Positive and Negative Modulation of Human Immunodeficiency Virus Type 1 Rev Function by <i>cis</i> and <i>trans</i> Regulators of Viral RNA Splicing
Bibliographic record
Abstract
Expression of the entire complement of human immunodeficiency virus type 1 (HIV-1) viral proteins depends on the competing activities of viral RNA splicing and export into the cytoplasm by Rev. To investigate the possibility that modulation of viral RNA metabolism may alter Rev function, we analyzed the impact of multiple SR proteins on both processes. While overexpression of several of the SR factors altered splicing of HIV-1 env mRNA, they had disparate effects on Rev function that varied with the cell line used. Subsequent examination of exon splicing enhancer (ESE) and/or silencer (ESS) deletions suggests that the effects of the SR proteins on Rev function are not mediated through interaction with these elements. However, analysis of the deletions did indicate that the ESE and/or ESS does have significant effects on Rev function, with deletion of the ESS augmenting the magnitude of the response to Rev and deletion of the ESE significantly reducing it. In situ hybridization and reverse transcription-PCR indicated that the loss of Rev response upon deletion of the ESE was due to a failure of Rev to induce transport of the unspliced RNA into the cytoplasm. Together, the data indicate that cellular splicing factors and viral regulatory elements can have significant stimulatory and inhibitory effects on Rev function, raising the possibility that cells can be rendered permissive or nonpermissive for virus replication by modulation of splicing activities.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".