Nuclear Factor 1 Interferes with Sp1 Binding through a Composite Element on the Rat Poly(ADP-ribose) Polymerase Promoter to Modulate Its Activity in Vitro
Bibliographic record
Abstract
Poly(ADP-ribose) polymerase-1 (PARP-1) catalyzes the rapid and extensive poly(ADP-ribosyl)ation of nuclear proteins in response to DNA strand breaks, and its expression, although ubiquitous, is modulated from tissue to tissue and during cellular differentiation. PARP-1 gene promoters from human, rat, and mouse have been cloned, and they share a structure common to housekeeping genes, as they lack a functional TATA box and contain multiple GC boxes, which bind the transcriptional activator Sp1. We have previously shown that, although Sp1 is important for rat PARP1 (rPARP) promoter activity, its finely tuned modulation is likely dependent on other transcription factors that bind the rPARP proximal promoter in vitro. In this study, we identified one such factor as NF1-L, a rat liver isoform of the nuclear factor 1 family of transcription factors. The NF1-L site on the rPARP promoter overlaps one of the Sp1 binding sites previously identified, and we demonstrated that binding of both factors to this composite element is mutually exclusive. Furthermore, we provide evidence that NF1-L has no effect by itself on rPARP promoter activity, but rather down-regulates the Sp1 activity by interfering with its ability to bind the rPARP promoter in order to modulate transcription of the rPARP gene.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".