The UVA and Aqueous Stability of Flavonoids Is Dependent on B-Ring Substitution
Bibliographic record
Abstract
Flavonols such as kaempferol and quercetin are believed to provide protection against ultraviolet (UV)-induced damage to plants. Recent in vitro studies have examined the ability of flavonols to protect against UV-induced damage to mammalian cells. Stability of flavonols in cell culture media, however, has been problematic, especially for quercetin, one of the most widely studied flavonols. As part of our investigations into the potential for flavonols to protect skin against UV-induced damage, we have determined the stability of a series of flavonols that differ only in the number of substituents on the B-ring. We measured the stability of these flavonols over time to UVA radiation, Dulbecco's modified Eagle's medium (DMEM), and Dulbecco's phosphate-buffered saline (DPBS) using high performance liquid chromatography with UV detection (HPLC-UV). The identification of the breakdown products of flavonols was accomplished by using a hybrid quadrupole linear ion trap mass spectrometer coupled with liquid chromatography. Tandem mass spectrometric analysis (MS/MS) of flavonol photoproducts was confirmed by comparing with the known standard samples. We have determined that flavonol stability decreases with increasing B-ring substitution, suggesting that future investigation of potential photoprotective flavonols will need to be cognizant of this trend.
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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 | 0.001 |
| 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".