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Macaluso, M.

Publications and source records attributed to Macaluso, M..

2 recordsLinked to original sources

RORγt-Expressing Pathogenic CD4+T Cells Cause Brain Inflammation During Chronic Colitis

Neurobehavioral disorders and brain abnormalities have been extensively reported in both Crohns Disease (CD) and Ulcerative Colitis (UC) patients. However, the mechanism causing neuropathological disorders in inflammatory bowel disease (IBD) patients remains unknown. Studies have linked the Th17 subset of CD4+T cells to brain diseases associated with neuroinflammation and cognitive impairment, including multiple sclerosis (MS), ischemic brain injury and Alzheimers disease. To better understand how CD4+T lymphocytes, contribute to brain pathology in chronic intestinal inflammation, we investigated the development of brain inflammation in the T cell transfer model of chronic colitis. Our findings demonstrate that CD4+T cells infiltrate the brain of colitic Rag1-/- mice in proportional levels to colitis severity. Colitic mice developed hypothalamic astrogliosis that correlated with neurobehavioral disorders. Moreover, the brain-infiltrating CD4+T cells expressed Th17 cell transcription factor ROR{gamma}t and displayed a pathogenic Th17 cellular phenotype similar to colonic Th17 cells. Adoptive transfer of ROR{gamma}t-deficient naive CD4+T cells failed to cause brain inflammation and neurobehavioral disorders in Rag1-/- recipients, with significantly less brain infiltration of CD4+T cells. These findings suggest that pathogenic ROR{gamma}t+CD4+T cells that aggravate colitis migrate preferentially into the brain, contributing to brain inflammation and neurobehavioral disorders, thereby linking colitis severity to neuroinflammation.

immunology↗

Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant performance gains over established algorithms. These include algorithms for antibody clustering, imputing gene expression data, and querying the Connectivity Map (CMap). Performance gains are evaluated quantitatively using realistic, albeit sanitized, data sets. The solutions produced through these competitions are then examined with respect to their utility and the prospects for implementation in the field. We present the decision process and competition design considerations that lead to these successful outcomes as a model for researchers who want to use competitions and non-domain crowds as collaborators to further their research.

bioinformatics↗