Pluronic-based micelle encapsulation potentiates myricetin-induced cytotoxicity in human glioblastoma cells
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
As one of the natural herbal flavonoids, myricetin has attracted much research interest, mainly owing to its remarkable anticancer properties and negligible side effects. It holds great potential to be developed as an ideal anticancer drug through improving its bioavailability. This study was performed to investigate the effects of Pluronic-based micelle encapsulation on myricetin-induced cytotoxicity and the mechanisms underlying its anticancer properties in human glioblastoma cells. Cell viability was assessed using a methylthiazol tetrazolium assay and a real-time cell analyzer. Immunoblotting and quantitative reverse transcriptase polymerase chain reaction techniques were used for determining the expression levels of related molecules in protein and mRNA. The results indicated that myricetin-induced cytotoxicity was highly potentiated by the encapsulation of myricetin. Mitochondrial apoptotic pathway was demonstrated to be involved in myricetin-induced glioblastoma cell death. The epidermal growth factor receptor (EGFR)/PI3K/Akt pathway located in the plasma membrane and cytosol and the RAS-ERK pathway located in mitochondria served as upstream and downstream targets, respectively, in myricetin-induced apoptosis. MiR-21 inhibitors interrupted the expression of EGFR, p-Akt, and K-Ras in the same fashion as myricetin-loaded mixed micelles (MYR-MCs) and miR-21 expression were dose-dependently inhibited by MYR-MCs, indicating the interaction of miR-21 with MYR-MCs. This study provided evidence supportive of further development of MYR-MC formulation for preferentially targeting mitochondria of glioblastoma cells.
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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) | 0.000 | 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 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".