Regulation of HIV-1 gene expression by clade-specific Tat proteins
Bibliographic record
Abstract
The major group of HIV-1 viruses that comprises the current global pandemic evolved, during their worldwide spread, into at least 10 distinct subtypes or clades. Subtype C predominates in sub-Saharan Africa and is responsible for the majority of the worldwide HIV-1 infections, while subtype B predominates in North America and Europe and subtype A/E is prevalent in Southeast Asia. Functional distinctions in the arrangement of NF-kappaB elements within the long terminal repeat (LTR) among HIV-1 subtypes have been identified, thus raising the possibility that transcriptional divergence amongst the subtypes of HIV-1 has occurred. In addition, significant amino acid variations have been observed amongst the clade-specific Tat proteins. In the present study, we sought to examine clade specific interactions between Tat, TAR and cellular proteins as well as to determine how these interactions may modulate the efficiency of HIV-1 gene transcription. Our results indicate that while sequence variation in the NF-kappaB region of the clade-specific LTRs plays a modest role in altering HIV-1 expression, clade-specific Tat proteins significantly modify viral gene expression.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".