Terpolymer Micelles for the Delivery of Arsenic to Breast Cancer Cells: The Effect of Chain Sequence on Polymeric Micellar Characteristics and Cancer Cell Uptake
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide In this study, we developed a micellar platform composed of terpolymers for the encapsulation of inorganic arsenite or arsenous acid (As III ). For this purpose, a series of terpolymers composed of poly(ethylene oxide) (PEO, block A ), poly(α-carboxylate-ε-carprolactone) (PCCL, block B ), and poly(ε-caprolactone) (PCL, block C ) with either a blocked, i.e., BC or CB, or random, i.e., (B/C) ran block copolymer sequence in the polyester segment was synthesized. The COOH groups on block B were further modified with mercaptohexylamine for As III encapsulation. We then investigated how sequence of terpolymers can affect the stability and surface charge of micelles as well as the cellular uptake of their cargo, i.e., As III, by MDA-MB-435 cancer cells. 1 H NMR spectroscopy in D 2 O and CDCl 3 was also used to study the structure of different terpolymer micelles. Our results showed micelles with ABC sequence to have better stability over those of ACB and A(B/C) ran as reflected by a lower critical micellar concentration. The As III -loaded ABC micelles were less negatively charged on the surface than the other two types of terpolymer micelles. In line with this observation, ABC micelles showed a substantially enhanced uptake of As III by MDA-MB-435 cancer cells. Stability and surface charge are key parameters that can influence the performance of polymeric micelles as nanodrug carriers. Based on these results, we suggest ABC micelles to have improved characteristics for As III delivery compared to ACB and A(B/C) ran micelles.
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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 | 0.001 | 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".