Evaluation of inflammatory responses induced via intra-articular injection of interleukin-1 in horses receiving a dietary nutraceutical and assessment of the clinical effects of long-term nutraceutical administration
Bibliographic record
Abstract
OBJECTIVE: To evaluate inflammatory responses induced via intra-articular recombinant human interleukin (IL)-1beta treatment in horses receiving a dietary nutraceutical (DN; composed of mussel, shark cartilage, abalone, and Biota orientalis lipid extract) and assess the clinical effects of long-term DN administration. ANIMALS: 22 healthy horses. PROCEDURES: 12 horses were fed 0, 15, 45, or 75 mg of DN (3 horses/treatment) daily for 84 days. General health and clinicopathologic variables were monitored at intervals. Ten other horses received 0 or 15 g of DN/d (5 horses/treatment) for 29 days (beginning day -14). One intercarpal joint in each horse was injected twice with IL-1beta (10 and 100 ng on days 0 and 1, respectively), and the contralateral joint was similarly injected with saline (0.9% NaCl) solution. Synovial fluid prostaglandin E(2) (PGE(2)), sulfated glycosaminoglycan (GAG), nitric oxide (NO), and protein concentrations and leukocyte counts were analyzed before and at intervals after injections. RESULTS: Administration of the DN (up to 75 g/d) to horses for 84 days did not induce any adverse effects. In the other experiment, synovial fluid PGE(2), GAG, and protein concentrations and leukocyte count increased after intra-articular injections of IL-1beta (compared with effects of saline solution injections) in horses that received no DN; NO concentration was not affected. In horses that were fed the DN, intra-articular IL-1beta injections did not induce significant increases in synovial fluid PGE(2) and GAG concentrations. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that administration of the DN may be useful in preventing inflammation associated with arthritis and degenerative joint disease in horses.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".