Back

Multiparametric Characterization of Individual Suspended Nanoparticles using Confocal Fluorescence and Interferometric Scattering Microscopy with Microfluidic Confinement

Boateng, E.; Olsen, E.; Kamanzi, A.; Zhang, Y.; Zhao, B.; Cullis, P.; Leslie, S.

2025-07-31 biophysics
10.1101/2025.07.25.666405 bioRxiv
Show abstract

Detailed characterization of the size, mass, payload, and structure of suspended mRNA-lipid nanoparticles (LNPs) is necessary to improve our understanding of how these heterogenous properties influence therapeutic efficacy and potency. Methods currently in use face limitations in reporting ensemble-average particle properties or requiring dedicated home-built microscopes that are beyond the reach of nanoparticle developers. In this work, we overcome these limitations by combining a commercially available confocal microscope and a convex lens-induced confinement (CLiC) instrument to achieve simultaneous characterization and correlation of the size, mass, refractive index, and nucleic acid payload of individual LNPs. We established the accuracy and precision of our method using nanosized beads and used it to investigate the size, payload, and water content of LNPs in different solvent pH. By employing readily available microscopy tools, we open the door to widespread adoption of our quantitative, in-solution nanoparticle characterization method.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

1
Small
○ 78 papers in training set
Top 0.1%
9.5%
Similar papers in this journal
2
ACS Nano
● 113 papers in training set
Top 0.3%
6.1%
Similar papers in this journal
3
Advanced Functional Materials
○ 46 papers in training set
Top 0.3%
4.2%
Similar papers in this journal
4
Analytical Chemistry
● 218 papers in training set
Top 0.9%
3.9%
Similar papers in this journal
5
ACS Applied Materials & Interfaces
● 39 papers in training set
Top 0.2%
3.9%
6
Langmuir
● 36 papers in training set
Top 0.1%
3.9%
Similar papers in this journal
7
Nature Communications
○ 5641 papers in training set
Top 34%
3.4%
8
Nanoscale
● 42 papers in training set
Top 0.2%
3.4%
9
Nano Letters
● 71 papers in training set
Top 0.4%
3.2%
10
ACS Sensors
● 49 papers in training set
Top 0.3%
3.1%
11
Advanced Materials
○ 56 papers in training set
Top 0.4%
3.1%
12
Nanoscale Advances
● 15 papers in training set
Top 0.1%
2.7%
50% of probability mass above
13
Science Advances
● 1243 papers in training set
Top 14%
2.6%
14
ACS Applied Bio Materials
● 24 papers in training set
Top 0.3%
2.3%
15
Angewandte Chemie International Edition
○ 93 papers in training set
Top 0.8%
2.1%
16
Journal of Colloid and Interface Science
○ 12 papers in training set
Top 0.1%
1.9%
17
Small Methods
○ 29 papers in training set
Top 0.2%
1.9%
18
Advanced Healthcare Materials
○ 85 papers in training set
Top 0.9%
1.7%
19
Journal of Nanobiotechnology
○ 14 papers in training set
Top 0.2%
1.7%
20
ChemBioChem
○ 55 papers in training set
Top 0.6%
1.7%
21
Biophysical Reports
○ 37 papers in training set
Top 0.2%
1.5%
22
Scientific Reports
○ 3612 papers in training set
Top 59%
1.4%
23
The Journal of Physical Chemistry Letters
● 63 papers in training set
Top 0.5%
1.3%
24
Advanced Science
○ 286 papers in training set
Top 6%
1.3%
25
Lab on a Chip
● 96 papers in training set
Top 0.8%
1.1%
26
Advanced Materials Interfaces
○ 10 papers in training set
Top 0.1%
1.1%
27
Chemical Communications
● 25 papers in training set
Top 0.4%
1.1%
28
Analytica Chimica Acta
○ 17 papers in training set
Top 0.3%
1.1%
29
Biophysical Journal
○ 631 papers in training set
Top 4%
1.1%
30
ACS Omega
● 105 papers in training set
Top 3%
1.0%

"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.