Analysis of Lidocaine and Its Major Metabolite, Monoethylglycinexylidide, in Elk Velvet Antler by Liquid Chromatography with UV Detection and Confirmation by Electrospray Ionization Tandem Mass Spectrometry
Bibliographic record
Abstract
A sensitive liquid chromatographic (LC) method with UV detection was developed for the determination of residues of lidocaine (LID) and its major metabolite, monoethylglycinexylidide (MEGX), in elk velvet antler. The drugs were extracted from alkaline velvet antler homogenates, cleaned up on a C(18) solid-phase extraction cartridge, and separated on an Inertsil ODS-3 (3.0 x 250 mm, 5 microm) column using an isocratic mobile phase made up of 0.05 M phosphate buffer (pH 4.0)/acetonitrile (88:12, v/v) at a flow rate of 1.0 mL/min. The limits of quantification for LID and its major metabolite, MEGX, were 10 and 20 ng/g, respectively. The method was validated and used to measure the concentration of residues of LID and MEGX in elk velvet antlers harvested after either LID anesthesia or application of a drug-free control method (electro-anesthesia, EA). No LID or MEGX residues were detected in any of the antlers harvested after EA application. No MEGX residues were detected in any of the velvet antlers harvested after LID application, but residues of LID ranging in concentration from 68 to 4300 ng/g were detected in the three sections of the velvet antlers harvested after LID administration. LC-tandem mass spectrometry was used to confirm the presence of lidocaine detected in the velvet antlers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".