Evidence for the role of AMPK in regulating PGC‐1 alpha expression and mitochondrial proteins in mouse epididymal adipose tissue
Bibliographic record
Abstract
OBJECTIVE: PGC-1α is a transcriptional co-activator and master regulator of mitochondrial biogenesis. While extensively studied in skeletal and cardiac muscle, recent findings suggest that white adipose tissue PGC-1α plays an important role in regulating glucose homeostasis. The purpose of the present investigation was to evaluate the role of AMPK in regulating PGC-1α and mitochondrial enzymes in mouse epididymal and inguinal subcutaneous adipose tissue. METHODS: Mitochondrial protein content and norepinephrine and CL 316,243-induced PGC-1α mRNA expression were studied in mouse epididymal and inguinal adipose tissue from wild-type and AMPK β1(-/-) mice. RESULTS: The protein content and phosphorylation of AMPKα was reduced in epididymal adipose tissue from AMPK β1(-/-) compared to WT mice, concomitant with decreases in PGC-1α and mitochondrial marker proteins. Norepinephrine and CL 316,243-mediated induction of PGC-1α were decreased in cultured epididymal adipose tissue from AMPK β1(-/-) relative to WT mice. In inguinal adipose tissue from AMPK β1(-/-) mice, mitochondrial marker protein content and norepinephrine and CL 316,243-mediated increases in PGC-1α were normal despite reductions in the content and phosphorylation of AMPKα. CONCLUSIONS: Norepinephrine- and CL 316,243-mediated induction of PGC-1α and mitochondrial protein expression is regulated by AMPK in epididymal, but not inguinal adipose tissue.
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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 | 0.001 | 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 | 0.001 |
| 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".