the univariate GAM, age and number of deliveries exhibited a non-linear association with the HLA antibody positivity rate (the positivity rate increased sharply between 25-35 years of age and stabilized after 3 deliveries). Besides, the interval from the last pregnancy to blood donation showed a linear association with the HLA antibody positivity rate, and the positivity rate decreased as the interval prolonged (P<0.05). In the random forest model, age (mean decrease gini=29.26) and interval from the last pregnancy to blood donation (mean decrease gini=22.02) were core predictive variables: age was more conducive to identifying positive samples, while the interval from the last pregnancy to blood donation was more helpful for excluding negative samples. The number of deliveries (mean decrease accuracy=16.98) made a significant contribution to predicting positive samples, whereas the number of abortions had no impact. The model had an AUC of 0.583 (95% CI: 0.593 8-0.770 2), indicating a certain predictive value. Conclusion: The associated variables identified by the univariate GAM model, including age, interval from the last pregnancy to blood donation, and number of deliveries, provide a basis for key variables in the random forest model. All three variables have predictive value for HLA antibody positivity, which can provide evidence-based support for personalized transfusion management and stratified screening of female blood donors in this region.

ObjectiveTo explore the role of the Plan-Do-Check-Act （PDCA） cycle process management in improving the operational efficiency of ethics committees. MethodsA retrospective analysis was employed on the operation status of the medical ethics committee of the First Affiliated Hospital in Soochow University before and after the implementation of PDCA cycle management. The changes in the number of ethical review projects， processing duration， review time， opinion conveying duration， frequency of ethical review meetings， attendance rate of ethics committee members at meetings， and external satisfaction evaluation before and after the implementation of PDCA cycle management were compared， analyzing the impact of PDCA cycle management on the operational efficiency of the ethics committee. ResultsSignificant differences were observed in the number of ethical review projects， processing duration， review time， opinion conveying duration， frequency of ethical review meetings， attendance rate of ethics committee members at meetings， and external satisfaction before and after the implementation of PDCA cycle management （P<0.001）. ConclusionPDCA cycle management could effectively identify problems in the operation of ethics committees and contribute to improving their operational efficiency.

OBJECTIVETo explore the molecular basis for a CD36 deficiency individual and distribution of CD36 gene mutation in Guangxi population.

METHODSA female individual was studied. CD36 phenotype was detected by monoclonal antibody immobilization of platelet antigens assay (MAIPA) and flow cytometry (FCM). The coding regions of the CD36 gene were sequenced. A DNA-based polymerase chain reaction-sequence specific primer (PCR-SSP) assay was used to verify the identified mutation. Cell lines expressing the mutant and wild-type CD36[CD36(MT) and CD36(WT)] were established, with the expression of CD36 determined by Western blotting. The distribution of CD36 gene mutation was investigated among 1010 unrelated individuals with the PCR-SSP assay.

RESULTSBoth MAIPA and FCM assays showed that the patient had type II CD36 deficiency. DNA sequencing showed that she has carried a heterozygous mutation T538C (Trp180Arg) in the exon 6 of CD36. Sequencing of cDNA clone confirmed that there was a nucleotide substitution at position 538 (538T>C). Western blotting also confirmed that the CD36 did not express on the CD36(MT) cell line that expressed the 538C mutant, but did express on the CD36(WT) cell line. The novel CD36 mutation T538C was further verified with 100% concordance of genotyping results by DNA-based PCR-SSP assay and 1010 unrelated individuals. No CD36 538C allele was detected among the 1010 individuals.

CONCLUSIONThis study has identified a novel CD36 mutation T538C(Trp180Arg)(GenBank: HM217022.1), and established a genotyping method for the novel sequence-specific primer PCR. The novel mutation is rare in Guangxi and can cause type II CD36 deficiency.

Base Sequence ; Blood Platelet Disorders ; genetics ; Blood Platelets ; cytology ; metabolism ; Blotting, Western ; CD36 Antigens ; genetics ; metabolism ; Cells, Cultured ; DNA Mutational Analysis ; DNA Primers ; genetics ; Exons ; genetics ; Female ; Flow Cytometry ; Fluorescent Antibody Technique ; Genetic Diseases, Inborn ; genetics ; Genotype ; Genotyping Techniques ; methods ; Humans ; Middle Aged ; Monocytes ; cytology ; metabolism ; Mutation, Missense ; Polymerase Chain Reaction ; methods