Over-Expressing Mitofusin-2 in Healthy Mature Mammalian Skeletal Muscle Does Not Alter Mitochondrial Bioenergetics
Bibliographic record
Abstract
The role of mitofusin-2 (MFN-2) in regulating mitochondrial dynamics has been well-characterized in lower order eukaryotic cell lines through the complete ablation of MFN-2 protein. However, to support the contractile function of mature skeletal muscle, the subcellular architecture and constituent proteins of this tissue differ substantially from simpler cellular organisms. Such differences may also impact the role of MFN-2 in mature mammalian muscle, and it is unclear if minor fluctuations in MFN-2, as observed in response to physiological perturbations, has a functional consequence. Therefore, we have transiently transfected MFN-2 cDNA into rat tibialis anterior muscle to determine the effect of physiolgically relevant increases in MFN-2 protein on mitochondrial bioenergetics. Permeabilized muscle fibres generated from muscle following MFN-2-transfection were used for functional assessments of mitochondrial bioenergetics. In addition, we have further established a novel method for selecting fibre bundles that are positively transfected, and using this approach transient transfection increased MFN-2 protein ∼2.3 fold in selected muscle fibres. However, this did not alter maximal rates of oxygen consumption or the sensitivity for ADP-stimulated respiration. In addition, MFN-2 over-expression did not alter rates of H(2)O(2) emission. Altogether, and contrary to evidence from lower order cell lines, our results indicate that over-expressing MFN-2 in healthy muscle does not influence mitochondrial bioenergetics in mature mammalian skeletal muscle.
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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) | 0.001 | 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".