Morphology-Induced Defects Enhance Lipid Transfer Rates
Bibliographic record
Abstract
Molecular transfer between nanoparticles has been considered to have important implications regarding nanoparticle stability. Recently, the interparticle spontaneous lipid transfer rate constant for discoidal bicelles was found to be very different from spherical, unilamellar vesicles (ULVs). Here, we investigate the mechanism responsible for this discrepancy. Analysis of the data indicates that lipid transfer is entropically favorable, but enthalpically unfavorable with an activation energy that is independent of bicelle size and long- to short-chain lipid molar ratio. Moreover, molecular dynamics simulations reveal a lower lipid dissociation energy cost in the vicinity of interfaces ("defects") induced by the segregation of the long- and short-chain lipids in bicelles; these defects are not present in ULVs. Taken together, these results suggest that the enhanced lipid transfer observed in bicelles arises from interfacial defects as a result of the hydrophobic mismatch between the long- and short-chain lipid species. Finally, the observed lipid transfer rate is found to be independent of nanoparticle stability.
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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) | 0.000 | 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".