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Media Contacts
![Two hybrid poplar plants, middle and right, engineered with the PtrXB38 hub gene exhibited a drastic increase in root and callus formation compared with a wild-type control plant, left. Credit: Tao Yao/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-10/Poplar%20root%20story%20tip%20as%20JPEG_0.jpg?h=7bc542ef&itok=HNxpeEt6)
Oak Ridge National Laboratory scientists identified a gene “hotspot” in the poplar tree that triggers dramatically increased root growth. The discovery supports development of better bioenergy crops and other plants that can thrive in difficult conditions while storing more carbon belowground.
![Biopsy from the tubular esophagus showing incomplete intestinal metaplasia, goblet cells with interposed cells having gastric foveolar-type mucin consistent with Barrett esophagus. Negative for dysplasia. H&E stain. Credit: Creative Commons](/sites/default/files/styles/list_page_thumbnail/public/2021-11/1200px-Barrett_esophagus_high_mag%5B1%5D_2.jpg?h=10d202d3&itok=qDgHrzu5)
A team including researchers from the Department of Energy’s Oak Ridge National Laboratory has developed a digital tool to better monitor a condition known as Barrett’s esophagus, which affects more than 3 million people in the United States.
![This simulation of a fusion plasma calculation result shows the interaction of two counter-streaming beams of super-heated gas. Credit: David L. Green/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-02/Fusion_plasma_simulation.jpg?h=d0852d1e&itok=CDWgjLPL)
The prospect of simulating a fusion plasma is a step closer to reality thanks to a new computational tool developed by scientists in fusion physics, computer science and mathematics at ORNL.
![Computing—Routing out the bugs](/sites/default/files/styles/list_page_thumbnail/public/2019-11/VA-HealthIT-2019-P04263.jpg?h=784bd909&itok=uwv091uK)
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool