Serum metabolomics of Alaskan sled dogs during endurance racing
Bibliographic record
Abstract
Long distance racing sled dogs are fed diets high in fat since lipid metabolism has long been thought to be the major substrate utilised during endurance racing. However, recent studies suggests that sled dogs are equally, if not more, dependent on carbohydrate metabolism. Considering the metabolic disparity regarding the energetics of endurance exercise, our study aimed to explore the serum metabolomic profiles of sled dogs running a 1,609 km (1000 mile) race. We hypothesised that there would be amino acid depletion due to gluconeogenesis and alteration in the citric acid cycle (CAC) based on the limited carbohydrate diet they consume. Serum was obtained from 6 Alaskan sled dogs approximately 24 h prior to the race (Whitehorse), at the midrace checkpoint (Dawson City), and again at the finish (Fairbanks). Serum was analysed using liquid chromatography-mass spectrometry for over 200 metabolites involved in amino acid, lipid, and carbohydrate metabolism with MetaboAnalyst Software 3.0. Major metabolic changes observed were decreased free fatty acids and enhanced acyl-carnitine derivatives during the race compared to baseline. Serum depletion of nearly all amino acids except for branched chain amino acids and phenylalanine was observed suggesting extensive protein catabolism. Many of the CAC intermediates were variable with increases in abnormal end glycation products. These results highlight that sled dogs display general amino acid depletion for pyruvate, acetyl CoA and CAC pathway intermediates with increased carnitine bound lipid metabolites, suggesting rate limiting beta-oxidation during endurance exercise, particularly at mid race. Further metabolomic studies to assess the influence of exercise and nutritional regimens are warranted to better understand substrate utilisation in working dogs.
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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 | 0.000 | 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 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".