An Insight on Microfluidic Organ-on-a-Chip Models for PM2.5-Induced Pulmonary Complications

Disha Shah1, Bhavarth Dave1, Mehul R Chorawala1

  • 1Department of Pharmacology and Pharmacy Practice, L. M. College of Pharmacy Navrangpura, Ahmedabad, Gujarat 380009, India.

ACS Omega
|April 1, 2024
PubMed

Insights

Lung-on-a-chip models offer advanced insights into respiratory diseases caused by fine particulate matter (PM2.5). This review explores their potential in understanding and modeling PM2.5-induced pulmonary complications.

Area of Science:

  • Pulmonary Medicine
  • Biomedical Engineering
  • Toxicology

Background:

  • Pulmonary diseases like asthma and lung cancer significantly impact global health.
  • Exposure to particulate matter (PM), especially PM2.5, is linked to respiratory issues.
  • Traditional 2D cell cultures and animal models inadequately replicate in vivo lung conditions.

Purpose of the Study:

  • To review the utility of lung-on-a-chip models in simulating pulmonary complications.
  • To specifically examine the role of these advanced models in understanding PM2.5-induced lung damage.

Main Methods:

  • Review of current literature on lung-on-a-chip technology.
  • Focus on microfluidic organ-on-a-chip systems for respiratory research.
  • Analysis of studies investigating PM2.5 effects on lung models.

Main Results:

  • Three-dimensional (3D) organ-on-a-chip models, including lung-on-a-chip, are emerging as superior alternatives to conventional models.
  • These advanced models show promise in replicating the complex cellular microenvironment of the lungs.
  • Lung-on-a-chip technology can potentially elucidate the mechanisms of PM2.5-induced pulmonary pathologies.

Conclusions:

  • Lung-on-a-chip models represent a significant advancement in pulmonary research.
  • They offer a more physiologically relevant platform for studying the impact of environmental exposures like PM2.5.
  • This technology holds promise for developing better diagnostics and therapeutics for lung diseases.

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