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Historically, liver allografts with >30% macrosteatosis (MaS) on donor biopsy have been associated with early allograft dysfunction and worse graft survival; however, successful outcomes have been reported in small cohorts. This study proposes an elevated MaS threshold for organ utilization without detriment to graft survival.
Pubmed ID: 32240235
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The only national patient waiting list and an online database system, called UNet, that links all of the professionals involved in the donation and transplantation system for the collection, storage, analysis, and publication of all OPTN data pertaining to the patient waiting list, organ matching, and transplants. The system contains data regarding every organ donation and transplant event occurring in the U.S. since October 1, 1987. UNet is a fail-safe, 24/7, secure Internet-based transplant information database created to enable the nation''''s organ transplant institutions to: * register patients for transplants * match donated organs to waiting patients * manage the time-sensitive, life-critical data of all patients, before and after their transplants Data reports are available by type: National Data, Regional Data, State Data, Center Data, Build Advanced Report, and Annual Report Data. UNet is being used right now by all of the nation''''s organ transplant programs, organ procurement organizations, and histocompatibility (tissue typing) laboratories working cooperatively to efficiently share a limited number of donated organs among thousands of patients.
View all literature mentionsA next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.
View all literature mentionsWelcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
