Prostaglandin E2-Mediated Activation of HIV-1 Long Terminal Repeat Transcription in Human T Cells Necessitates CCAAT/Enhancer Binding Protein (C/EBP) Binding Sites in Addition to Cooperative Interactions Between C/EBPβ and Cyclic Adenosine 5′-Monophosphate Response Element Binding Protein
Bibliographic record
Abstract
Previous work indicates that treatment of human T cells with PGE(2) results in an increase of HIV-1 long terminal repeat (LTR) transcriptional activity. The noticed PGE(2)-mediated activation of virus gene activity required the participation of specific intracellular second messengers such as calcium and two transcription factors, i.e., NF-kappaB and CREB. We report in this work that the nuclear transcription factor CCAAT/enhancer binding protein (C/EBP) is also important for PGE(2)-dependent up-regulation of HIV-1 LTR-driven gene activity. The implication of C/EBP was shown by using a trans-dominant negative inhibitor of C/EBP (i.e., liver-enriched transcriptional inhibitory protein) and several molecular constructs carrying site-directed mutations in the C/EBP binding sites located within the HIV-1 LTR. Mutated HIV-1 LTR constructs also revealed the involvement of the two most proximal C/EBP binding sites. Data from cotransfection experiments with vectors coding for dominant negative mutants and gel mobility shift assays indicated that PGE(2)-mediated induction of HIV-1 LTR activity results from a cooperative interaction between C/EBPbeta and CREB, two members of the basic leucine zipper family of transcription factors. Altogether these findings indicate that treatment of human T cells with PGE(2) induces HIV-1 LTR activity through a complex interplay between C/EBPbeta and CREB. Such a combinatorial regulation may represent a mechanism that permits a fine regulation of HIV-1 expression by PGE(2) in human T cells.
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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 | 0.001 |
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".