Anti‐inflammatory benefits of retinoids: retinoic acid and oxidatively‐transformed β‐carotene induce neutrophil apoptosis and inhibit leukotriene B <sup>4</sup> synthesis
Bibliographic record
Abstract
Clearance of apoptotic neutrophils following infection is critical for the resolution of inflammation. Little is known about the effects of retinoid products (vitamin A derivatives) in innate immune cells in the context of an inflammatory response. Hypothesis Retinoic acid (RA) or oxidatively‐transformed β‐carotene (OxβC), a retinoid derivative, may have immuno‐modulatory benefits by promoting neutrophil apoptosis and inhibiting proinflammatory signaling. Aim To evaluate the effects of RA and OxβC in model of Mannheimia haemolytica ‐induced bovine respiratory disease, a disease associated with severe inflammation. Results In vitro, RA and OxβC dose‐dependently induced apoptosis, but not necrosis, in circulating bovine neutrophils, but not in epithelial cells. In M. haemolytica‐ challenged calves (2×10 7 CFU), animals that received a 28‐day dietary OxβC treatment (10 mg/kg) had elevated apoptotic leukocytes and reduced LTB 4 levels in their lower airways 3 h post‐infection versus infected‐untreated calves. Conclusion RA and OxβC promote cell‐selective apoptosis and inhibit the synthesis of proinflammatory LTB 4 , which in turn may confer yet unrecognized anti‐inflammatory benefits. Supported by NSERC.
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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) | 0.002 | 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".