Applications of nanoparticle drug delivery systems for the reversal of multidrug resistance in cancer
Bibliographic record
Abstract
Multidrug resistance (MDR) to chemotherapy presents a major obstacle in the treatment of cancer patients, which directly affects the clinical success rate of cancer therapy. Current research aims to improve the efficiency of chemotherapy, whilst reducing toxicity to prolong the lives of cancer patients. As with good biocompatibility, high stability and drug release targeting properties, nanodrug delivery systems alter the mechanism by which drugs function to reverse MDR, via passive or active targeting, increasing drug accumulation in the tumor tissue or reducing drug elimination. Given the potential role of nanodrug delivery systems used in multidrug resistance, the present study summarizes the current knowledge on the properties of liposomes, lipid nanoparticles, polymeric micelles and mesoporous silica nanoparticles, together with their underlying mechanisms. The current review aims to provide a reliable basis and useful information for the development of new treatment strategies of multidrug resistance reversal using nanodrug delivery systems.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".