The Relationship between Muscle Fiber Type-Specific PGC-1α Content and Mitochondrial Content Varies between Rodent Models and Humans
Bibliographic record
Abstract
PGC-1α regulates critical processes in muscle physiology, including mitochondrial biogenesis, lipid metabolism and angiogenesis. Furthermore, PGC-1α was suggested as an important regulator of fiber type determination. However, whether a muscle fiber type-specific PGC-1α content exists, whether PGC-1α content relates to basal levels of mitochondrial content, and whether such relationships are preserved between humans and classically used rodent models are all questions that have been either poorly addressed or never investigated. To address these issues, we investigated the fiber type-specific content of PGC-1α and its relationship to basal mitochondrial content in mouse, rat and human muscles using in situ immunolabeling and histochemical methods on muscle serial cross-sections. Whereas type IIa fibers exhibited the highest PGC-1α in all three species, other fiber types displayed a hierarchy of type IIx>I>IIb in mouse, type I = IIx> IIb in rat, and type IIx>I in human. In terms of mitochondrial content, we observed a hierarchy of IIa>IIx>I>IIb in mouse, IIa >I>IIx> IIb in rat, and I>IIa> IIx in human skeletal muscle. We also found in rat skeletal muscle that type I fibers displayed the highest capillarization followed by type IIa >IIx>IIb. Finally, we found in human skeletal muscle that type I fibers display the highest lipid content, followed by type IIa>IIx. Altogether, our results reveal that (i) the fiber type-specific PGC-1α and mitochondrial contents were only matched in mouse, (ii) the patterns of PGC-1α and mitochondrial contents observed in mice and rats do not correspond to that seen in humans in several respects, and (iii) the classical phenotypes thought to be regulated by PGC-1α do not vary exclusively as a function of PGC-1α content in rat and human muscles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".