α-amyrin-loaded nanocapsules produce selective cytotoxic activity in leukemic cells
Bibliographic record
Abstract
INTRODUCTION: Amyrins are triterpenes that have attractive pharmacological potential; however, their low water solubility and erratic stomach absorption hinders their use as a drug. The aim of this paper was to develop a novel α-amyrin-loaded nanocapsule for intestinal delivery and evaluate, preliminarily, its cytotoxic ability against leukemic cells. MATERIAL AND METHODS: Five nanocapsule formulations were designed by the solvent displacement-evaporation method. Poly-ε-caprolactone, Eudragit® E100, and Kollicoat® Mae 100 P were used as film-former materials. Particle size, polydispersity index (PdI), zeta potential, and the pH of all formulations were measured. The cytotoxic potential of the nanocapsules was evaluated in vitro using different leukemic lineages RESULTS: Nanocapsules coated with Kollicoat® Mae 100 P presented the smallest particle size (130 nm), the lowest zeta-potential (-38 mV), and the narrowest size distribution (PdI = 0.100). The entrapment efficiency was 65.47%, while the loading capacity was 2.40%. Nanocapsules release 100% of α-amyrin in 40 min (pH 7.4), by using a possible mechanism of swelling-diffusion. The formulation showed excellent on-shelf physicochemical stability during one year. Additionally, nanocapsules produced a selective cytotoxic effect on a human leukemia lineage Kasumi-1, an acute myeloid leukemia cell line, and produced cell death by apoptosis CONCLUSION: α-amyrin-loaded nanocapsules appear to be a promising nanoformulation that could be used against leukemia.
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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".