Serum myoglobin, creatine kinase, and cell‐free DNA in endurance sled dogs and sled dogs with clinical rhabdomyolysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether cell-free DNA (cfDNA) concentrations are increased in dogs with exertional rhabdomyolysis and whether concentrations are correlated with serum myoglobin concentration and creatine kinase activity. DESIGN: Observational cohort study. SETTING: Yukon Quest 1,000-mile International Sled Dog Race 2015. ANIMALS: Twelve normal competitive sled dogs; 5 dogs with rhabdomyolysis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Blood was collected from all confirmed cases of exertional rhabdomyolysis and compared to the winning team at the midrace point. Results indicate that median cfDNA did not increase, but decreased by the race finish (prerace = 314.2 ng/mL versus midrace = 283.7 ng/mL versus postrace = 249.5 ng/mL). There were no rises in median cfDNA in dogs with rhabdomyolysis (255 ng/mL) negating its potential utility as a measure of acute skeletal muscle compromise. In contrast, myoglobin concentration and creatine kinase activity at the midrace point for normal dogs were significantly lower than dogs with rhabdomyolysis. Values for myoglobin and creatine kinase were strongly positively correlated (R = 0.91). CONCLUSIONS: cfDNA is not a useful biomarker for exertional rhabdomyolysis in contrast to myoglobin and creatine kinase. Further evaluation of timing and clinical signs suggests that exertional rhabdomyolysis occurs early in endurance activities. Among the dogs with rhabdomyolysis, the dog that demonstrated clinical signs had the highest serum creatine kinase activity and myoglobin concentration.
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 | 0.001 |
| 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 | 0.001 |
| 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".