Prediction of martensite start temperature by neural network analysis

Commercial steels are nowadays sophisticated alloys formed by a large number of alloying elements. The martensite start ( Ms) temperature of such steels is of vital engineering importance, and its prediction through models allows us to enhance the design and development of industrial products. In the present work, Ms temperature dependence on chemical composition has been examined by neural network analysis. Neural networks represent powerful methods of non-linear regression modelling. The network is a mathematical function which is fitted to experimental data. The influence of alloying elements such as C, Mn, Si, Cr, Ni, Mo, V, Co, W, Al, Nb, Cu, B and N on Ms temperature was analysed. Finally, a new empirical equation for Ms temperature was derived based on the neural network results.Peer Reviewe

Paired opposing leukocyte receptors recognizing rapidly evolving ligands are subject to homogenization of their ligand binding domains

Some leukocyte receptors come in groups of two or more where the partners share ligand(s) but transmit opposite signals. Some of the ligands, such as MHC class I, are fast evolving, raising the problem of how paired opposing receptors manage to change in step with respect to ligand binding properties and at the same time conserve opposite signaling functions. An example is the KLRC (NKG2) family, where opposing variants have been conserved in both rodents and primates. Phylogenetic analyses of the KLRC receptors within and between the two orders show that the opposing partners have been subject to post-speciation gene homogenization restricted mainly to the parts of the genes that encode the ligand binding domains. Concerted evolution similarly restricted is demonstrated also for the KLRI, KLRB (NKR-P1), KLRA (Ly49), and PIR receptor families. We propose the term merohomogenization for this phenomenon and discuss its significance for the evolution of immune receptors

The complete inventory of receptors encoded by the rat natural killer cell gene complex

The natural killer cell gene complex (NKC) encodes receptors belonging to the C-type lectin superfamily expressed primarily by NK cells and other leukocytes. In the rat, the chromosomal region that starts with the Nkrp1a locus and ends with the Ly49i8 locus is predicted to contain 67 group V C-type lectin superfamily genes, making it one of the largest congregation of paralogous genes in vertebrates. Based on physical proximity and phylogenetic relationships between these genes, the rat NKC can be divided into four major parts. We have previously reported the cDNA cloning of the majority of the genes belonging to the centromeric Nkrp1/Clr cluster and the two telomeric groups, the Klre1–Klri2 and the Ly49 clusters. Here, we close the gap between the Nkrp1/Clr and the Klre1–Klri2 clusters by presenting the cDNA cloning and transcription patterns of eight genes spanning from Cd69 to Dectin1, including the novel Clec2m gene. The definition, organization, and evolution of the rat NKC are discussed

Expression Profiling of Major Histocompatibility and Natural Killer Complex Genes Reveals Candidates for Controlling Risk of Graft versus Host Disease

Background: The major histocompatibility complex (MHC) is the most important genomic region that contributes to the risk of graft versus host disease (GVHD) after haematopoietic stem cell transplantation. Matching of MHC class I and II genes is essential for the success of transplantation. However, the MHC contains additional genes that also contribute to the risk of developing acute GVHD. It is difficult to identify these genes by genetic association studies alone due to linkage disequilibrium in this region. Therefore, we aimed to identify MHC genes and other genes involved in the pathophysiology of GVHD by mRNA expression profiling. Methodology/Principal Findings: To reduce the complexity of the task, we used genetically well-defined rat inbred strains and a rat skin explant assay, an in-vitro-model of the graft versus host reaction (GVHR), to analyze the expression of MHC, natural killer complex (NKC), and other genes in cutaneous GVHR. We observed a statistically significant and strong up or down regulation of 11 MHC, 6 NKC, and 168 genes encoded in other genomic regions, i.e. 4.9%, 14.0%, and 2.6% of the tested genes respectively. The regulation of 7 selected MHC and 3 NKC genes was confirmed by quantitative real-time PCR and in independent skin explant assays. In addition, similar regulations of most of the selected genes were observed in GVHD-affected skin lesions of transplanted rats and in human skin explant assays. Conclusions/Significance: We identified rat and human MHC and NKC genes that are regulated during GVHR in skin explant assays and could therefore serve as biomarkers for GVHD. Several of the respective human genes, including HLA-DMB, C2, AIF1, SPR1, UBD, and OLR1, are polymorphic. These candidates may therefore contribute to the genetic risk of GVHD in patients