Quantitative determination of capsaicin, a transient receptor potential channel vanilloid 1 agonist, by liquid chromatography quadrupole ion trap mass spectrometry: evaluation of <i>in vitro</i> metabolic stability
Bibliographic record
Abstract
Capsaicin is the most abundant pungent molecule present in red peppers and it is widely used for food flavoring, in pepper spray in self-defense devices and more recently in ointments for the relief of neuropathic pain. Capsaicin is a selective agonist of transient receptor potential channel, vanilloid subfamily member 1. A selective and sensitive quantitative method for the determination of capsaicin by LC-ESI/MS/MS was developed. The method consisted of a protein precipitation extraction followed by analysis using liquid chromatography electrospray quadrupole ion trap mass spectrometry. The chromatographic separation was achieved using a 100 x 2 mm C(18) Waters Symmetry column combined with a gradient mobile phase composed of acetonitrile and 0.1% formic acid aqueous solution at a flow rate of 220 microL/min. The mass spectrometer was operating in full-scan MS/MS mode using two-segment analysis. An analytical range of 10-5000 ng/mL was used in the calibration curve constructed in rat plasma. The interbatch precision and accuracy observed were 6.5, 6.7, 5.3 and 101.2, 102.7, 103.5% at 50, 500 and 5000 ng/mL, respectively. An in vitro metabolic stability study was performed in rat, dog and mouse liver microsomes and the novel analytical method was adapted and used to determine intrinsic clearance of capsaicin. Results suggest very rapid degradation with T(1/2) ranging from 2.3 to 4.1 min and high clearance values suggesting that drug bioavailability will be considerably reduced, consequently affecting drug response and efficacy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".