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The lung is a complex multiscale organ that serves as the primary interface between the environment and the tissues of the body. Homeostatic maintenance of lung function throughout life is essential for health. While failure of lung homeostasis underlies many of the most common chronic diseases that afflict mankind, the precise pathophysiologic mechanisms involved are often unclear. Investigative techniques such as microscopic imaging and atomic force microscopy are providing new insights into lung tissue properties at the micro scale. It nevertheless remains to be seen how this growing body of information can be integrated into a comprehensive picture of the lung. Mathematical and computational modeling has emerged as an essential tool for gaining such a holistic understanding. This book introduces the reader to the art of modeling as a means of linking lung structure to function over multiple length scales from the intracellular level to that of the whole organ, with specific attention given to the pathophysiology of a number of common lung diseases and aging.
introduction.- lung anatomy and physiology.- lumped parameter models of lung function.- parenchymal tissue elasticity.- tissue viscoelasticity.- homeostasis and repair.- asthma.- pulmonary fibrosis.- chronic obstructive pulmonary disease.- acute lung injury.- lung defenses.- the aging lung.- what is coming next.
Béla Suki graduated as a physicist from the University of Szeged, Hungary where he also received his PhD in biomechanics in 1987. He spent time as a research fellow at INSERM in Nancy, France and in the Meakins-Christie Laboratories, McGill University, Montreal Canada. In 1990, he joined the Department of Biomedical Engineering at Boston University where he became full professor in 2007. His research focuses on the complexity of multiscale structure-function relationships in the lung. This includes the development of networks to understand how the rupture of collagen and elastin fibres contributes to the progression of emphysema, how characteristic parenchymal structures develop in pulmonary fibrosis, and how dynamic stretch patterns affect cell function with implications for mechanical ventilation. Dr. Suki is a Fellow of the American Institute for Medical and Biological Engineering and a Fellow of the Biomedical Engineering Society. He is also a recipient of a Presidential Award from the NIH to support innovative high-risk research, and the Joseph R. Rodarte award for Scientific Distinction from the American Thoracic Society. In 2021, Dr. Suki published a book entitled “Structure and function of the extracellular matrix: A multiscale quantitative approach” (Academic Press).
Jason H.T. Bates obtained an undergraduate degree in physics from the University of Canterbury, New Zealand, in 1978, a PhD in Medicine from the University of Otago, New Zealand, in 1981, and a DSc from the University of Canterbury in 1994. Dr. Bates spent the early part of his career in the Meakins-Christie Laboratories of McGill University, Montreal. He moved to the University of Vermont in 1999 where he is currently a Professor of Medicine, Molecular Physiology & Biophysics, and Electrical & Biomedical Engineering. He has worked predominately in the field of lung mechanics, focusing on the biophysical mechanisms of airways responsiveness and the pathophysiology of ventilator-induced lung injury and pulmonary fibrosis, making extensive use of mathematical and computational modeling. Dr. Bates is a Fellow of the American Institute for Medical & Biological Engineering, a Fellow of the Biomedical Engineering Society, a Fellow of the American Thoracic Society, and a Senior member of the Institute of Electrical & Electronic Engineers. He is also a recipient of Joseph Rodarte Award for Scientific Distinction, the Solbert Permutt Trailblazer Award, the Dr. Robert Crapo Memorial Lifetime Achievement Award in Pulmonary Diagnostics, and a Recognition Award for Scientific Accomplishments, all from the American Thoracic Society. In 2009, Dr. Bates published a book entitled “Lung Mechanics. An Inverse Modeling Approach” (Cambridge University Press).


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