Role of HIV-1 minority populations on resistance mutational pattern evolution and susceptibility to protease inhibitors

We investigated, in the protease and GAG cleavage sites, the role of minority populations on the evolution of resistance to a subsequent boosted protease inhibitor (PI) regimen after a first failure to nelfinavir. Two pathways were observed: the addition of mutations to a currently dominant genotype when minority variants are not shown, or the emergence of a minority variant as a dominant strain. These minor species, not detected by standard genotype, may influence PI susceptibility.     

Polymorphisms of protein tyrosine phosphatase CD148 influence FcγRIIA-dependent platelet activation and the risk of heparin-induced thrombocytopenia

Heparin-induced thrombocytopenia (HIT) is due primarily to IgG antibodies specific to platelet factor 4/heparin complexes (PF4/Hs) that activate platelets via FcγRIIA. CD148 is a protein tyrosine phosphatase that regulates Src kinases and collagen-induced platelet activation. Three polymorphisms affecting CD148 (Q276P, R326Q, and D872E) were studied in HIT patients and 2 control groups, with or without antibodies to PF4/Hs. Heterozygote status for CD148 276P or 326Q alleles was less frequent in HIT patients, suggesting a protective effect of these polymorphisms. Aggregation tests performed with collagen, HIT plasma, and monoclonal antibodies cross-linking FcγRIIA showed consistent hyporesponsiveness of platelets expressing the 276P/326Q alleles. In addition, platelets expressing the 276P/326Q alleles exhibited a greater sensitivity to the Src family kinases inhibitor dasatinib in response to collagen or ALB6 cross-linking FcγRIIA receptors. Moreover, the activatory phosphorylation of Src family kinases was considerably delayed as well as the phosphorylation of Linker for activation of T cells and phospholipase Cγ2, 2 major signaling proteins downstream from FcγRIIA. In conclusion, this study shows that CD148 polymorphisms affect platelet activation and probably exert a protec-tive effect on the risk of HIT in patients with antibodies to PF4/Hs.     

Prediction of the Total Liver Weight using anthropological clinical parameters: does complexity result in better accuracy?

Background

The performance of linear models predicting Total Liver Weight (TLW) remains moderate. The use of more complex models such as Artificial Neural Network (ANN) and Generalized Additive Model (GAM) or including the variable “steatosis” may improve TLW prediction. This study aimed to assess the value of ANN and GAM and the influence of steatosis for predicting TLW.