Repositioning the Early Pathology of Type 1 Diabetes to the Extraislet Vasculature.

Type 1 diabetes (T1D) is a prototypic T cell-mediated autoimmune disease. Because the islets of Langerhans are insulated from blood vessels by a double basement membrane and lack detectable lymphatic drainage, interactions between endocrine and circulating T cells are not permitted. Thus, we hypothesized that initiation and progression of anti-islet immunity required islet neolymphangiogenesis to allow T cell access to the islet. Combining microscopy and single cell approaches, the timing of this phenomenon in mice was situated between 5 and 8 wk of age when activated anti-insulin CD4 T cells became detectable in peripheral blood while peri-islet pathology developed. This "peri-insulitis," dominated by CD4 T cells, respected the islet basement membrane and was limited on the outside by lymphatic endothelial cells that gave it the attributes of a tertiary lymphoid structure. As in most tissues, lymphangiogenesis seemed to be secondary to local segmental endothelial inflammation at the collecting postcapillary venule. In addition to classic markers of inflammation such as CD29, V-CAM, and NOS, MHC class II molecules were expressed by nonhematopoietic cells in the same location both in mouse and human islets. This CD45- MHC class II+ cell population was capable of spontaneously presenting islet Ags to CD4 T cells. Altogether, these observations favor an alternative model for the initiation of T1D, outside of the islet, in which a vascular-associated cell appears to be an important MHC class II-expressing and -presenting cell.

Drug Repurposing using consilience of Knowledge Graph Completion methods.

While link prediction methods in knowledge graphs have been increasingly utilized to locate potential associations between compounds and diseases, they suffer from lack of sufficient evidence to explain why a drug and a disease may be indicated. This is especially true for knowledge graph embedding (KGE) based methods where a drug-disease indication is linked only by information gleaned from a vector representation. Complementary pathwalking algorithms can increase the confidence of drug repurposing candidates by traversing a knowledge graph. However, these methods heavily weigh the relatedness of drugs, through their targets, pharmacology or shared diseases. Furthermore, these methods can rely on arbitrarily extracted paths as evidence of a compound to disease indication and lack the ability to make predictions on rare diseases. In this paper, we evaluate seven link prediction methods on a vast biomedical knowledge graph for drug repurposing. We follow the principle of consilience, and combine the reasoning paths and predictions provided by path-based reasoning approaches with those of KGE methods to identify putative drug repurposing indications. Finally, we highlight the utility of our approach through a potential repurposing indication.

Perspectives on tracking data reuse across biodata resources.

Motivation: Data reuse is a common and vital practice in molecular biology and enables the knowledge gathered over recent decades to drive discovery and innovation in the life sciences. Much of this knowledge has been collated into molecular biology databases, such as UniProtKB, and these resources derive enormous value from sharing data among themselves. However, quantifying and documenting this kind of data reuse remains a challenge. Results: The article reports on a one-day virtual workshop hosted by the UniProt Consortium in March 2023, attended by representatives from biodata resources, experts in data management, and NIH program managers. Workshop discussions focused on strategies for tracking data reuse, best practices for reusing data, and the challenges associated with data reuse and tracking. Surveys and discussions showed that data reuse is widespread, but critical information for reproducibility is sometimes lacking. Challenges include costs of tracking data reuse, tensions between tracking data and open sharing, restrictive licenses, and difficulties in tracking commercial data use. Recommendations that emerged from the discussion include: development of standardized formats for documenting data reuse, education about the obstacles posed by restrictive licenses, and continued recognition by funding agencies that data management is a critical activity that requires dedicated resources. Availability and implementation: Summaries of survey results are available at: https://docs.google.com/forms/d/1j-VU2ifEKb9C-sW6l3ATB79dgHdRk5v_lESv2hawnso/viewanalytics (survey of data providers) and https://docs.google.com/forms/d/18WbJFutUd7qiZoEzbOytFYXSfWFT61hVce0vjvIwIjk/viewanalytics (survey of users).