Topography of pleural epithelial structure enabled by en face isolation and machine learning. Issue 1 (11th December 2022)
- Record Type:
- Journal Article
- Title:
- Topography of pleural epithelial structure enabled by en face isolation and machine learning. Issue 1 (11th December 2022)
- Main Title:
- Topography of pleural epithelial structure enabled by en face isolation and machine learning
- Authors:
- Liu, Betty S.
Valenzuela, Cristian D.
Mentzer, Katherine L.
Wagner, Willi L.
Khalil, Hassan A.
Chen, Zi
Ackermann, Maximilian
Mentzer, Steven J. - Abstract:
- Abstract: Pleural epithelial adaptations to mechanical stress are relevant to both normal lung function and parenchymal lung diseases. Assessing regional differences in mechanical stress, however, has been complicated by the nonlinear stress–strain properties of the lung and the large displacements with ventilation. Moreover, there is no reliable method of isolating pleural epithelium for structural studies. To define the topographic variation in pleural structure, we developed a method of en face harvest of murine pleural epithelium. Silver‐stain was used to highlight cell borders and facilitate imaging with light microscopy. Machine learning and watershed segmentation were used to define the cell area and cell perimeter of the isolated pleural epithelial cells. In the deflated lung at residual volume, the pleural epithelial cells were significantly larger in the apex (624 ± 247 μm 2 ) than in basilar regions of the lung (471 ± 119 μm 2 ) ( p < 0.001). The distortion of apical epithelial cells was consistent with a vertical gradient of pleural pressures. To assess epithelial changes with inflation, the pleura was studied at total lung capacity. The average epithelial cell area increased 57% and the average perimeter increased 27% between residual volume and total lung capacity. The increase in lung volume was less than half the percent change predicted by uniform or isotropic expansion of the lung. We conclude that the structured analysis of pleural epithelial cellsAbstract: Pleural epithelial adaptations to mechanical stress are relevant to both normal lung function and parenchymal lung diseases. Assessing regional differences in mechanical stress, however, has been complicated by the nonlinear stress–strain properties of the lung and the large displacements with ventilation. Moreover, there is no reliable method of isolating pleural epithelium for structural studies. To define the topographic variation in pleural structure, we developed a method of en face harvest of murine pleural epithelium. Silver‐stain was used to highlight cell borders and facilitate imaging with light microscopy. Machine learning and watershed segmentation were used to define the cell area and cell perimeter of the isolated pleural epithelial cells. In the deflated lung at residual volume, the pleural epithelial cells were significantly larger in the apex (624 ± 247 μm 2 ) than in basilar regions of the lung (471 ± 119 μm 2 ) ( p < 0.001). The distortion of apical epithelial cells was consistent with a vertical gradient of pleural pressures. To assess epithelial changes with inflation, the pleura was studied at total lung capacity. The average epithelial cell area increased 57% and the average perimeter increased 27% between residual volume and total lung capacity. The increase in lung volume was less than half the percent change predicted by uniform or isotropic expansion of the lung. We conclude that the structured analysis of pleural epithelial cells complements studies of pulmonary microstructure and provides useful insights into the regional distribution of mechanical stresses in the lung. … (more)
- Is Part Of:
- Journal of cellular physiology. Volume 238:Issue 1(2023)
- Journal:
- Journal of cellular physiology
- Issue:
- Volume 238:Issue 1(2023)
- Issue Display:
- Volume 238, Issue 1 (2023)
- Year:
- 2023
- Volume:
- 238
- Issue:
- 1
- Issue Sort Value:
- 2023-0238-0001-0000
- Page Start:
- 274
- Page End:
- 284
- Publication Date:
- 2022-12-11
- Subjects:
- epithelium -- lung -- machine learning -- morphometry -- pleura
Physiology -- Periodicals
Cell physiology -- Periodicals
571.6 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-4652 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/jcp.30927 ↗
- Languages:
- English
- ISSNs:
- 0021-9541
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4955.020000
British Library DSC - BLDSS-3PM
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