Determination of (-)-epigallocatechin-3-gallate octaacetate and its metabolites in plasma of rats for pharmacokinetic study by ultra-performance-liquid-chromatography coupled to quadrupole-time-of-flight-mass-spectrometry
Bibliographic record
Abstract
(-)-Epigallocatechin-gallate octaacetate (pro-EGCG), a prodrug of epigallocatechin-gallate (EGCG), has been used for pre-clinical study for the treatment of endometriosis. A validated analytical method has been developed for the determination of plasma pro-EGCG and its metabolites after oral administration using ultra-performance-liquid-chromatography coupled to quadrupole-time-of-flight-mass-spectrometry (UPLC-Qtof-MS). This method is more robust, rapid, sensitive, simpler, and able to detect pro-EGCG metabolites compared to our previous method. Pro-EGCG in the plasma was stabilized from rapid degradation by formic acid, extracted by isopropanol/methyl-tert-butyl ether mixture, separated by UPLC core column, and quantified by an exact mass method with Qtof-MS. The lower limit of quantification (LLOQ), intra-day and inter-day precision, and accuracy for the range of 0.01–2.5 μg/mL were within acceptable limits. The sensitivity was improved by 25 folds using pro-EGCG ammonium adduct [M + NH4]+. This is the first report on the pharmacokinetics of oral administration with maximum-concentration (Cmax) was 0.067 ± 0.04 μg/mL, time-of-maximum-concentration (Tmax) was 1.33 h, area-under-curve (AUC) was 0.20 ± 0.05 h × µg/mL, and elimination-rate was 0.20 ± 0.11 hr−1. The pharmacokinetic profiles of pro-EGCG metabolites, (-)-epigallocatechin-gallate (EGCG) diacetates and EGCG triacetates, were also presented. This method is robust, rapid, and sensitive for the pharmacokinetic study of pro-EGCG and metabolites.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".