Mechanism of promoter activity of the β‐amyloid precursor protein gene in different cell lines: identification of a specific 30 bp fragment in the proximal promoter region
Bibliographic record
Abstract
The amyloid beta-protein (Abeta) deposited in brains of Alzheimer's disease (AD) patients is proteolytically derived from a large Abeta precursor protein (APP). APP gene expression patterns in the AD brain region indicate that abnormalities of gene regulation may be important in AD pathology. To understand the contribution of different cell types to APP gene expression, we studied it at four levels: promoter activity (by reporter gene assay of transfected cells), DNA-nuclear protein interaction (by electrophoretic mobility shift assay), RNA message and protein (by northern and western blotting, respectively). APP mRNA and protein expression levels were greater in neuroblastoma and PC12 cells than in glial or cervix epithelial cells. Relative activity among 12 different promoter regions and within single regions varied according to cell type/cell line. An upstream regulatory region containing a GATA-1 site is necessary for activity in PC12 and glial cells but not in neuroblastoma cells. DNA-protein interactions were examined in three distal and one proximal promoter elements in nuclear extracts belonging to neuronal and non-neuronal cells. The proximal promoter region is important for cell line-specific APP gene expression. Characterization of the APP regulatory region's interaction with cell type-specific nuclear factor(s) is important to understand tissue-specific expression of APP seen in AD subjects.
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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 | 0.001 |
| 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 | 0.001 |
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".