Identification of an octamer-binding site controlling the activity of the small breast epithelial mucin gene promoter
Bibliographic record
Abstract
e human small breast epithelial mucin (SBEM) gene has been identified as being preferentially expressed in mammary epithelial cells and over-expressed in breast tumors. In this report, we have characterized the promoter of SBEM gene in order to identify sequences responsible for this strong mammary expression. A series of SBEM promoter/luciferase constructs were transiently transfected into both breast (MCF-7, BT-20) and non-breast (HeLa and HepG2) cell lines. In addition to the minimal promoter and to a repressor region, we have identified an 87-bp sequence (-357/-270) driving a strong breast-specific expression. Site-directed mutagenesis of a putative octamer-binding transcription factor binding site located within this latter region led to a strong decrease of the transcriptional activity of the SBEM promoter. Furthermore, transient over-expression of Oct1 and Oct2 not only increased SBEM promoter reporter activity, but also enhanced endogenous SBEM mRNA level. Overall, the data suggest that octamer-binding transcription factors participate in the strong expression of SBEM gene in breast tissues. Clarifying the SBEM gene regulation will help to dissect mechanisms underlying transcription of normal breast and breast cancer-associated genes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".