Computer modeling of the Purkinje neuron helps explain its branching network of nearly 200,000 connections to other brain cells.
High performance computing and communications is providing valuable insights into the mysteries of human health and disease. These sophisticated new techniques allow for unprecedented study and understanding of the remarkable self-assembly of atoms into molecules, molecules into cells, cells into tissues, and organ systems into the complete organisms that constitute humanity itself. Important new medical knowledge and new diagnostic tools have resulted from the HPCC Program.
At the molecular level, supercomputing and scientific visualization have provided valuable insights into the molecular basis of asthma. Corporate scientists at Eli Lilly collaborated with visualization specialists at the National Center for Supercomputer Applications to model the three-dimensional molecular motions of leukotrienes, naturally occurring "messenger molecules" that induce the lungs to become stiff and inflamed. With the goal of designing new medicines to block the leukotriene receptor in the lungs, these researchers used supercomputers to calculate the position of each atom in several related leukotriene molecules; three-dimensional scientific visualization then displayed the subtle differences in atom positioning that are crucial to biological activity. More effective medications with fewer side effects are the goal of this high performance molecular dynamics computing.
Molecules assemble themselves into cells and tissues, and at this
level also computerized analysis has expanded our knowledge. One
of the most complicated cells in the brain is a neuron called the
Purkinje cell; each one of these cells may have up to 200,000
electrical connections with other brain cells. Researchers at the
California Institute of Technology used an experimental massively
parallel computer to model the response of Purkinje cells to chemical
and electrical stimuli. Their model emulates the observed behavior
of the living cell, and provides evidence that although the
connections to other neurons are voluminous, there is an elegant
simplicity in the spatial arrangement of these brain interconnections.
Massively parallel supercomputing turns two-dimensional magnetic
resonance images into three-dimensional maps that can identify
early breast cancers.
Cells and tissues organize into body systems, which can also be better
understood using HPCC technologies.
Magnetic Resonance Imaging (MRI)
is a widely used method for imaging internal structure of the
human body that produces two-dimensional cross section views.
Researchers at Sandia National Laboratories, in collaboration with
Baylor University Medical Center in Dallas and the Department of
Veterans Affairs Medical Center in Albuquerque, have used
massively parallel supercomputers to turn two-dimensional MRI
images into three-dimensional views, and revealed previously
hidden information. Communicating their data via the Internet,
these groups compared three-dimensional MRI to standard X-ray
mammography for the detection of early breast cancer, and found
that the new technique revealed early tumors that could not be
detected by mammography.
The molecular dynamics of three different leukotriene (LTC4, LTD4,
and LTE4) molecules portrayed with a new supercomputing
visualization technique called "ghosting." Dense shadows represent
the configurations in which the molecules spend a greater amount of
time, while the range of molecular movement is shown by the extent
of the dot patterns.
