The Supersized Science podcast highlights research and discoveries nationwide enabled by advanced computing technology and expertise at the Texas Advanced Computing Center of the University of Texas at Austin. TACC science writer Jorge Salazar hosts Supersized Science. Supersized Science is part of the Texas Podcast Network, brought to you by The University of Texas at Austin. Podcasts are produced by faculty members and staffers at UT Austin who work with University Communications to craft content that adheres to journalistic best practices. The University of Texas at Austin offers these podcasts at no charge. Podcasts appearing on the network and this webpage represent the views of the hosts and not of The University of Texas at Austin.
06-12-2017
Some secrets of our skeletons might be found in the silky webs of golden orb weaver spiders, according to experiments guided by supercomputers.
Scientists don’t yet understand the details of osteogenesis, or how bones form. A study found that silica combined with engineered silk derived from the dragline of golden orb weaver spider webs could be fine-tuned to activate genes in human stem cells that initiated biomineralization, a key step in bone formation.
The study appeared September 2017 in the journal Advanced Functional Materials. The authors used supercomputers through and allocation from XSEDE, the Xtreme Science and Engineering Discovery Environment, funded by the National Science Foundation. Stampede at the Texas Advanced Computing Center (TACC) and Comet at the San Diego Supercomputing Center helped scientists model the protein folding of integrin, an essential step in the intracellular pathways that lead to osteogenesis. This research will help larger efforts to cure bone disorders such as osteoporosis or calcific aortic valve disease.
Joining host Jorge Salazar of TACC on the podcast to talk about the bone formation study are Zaira Martín-Moldes of the Kaplan Lab at Tufts University and Davoud Ebrahimi at the Laboratory for Atomistic and Molecular Mechanics of the Massachusetts Institute of Technology.
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Filetype: MP3 - Size: 28.01MB - Duration: 20:09 m (192 kbps 44100 Hz)
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