Extrusion of small vesicles through nanochannels: A model for experiments and molecular dynamics simulations
Bibliographic record
Abstract
We propose a model that predicts the final sizes of lipid bilayer vesicles produced by pressure extrusion through nanochannels and we conduct large-scale coarse-grained molecular dynamics simulations of the phenomenon. We show that, to a first approximation independent of pressure, vesicle size can be predicted by a simple geometrical argument that considers an invariable inner vesicle volume enclosed by a finitely extensible lipid bilayer. The pressure dependence is then incorporated in our model by arguing that the effective channel radius decreases with increasing pressure due to a thickening of the lubrication layer between the vesicles and the channel wall. We fit our model to the experimental data of Patty and Frisken [Biophys. J. 85, 996 (2003)]. We predict that at high pressure, vesicle size significantly depends on channel length and, therefore, flow rate. The CGMD simulations reproduce the physical principles of the model. They also show the build-up of the stress in the vesicle, and typical rupture scenarios as the pressure gradient is increased.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".