The Regulation of C/EBPβ Activity and Adipogenesis by the Smad3 MH1 Domain
Bibliographic record
Abstract
Retinoic Acid (RA) is a potent anti-adipogenic molecule. Recent experiments in our lab identified the transcription factor Smad3 as a novel RA target gene required for RA-mediated inhibition of adipogenesis. Smad3 was demonstrated to inhibit C/EBPβ DNA binding via an interaction between the Smad3-MH1 domain and C/EBPβ. The goal of this thesis was to evaluate the anti-adipogenic potential of the isolated Smad3 MH1 domain in the absence of RA treatment. Pooled 3T3-L1 preadipocyte stable cell lines expressing MH1 and empty vector controls were created and induced to differentiate. While MH1 protein expression was difficult to detect due to high protein lability, C/EBPβ DNA binding to its response element within the C/EBPα promoter was inhibited in MH1-expressing cells. Despite this, loss of C/EBPβ occupancy at the C/EBPα promoter did not result in changes in C/EBPα gene expression though adipogenesis was inhibited in these cultures. In contrast, PPARγ levels were reduced in MH1-expressing cells suggesting that regulation of PPARγ expression by the isolated MH1 domain drives the inhibition of adipogenesis in this model. The second goal of this thesis was to evaluate the regulation of Smad3 by RA. We determined that RA directly activates Smad3 transcription, which is not dependent on promoter demethylation. Furthermore, RA induces Smad3 nuclear accumulation in the absence of Smad3 phosphorylation.
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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) | 0.003 | 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".