Stability of Self-Assembled Polymeric Micelles in Serum
Bibliographic record
Abstract
The stability of polymeric nanoparticles in serum is critical to their use in drug delivery where dilution after intravenous injection often results in nanoparticle disassembly and drug unloading; however, few investigate this in biologically relevant media. To gain greater insight into nanoparticle stability in blood, the stability of self-assembled polymeric micelles of poly(d,l-lactide-co-2-methyl-2-carboxytrimethylene carbonate)-g-poly(ethylene glycol), P(LA-co-TMCC)-g-PEG, were tested in both serum and individual serum protein solutions. By encapsulating Förster resonance energy transfer pairs and following their release by fluorescence, these micelles demonstrated excellent thermodynamic and kinetic stability in the presence of serum. Further analyses by fast protein liquid chromatography and dynamic light scattering confirmed these data. Moreover, these micelles are compatible with red blood cells, as shown by a hemolysis assay. The stability and compatibility demonstrated in blood suggest that these micelles may be stable in vivo, which is critical for intravenous drug delivery applications. This comprehensive approach to understanding micelle stability and compatibility is broadly applicable.
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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 | 0.001 |
| 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".