Poly(ADP-ribose) Polymerase-1 Is a Negative Regulator of HIV-1 Transcription through Competitive Binding to TAR RNA with Tat·Positive Transcription Elongation Factor b (p-TEFb) Complex
Bibliographic record
Abstract
Human immunodeficiency virus, type 1 (HIV-1) transcription is regulated by a virus-encoded protein, Tat, which forms a complex with a host cellular factor, positive transcription elongation factor b (P-TEFb). When this complex binds to TAR RNA synthesized from the HIV-1 long terminal repeat promoter element, transcription is trans-activated. In this study we showed that, in host cells, HIV-1 transcription is negatively regulated by competition of poly(ADP-ribose) polymerase-1 (PARP-1) with Tat.P-TEFb for binding to TAR RNA. PARP-1, which has a high affinity for TAR RNA (K(D) = 1.35 x 10(-10) M), binds to the loop region of TAR RNA and displaces Tat or Tat.P-TEFb from the RNA. In vitro transcription assays showed that this displacement leads to suppression of Tat-mediated trans-activation of transcription. Furthermore in vivo expression of luciferase or destabilized enhanced green fluorescent protein genes under the control of the HIV-1 long terminal repeat promoter was suppressed by PARP-1. Thus, these results suggest that PARP-1 acts as a negative regulator of HIV-1 transcription through competitive binding with Tat or the Tat.P-TEFb complex to TAR RNA.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".