Mutual effects between aromatic amino acids and guanosine upon vitamin B2 photosensitization in the presence of visible light
Bibliographic record
Abstract
Considering the importance of the visible-light-induced photodynamic effect in complex bioenvironments, mutual effects between the individual aromatic amino acids (AAs) tyrosine (Tyr), tryptophan (Trp), and histidine (His) and the nucleoside guanosine (GUO) were investigated in pH 7 aqueous solution with vitamin B2 (riboflavin (Rf)) as a dye sensitizer. The quantum yields of oxygen uptake (Φ–O2) for most of the AA−GUO mixtures studied, taken as a measure of overall photooxidation susceptibility, are not straightforwardly predictable from the individual behaviour of the components of the mixture. The final result depends on several connected factors, such as the respective abilities of the substrates as quenchers of the long-lived Rf triplet excited state and the generated reactive oxygen species singlet molecular oxygen (O2(1Δg)) and superoxide radical anion ([Formula: see text]). A mechanistic interpretation of the Rf-sensitized results can be roughly resumed as follows: Tyr at pH 7 exerts a protective effect on the photooxidation of the mixture Tyr−GUO due to the O2(1Δg) physical quenching by the AA. The same effect was observed for Trp−GUO and His−GUO at pH 7. In these cases, it is attributed to the quenching of 3Rf* by GUO in detriment of the Type II route. For the system Tyr−GUO at pH 9, a marked decrease in the Φ–O2 occurred for the mixture as compared with the respective Φ–O2 for the individual components. It was ascribed to the participation of a radical-mediated mechanism without oxygen consumption in a competitive pathway with the [Formula: see text]-mediated route.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".