Cat and Mouse: HIV Transcription in Latency, Immune Evasion and Cure/Remission Strategies
Bibliographic record
Abstract
There is broad scientific and societal consensus that finding a cure for HIV infection must be pursued. The major barrier to achieving a cure for HIV/AIDS is the capacity of the HIV virus to avoid both immune surveillance and current antiretroviral therapy (ART) by rapidly establishing latently infected cell populations, termed latent reservoirs. Here, we provide an overview of the rapidly evolving field of HIV cure/remission research, highlighting recent progress and ongoing challenges in the understanding of HIV reservoirs, the role of HIV transcription in latency and immune evasion. We review the major approaches towards a cure that are currently being explored and further argue that small molecules that inhibit HIV transcription, and therefore uncouple HIV gene expression from signals sent by the host immune response, might be a particularly promising approach to attain a cure or remission. We emphasize that a better understanding of the game of "cat and mouse" between the host immune system and the HIV virus is a crucial knowledge gap to be filled in both cure and vaccine research.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".