Development and Characterization of Liposomal Disodium Ascorbyl Phytostanyl Phosphates (FM‐VP4)
Bibliographic record
Abstract
The specific objectives of this project were (1) to develop liposomal disodium ascorbyl phytostanyl phosphate (FM-VP4) formulations, (2) to develop a liquid chromatography/mass spectrometry/mass spectrometry (LC/MS/MS) assay for quantification of FM-VP4 in liposomal formulations and plasma sample, and (3) to characterize liposomal FM-VP4 formulations by finding optimal drug-to-lipid ratios and determining the degradation of FM-VP4 in liposomes. Section 2 describes an LC/MS/MS assay developed for the identification and quantification of FM-VP4 in liposomal formulations to provide estimates of drug concentrations and encapsulation efficiency. The extra step of removing plasma proteins prior to LC/MS/MS assay yields an analysis of FM-VP4 in plasma samples. Section 3 describes experiments designed to find the optimal drug-to-lipid ratio for liposomal FM-VP4 formulations by comparing encapsulation efficiencies and varying the lipid compositions. Additionally, this section details our degradation studies to determine if liposomes have any protective effects on FM-VP4; these studies tested various lipid compositions at 37 degrees C in rabbit plasma. The mechanism of how FM-VP4 lowers low-density lipoprotein (LDL) cholesterol and total cholesterol levels in various animal models is presently unknown. However, before the mechanism of action could be studied, FM-VP4 first had to be delivered efficiently into plasma or cultured cell. The low systemic bioavailability and cellular uptake of FM-VP4 further suggested the importance of finding an efficient delivery vehicle for this drug. This project proposed a framework for such delivery and paves the way for further investigation into how FM-VP4 works in vivo and in vitro.
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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 | 0.000 | 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 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".