β-Carotene autoxidation: oxygen copolymerization, non-vitamin A products, and immunological activity
Bibliographic record
Abstract
Carotenoids are reported to have immunological effects independent of vitamin A activity. Although antioxidant activity has been suggested as a basis of action, the ability of carotenoids to autoxidize to numerous non-vitamin A products with immunological activity is an alternative yet to be fully explored. We have undertaken a systematic study of β-carotene autoxidation and tested the product mixture for immunological activity. Autoxidation proceeds predominantly by oxygen copolymerization, leading to a defined, reproducible product corresponding to net uptake of almost 8 molar equivalents of oxygen. The product, termed OxC-beta, empirical formula C40H60O15 versus C40H56 for β-carotene, contains more than 30% oxygen (w/w) and 85% β-carotene oxygen copolymers (w/w) as well as minor amounts of many C8−C18 norisoprenoid compounds. No vitamin A or higher molecular weight norisoprenoids are present. The predominance of polymeric products has not been reported previously. The polymer appears to be a less polymerized form of sporopollenin, a biopolymer found in exines of spores and pollen. Autoxidations of lycopene and canthaxanthin show a similar predominance of polymeric products. OxC-beta exhibits immunological activity in a PCR gene expression array, indicating that carotenoid oxidation produces non-vitamin A products with immunomodulatory potential.
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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".