The Adipocyte-Expressed Forkhead Transcription Factor Foxc2 Regulates Metabolism Through Altered Mitochondrial Function
Bibliographic record
Abstract
OBJECTIVE: Previous findings demonstrate that enhanced expression of the forkhead transcription factor Foxc2 in adipose tissue leads to a lean and insulin-sensitive phenotype. These findings prompted us to further investigate the role of Foxc2 in the regulation of genes of fundamental importance for metabolism and mitochondrial function. RESEARCH DESIGN AND METHODS: The effects of Foxc2 on expression of genes involved in mitochondriogenesis and mitochondrial function were assessed by quantitative real-time PCR. The potential of a direct transcriptional regulation of regulated genes was tested in promoter assays, and mitochondrial morphology was investigated by electron microscopy. Mitochondrial function was tested by measuring oxygen consumption and extracellular acidification rates as well as palmitate oxidation. RESULTS: Enhanced expression of FOXC2 in adipocytes or in cells with no endogenous Foxc2 expression induces mitochondriogenesis and an elongated mitochondrial morphology. Together with increased aerobic metabolic capacity, increased palmitate oxidation, and upregulation of genes encoding respiratory complexes and of brown fat-related genes, Foxc2 also specifically induces mitochondrial fusion genes in adipocytes. Among tested forkhead genes, Foxc2 is unique in its ability to trans-activate the nuclear-encoded mitochondrial transcription factor A (mtTFA/Tfam) gene--a master regulator of mitochondrial biogenesis. In human adipose tissue the expression levels of mtTFA/Tfam and of fusion genes also correlate with that of Foxc2. CONCLUSIONS: We previously showed that a high-calorie diet and insulin induce Foxc2 in adipocytes; the current findings identify a previously unknown role for Foxc2 as an important metabo-regulator of mitochondrial morphology and metabolism.
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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".