Sustained, Strenuous Exercise in Sled Dogs Depresses Copper Enzyme Activities
Bibliographic record
Abstract
1744 Copper is an essential nutrient with multiple metalloenzyme functions that can impact exercise performance. Limited research shows mixed results as to whether strenuous exercise depletes body copper, but these studies have two limitations: one, some exercise durations tested may have been too short to pull copper from its tightly bound functional sites; two, the studies mostly measure fluid copper levels, not copper function as rejected by metalloenzyme activities. PURPOSE: To examine the response of three blood copper metalloenzyme activities to sustained, strenuous exercise in sled dogs. METHODS: Copper metalloenzyme activities were examined before and after a race lasting 12–15 days (Yukon Quest), and before and after a 3 day training run in preparation for the Iditarod race. Three copper enzyme activities were measured: plasma ceruloplasmin, plasma diamine oxidase, and erythrocyte superoxide dismutase, each of which is sensitive to moderate copper depletion. RESULTS: Ceruloplasmin activities were reduced by both the race and training run; erythrocyte superoxide dismutase activities were depressed by the race, but not the shorter training run; plasma diamine oxidase activities were depressed by training run (untested in the race). The depressions in enzyme activities were not the result of dilution effects, nor were the effects on ceruloplasmin and superoxide dismutase just a general depletion of antioxidant enzymes (activities of erythrocyte glutathione peroxidase, another antioxidant enzyme, were not changed by the runs). CONCLUSION: Sustained strenuous exercise in sled dogs depressed blood activities of three copper enzymes; possibly the depressions could have been prevented by increased copper intake, but for the training run, copper intake should have exceed normally adequate levels.
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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) | 0.001 | 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".