Deciphering the interaction between Twist1 and PPARγ during adipocyte differentiation
Bibliographic record
Abstract
Obesity, a worldwide epidemic in recent years, is mainly due to the uncontrolled development of adipose tissues, which includes adipocyte hypertrophy and hyperplasia. Adipocyte differentiation is a process involving multiple transcription factor cascades, and the exact mechanism has not yet been defined. As a bHLH transcription factor, Twist1 exerts its activity by forming homo- or heterodimers with other factors. In this study, we showed Twist1 restricts adipogenesis through PPARγ. Expression of various differentiation markers (including PPARγ and adiponectin) and triglyceride-containing lipid droplets were decreased with overexpression of Twist1. Pathway enrichment analysis of RNA-seq data showed that differentially expressed genes (DEGs) caused by Twist1 overexpression were significantly related to lipolysis and PPARγ signaling. This implicates that Twist1 plays important regulatory roles in these processes. ChIP and dual luciferase assays showed that Twist1 could bind either PPARγ or adiponectin promoter to repress their respective transcription or directly to PPARγ protein to regulate its transcriptional activity. Furthermore, Twist1 directly interacted RXRα, which usually forms heterodimer with PPARγ to regulate adipogenesis. Taken together, our results suggest that Twist1 is an inhibitory modulator of adipogenesis and its function is likely through direct interaction with PPARγ protein or its gene promoter.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".