Recent advances in stimuli-responsive degradable block copolymer micelles: synthesis and controlled drug delivery applications
Bibliographic record
Abstract
(Bio)degradation in response to external stimuli (stimuli-responsive degradation, SRD) is a desired property in constructing novel nanostructured materials. For polymer-based multifunctional drug delivery applications, the degradation enables fast and controlled release of encapsulated therapeutic drugs from delivery vehicles in targeted cells. It also ensures the clearance of the empty device after drugs are delivered to the body. This review summarizes recent development of various strategies to the design and synthesis of self-assembled micellar aggregates based on novel amphiphilic block copolymers having different numbers of stimuli-responsive cleavable elements at various locations. These cleavable linkages including disulfide, acid-labile, and photo-cleavable linkages are incorporated into micelles, and then are cleaved in response to cellular triggers such as reductive reaction, light, and low acid. The well-designed SRD micelles have been explored as controlled/enhanced delivery vehicles of drugs and genes. For future design and development of effective stimuli-responsive degradable micelles toward tumor-targeting delivery applications in vivo, a high degree of control over degradation for tunable release of encapsulated anticancer drugs as well as bioconjugation for active tumor-targeting is required.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".