Microporous Structure and Drug Release Kinetics of Polymeric Nanoparticles
Bibliographic record
Abstract
The aim of the present study was to characterize pegylated nanoparticles (NPs) for their microporosity and study the effect of microporosity on drug release kinetics. Blank and drug-loaded NPs were prepared from three different pegylated polymers, namely, poly(ethylene glycol)1%-graft-poly(D,L)-lactide, poly(ethylene glycol)5%-graft-poly(D,L)-lactide, and the multiblock copolymer (poly(D,L)-lactide-block-poly(ethylene glycol)-block-poly(D,L)-lactide)n. These NPs were characterized for their microporosity using nitrogen adsorption isotherms. NPs of the multiblock copolymer showed the least microporosity and Brunauer-Emmett-Teller (BET) surface area, and that of PEG1%-g-PLA showed the maximum. Based on these results, the structural organization of poly(D,L)-lactide (PLA) and poly(ethylene glycol) (PEG) chains inside the NPs was proposed and was validated with differential scanning calorimetry (DSC) and X-ray photoelectron spectroscopy (XPS) surface analysis. An in vitro drug release study revealed that PEG1%-g-PLA NPs exhibited slower release despite their higher surface area and microporosity. This was attributed to the presence of increased microporosity forming tortuous internal structures, thereby hindering drug diffusion from the matrix. Thus, it was concluded that the microporous structure of NPs, which is affected by the molecular architecture of polymers, determines the release rate of the encapsulated drug.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".