Biodegradable Polylactide Nanocapsules Containing Quercetin for In Vitro Suppression of Mouse B16F10 and Human Sk-Mel-28 Melanoma Cell Lines
Bibliographic record
Abstract
Background: Quercetin is a flavonoid found in various dietary sources. It is a prodrug converted by overexpressed tyrosinase in melanoma into an active o-quinone that suppresses tumour growth. However, injected quercetin is rapidly cleared from the tumour site. Method: Our study aimed to enhance quercetin’s efficacy through nanoencapsulation using biodegradable nanocapsules, which were tested in both mouse and human melanoma cell lines in 2D and 3D models. Results: Nanoencapsulation achieved sustained release and improved bioavailability. In mouse 2D cultures, quercetin nanocapsules (Q-nanos) reduced cell viability to 28%, compared with 46% for free quercetin (Q-only) (p < 0.05). In 3D cultures simulating in vivo conditions, Q-nanos reduced viability to 43%, showing significant anti-melanoma activity, while Q-only resulted in 72% viability (p > 0.05 vs. control). A similar trend was observed in human melanotic melanoma, where both Q-nanos and Q-only were effective compared with the controls, with Q-nanos demonstrating superior tumour inhibition (p < 0.05). Conclusions: These findings show the superior efficacy of nanoencapsulated quercetin over free quercetin. Nanoencapsulation prolonged quercetin’s bioavailability, enhanced tumour regression, and addressed limitations associated with the rapid clearance of free quercetin.
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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".