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Virtual lung models every breath you take A virtual lung model developed at DOE's Pacific Northwest National Laboratory may help predict the impact of pollutants on respiratory systems and provide new insights into asthma, a condition afflicting 15 million American adults, as well as other pulmonary diseases.
The computer model, called the virtual respiratory tract, provides an unprecedented, three-dimensional view of how pollutants enter, travel through and collect in the entire respiratory system. PNNL scientists have developed a complete model of a rat's respiratory tract, which includes the nose, larynx and lungs, and have nearly completed a similar model of the human. Collaborations will prove key to continuing the research. PNNL scientists anticipate continuing to work with researchers at the University of California, Davis, who have conducted extensive research into asthma using animal models, and the University of Washington's pulmonary biology and bioengineering programs. Understanding biological impacts from pollution has become more important as respiratory ailments have increased, as evidenced by the nearly doubling of asthma sufferers since 1980. By learning how particulates travel through the lungs, scientists can design treatments that more precisely target drug delivery for pulmonary diseases and understand how pollutants impact differently damaged and healthy lungs. "We designed a tool that will open up new possibilities for understanding how our environment affects our bodies," said Rick Corley, PNNL environmental toxicologist. Using the virtual respiratory tract, PNNL scientists can analyze the influence of various factors, such as the amount of pollutants or length of exposure, on healthy versus diseased lungs by manipulating the computer model. For example, they can begin to simulate how gases, vapors and particulates may act differently within lungs of people suffering from cystic fibrosis, emphysema and asthma.
PNNL scientists designed the highly detailed virtual respiratory tract by combining the powerful capabilities of supercomputers, rapid semi-automated computer modeling and nuclear magnetic resonance imaging systems.
Submitted by DOE's Pacific Northwest National Laboratory |
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