In Progress, 2012
- Modeling Aortic Aneurysms
- When Small Worlds Collide
- Force Field of the Sugar Pucker
- Fighting Dengue Resurgence
With help from XSEDE consulting and computing resources, researchers have done computational modeling of the biomechanics of aortic aneurysms starting from medical images of individual patients
Abdominal aortic aneurysm (AAA), an enlargement of the abdominal aorta by 50 percent or more, occurs in more than 8 percent of people over 65. It can lead to fatal rupture and is the tenth-leading cause of death for men over 50. Current medical practice lacks the ability to fully assess AAA risk of rupture, with one of the known factors being AAA wall stress, for which there are no reliable in vivo measurement techniques.
Many key parameters of AAAs, furthermore, show wide variation among individuals. Ender Finol, director of the Vascular Biomechanics and Biofluids Laboratory at The University of Texas at San Antonio, has developed computational protocols (finite-element analysis using ADINA software) for modeling patient-specific AAA features so that they can be translated to reliable individualized wall-stress predictions. The goal is to use this modeling for to assess of the risk for rupture for individual patients, and thereby to help guide decisions about surgical intervention.
Finol, who until a year ago was at Carnegie Mellon, collaborates with Pittsburgh’s Allegheny General Hospital in gathering imaging data of AAA patients. XSEDE consultant Anirban Jana of PSC has provided advice on ADINA options and coding (with software called MATLAB) and in developing a method to initialize the model — to set its boundary conditions — from patient-specific profiles. “Anirban’s role has been more than just to help launch our finite-element models,” says Finol. “He has been a member of the advisory committee for my doctoral student, Samarth Raut, who did much of our AAA modeling. Anirban has provided valuable input regularly to this project.”
With computations on XSEDE’s Pople (now decommissioned) and Blacklight, Finol has presented conference papers (with Jana as co-author) on computational solid-stress (CSS) modeling of patient-specific AAAs. Results show wall stresses more sensitive to changes in AAA shape, and the work, further, suggests that rupture risk may be characterized in relation to AAA morphology. In ongoing work with Blacklight, Finol is increasing the number of patient-specific AAA cases modeled, with the aim of completing analysis from 200 individual AAAs, each of which requires geometry reconstruction and meshing with nearly three-million degrees of freedom for a CSS simulation. Using the shared-memory version of ADINA, Jana has found that the problem optimizes at eight cores with up to 32 cores for faster time to solution.
The cut-section graphic (right), from modeling by Finol and colleagues, zooms into the interior of an abdominal aortic aneurysm, showing wall thickness and indicating wall stress (increasing from blue to red). “We have software to make computational models from medical images of individual patients,” says Finol, “which takes into account their aortic wall thickness, slice by slice, in vivo, and from that to predict wall-stress distribution. No one else has done this before with this level of accuracy.”
With the advantage of large memory per processor on Blacklight, researchers are learning about how collisions alter spin in the quantum world
Imagine that you’re a fastball pitcher, but instead of a baseball you’re hurling a helium atom toward, not a batter’s swinging bat, but a spinning molecule of sodium-potassium, NaK. You wouldn’t be able to see what happens, but the impact releases energy from NaK and changes its orientation in space. “Some collisions are head-on,” says physicist A. Peet Hickman of Lehigh University, “and some are glancing blows.”
Hickman and colleagues are using Blacklight to do calculations that model this kind of collision, to see how the impact changes quantum properties of the rotating NaK. Their calculations go hand-in-hand with experiments of John Huennekens and his group in Lehigh’s Department of Physics, using a polarized laser beam to rotate NaK molecules as they are smashed into by helium atoms (or in other experiments, atoms of argon or potassium). The Lehigh experiments measure rates of collision that change NaK’s rotational quantum number J.
It’s pure research, gaining fundamental knowledge about the topsy-turviness of how things happen in the quantum world, where the rules of the macroscopic every-day world we live in don’t apply. This research holds possibilities for “quantum computing” in which changing the spin of an atom, switching from one angular momentum to another, could be a way of storing binary information at much higher density than current technologies.
The researchers used Blacklight (with code that Hickman wrote) for extensive calculations that use the laws of quantum mechanics to determine the outcome of the collisions. Hickman also used XSEDE resources at Texas, Illinois and San Diego for electronic-structure calculations that show how the energy properties of NaK depend on the bond length between Na and K. Their theoretical results are in good agreement with some of the main features of the experimental results (see figure), and provide several predictions that can be tested in future experimental work, among them that the vibrational level has a significant effect on the rate of rotational transitions. Experimental work is underway to test this prediction. Further calculations have shown that orientation of the NaK molecules tends to be preserved in collisions with helium, even when the rotational energy changes significantly, and that this effect is very sensitive to the vibrational level. The calculations involved solving several hundred coupled differential equations, and Blacklight (which achieved 87 percent memory utilization on 96 cores) was particularly valuable, says Hickman, because of its large memory per processor.
Comparison of experimental and theoretical rate constants for rotationally inelastic scattering of helium and sodium-potassium at 600° Kelvin. These preliminary theoretical calculations were carried out for vibrational level (v) = 15. In agreement with experiment, rates for inelastic transitions with an even change in rotational quantum number (ΔJ) were found to be larger than those with odd ΔJ.
