CAR-T cell therapy is already a potent treatment for certain cancers. Now, a small study is showing early promise for managing HIV. A Miracle cancer therapy that involves engineering a patient's own immune cells is being repurposed for HIV, and early results from two individuals hint at its promise for long-term control of the virus. As part of a clinical trial, scientists took people's own immune cells and reprogrammed them in a lab to recognize and attack HIV in the body. After a single infusion of the modified cells, two individuals with HIV now have undetectable levels of the virus--one for nearly two years and the other for almost a year.

Ancient viruses, whose DNA has hitchhiked within the human genome for millennia, may be the cause of many age-related conditions. Scientists have proven for the first time that they can use this viral DNA -- known as'retroelements' -- to predict the age of human cells with'high accuracy.' In recent years, this seemingly inactive'junk' DNA from retroelements has been linked to everything from sleep patterns and memory formation to bipolar disorder. Armed with their new ability to track a person's age via this ancient viral DNA, the scientists now plan to investigate whether new antiviral treatments could reverse the conditions of aging, by deactivating the worst of these viral'retroelement' genes. The new research harnesses previously unknown features of this ancient viral DNA, creating a biological clock to track a person's age from the DNA's chemical changes.

Motivation: In predicting HIV therapy outcomes, a critical clinical question is whether using historical information can enhance predictive capabilities compared with current or latest available data analysis. This study analyses whether historical knowledge, which includes viral mutations detected in all genotypic tests before therapy, their temporal occurrence, and concomitant viral load measurements, can bring improvements. We introduce a method to weigh mutations, considering the previously enumerated factors and the reference mutation-drug Stanford resistance tables. We compare a model encompassing history (H) with one not using it (NH). Results: The H-model demonstrates superior discriminative ability, with a higher ROC-AUC score (76.34%) than the NH-model (74.98%). Significant Wilcoxon test results confirm that incorporating historical information improves consistently predictive accuracy for treatment outcomes. The better performance of the H-model might be attributed to its consideration of latent HIV reservoirs, probably obtained when leveraging historical information. The findings emphasize the importance of temporal dynamics in mutations, offering insights into HIV infection complexities. However, our result also shows that prediction accuracy remains relatively high even when no historical information is available. Supplementary information: Supplementary material is available.