Poly(Ethylene Glycol)–Polylactide Micelles for Cancer Therapy
Bibliographic record
Abstract
For the treatment of malignancy, many therapeutic agents, including small molecules, photosensitizers, immunomodulators, proteins and genes, and so forth, have been loaded into nanocarriers for controllable cancer therapy. Among these nanocarriers, polymeric micelles have been considered as one of the most promising nanocarriers, some of which have already been applied in different stages of clinical trials. The successful advantages of polymeric micelles from bench to bedside are due to their special core/shell structures, which can carry specific drugs in certain disease conditions. Particularly, poly(ethylene glycol)-polylactide (PEG-PLA) micelles have been considered as one of the most promising platforms for drug delivery. The PEG shell effectively prevents the adsorption of proteins and phagocytes, thereby evidently extending the blood circulation period. Meanwhile, the hydrophobic PLA core can effectively encapsulate many therapeutic agents. This review summarizes recent advances in PEG-PLA micelles for the treatment of malignancy. In addition, future perspectives for the development of PEG-PLA micelles as drug delivery systems are also presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".