Differential Scanning Calorimetry and Fourier Transform Infrared Spectroscopic Studies of Phospholipid Organization and Lipid−Peptide Interactions in Nanoporous Substrate-Supported Lipid Model Membranes
Bibliographic record
Abstract
High-sensitivity differential scanning calorimetry was utilized to examine whether lipids capable of forming an inverted nonlamellar hexagonal II (HII) phase can be deposited into nanoporous substrate-supported arrays. Particularly, we compare the thermotropic phase properties of nanoconfined unsaturated 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine lipid bilayers with unsupported dispersions to assess nanoconfinement effects, focusing on the lamellar fluid (Lalpha) to HII phase transition. Experimental results provide direct and clear evidence for the formation of an HII phase upon both heating and cooling. However, a small shift in the Lalpha/HII phase transition temperature, as well as an increase in the magnitude of the associated temperature hysteresis, was observed in the nanoporous substrate-supported system. Additionally, nanoconfinement effects on the interaction and location of the antimicrobial peptide gramicidin S (GS) with nanoporous substrate-supported cardiolipin bilayers were examined by Fourier transform infrared spectroscopy as a function of temperature and phospholipid phase state. Upon heating, GS molecules began to insert into nanoconfined, substrate-supported cardiolipin bilayers at lower temperatures relative to the gel/liquid-crystalline phase transition temperature than into unsupported bilayers. The reduction in the polarity and hydrogen-bonding potential environment of GS in the Lalpha state suggests that GS is located at the polar/apolar interfacial region in both supported and unsupported cardiolipin bilayers and that the capacity of GS to interact with nanoporous substrate-supported cardiolipin bilayers was not significantly hindered by nanoconfinement. These studies further demonstrate the usefulness of supported lipid bilayers inside nanoporous substrates.
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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".