Mechanism of sensitization of MDR cancer cells by Pluronic block copolymers: Selective energy depletion
Bibliographic record
Abstract
This paper, for the first time, demonstrates that exposure of cells to the poly(ethylene oxide)-poly(propylene oxide) block copolymer, Pluronic P85, results in a substantial decrease in ATP levels selectively in MDR cells. Cells expressing high levels of functional P-glycoprotein (MCF-7/ADR, KBv; LLC-MDR1; Caco-2, bovine brain microvessel endothelial cells [BBMECs]) are highly responsive to Pluronic treatment, while cells with low levels of P-glycoprotein expression (MCF-7, KB, LLC-PK1, human umbilical vein endothelial cells [HUVECs] C2C12 myoblasts) are much less responsive to such treatment. Cytotoxicity studies suggest that Pluronic acts as a chemosensitizer and potentiates cytotoxic effects of doxorubicin in MDR cells. The ability of Pluronic to inhibit P-glycoprotein and sensitize MDR cells appears to be a result of ATP depletion. Because many mechanisms of drug resistance are energy dependent, a successful strategy for treating MDR cancer could be based on selective energy depletion in MDR cells. Therefore, the finding of the energy-depleting effects of Pluronic P85, in combination with its sensitization effects is of considerable theoretical and practical significance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".