Back

Measuring RBC deformability and its heterogeneity using a fast microfluidic device

Kumari, S.; Mehendale, N.; Roy, T.; Sen, S.; Mitra, D.; Paul, D.

2023-07-19 bioengineering
10.1101/2023.07.18.549500 bioRxiv
Show abstract

We report a high-throughput microfluidic device to determine the Youngs modulus of single red blood cells (RBCs). Our device consists of a single channel opening into a funnel, with a semi-circular obstacle placed at the mouth of the funnel. As a RBC passes the obstacle, it deflects from its original path. Using populations of artificially-stiffened RBCs, we show that the stiffer RBCs deflect more compared to the healthy RBCs. We then generate a calibration curve that maps each RBC trajectory to its Youngs modulus obtained using an atomic force microscope. Finally, we sort a mixed population of RBCs based on their deformability alone. Our device could potentially be further miniaturized to sort and obtain the elastic constants of nanoscale objects, such exosomes, whose shape change is difficult to monitor by optical microscopy.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Lab on a Chip
● 96 papers in training set
Top 0.1%
22.4%
Similar papers in this journal
2
Scientific Reports
○ 3612 papers in training set
Top 6%
8.0%
Similar papers in this journal
3
Soft Matter
● 60 papers in training set
Top 0.2%
5.6%
Similar papers in this journal
4
Small
○ 78 papers in training set
Top 0.2%
4.4%
Similar papers in this journal
5
APL Bioengineering
● 19 papers in training set
Top 0.1%
4.1%
Similar papers in this journal
6
Biophysical Journal
○ 631 papers in training set
Top 2%
3.3%
7
Analytical Chemistry
● 218 papers in training set
Top 0.9%
3.3%
50% of probability mass above
8
Nature Communications
○ 5641 papers in training set
Top 34%
3.3%
9
Science Advances
● 1243 papers in training set
Top 10%
3.3%
10
ACS Biomaterials Science & Engineering
● 37 papers in training set
Top 0.3%
2.8%
11
ACS Nano
● 113 papers in training set
Top 0.9%
2.4%
12
Communications Biology
○ 993 papers in training set
Top 10%
2.2%
13
Langmuir
● 36 papers in training set
Top 0.2%
2.2%
14
eLife
● 5828 papers in training set
Top 45%
2.2%
15
Advanced Materials Technologies
○ 29 papers in training set
Top 0.3%
1.8%
16
Annals of Biomedical Engineering
○ 37 papers in training set
Top 0.6%
1.7%
17
Frontiers in Bioengineering and Biotechnology
○ 98 papers in training set
Top 1%
1.5%
18
Bioengineering & Translational Medicine
○ 21 papers in training set
Top 0.3%
1.5%
19
Nanoscale
● 42 papers in training set
Top 0.5%
1.1%
20
ACS Applied Bio Materials
● 24 papers in training set
Top 0.6%
1.1%
21
ACS Omega
● 105 papers in training set
Top 3%
1.1%
22
Physics of Fluids
● 13 papers in training set
Top 0.1%
1.1%
23
Nano Letters
● 71 papers in training set
Top 1%
1.0%
24
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 40%
0.9%
25
Small Methods
○ 29 papers in training set
Top 0.7%
0.9%
26
PLOS ONE
● 5266 papers in training set
Top 61%
0.6%
27
Biofabrication
○ 36 papers in training set
Top 0.7%
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.