Miktoarm Star Micelles Containing Curcumin Reduce Cell Viability of Sensitized Glioblastoma
Bibliographic record
Abstract
Glioblastoma multiforme (GBM) is the most common and lethal primary intracranial tumor in humans. Monotherapeutic interventions have not been successful. The objective of the current studies was to establish the effective combination therapy consisting of pifitrin as a sensitizer, and curcumin as therapeutic incorporated into miktoarm micelles. A2B type miktoarm stars were prepared using a combination of click chemistry with ring opening polymerization on a core with orthogonal functionalities. These self-assemble into spherical micelles with hydrophobic core and hydrophilic corona structure. Micellar delivery systems for curcumin based on these miktoarm star polymers were prepared, characterized and tested on cultures sensitized with pifitrin. The results show that: (1) pifitrin and temozolamide in combination with curcumin cause significant cell death compared with the individual therapeutics (incorporated or not in micelles), and (2) repeated exposure to the same treatments is necessary to fully prevent a re-growth of glioblastoma cells both in 2D and 3D cultures. Although the incorporation of curcumin into A2B star polymer micelles did not increase the extent of cell death compared with curcumin alone, the advantage of micelles is that they significantly increase the aqueous solubility of curcumin and sustain its release; this will likely reduce the frequency of its administration required to be effective in vivo. A2B miktoarm polymers could be a new viable delivery system for curcumin and other anticancer drugs with similar limitations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".