Generating Giant Membrane Vesicles from Live Cells with Preserved Cellular Properties.
Clicks: 402
ID: 55850
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
402 views
47 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #3 of 9 articles by views in research (washington, dc)
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Biomimetic giant membrane vesicles, with size and lipid compositions comparable to cells, have been recognized as an attractive experimental alternative to living systems. Due to the similarity of their membrane structure to that of body cells, cell-derived giant plasma membrane vesicles have been used as a membrane model for studying lipid/protein behavior of plasma membranes. However, further application of biomimetic giant membrane vesicles has been hampered by the side-effects of chemical vesiculants and the utilization of osmotic buffer. We herein develop a facile strategy to derive giant membrane vesicles (GMVs) from mammalian cells in biofriendly medium with high yields. These GMVs preserve membrane properties and adaptability for surface modification and encapsulation of exogenous molecules, which would facilitate their potential biological applications. Moreover, by loading GMVs with therapeutic drugs, GMVs could be employed for drug transport to tumor cells, which represents another step forward in the biomedical application of giant membrane vesicles. This study highlights biocompatible GMVs with biomimicking membrane surface properties and adaptability as an ideal platform for drug delivery strategies with potential clinical applications.
| Reference Key |
liu2019generatingresearch
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Liu, Qiaoling;Bi, Cheng;Li, Jiangling;Liu, Xuejiao;Peng, Ruizi;Jin, Cheng;Sun, Yang;Lyu, Yifan;Liu, Hui;Wang, Huijing;Luo, Can;Tan, Weihong; |
| Journal | research (washington, dc) |
| Year | 2019 |
| DOI |
10.34133/2019/6523970
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.