Regulation of Skeletal Muscle Mitochondrial Content During Aging
Bibliographic record
Abstract
Mitochondrial content of skeletal muscle varies among fiber types, and changes in complex ways during aging. We evaluated the regulatory origins of differences in mitochondrial content among muscles of varied fiber type in F344xBNF1 rats, and how these regulatory patterns are altered with aging. In adult (12 month) animals we found that units citrate synthase (CS)/g tissue, a marker for mitochondrial content, varied approximately 3-fold among 10 skeletal muscles. Stoichiometric relationships between CS and isocitrate dehydrogenase, aconitase, and cytochrome c oxidase were generally preserved across fiber types. Among the 10 muscles of adult rats, CS content correlated with nuclear content (R2= 0.36). Muscles differed widely in CS messenger RNA (mRNA)/DNA (an index of variation in transcriptional regulations) and units CS/CS mRNA (an index of variation in posttranscriptional regulations). All muscles of aged rats (35 months) showed an increase in mg DNA/g, suggestive of atrophy. Age-dependent declines in units CS/DNA were accompanied by reductions in CS mRNA/DNA and/or units CS/CS mRNA, depending on muscle fiber type. Thus, declines in units CS/DNA with age appeared to be due to transcriptional as well as translational variations. Differences in mitochondrial content among muscle fiber types and age groups may arise from variations in nuclear content and posttranscriptional processes, as well as transcriptional regulation.
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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) | 0.000 | 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 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".