In work aimed at developing drugs to knockout viral diseases, researchers are using Blacklight and other XSEDE resources for precise quantum calculations of the “force field” of RNA
Sugar Pucker of RNA
The transition that occurs between these two conformations of the “sugar pucker” in RNA, C3'-endo (top) and C2'-endo, are critical in accurate structural models of RNA, which can lead to new drug therapies to defeat viral diseases such as AIDS, hepatitis C and yellow fever.
To find drugs that can deliver a knockout punch to a virus is a Mount Everest research problem. The intense effort spurred by the AIDS epidemic brought into being a small arsenal of anti-viral drugs — effective at managing symptoms, but far from a cure. For many viruses with fatal implications for humans, to go for the jugular means going for the RNA, the molecule by which most viruses — including HIV, hepatitis C, yellow fever and others — insert their genetic material and take over the cell’s replication machinery.
University of Utah computational biochemist Tom Cheatham leads a team of researchers who use computational modeling to help design new therapeutic drugs. Their progress depends on the accuracy of “force fields” to model the structure of biomolecules. A recent focus of Cheatham and graduate-student colleague Niel Henriksen is the “sugar pucker” of RNA.
One of the main components of RNA helical structure is a ring-like structure called the “sugar pucker” — chemically, ribose (C10H5O5). “RNA performs many critical functions in biology,” says Henriksen, “and it accomplishes this by adopting a vast number of complex conformations. This flexibility is partly enabled by the sugar ring flipping between two conformations, called C3'-endo and C2'-endo.”
Cheatham and Henriksen have identified a problem with the RNA force field’s ability to accurately predict the energy difference in the sugar pucker flipping between the two differently oriented structures. They have used XSEDE resources, both Kraken at NICS in Tennessee and PSC’s Blacklight, to address this problem. For some calculations, says Henriksen, Kraken offers the advantage of many thousands of processors. Blacklight has proven to be especially useful for quantum-mechanical calculations, which require huge amounts of memory. “The different XSEDE machines,” says Henriksen, “have different strong points, but Blacklight is suited nicely for this work.”
With Blacklight, Cheatham and Henriksen calculated highly accurate values for the C3'-endo to C2'-endo transition. They are in process of refining the force fields, and they are validating their findings to demonstrate that they represent substantial improvement. “We hope these improvements will allow more accurate investigations of RNA,” says Henriksen, “and lead to new drug therapies targeting RNA.”
PSC researchers are collaborating with the University of Pittsburgh MIDAS National Center of Excellence to develop epidemiological modeling that can help to control the spread of dengue fever
Dengue fever isn’t near the top of the mind, generally speaking, when people think about major health problems. This tropical disease, transmitted by mosquito (Aedes aegypti), seemed in the 1970s to be contained in the western hemisphere and well on the way to eradication, thanks mainly to programs that reduced the standing-water breeding habitat of the mosquitoes. With world travel and the growth of urban populations, however, dengue has come back with a vengeance, including rapidly growing incidence in Africa, Asia and Brazil.
PSC scientists Nathan Stone and Shawn Brown are collaborating with the National Institutes of Health MIDAS (Models of Infectious Disease Agent Study) Center of Excellence, led by Donald Burke of the University of Pittsburgh Graduate School of Public Health, to develop computational modeling that can help to determine the impact of potential interventions on the spread of dengue. In this work, Stone and Brown also collaborate with Derek Cummings of Johns Hopkins University and John Greffenstette of the University of Pittsburgh Graduate School of Public Health.
The World Health Organization (WHO) now estimates that half the world’s population is at risk for dengue. The mosquito-borne dengue virus, says the WHO, infects 50 to 100 million people every year, with tens of thousands of fatal cases. In some areas dengue has become epidemic, such as Thailand, where about 70 percent of the population are either carriers or symptomatic. Symptoms, along with fever, include headaches and muscle and joint pain; for a small proportion of dengue infections, most commonly the second exposure, a hemorrhagic fever can lead to bleeding and sometimes fatal low blood pressure. Currently there is no real therapy — beyond aspirin, rest and fluid replacement— and no vaccine; to stop transmission is the only effective way to prevent dengue epidemics.
Stone and his collaborators are working to develop mathematical modeling that can show how human organization — from houses and communities to nations and continents — and movement patterns can have an impact on the spread of dengue. Their model, called CLARA — for Clara Ludlow, who helped to pioneer study of mosquitoes as a disease vector — incorporates features that go beyond prior epidemiological modeling. These include complete information on the A. aegypti mosquito life cycle, from eggs to larvae to adult. CLARA, notes Stone, also includes genetic information on A. aegypti, which bears on research on the effectiveness of dengue intervention with a bacterium, called Wolbachia, that shortens the life span of A. aegypti. “No other model,” says Stone, “includes all these features.”
World distribution of dengue fever, 2006, showing areas infested with Aedes aegypti (blue) and areas with A. aegypti and recent epidemic dengue fever (red).