Effect of the Polymer Architecture on the Structural and Biophysical Properties of PEG–PLA Nanoparticles
Bibliographic record
Abstract
Polymers made of poly(ethylene glycol) chains grafted to poly(lactic acid) chains (PEG-g-PLA) were used to produce stealth drug nanocarriers. A library of comblike PEG-g-PLA polymers with different PEG grafting densities was prepared in order to obtain nanocarriers with dense PEG brushes at their surface, stability in suspension, and resistance to protein adsorption. The structural properties of nanoparticles (NPs) produced from these polymers by a surfactant-free method were assessed by dynamic light scattering, ζ potential, and transmission electron microscopy and found to be controlled by the amount of PEG present in the polymers. A critical transition from a solid NP structure to a soft particle with either a "micellelike" or a "polymer nanoaggregate" structure was observed when the PEG content was between 15 and 25% w/w. This structural transition was found to have a profound impact on the size of the NPs, their surface charge, their stability in suspension in the presence of salts, and the binding of proteins to the surface of the NPs. The arrangement of the PEG-g-PLA chains at the surface of the NPs was investigated by (1)H NMR and X-ray photoelectron spectroscopy (XPS). NMR results confirmed that the PEG chains were mostly segregated at the NP surface. Moreover, XPS and quantitative NMR allowed quantification of the PEG chain coverage density at the surface of the solid NPs. Concordance of the results between the two methods was found to be remarkable. Physical-chemical properties of the NPs such as resistance to aggregation in a saline environment as well as antifouling efficacy were related to the PEG surface density and ultimately to the polymer architecture. Resistance to protein adsorption was assessed by isothermal titration calorimetry using lysozyme. The results indicate a correlation between the PEG surface coverage and level of protein interactions. The results obtained lead us to propose such PEG-g-PLA polymers for nanomedicine development as an alternative to the predominant polyester-PEG diblock polymers.
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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 | 0.001 | 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 | 0.001 |
| 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".