Modeling and functional analysis of AEBP1, a transcriptional repressor
Bibliographic record
Abstract
Adipocyte enhancer binding protein 1 (AEBP1) is a transcriptional repressor of the aP2 gene, which encodes the adipocyte lipid binding protein and is involved in the differentiation of preadipocytes into mature adipocytes. It is an isoform of aortic carboxypeptidase-like protein (ACLP), which is a part of the extracellular matrix. AEBP1 and ACLP contain a conserved carboxypeptidase domain which is critical for the function of AEBP1 as a transcriptional repressor. Homology modeling and multiple alignment of AEBP1 homologues were performed to identify putative domains and critical residues that were then deleted or mutated in mouse AEBP1. Expression of wild-type and mutant AEBP1 proteins in CHO cells was performed, and their function in transcriptional repression was assayed by luciferase assay. All deletion forms of AEBP1 were able to repress transcription driven by the aP2 promoter. The DNA binding domain of AEBP1 was mapped by electrophoretic mobility shift assays to a region of the C-terminus rich in basic residues. However, wild-type AEBP1 was not able to interact strongly with DNA, suggesting that AEBP1 might function predominantly as a corepressor, independent of DNA binding. AEBP1 was also found to interact with Ca2+/calmodulin through this basic region, suggesting another mechanism of functional regulation.
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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 | 0.001 | 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".