Safety and Immunogenicity of Stabilized CH505 TF chTrimer Vaccination in Adults Living With HIV-1 on Suppressive Antiretroviral Therapy

The objective of this study is to assess the safety, tolerability, and immunogenicity of a vaccination with stabilized CH505 TF chTrimer admixed with 3M-052-AF + Aluminum hydroxide (Alum), to assess the effect of CH505 TF chTrimer vaccine as a therapeutic vaccine in adults living with HIV-1 on suppressive antiretroviral therapy (ART) with the aim of inducing new HIV-1 Envelope (Env) B-cell neutralizing immune responses.

Contact Information

Office/Contact: Aleen Khodabakhshian
Phone: 310-557-3798
Email: akhodabakhshian@mednet.ucla.edu
 

Master Protocol for Evaluating Multiple Infection Diagnostics for Ciprofloxacin-Resistant Neisseria Gonorrhoeae

The goal of this study is to learn if a few investigational tests can correctly find the gene mutation (mutant allele gyrA 91F) that predicts ciprofloxacin resistance in clinical specimens that harbor Neisseria gonorrhoeae.

Contact Information

Office/Contact: Lina Castro, PHM, MPH, M(ASCP)CM, TS (ABB)
Phone: 415-554-2800
Email: lina.castro@sfdph.org
 

Tecovirimat Is Safe but Ineffective as Treatment for Clade II Mpox

Monotherapy with the antiviral drug tecovirimat was safe but ineffective as an mpox treatment in an international clinical trial.

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As Prevention Strategy for Sexually Transmitted Infections Rolls Out, Experts Highlight both Promise and Knowledge Gaps

DoxyPEP is reducing the rate of syphilis and chlamydia but has had little to no effect on gonorrhea and needs close monitoring for antibiotic resistance.

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NIH Study Finds Tecovirimat Was Safe but Did Not Improve Mpox Resolution or Pain

Tecovirimat was safe but did not reduce the time to lesion resolution or reduce pain among adults with mild to moderate clade II mpox and a low risk of severe disease in an international study.

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Explainable artificial intelligence and domain adaptation for predicting HIV infection with graph neural networks

Researchers investigated deep learning methods for graph neural networks to predict HIV infections with social network information. Using network data from two cohorts of men in different cities, researchers used GNNExplainer to determine feature importance from graph attention network (GAT) models. Their findings reinforced potential application of GAT models in predicting HIV infections.

Link Type
Data-Sci-Publications
Publish or Event Date
Link URL
https://pmc.ncbi.nlm.nih.gov/articles/PMC11488171/
Short Title
Explainable artificial intelligence and domain adaptation
Content Coordinator
Lisa Mayer
Content Manager
Reed Shabman
Publication Source

Annals of Medicine

NIH Statement on World AIDS Day

Together with our partners, the National Institutes of Health (NIH) commemorates World AIDS Day and affirms our commitment to bolstering the extraordinary gains achieved in HIV science and to persevering until we end HIV-related illness and stigma. As we mark this observance, we celebrate the people who enable scientific progress, honor the loved ones and leaders we have lost, and reflect on the work that remains to ensure the health and life quality of all people affected by, and living with, HIV.

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Mpox Vaccine Antibody Responses Waned Within a Year, Study Shows

How Doxycycline for STI Prevention Affects the Gut Microbiome

Among People with HIV, Mpox Vaccine Protects Well

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