Development of a sensitive and specific liquid chromatography/mass spectrometry method for the quantification of cucurbitacin I (JSI-124) in rat plasma.
Bibliographic record
Abstract
PURPOSE: To develop a liquid chromatography/mass spectrometry (LC-MS) method for the quantitative analysis of cucurbitacin I (JSI-124), an anti-cancer inhibitor of the janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling pathway, in rat plasma samples. METHODS: Standard samples of cucurbitacin I were prepared from a stock solution (1 mg/mL) in methanol. Internal standard (I.S.) was 4-hydroxybenzophenone. Extraction of cucurbitacin I and I.S. from rat plasma was performed using acetonitrile/dichloromethane. LC-MS analyses were performed using a Waters Micromass ZQ 4000 spectrometer, and chromatographic separation was achieved using a Waters XTerraMSC18 3.5 microm (2.1 x 50 mm) column as the stationary phase. The mobile phase consisting of a mixture of acetonitrile: water containing 1% formic acid with initial ratio of 20:80, employing a linear gradient to a final ratio of 40:60 v/v over 13 minutes, was delivered at a constant flow rate of 0.2 mL/min. The mass spectrometer was operated in negative ionization mode and analytes were quantified with single ion recording (SIR) at m/z 559 for cucurbitacin I and m/z 196.8 for I.S. RESULTS: Calibration curves with r2 > 0.999 were constructed over the concentration range of 5-10000 ng/mL for the solution of cucurbitacin I in methanol and 10-1000 ng/mL for rat plasma samples. The extraction recoveries were 86 and 98% for 50 ng/mL and 1000 ng/mL plasma concentration of cucurbitacin I, respectively. The intra- and inter-day coefficients of variation were less than 15%, and mean intraday errors were less than 10% at plasma concentration extending from 10-1000 ng/mL. CONCLUSION: The developed assay is sensitive, specific, reproducible and reliable for quantitative analysis of cucurbitacin I. Application in a pharmacokinetic assessment was proven in the rats given the drug.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 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".