Biophysical analysis of gelatin and PLGA nanoparticle interactions with complex biomimetic lung surfactant models
Bibliographic record
Abstract
Biocompatible materials are increasingly used for pulmonary drug delivery, and it is essential to understand their potential impact on the respiratory system, notably their effect on lung surfactant, a monolayer of lipids and proteins, responsible for preventing alveolar collapse during breathing cycles. We have developed a complex mimic of lung surfactant composed of eight lipids mixed in ratios reported for native lung surfactant. A synthetic peptide based on surfactant protein B was added to better mimic the biological system. This model was used to evaluate the impact of biocompatible gelatin and poly(lactic-co-glycolic acid) nanoparticles. Surface pressure-area isotherms were used to assess lipid packing, film compressibility and stability, whereas the lateral organization was visualized by Brewster angle microscopy. Nanoparticles increased film fluidity and altered the monolayer collapse pressure. Bright protruding clusters formed in their presence indicate a significant impact on the lateral organization of the surfactant film. Altogether, this work indicates that biocompatible materials considered to be safe for drug delivery still need to be assessed for their potential detrimental impact before use in therapeutic applications.
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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) | 0.001 | 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".