Back

Airway smooth muscle--on-a-chip: a microfluidic approach to study alveolar smooth muscle remodelling

Suhail, A.; Xavier, J.; PK, H.; Krishnan MJ, A.; Pradeep, A.; KB, M.; S, R.; NS, R.; Bernardino de la Serna, J.

2025-03-15 bioengineering
10.1101/2025.03.13.643111 bioRxiv
Show abstract

Respiratory illnesses, like chronic obstructive pulmonary disease (COPD) and asthma, pose significant global health challenges due to their chronic nature and limited treatment options. Airway smooth muscle (ASM) plays a vital role in respiratory diseases, particularly in airway remodelling and obstruction. ASM, which encircles the bronchial tree and extends to the trachea, plays a vital yet not fully understood role in lung physiology. However, its dysfunction is strongly associated with asthma and COPD progression, leading to excessive contraction, increased inflammatory mediator release, and ASM hypertrophy. However, identifying its precise function is challenging due to limitations in existing research models for assessing ASM contraction. In vivo models offer a comprehensive physiological perspective but possess ethical concerns and they do not allow for the direct measurement of ASM contraction. Meanwhile, ex vivo and in vitro models provide a more direct assessment; however, they lack crucial physiological factors. Understanding how ASM cells interact with their surroundings is essential for gaining deeper insights into respiratory disorders. To address this gap, we aimed to mimic the human airway smooth muscle-on-a-chip model, incorporating ASM cells in a 3D microenvironment. This microfluidic platform provides a physiologically relevant environment, allowing for studying complex mechanisms that drive airway remodelling and dysfunction in respiratory diseases. The ASM-on-a-chip is designed for long-term 3D cell culture of ASM cells that reorient itself to form a smooth muscle fibre. The design provides side channels for manipulating the constituent of the hydrogel to study the effect of compounds on AMS remodelling.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
Lab on a Chip
88 papers in training set
Top 0.1%
38.0%
2
ACS Biomaterials Science & Engineering
37 papers in training set
Top 0.1%
14.4%
50% of probability mass above
3
APL Bioengineering
18 papers in training set
Top 0.1%
4.2%
4
Advanced Science
249 papers in training set
Top 5%
3.7%
5
Advanced Healthcare Materials
71 papers in training set
Top 0.6%
3.6%
6
Scientific Reports
3102 papers in training set
Top 55%
1.8%
7
ACS Applied Bio Materials
21 papers in training set
Top 0.3%
1.8%
8
Advanced Materials Technologies
27 papers in training set
Top 0.3%
1.7%
9
Biofabrication
32 papers in training set
Top 0.4%
1.7%
10
Bioengineering & Translational Medicine
21 papers in training set
Top 0.4%
1.7%
11
Bioactive Materials
18 papers in training set
Top 0.5%
1.3%
12
Advanced Functional Materials
41 papers in training set
Top 1%
1.2%
13
Analytical Chemistry
205 papers in training set
Top 2%
1.2%
14
Biosensors and Bioelectronics
52 papers in training set
Top 1%
1.2%
15
Materials Today Bio
18 papers in training set
Top 0.4%
1.1%
16
Small
70 papers in training set
Top 0.8%
1.0%
17
Journal of Colloid and Interface Science
12 papers in training set
Top 0.3%
0.9%
18
PLOS ONE
4510 papers in training set
Top 64%
0.9%
19
ACS Omega
90 papers in training set
Top 3%
0.9%
20
Advanced Biology
29 papers in training set
Top 0.9%
0.9%
21
Biomaterials
78 papers in training set
Top 1%
0.8%
22
American Journal of Respiratory Cell and Molecular Biology
38 papers in training set
Top 0.8%
0.7%
23
ACS Nano
99 papers in training set
Top 4%
0.7%
24
Nano Letters
63 papers in training set
Top 3%
0.6%
25
iScience
1063 papers in training set
Top 37%
0.6%
26
Physics of Fluids
13 papers in training set
Top 0.5%
0.5%
27
Small Methods
26 papers in training set
Top 2%
0.5%
28
Nature Communications
4913 papers in training set
Top 67%
0.5%
29
Cell Reports Physical Science
18 papers in training set
Top 1%
0.5%
30
Chemical Engineering Journal
10 papers in training set
Top 0.8%
0.5%