MicroRNA-298 and MicroRNA-328 Regulate Expression of Mouse β-Amyloid Precursor Protein-converting Enzyme 1
Bibliographic record
Abstract
MicroRNAs (miRNAs) are key regulatory RNAs known to repress mRNA translation through recognition of specific binding sites located mainly in their 3'-untranslated region (UTR). Loss of specific miRNA control of gene expression is thus expected to underlie serious genetic diseases. Intriguingly, previous post-mortem analyses showed higher beta-amyloid precursor protein-converting enzyme (BACE) protein, but not mRNA, levels in the brain of patients that suffered from Alzheimer disease (AD). Here we also observed a loss of correlation between BACE1 mRNA and protein levels in the hippocampus of a mouse model of AD. Consistent with an impairment of miRNA-mediated regulation of BACE1 expression, these findings prompted us to investigate the regulatory role of the BACE1 3'-UTR element and the possible involvement of specific miRNAs in cultured neuronal (N2a) and fibroblastic (NIH 3T3) cells. Through various experimental approaches, we validated computational predictions and demonstrated that miR-298 and miR-328 recognize specific binding sites in the 3'-UTR of BACE1 mRNA and exert regulatory effects on BACE1 protein expression in cultured neuronal cells. Our results may provide the molecular basis underlying BACE1 deregulation in AD and offer new perspectives on the etiology of this neurological disorder.
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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".