Heterogeneity of Signal Transducer and Activator of Transcription Binding Sites in the Long-Terminal Repeats of Distinct HIV-1 Subtypes
Bibliographic record
Abstract
HIV-1 can be subdivided into distinct subtypes; the consequences of such a genomic variability remain largely speculative. The long terminal repeats (LTR) control HIV transcription and reflect the major differences of distinct viral subtypes. Three regions in the HIV-1 subtype B LTR are close matches to the Signal Transducer and Activator of Transcription (STAT) consensus sequence. Here, we show heterogeneity in these putative STAT binding sites among HIV-1 LTR subtypes A through G. Transfection of constitutively activated STAT5 lead to transcriptional activation of HIV-1 expression in 293T cells transfected with a reporter assay driven by HIV-1 LTR subtype B. Constitutively activated STAT5 transactivated the LTR of various subtypes in U937 cells with different potency. These findings support and expand the potential relevance of STAT5 activation in HIV infection and may bear relevance for a differential regulation of latency and expression of different subtypes of HIV-1.
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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) | 0.001 | 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".