Assessment of protein synthesis in highly aerobic canine species at the onset and during exercise training
Bibliographic record
Abstract
Canis lupus familiaris, the domesticated dog, is capable of extreme endurance performance. The ability to perform sustained aerobic exercise is dependent on a well-developed mitochondrial reticulum. In this study we examined the cumulative muscle protein and DNA synthesis in groups of athletic dogs at the onset of an exercise training program and following a strenuous exercise training program. We hypothesized that both at the onset and during an exercise training program there would be greater mitochondrial protein synthesis rates compared with sedentary control with no difference in mixed or cytoplasmic protein synthesis rates. Protein synthetic rates of three protein fractions and DNA synthesis were determined over 1 wk using (2)H2O in competitive Alaskan Huskies and Labrador Retrievers trained for explosive device detection. Both groups of dogs had very high rates of skeletal muscle protein synthesis in the sedentary state [Alaskan Huskies: Mixed = 2.28 ± 0.12, cytoplasmic (Cyto) = 2.91 ± 0.10, and mitochondrial (Mito) = 2.62 ± 0.07; Labrador Retrievers: Mixed = 3.88 ± 0.37, Cyto = 3.85 ± 0.06, and Mito = 2.92 ± 0.20%/day]. Mitochondrial (Mito) protein synthesis rates did not increase at the onset of an exercise training program. Exercise-trained dogs maintained Mito protein synthesis during exercise training when mixed (Mixed) and cytosolic (Cyto) fractions decreased, and this coincided with a decrease in p-RpS6 but also a decrease in p-ACC signaling. Contrary to our hypothesis, canines did not have large increases in mitochondrial protein synthesis at the onset or during an exercise training program. However, dogs have a high rate of protein synthesis compared with humans that perhaps does not necessitate an extra increase in protein synthesis at the onset of aerobic exercise training.
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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 | 0.000 |
| 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) | 0.001 | 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".