Avocado-derived polyols for use as novel co-surfactants in low energy self-emulsifying microemulsions
Bibliographic record
Abstract
Avocado (Persea americana Mill.; Lauraceae) seed-derived polyhydroxylated fatty alcohols (PFAs) or polyols (i.e., avocadene and avocadyne) are metabolic modulators that selectively induce apoptosis of leukemia stem cells and reverse pathologies associated with diet-induced obesity. Delivery systems containing avocado polyols have not been described. Herein, natural surface active properties of these polyols are characterized and incorporated into self-emulsifying drug delivery systems (SEDDS) that rely on molecular self-assembly to form fine, transparent, oil-in-water (O/W) microemulsions as small as 20 nanometers in diameter. Mechanistically, a 1:1 molar ratio of avocadene and avocadyne (i.e., avocatin B or AVO was shown to be a eutectic mixture which can be employed as a novel, bioactive, co-surfactant that significantly reduces droplet size of medium-chain triglyceride O/W emulsions stabilized with polysorbate 80. In vitro cytotoxicity of avocado polyol-SEDDS in acute myeloid leukemia cell lines indicated significant increases in potency and bioactivity compared to conventional cell culture delivery systems. A pilot pharmacokinetic evaluation of AVO SEDDS in C57BL/6J mice revealed appreciable accumulation in whole blood and biodistribution in key target tissues. Lastly, incorporation of AVO in SEDDS significantly improved encapsulation of the poorly water-soluble drugs naproxen and curcumin.
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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 | 0.000 | 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 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".