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Full-Text Articles in Oncology
Human Islet Response To Selected Type 1 Diabetes-Associated Bacteria: A Transcriptome-Based Study, Ahmed M. Abdellatif, Heather Jensen Smith, Robert Z. Harms, Nora Sarvetnick
Human Islet Response To Selected Type 1 Diabetes-Associated Bacteria: A Transcriptome-Based Study, Ahmed M. Abdellatif, Heather Jensen Smith, Robert Z. Harms, Nora Sarvetnick
Journal Articles: Eppley Institute
Type 1 diabetes (T1D) is a chronic autoimmune disease that results from destruction of pancreatic β-cells. T1D subjects were recently shown to harbor distinct intestinal microbiome profiles. Based on these findings, the role of gut bacteria in T1D is being intensively investigated. The mechanism connecting intestinal microbial homeostasis with the development of T1D is unknown. Specific gut bacteria such as Bacteroides dorei (BD) and Ruminococcus gnavus (RG) show markedly increased abundance prior to the development of autoimmunity. One hypothesis is that these bacteria might traverse the damaged gut barrier, and their constituents elicit a response from human islets that causes …
Genomic Prediction Of Relapse In Recipients Of Allogeneic Haematopoietic Stem Cell Transplantation., J Ritari, K Hyvärinen, S Koskela, M Itälä-Remes, R Niittyvuopio, A Nihtinen, U Salmenniemi, M Putkonen, L Volin, T Kwan, T Pastinen, J Partanen
Genomic Prediction Of Relapse In Recipients Of Allogeneic Haematopoietic Stem Cell Transplantation., J Ritari, K Hyvärinen, S Koskela, M Itälä-Remes, R Niittyvuopio, A Nihtinen, U Salmenniemi, M Putkonen, L Volin, T Kwan, T Pastinen, J Partanen
Manuscripts, Articles, Book Chapters and Other Papers
Allogeneic haematopoietic stem cell transplantation currently represents the primary potentially curative treatment for cancers of the blood and bone marrow. While relapse occurs in approximately 30% of patients, few risk-modifying genetic variants have been identified. The present study evaluates the predictive potential of patient genetics on relapse risk in a genome-wide manner. We studied 151 graft recipients with HLA-matched sibling donors by sequencing the whole-exome, active immunoregulatory regions, and the full MHC region. To assess the predictive capability and contributions of SNPs and INDELs, we employed machine learning and a feature selection approach in a cross-validation framework to discover the …