Search

Pregnancy presents a great challenge to the maternal immune system. Given that maternal alloreactive lymphocytes are not depleted during pregnancy, local and/or systemic mechanisms have to serve a central function in altering the maternal immune responses. Regulatory T cells (Tregs) and the PD-1/ PD-L1 pathway are both critical in controlling the immune responses. Recent studies have proved the critical function of the PD-1/ PD-L1 pathway in regulating the T-cell homeostasis and the peripheral tolerance through promoting the development and function of Tregs, and inhibiting the activation of effector T cells. The function of the PD-1/ PD-L1 pathway in feto-maternal interface and pregnancy has been investigated in human and animal models of pregnancy. In this review, we provide recent insight into the role of the PD-1/ PD-L1 pathway in regulating T-cell homeostasis, maternal tolerance, and pregnancy-related complications as well as its possible applicability in clinical immunotherapy. [ABSTRACT FROM AUTHOR]

Problem We aim to investigate the proportion and absolute counts of peripheral blood monocyte subsets in women with normal pregnancy ( NP) and pre-eclampsia ( PE), and their correlation with the clinical manifestation and severity of PE. Method of study Peripheral blood was obtained from women with NP ( n = 30), mild PE ( MPE, n = 15) and severe PE ( SPE, n = 30). The proportion and absolute counts of CD16+ monocytes and the subsets including intermediate ( CD14++ CD16+ HLA- DR+) and non-classical ( CD14+ CD16++ HLA- DR+) monocytes were determined by flow cytometric analysis. Results Women with MPE and SPE had significantly increased absolute count of CD14++ CD16+ HLA- DR+ monocyte subsets ( P < 0.01 each) as compared to NP women. In addition, there were significant differences in the absolute count of CD14++ CD16+ HLA- DR+ monocyte subsets between MPE and SPE groups ( P < 0.05). The proportion of CD14++ CD16+ HLA- DR+ monocyte subsets was significantly increased in SPE compared to MPE and NP ( P < 0.01 each). The absolute count ( r = 0.332, P < 0.05) and proportion ( r = 0.447, P < 0.01) of CD14++ CD16+ HLA- DR+ monocytes were positively correlated with the severity of PE. Multivariate logistic regression analysis further revealed that the absolute count of CD14++ CD16+ HLA- DR+ monocytes was a potential marker for PE ( P < 0.01). Conclusion A preferential increase in peripheral blood CD14++ CD16+ HLA- DR+ monocytes is quantitatively correlated with clinical manifestation of PE. [ABSTRACT FROM AUTHOR]

Background: The quantification of mitochondrial DNA heteroplasmy for the diagnosis of mitochondrial disease or after mitochondrial donation, is performed mainly using next-generation sequencing strategies (NGS). Digital PCR (dPCR) has the potential to offer an accurate alternative for mutation load quantification., Methods: We assessed the mutation load of 23 low-input human samples at the m.11778 locus, which is associated with Leber's hereditary optic neuropathy (LHON) using 2 droplet digital PCR platforms (Stilla Naica and Bio-Rad QX200) and the standard NGS strategy. Assay validation was performed by analyzing a titration series with mutation loads ranging from 50% to 0.01%., Results: A good concordance in mutation rates was observed between both dPCR techniques and NGS. dPCR established a distinctly lower level of background noise compared to NGS. Minor alleles with mutation loads lower than 1% could still be detected, with standard deviations of the technical replicates varying between 0.07% and 0.44% mutation load. Although no significant systematic bias was observed when comparing dPCR and NGS, a minor proportional bias was detected. A slight overestimation of the minor allele was observed for the NGS data, most probably due to amplification and sequencing errors in the NGS workflow., Conclusion: dPCR has proven to be an accurate tool for the quantification of mitochondrial heteroplasmy, even for samples harboring a low mutation load (<1%). In addition, this alternative technique holds multiple benefits compared to NGS (e.g., less hands-on time, more straightforward data-analysis, and a lower up-front capital investment)., (© American Association for Clinical Chemistry 2021.)