A liquid chromatography–mass spectrometry assay method for simultaneous determination of amiodarone and desethylamiodarone in rat specimens
Bibliographic record
Abstract
A liquid chromatographic-mass spectrometry (LC/MS) assay method was developed for the determination of amiodarone and desethylamiodarone in rat specimens. Analytes were extracted using liquid-liquid extraction in hexane. The LC/MS system consisted of a Waters Micromass ZQtrade mark 4000 spectrometer with an autosampler and pump. A C(18) 3.5 microm (2.1 x 50 mm) column heated to 45 degrees C was used for separation. The mobile phase consisted of methanol and 0.2% aqueous formic acid pumped at 0.2 mL/min as a linear gradient. Components eluted within 12 min. The concentrations of ethopropazine (internal standard), desethylamiodarone and amiodarone were monitored for m/z of 313.10, combination of 546.9 and 617.73, and 645.83, respectively. In plasma (0.1 mL), linearity was achieved between the peak area ratios and concentrations over the range of 2.5-1000 ng/mL for both amiodarone and desethylamiodarone (r(2) > 0.999). The intraday and interday CV were equal or less than 18%, and mean error was <12%. Similarly, in homogenates containing 0.1 g of rat tissue, linearity was observed in standards ranging from 5 to 5000 ng/g. The method was successfully used to measure tissue and plasma concentrations of drug. The validated lower limit of quantitation was 2.5 ng/mL for drug and metabolite, based on 0.1 mL of plasma.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".