A bioavailable form of curcumin suppresses cationic host defence peptides cathelicidin and calprotectin in a murine model of collagen-induced arthritis
Bibliographic record
Abstract
Curcumin, a component of the South-Asian spice turmeric, elicits anti-inflammatory functions. We have previously demonstrated that a highly bioavailable formulation of cucurmin, Cureit/Acumin™ (CUR), can suppress disease onset and severity, in a collagen-induced arthritis (CIA) mouse model. In a previous study, we have also shown that the abundance of antimicrobial host defence peptides, specifically cathelicidin (CRAMP) and calprotectin (S100A8 and S100A9), is significantly increased in the joint tissues of CIA mice. Elevated levels of cathelicidin and calprotectin have been associated with the pathogenesis of rheumatoid arthritis. Therefore, in this study, we examined the effect CUR administration on the abundance of cathelicidin and calprotectin in the joints, in a CIA mouse model. Here, we demonstrate that daily oral administration of CUR significantly reduces the elevated levels of CRAMP and calprotectin to baseline in the joints of CIA mice. We also show a linear correlation between the abundance of these peptides in the joints with serum inflammatory cytokines TNFα, IFNγ, and MCP-1. Overall, our results suggest that oral administration of a bioavailable CUR can suppress cathelicidin and calprotectin in the joints and regulate both local (joints) and systemic (serum) inflammation, in inflammatory arthritis.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".