Disposition, Metabolism and Histone Deacetylase and Acetyltransferase Inhibition Activity of Tetrahydrocurcumin and Other Curcuminoids
Bibliographic record
Abstract
). Curcuminoids have been established to have a variety of pharmacological activities and are used as natural health supplements. The purpose of this study was to identify the metabolism, excretion, antioxidant, anti-inflammatory and anticancer properties of these curcuminoids and to determine disposition of THC in rats after oral administration. We developed a UHPLC-MS/MS assay for THC in rat serum and urine. THC shows multiple redistribution phases with corresponding increases in urinary excretion rate. In-vitro antioxidant activity, histone deacetylase (HDAC) activity, histone acetyltransferase (HAT) activity and anti-inflammatory inhibitory activity were examined using commercial assay kits. Anticancer activity was determined in Sup-T1 lymphoma cells. Our results indicate THC was poorly absorbed after oral administration and primarily excreted via non-renal routes. All curcuminoids exhibited multiple pharmacological effects in vitro, including potent antioxidant activity as well as inhibition of CYP2C9, CYP3A4 and lipoxygenase activity without affecting the release of TNF-α. Unlike curcumin and calebin-A, THC did not inhibit HDAC1 and PCAF and displayed a weaker growth inhibition activity against Sup-T1 cells. We show evidence for the first time that curcumin and calebin-A inhibit HAT and PCAF, possibly through a Michael-addition mechanism.
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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".