Analytical Method To Detect and Quantify Avocatin B in Hass Avocado Seed and Pulp Matter
Bibliographic record
Abstract
Avocatin B, an avocado-derived compound mixture, was demonstrated recently to possess potent anticancer activity by selectively targeting and eliminating leukemia stem cells. Avocatin B is a mixture of avocadene and avocadyne, two 17-carbon polyhydroxylated fatty alcohols (PFAs), first discovered in avocado seeds; their quantities in avocado pulp are unknown. Analytical methods to detect avocado seed PFAs have utilized NMR spectroscopy and GC-MS; both of these lack quantitative capacity and accuracy. Herein, we report a sensitive LC-MS method for the quantitation of avocadene and avocadyne in avocado seed and pulp. The method has a reliable and linear response range of 0.1–50 μM (0.03–17.2 ng/μL) for both avocadene and avocadyne ( r 2 > 0.990) with a lower limit of quantitation (LLOQ) of 0.1 μM. The intra- and interassay accuracy and precision of the quality control (QC) samples at LLOQ showed ≤18.2% percentage error and ≤14.4% coefficient of variation (CV). The intra- and interassay accuracy and precision for QC samples at low and high concentrations were well below 10% error and CV. This method was successfully applied to quantify avocadene and avocadyne in total lipid extracts of Hass avocado pulp and seed matter.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".