Back

Chiral Graphene Quantum Dots Enhanced Drug Loading into Exosomes

Zhang, Y.; Zhu, Y.; Kim, G.; Wang, C.; Zhu, R.; Lu, X.; Chang, H.-C.; Wang, Y.

2023-01-20 bioengineering
10.1101/2023.01.20.523510 bioRxiv
Show abstract

As nanoscale extracellular vesicles secreted by cells, exosomes have enormous potential as safe and effective vehicles to deliver drugs into lesion locations. Despite promising advances with exosome-based drug delivery systems, there are still challenges to drug loading into exosome, which hinder the clinical applications of exosomes. Herein, we report an exogenous drug-agnostic chiral graphene quantum dots (GQDs) exosome-loading platform, based on chirality matching with the exosome lipid bilayer. Both hydrophobic and hydrophilic chemical and biological drugs can be functionalized or adsorbed onto GQDs by {pi}-{pi} stacking and van der Waals interactions. By tuning the ligands and GQD size to optimize its chirality, we demonstrate drug loading efficiency of 66.3% and 64.1% for Doxorubicin and siRNA, which is significantly higher than other reported exosome loading techniques.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

1
Small
○ 78 papers in training set
Top 0.1%
7.6%
Similar papers in this journal
2
Advanced Functional Materials
○ 46 papers in training set
Top 0.2%
6.5%
Similar papers in this journal
3
Nano Letters
● 71 papers in training set
Top 0.2%
6.5%
Similar papers in this journal
4
ACS Nano
● 113 papers in training set
Top 0.3%
6.0%
Similar papers in this journal
5
Advanced Science
○ 286 papers in training set
Top 1%
5.3%
Similar papers in this journal
6
ACS Applied Bio Materials
● 24 papers in training set
Top 0.1%
5.0%
7
Nature Communications
○ 5641 papers in training set
Top 31%
4.2%
8
Angewandte Chemie International Edition
○ 93 papers in training set
Top 0.4%
3.3%
9
Journal of Controlled Release
○ 44 papers in training set
Top 0.3%
3.3%
10
ACS Applied Materials & Interfaces
● 39 papers in training set
Top 0.3%
3.1%
50% of probability mass above
11
Advanced Healthcare Materials
○ 85 papers in training set
Top 0.6%
3.1%
12
Science Advances
● 1243 papers in training set
Top 12%
3.1%
13
Nanoscale Advances
● 15 papers in training set
Top 0.1%
2.7%
14
Advanced Materials
○ 56 papers in training set
Top 0.5%
2.4%
15
Bioactive Materials
○ 20 papers in training set
Top 0.3%
2.0%
16
ACS Biomaterials Science & Engineering
● 37 papers in training set
Top 0.4%
2.0%
17
Nature Nanotechnology
○ 32 papers in training set
Top 0.4%
1.7%
18
Nanoscale
● 42 papers in training set
Top 0.4%
1.7%
19
Langmuir
● 36 papers in training set
Top 0.3%
1.7%
20
Analytical Chemistry
● 218 papers in training set
Top 2%
1.6%
21
Biomacromolecules
● 29 papers in training set
Top 0.3%
1.4%
22
ACS Sensors
● 49 papers in training set
Top 0.5%
1.3%
23
ChemBioChem
○ 55 papers in training set
Top 0.9%
1.1%
24
Chemical Communications
● 25 papers in training set
Top 0.5%
1.0%
25
Chemical Science
● 73 papers in training set
Top 2%
1.0%
26
Nature Chemistry
○ 42 papers in training set
Top 0.8%
1.0%
27
Journal of Colloid and Interface Science
○ 12 papers in training set
Top 0.2%
1.0%
28
Lab on a Chip
● 96 papers in training set
Top 0.9%
0.9%
29
Communications Chemistry
○ 48 papers in training set
Top 1%
0.9%
30
Journal of the American Chemical Society
● 217 papers in training set
Top 3%
0.8%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.