Long term exercise training exacerbates sarcopenia and only modestly attenuates apopotosis
Bibliographic record
Abstract
Apoptosis has been implicated in the age‐related loss of muscle known as sarcopenia. In addition, exercise training attenuates some markers of apoptosis. The purpose of this study was to evaluate the impact of a treadmill exercise training program initiated in late middle aged (LMA) rats and continued for 7 mo until senescence (SEN) (a period that spans a dramatic acceleration of muscle mass and functional decline) on gastrocnemius muscle (Gas) mass and markers of apoptosis. 62 male rats were randomly assigned to a training group (T) or sedentary group (S). Contrary to our expectation, following the 7 mo period the Gas mass was lower in T (890 ±60 mg) than C (1143 ± 85 mg; P<0.05). In situ immunolabeling experiments revealed that despite the fact that the loss of fast twitch fibers was markedly lower in T with aging, there was no difference between T and C in the fraction of nuclei that were TUNEL positive (3.0±0.5% vs 2.4±0.4%), or in the number of 8‐hydroxy guanosine positive spots per 100 fibers (1.3±0.3 vs 2.3±0.7). On the other hand, the fraction of fibers positive for activated caspase 3 was less in T (1.0±0.6%) vs C (2.3±0.5%; P<0.05). These results show that exercise training, although protecting fast twitch fibers with aging, had very modest impact on markers of apoptosis activation in Gas muscle of SEN rats. Supported by CIHR & AHFMR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".