Self-assembled supramolecular nanogels based on poly(vinyl alcohol) and gallic acid as nanocarriers for breast cancer treatment
Why this work is in the frame
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Bibliographic record
Abstract
A series of polyvinyl alcohol (PVA)-based materials cross-linked with varying amounts of gallic acid (GA) were synthesized using a simple one-pot methodology. Two protocols were developed to obtain microgels and nanogels, resulting in materials with sizes ranging from 800 to 1200 nm for microgels and from 180 to 400 nm for nanogels, the latter achieved through the incorporation of ultrasonication into the self-assembly process. The amount of GA was found to have a crucial role on the size of the micro/ nanogels, leading to particles of smaller size as the GA concentration increases for microgels, while quite the opposite trend was observed for nanogels. This behavior is attributed to the particle formation kinetics, leading to different structural arrangements. The different nano/microgels synthesized were characterized using DLS, TEM, FT-IR, and NMR. It was found that the synthesis performed under ultrasonication with 20 % GA gives rise to nanogels depicting the most favorable characteristics suitable for drug delivery applications, such as small sizes with a narrow distribution. Therefore, we used these nanogels as a prototype model for breast cancer treatment by encapsulating methylene blue (MB) and performing kinetics experiments of drug release at physiological (pH=7.4) and tumoral (pH=4.0) pH levels, along with cell viability and cytotoxicity assays. The selected NGs were found to be optimal nanocarriers for breast cancer treatment in vitro due to their suitable size [(173 ± 22) nm], excellent MB encapsulation efficiency (EE%) of up to 78 %, and controlled, pH-dependent release over time, with a higher release observed at pH 4. Furthermore, the MB-loaded system demonstrated enhanced drug efficacy and dark cytotoxicity against breast cancer cells in shorter periods.
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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 | 0.000 |
| 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 it