Gait, skin and coat, and plasma cytokine changes in response to exercise and trace mineral source
Bibliographic record
Abstract
This study explored whether trace mineral source (Zn, Mn, Cu, Fe, and Se) in a complete and balanced diet impacts gait and inflammation in Labrador Retrievers undergoing a 9-wk exercise regimen. Forty healthy, adult dogs, averaging 3 yr of age, were assigned to diets containing ether inorganic minerals (ING, n = 20) or amino acid complexed minerals (TMC, n = 20). After a 2-wk dietary acclimation, dogs began a progressively demanding exercise regimen, ending with an 8 km run. Fecal scores and food intake were recorded daily, while body weights and body condition scores were recorded weekly. Skin and coat condition were assessed at baseline, mid-study, and study end. Mobility and pain were evaluated before and after the first and last run using the Liverpool Osteoarthritis in Dogs (LOAD) and Canine Brief Pain Inventory (CBPI) questionnaires. Gait was assessed using the Gait4Dogs walkway system and the FRK Total Gait Inflammation Index Score. Both groups experienced a slight reduction in body weights (P < 0.01) and body condition scores (P < 0.01), likely due to the added energy expenditure of exercise. Skin and coat condition did not differ between the diets (P ≤ 0.15). The LOAD questionnaire tended to reveal perceptions of improved mobility after exercise (P ≤ 0.07), and a perceived improvement in the quality of life for TMC dogs after the final run was detected by the CBPI questionnaire (P < 0.01). Gait analysis revealed better left:right (L:R) symmetry ratios for step time (P = 0.01) in TMC fed dogs. Dogs from ING group had better cycle time L:R ratio (P = 0.03), though ratios for both groups were extremely close to 1:1. A treatment × time interaction for mean pressure L:R ratio revealed TMC dogs had a better ratio after the final run compared to ING dogs (P = 0.02), suggesting differences in how the two mineral sources influenced gait dynamics during the exercise regimen. Blood samples collected at 1, 6, and 24 h after the first and last runs revealed changes in several cytokines and chemokines, but only monocyte chemoattractant protein-1 (MCP-1) was influenced by a treatment × time interaction (P < 0.01). Circulating MCP-1 increased after the final exercise in dogs fed TMC but not in those fed ING. Overall, the results suggest that amino acid complexed minerals may offer advantages in perceived mobility, some gait parameters, and inflammatory responses during a sustained exercise regimen compared to inorganic minerals.
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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".