Searching the Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Pre-exposure prophylaxis (PrEP) reduces the risk of HIV infection among men who have sex with men by up to 99%. However, in real-world settings, PrEP users may exhibit risk compensation after uptake of PrEP, including more condomless anal intercourse (CAI) and increased sexually transmitted infection (STI) acquisition. HIV self-testing (HIVST) decreases CAI among men who have sex with men (MSM) by providing awareness of the HIV status of oneself and one's sexual partners. Here, we describe the rationale and design of a randomised waitlist-controlled trial to examine the impact of HIVST on risk compensation among PrEP users.
Pubmed ID: 32690516
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 19, 2020.A program to align short sequences that has been developed with an innovative strategy to perform fast gapped and ungapped alignment onto a reference sequence. It supports several data formats and allows the user to modulate very finely the sensitivity of the alignments. The program is designed to handle huge amounts of short reads generated by ILLUMINA, SOLiD and Roche-454 technology. The optimization of the internal data structure and a filter based on precomputed short-word alignments allow the program to skip false positives in the extension phase, thus reducing the execution time without loss of sensitivity. The final alignment is performed by dynamic programming.
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.
