A stereospecific high‐performance liquid chromatographic assay for the determination of ketoconazole enantiomers in rat plasma
Bibliographic record
Abstract
A stereospecific high-performance liquid chromatographic assay was developed for the quantitation of ketoconazole enantiomers (KTZ) in rat plasma. After protein precipitation of 100 microL plasma using acetonitrile, a wash step was performed using hexane. The supernatant was removed and KTZ enantiomers and amiodarone, the internal standard, were extracted using liquid-liquid extraction with tert-butyl methyl ether. After transfer and evaporation of the organic layer, the residue was reconstituted in mobile phase and injected into the HPLC through a chiral column. The mobile phase consisted of hexane:ethanol:2-propanol with diethyl amine, pumped at 1.5 mL/min. All components eluted within 18 min. KTZ enantiomers were baseline resolved and peaks were symmetrical in appearance with no interferences. Calibration curves were linear over the range 62.5-5000 ng/mL of enantiomer. The intraday and interday CV% assessments were <or=19 and <13%, respectively, and mean error was <4% for both enantiomers. The lower limit of quantitation was 62.5 ng/mL for each enantiomer based on 100 microL rat plasma. In rats, plasma concentrations of (+)-KTZ were higher than those of antipode after single oral doses. The assay was shown to be sensitive and appropriate for use in pharmacokinetics study of KTZ in rat.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".