Back

Design, Synthesis, and Biological Evaluation of Novel Mitochondria-targeting Exosomes

Yan, X.; Chen, X.; Shan, Z.; Bi, L.

2023-07-04 neuroscience
10.1101/2023.07.04.547719 bioRxiv
Show abstract

Mitochondrial dysfunction is implicated in both brain tumors and neurodegenerative diseases, leading to various cellular abnormalities that can promote tumor growth and resistance to thera-pies, as well as impaired energy production and compromised neuronal function. Developing targeted therapies aimed at restoring mitochondrial function and improving overall cellular health could potentially be a promising approach to treating these conditions. Brain-derived exosomes (BR-EVs) have emerged as potential drug delivery vessels for neurological conditions. Herein, we report a new method for creating mitochondria-targeting exosomes and test its application in vitro and in vivo.

Matching journals

The top 13 journals account for 50% of the predicted probability mass.

1
ACS Chemical Neuroscience
● 67 papers in training set
Top 0.1%
9.1%
Similar papers in this journal
2
Advanced Healthcare Materials
○ 85 papers in training set
Top 0.3%
5.6%
Similar papers in this journal
3
ACS Omega
● 105 papers in training set
Top 0.3%
4.4%
Similar papers in this journal
4
Journal of Extracellular Vesicles
○ 55 papers in training set
Top 0.2%
4.1%
Similar papers in this journal
5
Scientific Reports
○ 3612 papers in training set
Top 24%
4.1%
Similar papers in this journal
6
Small
○ 78 papers in training set
Top 0.4%
3.5%
7
ACS Biomaterials Science & Engineering
● 37 papers in training set
Top 0.2%
3.5%
8
Journal of Controlled Release
○ 44 papers in training set
Top 0.3%
3.5%
9
International Journal of Molecular Sciences
○ 494 papers in training set
Top 3%
3.3%
10
eLife
● 5828 papers in training set
Top 39%
2.7%
11
Bioactive Materials
○ 20 papers in training set
Top 0.2%
2.2%
12
Advanced Therapeutics
○ 17 papers in training set
Top 0.1%
2.2%
13
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 23%
2.2%
50% of probability mass above
14
PLOS ONE
● 5266 papers in training set
Top 42%
2.2%
15
Analytical Chemistry
● 218 papers in training set
Top 1%
2.2%
16
RSC Advances
● 22 papers in training set
Top 0.3%
1.9%
17
iScience
○ 1154 papers in training set
Top 16%
1.8%
18
Advanced Science
○ 286 papers in training set
Top 4%
1.8%
19
Science Advances
● 1243 papers in training set
Top 19%
1.8%
20
ACS Applied Bio Materials
● 24 papers in training set
Top 0.3%
1.8%
21
Nature Communications
○ 5641 papers in training set
Top 46%
1.5%
22
Cells
○ 249 papers in training set
Top 3%
1.5%
23
Biochemical and Biophysical Research Communications
○ 84 papers in training set
Top 1%
1.5%
24
Molecular Neurobiology
○ 53 papers in training set
Top 0.9%
1.1%
25
Chemical Communications
● 25 papers in training set
Top 0.4%
1.1%
26
Fluids and Barriers of the CNS
○ 28 papers in training set
Top 0.4%
1.1%
27
Molecular Therapy
○ 81 papers in training set
Top 2%
0.9%
28
Biomaterials Science
● 24 papers in training set
Top 0.6%
0.9%
29
ACS Nano
● 113 papers in training set
Top 2%
0.9%
30
Communications Biology
○ 993 papers in training set
Top 33%
0.6%

"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.