Simultaneous Determination of Levocetirizine and Pseudoephedrine in Dog Plasma by Liquid Chromatography-Mass Spectrometry in the Presence of Dextrocetirizine
Bibliographic record
Abstract
PURPOSE: This study describes the development of a rapid and sensitive LC-ESI-MS assay for simultaneous enantioselective determination of levocetirizine and pseudoephedrine in dog plasma in the presence of dextrocetirizine. METHODS: Separations were achieved on an Ultron ES-OVM chiral column using the mobile phase consisting of 10 mM aqueous NH4OAc (pH 6.6) and acetonitrile (9:1 v/v). RESULTS: The retention times of pseudoephedrine, dextrocetirizine, levocetirizine and diazepam (internal standard) were 5.2, 8.3, 9.6 and 11.6 min, respectively, and the total run time was less than 15 min. The assay was validated to demonstrate the linearity, accuracy and precision, recovery and stability. The calibration curves were linear over the concentration range from 1 - 200 ng/mL for levocetirizine and from 5 - 1000 ng/mL for pseudoephedrine. CONCLUSIONS: The developed assay was successfully applied to a pharmacokinetic study after oral administration of the racemic cetirizine (0.5 mg/kg, or 0.25 mg/kg as levocetirizine) and pseudoephedrine (12 mg/kg) in the dog. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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) | 0.000 | 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 | 0.001 | 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 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".