Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

News

ChrisJohnson galaFlyer 600x317 1We are pleased to announce the recipient of The Leonardo Award 2020 is Chris Johnson Ph.D. of the SCI Institute at the University of Utah for his curiosity, creativity and vision. Due to these unprecedented times, the Gala event was held virtually.

The event can be viewed here.
cinc2020
Congratulations to Wilson Good on winning the Rosanna Degani Young Investigators’ Award competition at the international Computing in Cardiology conference, Rimini, 16th September 2020.

Accumulation of collagen molecular unfolding is the mechanism of cyclic fatigue damage and failure in collagenous tissues

In understanding the failure of dense collagenous soft tissues over multiple loading cycles, the predominant hypothesis for development of overuse injuries is that repeated subfailure loading causes accumulation of “micro-damage”, and when this micro-damage accumulates at a rate that is faster than can be repaired, this results in injury in a clinical sense (tissue failure and resulting pain from the injury and overload of surrounding structures). However the specific nature of this micro-damage has remained unknown. In this study, we demonstrate that the micro-damage is actually collagen molecular unfolding, which accumulates with repeated cyclic loading. Our results provide a convincing explanation for the micro-damage hypothesis: Molecular-level collagen damage is generated by tissue-level loading, and the ability to repair this damage determines whether the applied loading leads to tissue failure.


You can read the full paper in Science Advances


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(A) Rat tail tendon fascicles were loaded in creep-fatigue to 40% of the ultimate tensile strength (UTS) until tissue failure. Incremental levels of fatigue were defined as the peak cyclic (creep) strain at 20, 50, and 80% of cycles to failure. (B) To label and quantify denatured collagen, we stained mechanically loaded fascicles with fluorescent CHP, which hybridizes to unfolded collagen α chains. The amount of denatured collagen was quantified on microplate via the fluorescence of bound F-CHP. Computational simulations were used to investigate the potential mechanisms of fascicle- and molecular-level fatigue behavior. (C) Biphasic finite-element simulations were used to study the potential role of fluid flow on strain rate–dependent fatigue behavior at the fascicle level. (D) MD simulations of collagen model peptides were used to identify molecular mechanisms of fatigue damage accumulation and strain rate dependence. GPO, glycine-proline-hydroxyproline.






Bei 683x1024University of Utah School of Computing assistant professor Bei Wang was awarded more than $832,000 from the U.S. Department of Energy’s Early Career Research Program, one of only 75 scientists in the nation and the only faculty member from the U to earn the award this year.

Wang’s project, titled “Topology-Preserving Data Sketching for Scientific Visualization,” will conduct a study of topology-preserving data sketching techniques to improve visual exploration and understanding of large scientific data.

As scientific simulations generate a large amount of data while the simulation is running, it has become challenging to keep track of interesting phenomena and apply appropriate actions such as storage, analysis, and visualization.

Data sketching uses ideas from statistics, geometry, and linear algebra to generate an approximation of each data instance for fast and efficient processing. At the same time, visualization plays an important role in a data processing pipeline. Topology-based methods in visualization provide powerful tools to summarize and present large and complex data in a simple and easy-to-understand way.

Wang’s project combines ideas from data sketching with topological techniques in visualization. The multidisciplinary project will be universally applicable in many scientific areas, including but not limited to computational fluid dynamics and materials science.

Wang, who is also a faculty member in the U’s Scientific Computing and Imaging Institute, is focused on the analysis and visualization of large and complex data. Her research interests include topological data analysis, data visualization, computational topology, computational geometry, machine learning, and data mining. She received a bachelor’s in computer science and mathematics from the University of Bridgeport and a doctorate in computer science from Duke University.

The Early Career Research Program, now in its eleventh year, is designed to “bolster the nation’s scientific workforce by providing support to exceptional researchers during crucial early career years,” according to the DOE. Awards are given to projects related to advanced scientific computing, basic energy sciences, biological and environmental research, fusion energy sciences, high energy physics and nuclear physics.
shapeworks 5 4We are excited to announce the new release of our software, ShapeWorks 5.4. ShapeWorks is now faster and uses less memory, with a scalable graphic user interface for large cohorts and a flexible, user-friendly project file format.

To download installation packages for Windows/Mac/Linux and/or the source code, please visit https://github.com/SCIInstitute/ShapeWorks/releases/tag/v5.4.1

Proof of principle study highlights mathematical methods that are uniquely suited for personalized medicine

For the past 70 years, the best indicator of life expectancy for a patient with glioblastoma (GBM) — the most common and the most aggressive brain cancer — has simply been age at diagnosis. Now, an international team of scientists has experimentally validated a predictor that is not only more accurate but also more clinically relevant: a pattern of co-occurring changes in DNA abundance levels, or copy numbers, at hundreds of thousands of sites across the whole tumor genome.

Conferences may be a little different this year, but that hasn't stopped SCI students from showing what they're made of. This week four publications were selected as finalists in two seperate conferences.  Adam Rauff and Steven LaBelle were selected as finalists for the (virtual) student PhD paper competition at the Summer Biomechanics, Bioengineering and Biotransport Conference in June (SB3C). At this same conference Jason Manning was selected as a finalist in the undergraduate student paper competition.

zengerCongradulations to Brian Zenger on receiving a 2020-21 University Graduate Fellowship. The award includes an $18,900 scholarship for the academic year as well as covering regular graduate tuition.

The UGRF affords Brian the opportunity to pursue his projects full-time during the 2020-21 academic year.
corona virus gettyCongratulations to Tolga Tasdizen whos Emerging COVID-19/SARS-CoV-2 Research Application has been awarded funding by the University of Utah Health’s 3i Initiative.

The project entitled AI/CXR Early Warning System for Infectious Respiratory Disease Outbreaks, proposes to research an early warning system for novel respiratory infectious disease outbreaks based on automated emerging cluster analysis of routine chest x-rays (CXR) using Artificial Intelligence/Machine Learning (AI/ML) and furthermore, to the use data collected during the COVID-19 pandemic to validate our proposed models.

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SCI Institute and CEDMAV alumnus, Brian Summa has been working with colleagues at Tulane University to study the effects of COVID-19 on lung tissue. This research is made possible using ViSUS to analyze high resolution histological volumes too large to visualize with other software.