The Effect of Different Lipid Components on the In Vitro Stability and Release Kinetics of Liposome Formulations
Bibliographic record
Abstract
Liposomes are colloidal carriers that form when certain (phospho)lipid molecules are hydrated in an aqueous media with some energy input. The ideal liposome formulation with optimum stability will improve drug delivery by decreasing the required dose and increasing the efficacy of the entrapped drug at the target organ or tissue. The most important parameter of interest in this article was to compare the efficacy of three different liposomes formulated with DSPC, DMPC, and DPPC, all saturated neutral phospholipids with different acyl chain lengths and transition temperatures. DMPC has a phase transition temperature (Tc) below 37 degrees C, whereas the other two phospholipids possess Tcs above the physiological temperature. These lipids were then added to a cholesterol concentration of 21% to optimize the stability of the vesicles. The liposomes were prepared by a sonication and incubated in phosphate buffered saline (PBS) at 4 degrees C and 37 degrees C. The encapsulation efficiency, initial size, and drug retention of the vesicles were tested over a 48-hr period employing radiolabeled inulin as a model drug. The phase transition temperature of liposomes, which depends on the Tc of the constituent lipids, was an important factor in liposome stability. Of all the liposomes tested, the greatest encapsulation efficiency was found for the DSPC liposomes (2.95%) that also had the greatest drug retention over 48 hr at both 4 degrees C (87.1 +/- 6.8%) and 37 degrees C (85.2 +/- 10.1%), none of these values being significantly different from time zero. The lowest drug retention was found for DMPC liposomes for which a significant difference in drug retention was seen after only 15 min at both 4 degrees C (47.3 +/- 6.9%) and 37 degrees C (53.8 +/- 4.3%). The DPPC liposomes showed a significant difference in drug retention after 3 hr at 4 degrees C (62.1 +/- 8.2%) and after 24 hr at 37 degrees C (60.8 +/- 8.9%). Following the initial drop at certain time intervals a plateau was reached for all of the liposome formulations after which no significant difference in drug retention was observed. In conclusion, liposomes with higher transition temperatures appear to be more stable in PBS either at 4 degrees C or 37 degrees C, indicating that the increase in acyl chain length (and therefore transition temperature) is directly proportional to 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".