Photooxidations Initiated or Sensitized by Biological Molecules: Singlet Oxygen Versus Radical Peroxidation in Micelles and Human Blood Plasma ¶
Bibliographic record
Abstract
Biomolecules common in blood plasma, including 2-methyl-1,4-naphthoquinone (vitamin K-0, 2), 2,3-dimethoxy-5-methyl-1,4-benzoquinone (ubiquinone-0, 3), bilirubin, 4, and urocanic acid, 5, were used as photoactivators for the photooxidation of methyl linoleate (ML) in 0.50 M sodium dodecyl sulfate micelles to mimic a bioenvironment. UV irradiation of 2 in this system initiated H-atom abstraction from ML (Type-I mechanism). The evidence includes kinetics of oxygen uptake, inhibition of oxidation by an antioxidant ((R)-(+)-6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid [Trolox], 7) and the analysis of four geometric hydroperoxides formed (cis, trans to trans, trans ratio of 0.5). In contrast, irradiation with a singlet-oxygen sensitizer, 3,5-di-t-butyl-1,2-benzoquinone, 1, formed six isomers by a Type-II mechanism, yielding a cis, trans to trans, trans isomer ratio of 6. Peroxidation activated by 3 or 4 with visible light occurred by a singlet-oxygen pathway (Type-II mechanism), as shown by kinetics of oxygen uptake and the effect of quenchers. In contrast, peroxidation in the presence of 5 in this system initiated H-atom abstraction from ML as shown by oxygen uptake and inhibition by Trolox. A comparison of thermal free-radical peroxidation with direct photooxidation of human blood plasma samples showed important differences. Blood plasma resisted thermal peroxidation because of natural antioxidants or on the addition of Trolox. In contrast, direct photooxidation involved singlet oxygen, according to the effect of quenchers and the lack of inhibition by antioxidants.
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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 | 0.001 | 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".