Partitioning of ethanol into lipid membranes and its effect on fluidity and permeability as seen by X-ray and neutron scattering
Bibliographic record
Abstract
We present a combined neutron and X-ray scattering investigation to study the effect of ethanol on the molecular structure and dynamics of lipid membranes. 1,2-Dimyristoyl-sn-glycero-3-phoshatidylcholine (DMPC) powder hydrated with a 5 wt% ethanol solution (corresponding to 2 mol% of ethanol) was used in this study. From high-resolution X-ray experiments the position and partitioning of the ethanol molecules in the phospholipid bilayers was determined in their gel and fluid phases. We find that the ethanol molecules reside in the head group region of the bilayers, with 1.6 ethanol molecules per lipid molecule in the gel phase and 1.2 ethanol molecules per lipid molecule in the fluid phase. We find evidence for enhanced permeability in both fluid and gel phases of the phospholipid bilayers in the presence of ethanol molecules. Elastic and quasi-elastic neutron scattering data, obtained using a neutron backscattering spectrometer, was used to study slow, nanosecond molecular dynamics on length scales corresponding to lipid diffusion, acyl chain dynamics and solvent dynamics. While the presence of ethanol molecules had no observable effect on these types of dynamics in the fluid (Lα) phase, the membranes appeared to have a higher degree of order in gel (Lβ) and ripple (Pβ′) phases. In particular, lipid diffusion was found to be slower by a factor of two in the more rigid gel phase when ethanol was present.
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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".