Resistance against Integrase Strand Transfer Inhibitors and Relevance to HIV Persistence
Bibliographic record
Abstract
Drug resistance prevents the successful treatment of HIV-positive individuals by decreasing viral sensitivity to a drug or a class of drugs. In addition to transmitted resistant viruses, treatment-naïve individuals can be confronted with the problem of drug resistance through de novo emergence of such variants. Resistant viruses have been reported for every antiretroviral drug tested so far, including the integrase strand transfer inhibitors raltegravir, elvitegravir and dolutegravir. However, de novo resistant variants against dolutegravir have been found in treatment-experienced but not in treatment-naïve individuals, a characteristic that is unique amongst antiretroviral drugs. We review here the issue of drug resistance against integrase strand transfer inhibitors as well as both pre-clinical and clinical studies that have led to the identification of the R263K mutation in integrase as a signature resistance substitution for dolutegravir. We also discuss how the topic of drug resistance against integrase strand transfer inhibitors may have relevance in regard to the nature of the HIV reservoir and possible HIV curative strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".