Properties of Liposomes Containing Natural and Synthetic Lipids Formed by Microfluidic Mixing
Bibliographic record
Abstract
Vesicle formation by a staggered herringbone microfluidic mixer is investigated in comparison to a sonication‐extrusion method. Experiments focused on the incorporation efficiency of lipid components, on dye entrapment efficiency, and on the barrier properties of the vesicle bilayers produced. The microfluidic method produces vesicles largely under the control of thermodynamic factors. As a result, the molecular parameters of the lipids (chain length, chain volume, head group area) directly control vesicle diameter. A hydrophobic branched chain sulfonate lipid is incorporated by microfluidic mixing but not by sonication‐extrusion. The vesicles produced by microfluidic mixing can be used to study ion transport by known ionophores and appear to have directly comparable barrier properties to those produced by sonication‐extrusion. Vesicles containing the branched chain sulfonate are highly permeable. The microfluidic mixing method produces predominantly unilamellar vesicles. Practical Applications : The microfluidic device examined offers a new method to reproducibly produce vesicles that are directly controlled by the molecular components of the lipid mixture. The authors show that this method produces vesicles that are equivalent to currently used methods in the study of synthetic ion channels and carriers. Looking forward, thermodynamically controlled self‐assembly will find application in the creation of new membrane systems and assemblies where the vesicles themselves are the building blocks in more extensive structures, and the active components in inter‐vesicle functions. A staggered herringbone microfluidic mixer reproducibly gives size‐controlled unilamellar vesicles having low‐permeability bilayer membranes.
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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 | 0.001 | 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 | 0.002 |
| 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".