Caffeic acid, chlorogenic acid, and dihydrocaffeic acid metabolism: glutathione conjugate formation.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The antioxidant properties of the dietary dihydroxycinnamic acids [caffeic (CA), dihydrocaffeic (DHCA), and chlorogenic (CGA) acids] have been well studied but little is known about their metabolism. In this article, evidence is presented showing that CA, DHCA, and CGA form quinoids and hydroxylated products when oxidized by peroxidase/H(2)O(2) or tyrosinase/O(2). Mass spectrometry analyses of the metabolites formed with peroxidase/H(2)O(2)/glutathione (GSH) revealed that mono- and bi-glutathione conjugates were formed for all three compounds except CGA, which formed a bi-glutathione conjugate only when GSH was present. In contrast, the metabolism of the dihydroxycinnamic acids by tyrosinase/O(2)/GSH resulted in the formation of only mono-glutathione conjugates. In the absence of GSH, hydroxylated products and p-quinones of CA or CGA were formed by peroxidase/H(2)O(2). DHCA formed a hydroxylated adduct (even though GSH was present), as well as the corresponding p-quinone and dihydroesculetin, an intramolecular cyclization product. NADPH also supported rat liver microsomal-catalyzed CA-, CGA-, and DHCA-glutathione conjugate formation, which was prevented by benzylimidazole, a cytochrome P450 inhibitor. Furthermore, the cytotoxicity of CA, CGA, and DHCA toward isolated rat hepatocytes was markedly enhanced by hydrogen peroxide or cumene hydroperoxide-supported cytochrome P450 and was prevented by benzylimidazole. Cytotoxicity was also markedly enhanced by dicumarol, an NADPH/oxidoreductase inhibitor. These results suggest that dihydroxycinnamic acids were metabolically activated by P450 peroxidase activity to form cytotoxic quinoid metabolites.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it