Insulin-like growth factor-1 coordinately induces the expression of fatty acid and cholesterol biosynthetic genes in murine C2C12 myoblasts
Bibliographic record
Abstract
BACKGROUND: We present evidence that a major aspect of the mechanism of acute signal transduction regulation by insulin-like growth factor-1 (IGF-1) in cultured murine myoblasts is associated with a broad perturbation of many components of cholesterol and fatty acid biosynthetic pathways. RESULTS: We have used microarray transcriptional analysis to examine the acute effects of IGF-1 on global patterns of gene expression in C2C12 myoblasts and have identified approximately 157 genes that are up-regulated and 75 genes down-regulated from 2- to 6-fold after treatment with IGF-1. Of the up-regulated genes, 19 genes are associated with cholesterol biosynthesis and 5 genes specify aspects of fatty acid biosynthesis. In addition 10 recognized transcription factors are significantly induced by IGF-1 at 1 hour. CONCLUSION: The SREBPs, important regulators of fatty acid and cholesterol biosynthesis, operate via a post-transcriptional route and no significant transcriptional induction was observed in the 4 hr of IGF-1 treatment. Since there are no prior reports of significant and coordinated perturbations of fatty acid and cholesterol biosynthetic pathways with IGF-1 in muscle cells, these findings provide a substantive expansion of our understanding of IGF-1 action and the signal transduction pathways mediated by it, its variants and insulin.
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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".