Subproteomic analysis of basic proteins in aged skeletal muscle following offgel pre-fractionation
Bibliographic record
Abstract
The progressive loss of skeletal muscle mass is a serious pathophysiological problem in the elderly, which warrants detailed biochemical studies into the underlying mechanism of age-related fiber degeneration. Over the last few years, mass spectrometry (MS)-based proteomics has identified a considerable number of new biomarkers of muscle aging in humans and animal models of sarcopenia. However, interpretation of the proteomic findings is often complicated by technical and biological limitations. Although gel electrophoresis-based approaches represent a highly sensitive analytical way for the large-scale and high-throughput survey of global changes in skeletal muscle proteins during aging, often the presence of components with an isoelectric point in the basic range is underestimated. We, therefore, carried out a comparative subproteomic study of young versus aged rat muscle focusing on potential changes in muscle proteins with an alkaline isoelectric point, using a combination of offgel electrophoresis and two-dimensional (2D) slab gel electrophoresis. Offgel electrophoresis was successfully applied as a prefractionation step to enrich basic protein species from crude tissue extracts representing young adult versus senescent muscle specimens. Proteomics has demonstrated alterations in a small cohort of basic proteins during muscle aging. The mass spectrometric identification of altered proteins and immunoblotting revealed a decrease in the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and a concomitant increase in mitochondrial creatine kinase (CK) and ubiquinol cytochrome‑c reductase. This agrees with the idea of a glycolytic-to-oxidative shift during muscle aging, which is indicative of an overall fast-to-slow transition process in senescent rat muscle. Thus, alterations in the abundance of metabolic enzymes appear to play a central role in the molecular pathogenesis of age‑dependent muscle wasting.
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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 | 0.001 | 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".