Photo-cross-linked and pH-Sensitive Biodegradable Micelles for Doxorubicin Delivery
Bibliographic record
Abstract
Cross-linked polymeric micelles have gained increasing research interest in the past decade due to the instability of existing polymeric micelles when used in vivo. In this study, we reported a series of covalently cross-linked pH-sensitive biodegradable micelles based on the poly(ethylene glycol)-hyperbranched poly(β-aminoester)s with acrylate group terminals (PEG-HBPAE-A) copolymers for intracellular delivery of doxorubicin (DOX). PEG-HBPAE-A can be self-assembled to form micellar nanoparticles in aqueous solution with diameters of approximately 160 nm. The non-cross-linked micelles (NCLMs) were cross-linked upon UV irradiation to form cross-linked micelles (CLMs). (1)H NMR, FT-IR and dynamic light scattering (DLS) were utilized to investigate the process of the UV cross-linking and the stability of CLMs. The results showed the significantly enhanced stability for CLMs in comparison to NCLMs. pH sensitivity of CLMs and NCLMs were also estimated by DLS. In vitro drug release studies confirmed that DOX release from DOX-loaded CLMs was greatly inhibited upon the neutral pH environment, whereas DOX underwent faster release in acidic conditions. MTT assays showed that DOX-loaded micelles had a similar inhibition rate for HepG-2 and MCF-7 cell lines compared with free DOX, whereas the blank CLMs and NCLMs showed very low cytotoxicity. Laser scanning confocal microscopy and real-time in situ fluorescence microscopy were exploited to investigate drug uptake in cells and drug distribution in the interior of cells. These results showed a promising nanocarrier for intracellular DOX delivery with great potential for cancer therapy.
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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".