Synthesis of a Labeled RGD−Lipid, Its Incorporation into Liposomal Nanoparticles, and Their Trafficking in Cultured Endothelial Cells
Bibliographic record
Abstract
The use of targeting ligands to enhance the delivery of liposomal nanoparticles (LNs) has moved slowly toward clinical application. This relative lack of clinical progression is further complicated by the existence of conflicting in vivo results in the literature. In this work, we describe new formulations of LNs that are targeted with an arginine-glycine-aspartic acid-containing peptide, cRGDfK, conjugated to the lipid distearoyl phosphatidylethanolamine (DSPE). These formulations may be able to circumvent some of the challenges encountered during the development of targeted-LNs. Of the constructs studied, a fluorescently labeled peptide-lipid conjugate was incorporated into LNs with high yield and accuracy. It is shown that the resulting targeted-LNs bind to human umbilical vein endothelial cells (HUVECs) with increasing avidity as the amount of peptide displayed on the LN surface increases. We specifically demonstrate the ability of targeted-LNs loaded with doxorubicin and incubated with HUVECs to deliver the drug to the cytosol. The cell does not internalize nontargeted LNs, supporting the notion that the RGD motif is associated with internalization of the targeted LN.
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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".