Steven J. Plimpton

Bio: Steven J. Plimpton is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Parallel algorithm & Direct simulation Monte Carlo. The author has an hindex of 44, co-authored 128 publications receiving 62532 citations.

Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach.

Abstract: Mycobacterium tuberculosis associated granuloma formation can be viewed as a structural immune response that can contain and halt the spread of the pathogen. In several mammalian hosts, including non-human primates, Mtb granulomas are often hypoxic, although this has not been observed in wild type murine infection models. While a presumed consequence, the structural contribution of the granuloma to oxygen limitation and the concomitant impact on Mtb metabolic viability and persistence remains to be fully explored. We develop a multiscale computational model to test to what extent in vivo Mtb granulomas become hypoxic, and investigate the effects of hypoxia on host immune response efficacy and mycobacterial persistence. Our study integrates a physiological model of oxygen dynamics in the extracellular space of alveolar tissue, an agent-based model of cellular immune response, and a systems biology-based model of Mtb metabolic dynamics. Our theoretical studies suggest that the dynamics of granuloma organization mediates oxygen availability and illustrates the immunological contribution of this structural host response to infection outcome. Furthermore, our integrated model demonstrates the link between structural immune response and mechanistic drivers influencing Mtbs adaptation to its changing microenvironment and the qualitative infection outcome scenarios of clearance, containment, dissemination, and a newly observed theoretical outcome of transient containment. We observed hypoxic regions in the containment granuloma similar in size to granulomas found in mammalian in vivo models of Mtb infection. In the case of the containment outcome, our model uniquely demonstrates that immune response mediated hypoxic conditions help foster the shift down of bacteria through two stages of adaptation similar to the in vitro non-replicating persistence (NRP) observed in the Wayne model of Mtb dormancy. The adaptation in part contributes to the ability of Mtb to remain dormant for years after initial infection.

Effect of shape and friction on the packing and flow of granular materials

Abstract: The packing and flow of aspherical frictional particles are studied using discrete element simulations. Particles are superballs with shape ${|x|}^{s}+{|y|}^{s}+{|z|}^{s}=1$ that varies from sphere ($s=2$) to cube ($s=\ensuremath{\infty}$), constructed with an overlapping-sphere model. Both packing fraction, $\ensuremath{\phi}$, and coordination number, $z$, decrease monotonically with microscopic friction $\ensuremath{\mu}$, for all shapes. However, this decrease is more dramatic for larger $s$ due to a reduction in the fraction of face-face contacts with increasing friction. For flowing grains, the dynamic friction $\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\ensuremath{\mu}}$---the ratio of shear to normal stresses---depends on shape, microscopic friction, and inertial number $I.$ For all shapes, $\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\ensuremath{\mu}}$ grows from its quasistatic value ${\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\ensuremath{\mu}}}_{0}$ as $(\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\ensuremath{\mu}}\ensuremath{-}{\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\ensuremath{\mu}}}_{0})=d{I}^{\ensuremath{\alpha}}$, with different universal behavior for frictional and frictionless shapes. For frictionless shapes the exponent $\ensuremath{\alpha}\ensuremath{\approx}0.5$ and prefactor $d\ensuremath{\approx}5{\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\ensuremath{\mu}}}_{0}$ while for frictional shapes $\ensuremath{\alpha}\ensuremath{\approx}1$ and $d$ varies only slightly. The results highlight that the flow exponents are universal and are consistent for all the shapes simulated here.

Parallel S n Sweeps on Unstructured Grids: Algorithms for Prioritization, Grid Partitioning, and Cycle Detection

Abstract: The method of discrete ordinates is commonly used to solve the Boltzmann transport equation. The solution in each ordinate direction is most efficiently computed by sweeping the radiation flux across the computational grid. For unstructured grids this poses many challenges, particularly when implemented on distributed-memory parallel machines where the grid geometry is spread across processors. We present several algorithms relevant to this approach: (a) an asynchronous message-passing algorithm that performs sweeps simultaneously in multiple ordinate directions, (b) a simple geometric heuristic to prioritize the computational tasks that a processor works on, (c) a partitioning algorithm that creates columnar-style decompositions for unstructured grids, and (d) an algorithm for detecting and eliminating cycles that sometimes exist in unstructured grids and can prevent sweeps from successfully completing. Algorithms (a) and (d) are fully parallel; algorithms (b) and (c) can be used in conjunction with (a) to achieve higher parallel efficiencies. We describe our message-passing implementations of these algorithms within a radiation transport package. Performance and scalability results are given for unstructured grids with up to 3 million elements (500 million unknowns) running on thousands of processors of Sandia National Laboratories' Intel Tflops machine and DEC-Alpha CPlant cluster.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。