Preparation of liposomes using supercritical carbon dioxide technology: Effects of phospholipids and sterols
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Liposomes were prepared utilizing a supercritical carbon dioxide (SC-CO 2 ) process. A phospholipid suspension was first equilibrated with CO 2 at 300 bar and then depressurized at a constant pressure and rate. The effects of phospholipid concentration, phospholipid type, sterol concentration and sterol type on particle size, uniformity, zeta potential and morphology were investigated. With increasing soy lecithin concentration (5–30 mM) at 50 °C, the smallest particle size of liposomes (146.1 ± 0.8 nm) was obtained at 30 mM with the polydispersity index (PdI) of 0.398 ± 0.008. Increased phospholipid concentration was favorable for the formation of smaller size vesicles with higher uniformity. Longer chain length of fatty acids in pure phospholipids resulted in a larger particle size with more spherical shape while a phospholipid with unsaturated fatty acyl chains resulted in increased asymmetry. With elevated β-sitosterol concentration (10%–50%), particle size and PdI increased to 245.5 ± 7.14 nm and 0.514 ± 0.018, respectively, with decreased absolute zeta potential . 6-Ketocholestanol showed the smallest diameter and PdI of liposomes with the most spherical shape among all sterol types tested. Soy lecithin exhibited the highest stability of vesicular systems due to its highest absolute zeta potential (− 58.3 ± 2.17 mV) among all the phospholipid types. The SC-CO 2 method demonstrated superior characteristics of liposomes over traditional thin film hydration method for a smaller size and PdI as well as enhanced intactness without leakage. It might offer a promising way to reduce usage of sterol in liposome formulations while eliminating organic solvent usage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it