Regulation of Substrate Oxidation Preferences in Muscle by the Peptide Hormone Adropin
Bibliographic record
Abstract
Rigorous control of substrate oxidation by humoral factors is essential for maintaining metabolic homeostasis. During feeding and fasting cycles, carbohydrates and fatty acids are the two primary substrates in oxidative metabolism. Here, we report a novel role for the peptide hormone adropin in regulating substrate oxidation preferences. Plasma levels of adropin increase with feeding and decrease upon fasting. A comparison of whole-body substrate preference and skeletal muscle substrate oxidation in adropin knockout and transgenic mice suggests adropin promotes carbohydrate oxidation over fat oxidation. In muscle, adropin activates pyruvate dehydrogenase (PDH), which is rate limiting for glucose oxidation and suppresses carnitine palmitoyltransferase-1B (CPT-1B), a key enzyme in fatty acid oxidation. Adropin downregulates PDH kinase-4 (PDK4) that inhibits PDH, thereby increasing PDH activity. The molecular mechanisms of adropin's effects involve acetylation (suggesting inhibition) of the transcriptional coactivator PGC-1α, downregulating expression of Cpt1b and Pdk4. Increased PGC-1α acetylation by adropin may be mediated by inhibiting Sirtuin-1 (SIRT1), a PGC-1α deacetylase. Altered SIRT1 and PGC-1α activity appear to mediate aspects of adropin's metabolic actions in muscle. Similar outcomes were observed in fasted mice treated with synthetic adropin. Together, these results suggest a role for adropin in regulating muscle substrate preference under various nutritional states.
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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".