Study of pH-Sensitive Copolymer/Phospholipid Complexes Using the Langmuir Balance Technique: Effect of Anchoring Sequence and Copolymer Molecular Weight
Bibliographic record
Abstract
The behavior of three copolymers of N-isopropylacrylamide (NIPAM), methacrylic acid (MAA), and hydrophobic moiety was studied at phospholipid monolayer/subphase interfaces. The hydrophobic moieties, N-terminal dioctadecylamine (DODA) and random octadecylacrylate (ODA), were used as anchoring groups. The interactions between a 1,2-distearoyl-sn-glycero-3-phosphatidylcholine (DSPC) monolayer and the copolymers were studied using the Langmuir balance technique. The effect of subphase pH, distribution of anchors along the copolymer chain, and copolymer molecular weight on the nature of the interactions between the copolymer chains and the DSPC monolayer were investigated. A first-order kinetics model was used to analyze the copolymers adsorption at the DSPC monolayer/subphase interface and allowed the interaction area between the copolymer chains and the DSPC monolayer, A(x), to be determined. The interaction area appears to depend on the subphase pH and the copolymer molecular weight. On decreasing pH, the interaction area of high molecular weight copolymers increases significantly; this is consistent with the copolymer chain phase transition from an extended coil to a collapsed globule while pH is lowered. In the latter conformation, strong hydrophobic attractive interactions between the copolymer chains and the hydrophobic part of the DSPC monolayer favor the copolymer intercalation, which could eventually provoke the phospholipidic layer destabilization or rupture.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".