Gelatin-Oxidized Alginate and Chitosan-Coated Zein Nanoparticle Hydrogel Composite to Enhance Breast Cancer Cytotoxicity in Dual-Drug Delivery
Bibliographic record
Abstract
This study explores the combined delivery of doxorubicin and quercetin using a gelatin-oxidized alginate-based hydrogel as a promising strategy for localized breast cancer therapy. Our approach involves the incorporation of doxorubicin within the hydrogel matrix and loading quercetin into chitosan-coated zein nanoparticles. The hydrogel exhibited self-healing properties attributed to Schiff base cross-linking and demonstrated injectability. Characterization of its microstructural, mechanical, and textural properties revealed a porous and flexible structure, demonstrating its suitability for drug release applications. Both drugs exhibited distinct in vitro release profiles at pH 6.8 (typical of tumor tissue), with doxorubicin at 81.2% and quercetin at 9.7%. After 72 h of release, the cytotoxicity against MCF-7 breast cancer cells was assessed. The hydrogel formulation containing doxorubicin increased the cytotoxic action by 4.66-fold, whereas the hydrogel composite, containing both doxorubicin and quercetin-loaded nanoparticles, enhanced it by 20.7-fold compared with doxorubicin alone. Thus, the findings of our study highlight the enhancing effect of the dual release system, thereby expanding the utility of gelatin-oxidized alginate-based hydrogels as advanced drug delivery systems, as exemplified by the combined delivery of doxorubicin and 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".