Factors Controlling Chromatin Organization and Nucleosome Positioning for Establishment and Maintenance of HIV Latency
Bibliographic record
Abstract
Transcription of the integrated HIV provirus is subject to regulation by chromatin organization and must employ host cell transcription factors and chromatin modifying complexes to promote the formation of latency, and then reverse this process to replicate in response to T cell activation. The repressed latent HIV-1 proviral 5' LTR is organized into a defined structure where two de-acetylated and positioned nucleosomes flank the enhancer region, presumably imposing a block to transcriptional initiation and elongation. LTR-associated nucleosomes undergo further histone H3 K9 trimethylation, to cause silencing by recruitment of HP1. In this article, we review current understanding of how the transcriptionally silenced provirus might be established through the function of transcription factors that bind conserved cis-elements, including SP1, YY1, NF-kappaB, CBF-1 and RBF-2 (USF/TFII-I), and propose mechanisms by which factors bound to the repressed LTR can enable reactivation in response to cell signaling.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".