Tailoring the Lamellarity of Liposomes Prepared by Dual Centrifugation
Bibliographic record
Abstract
Dual centrifugation (DC) is a new and versatile technique for the preparation of liposomes by in-vial homogenization of lipid-water mixtures. Size, size distribution, and entrapping efficiencies are strongly dependent on the lipid concentration during DC-homogenization. In this study, we investigated the detailed structure of DC-made liposomes. To do so, an assay to determine the ratio of inner to total membrane surfaces of liposomes (inaccessible surface) was developed based on either time-resolved or steady-state fluorescence spectroscopy. In addition, cryogenic electron microscopy (cryo-EM) was used to confirm the lamellarity results and learn more about liposome morphology. One striking result leads to the possibility of producing a novel type of liposome-small multilamellar vesicles (SMVs) with low PDI, sizes of the order of 100 nm, and almost completely filled with bilayers. A second particularly important finding is that VPGs can be prepared to contain open bilayer structures that will close spontaneously when, after storage, more aqueous phase is added and liposomes are formed. Through this process, a drug can effectively be entrapped immediately before application. In addition, dual centrifugation at lower lipid concentrations is found to produce predominantly unilamellar vesicles.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".