Differential expression of genes controlling mitochondrial biogenesis during C2C12 differentiation
Bibliographic record
Abstract
Myogenesis involves the fusion of myoblasts into myotubes. Mitochondrial biogenesis plays an important role in myogenesis, but the molecular mechanisms that govern the changes in mitochondria during differentiation have yet to be fully elucidated. Thus, we sought to describe the regulation of mitochondrial biogenesis during 8 days of C2C12 myoblast differentiation in culture. Cytochrome c oxidase (COX) activity, a marker of biogenesis, was increased by 2.6‐fold during differentiation. The mRNAs encoding the fusion protein mitofusin‐2 (Mfn2) increased by 20–30 fold by day 4, while no changes were observed in Fis1, a fission protein. This coincided with an increase in mitochondrial network formation, and a decrease in organelle granularity. Mitochondrial transcription factor A (Tfam) and COX subunit IV (COX IV) protein levels increased during differentiation, but no changes in mRNA levels were evident. Thus, differentiation of C2C12 cells promotes mitochondrial biogenesis via: mitochondrial fusion through an increase in the Mfn2‐to‐Fis1 ratio, increases in Tfam, the regulator of mtDNA gene transcription and translation. These changes contribute to the increase in mitochondrial function and content, evident from the changes in COX enzyme activity. These data suggest a well regulated pattern of gene expression that occurs during differentiation leading to mitochondrial biogenesis.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".