Screening and Identifying Reference Genes for Erythrocyte Production from Cord Blood CD34+ Cells Exposed to Hypoxia.

Cord blood (CB) CD34+ cells have the potential to be used to achieve artificial hematopoiesis because of their ability to expand and differentiate in multiple directions. However, the mechanism and molecular changes underlying such differentiation are still unclear. The differentiation of CB CD34+ cells is generally driven by subtle changes in gene expression. A crucial method for examining gene expression is quantitative real-time polymerase chain reaction, but the accuracy of the results is dependent on the use of reliable reference genes. Here, the transcription levels of 10 novel candidate reference genes (EIF4G2, DYNC1H1, LUC7L3, CD46, POLR1D, WSB1, GAPVD1, HGS, LGALS8, and RBM5) and 8 traditional reference genes (GAPDH, YWHAZ, ACTB, B2MG, TBP, HMBS, PPIA, HPRT1) in CB CD34+ cells under different oxygen concentrations were screened and evaluated by using the geNorm and NormFinder algorithms. Comprehensive analysis conducted by RefFinder online tool showed that TBP (a traditional reference gene) and EIF4G2 (a novel reference gene) had the most stable expression, whereas GAPDH and HMBS were the least suitable reference genes under these conditions. These results may serve as a basis for selecting reference genes with stable expression for more accurate normalization under different oxygen concentration stimulation during CB CD34+ cells differentiation.

Gene Expression Profile Reveals Hematopoietic-Related Molecule Changes in Response to Hypoxic Exposure.

The Qing-Tibet Plateau is characterized by low oxygen pressure, which is an important biomedical and ecological stressor. However, the variation in gene expression during periods of stay on the plateau has not been well studied. We recruited eight volunteers to stay on the plateau for 3, 7, and 30 days. Human Clariom D arrays were used to measure transcriptome changes in the mRNA expression profiles in these volunteers' blood. Analysis of variance (ANOVA) indicated that 699 genes were significantly differentially expressed in response to entering the plateau during hypoxic exposure. The genes with changes in transcript abundance were involved in the terms phosphoprotein, acetylation, protein binding, and protein transport. Furthermore, numerous genes involved in hematopoietic functions, including erythropoiesis and immunoregulation, were differentially expressed in response to hypoxia. This phenomenon may be one of reasons why the majority of people entering the plateau do not have excessive erythrocyte proliferation and are susceptible to infection.

[Analysis for Discordance of Positive and Negative Blood Typing by Gel Card].

OBJECTIVE: To explore the method of Gel card identifying ABO blood group, determine the inconsistent cause and the distribution of disease affecting factors, and put forward a method of its solutions. METHODS: To collect 240 positive and negative typing-discordant blood speciments from patients examined by Gel card and send these speciments to blood type reference laboratory for examining with the classic tube method and serological test, such as salivary blood-group substance, in order to performe genotyping method when serologic test can not be determined. RESULTS: Among 240 positive and negative typing-discordant blood speciments from patients examined by Gel card, 107 blood speciments were positive and negative consistent examined by false agglutination test (44.58%), 133 blood specinents were discordent examined by false agglutination (55.42%), out of them, 35 cases (14.58%) with inconsistent cold agglutination test, 22 cases (9.17%) with weakened AB antigenicity, 16 cases (6.67%) with ABO subtyping, 12 cases (5.00%) with positive direct antiglobulin test, 11 cases (4.58%) with reduced or without antibodies, 11 cases (4.58%) with false aggregation caused by drugs or protein, 11 cases (4.58%) with salivary blood-type substances, 8 cases (3.33%) with non-ABO alloantibody, and 7 cases (2.92%) with allogeneic bone marrow transplantation. The distribution of disease were following: blood disease (16.83%), tumor (11.88%), and cardiopulmonary diseases (11.39%); chi-square test results indicated that the distribution significantly different. CONCLUSION: The analysis of ABO blood grouping shows a variety factors influencing positive and negative blood typing, and the Gel Card identification can produc more false positive blood types. Therefore, more attention should be paid on the high incidence diseases, such as blood disease, tumor, and cardiopulmonary disease.