Probing Chitosan and Phospholipid Interactions Using Langmuir and Langmuir−Blodgett Films as Cell Membrane Models
Bibliographic record
Abstract
The interaction between chitosan and Langmuir and Langmuir-Blodgett (LB) films of dimyristoyl phosphatidic acid (DMPA) is investigated, with the films serving as simplified cell membrane models. At the air-water interface, chitosan modulates the structural properties of DMPA monolayers, causing expansion and decreasing the monolayer elasticity. As the surface pressure increased, some chitosan molecules remained at the interface, but others were expelled. Chitosan could be transferred onto solid supports alongside DMPA using the LB technique, as confirmed by infrared spectroscopy and quartz crystal microbalance measurements. The analysis of sum-frequency vibration spectroscopy data for the LB films combined with surface potential measurements for the monolayers pointed to chitosan inducing the ordering of the DMPA alkyl chains. Furthermore, the morphology of DMPA LB films, studied with atomic force microscopy, was affected significantly by the incorporation of chitosan, with the mixed chitosan-DMPA films displaying considerably higher thickness and roughness, in addition to chitosan aggregates. Because chitosan affected DMPA films even at pressures characteristic of cell membranes, we believe this study may help elucidate the role of chitosan in biological systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".