Quantitative determination of LY‐404,039, a metabotropic glutamate 2/3 receptor agonist, in rat plasma using chemical derivatization and HPLC–MRM/MS
Bibliographic record
Abstract
A rapid, selective and sensitive method was developed and validated for the determination of LY-404,039 concentration in rat plasma using a butylation derivatization step to improve chromatographic characteristics and enhance signal intensity. The method consisted of a protein precipitation extraction followed by derivatization with butanol/HCl and analysis by high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS). The separation was achieved using a 100 × 2.1 mm (2.6 μm) Thermo Scientific Accucore RP-MS column combined with an isocratic mobile phase composed of 40:60 acetonitrile-0.1% formic acid in water. An analytical range of 2.0-1,000 ng/ml was validated and used to quantify LY-404,039 in rat plasma. The novel method met all of the requirements of specificity, sensitivity, linearity, precision, accuracy and stability. A pharmacokinetic study was performed in rats and the novel analytical method was used as a routine analysis method to provide enhanced measurements of plasma concentrations of LY-404,039. The plasma pharmacokinetic results indicate very short terminal half-life (0.27 h ± 0.8) and high clearance (0.97 L/h/kg ± 0.12), suggesting that LY-404,039 is rapidly eliminated in the rat. Dose-dependent pharmacokinetics were observed following subcutaneous administration of LY-404,039 at doses of 0.1, 0.3 and 1.0 mg/kg.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".