Temperature Driven Annealing of Perforations in Bicellar Model Membranes
Bibliographic record
Abstract
Bicellar model membranes composed of 1,2-dimyristoylphosphatidylcholine (DMPC) and 1,2-dihexanoylphosphatidylcholine (DHPC), with a DMPC/DHPC molar ratio of 5, and doped with the negatively charged lipid 1,2-dimyristoylphosphatidylglycerol (DMPG), at DMPG/DMPC molar ratios of 0.02 or 0.1, were examined using small angle neutron scattering (SANS), (31)P NMR, and (1)H pulsed field gradient (PFG) diffusion NMR with the goal of understanding temperature effects on the DHPC-dependent perforations in these self-assembled membrane mimetics. Over the temperature range studied via SANS (300-330 K), these bicellar lipid mixtures exhibited a well-ordered lamellar phase. The interlamellar spacing d increased with increasing temperature, in direct contrast to the decrease in d observed upon increasing temperature with otherwise identical lipid mixtures lacking DHPC. (31)P NMR measurements on magnetically aligned bicellar mixtures of identical composition indicated a progressive migration of DHPC from regions of high curvature into planar regions with increasing temperature, and in accord with the "mixed bicelle model" (Triba, M. N.; Warschawski, D. E.; Devaux, P. E. Biophys. J.2005, 88, 1887-1901). Parallel PFG diffusion NMR measurements of transbilayer water diffusion, where the observed diffusion is dependent on the fractional surface area of lamellar perforations, showed that transbilayer water diffusion decreased with increasing temperature. A model is proposed consistent with the SANS, (31)P NMR, and PFG diffusion NMR data, wherein increasing temperature drives the progressive migration of DHPC out of high-curvature regions, consequently decreasing the fractional volume of lamellar perforations, so that water occupying these perforations redistributes into the interlamellar volume, thereby increasing the interlamellar spacing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".