MicroRNA-mediated inhibition of AMPK coordinates tissue-specific downregulation of skeletal muscle metabolism in hypoxic naked mole-rats
Bibliographic record
Abstract
Naked mole-rats reduce their metabolic requirements to tolerate severe hypoxia. However, the regulatory mechanisms that underpin this metabolic suppression have yet to be elucidated. 5'-AMP-activated protein kinase (AMPK) is the cellular 'master' energy effector and we hypothesized that alterations in the AMPK pathway contribute to metabolic reorganization in hypoxic naked mole-rat skeletal muscle. To test this hypothesis, we exposed naked mole-rats to 4 h of normoxia (21% O2) or severe hypoxia (3% O2), while indirectly measuring whole-animal metabolic rate and fuel preference. We then isolated skeletal muscle and assessed protein expression and post-translational modification of AMPK, and downstream changes in key glucose and fatty acid metabolic proteins mediated by AMPK, including acetyl-CoA carboxylase (ACC1), glycogen synthase (GS) and glucose transporters (GLUTs) 1 and 4. We found that in hypoxic naked mole-rats (1) metabolic rate decreased ∼80% and fuel use switched to carbohydrates, and that (2) levels of activated phosphorylated AMPK and GS, and GLUT4 expression were downregulated in skeletal muscle, while ACC1 was unchanged. To explore the regulatory mechanism underlying this hypometabolic state, we used RT-qPCR to examine 55 AMPK-associated microRNAs (miRNAs), which are short non-coding RNA post-transcriptional silencers. We identified changes in 10 miRNAs (three upregulated and seven downregulated) implicated in AMPK downregulation. Our results suggest that miRNAs and post-translational mechanisms coordinately reduce AMPK activity and downregulate metabolism in naked mole-rat skeletal muscle during severe hypoxia. This novel mechanism may support tissue-specific prioritization of energy for more essential organs in hypoxia.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".