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Using artificial intelligence, Oak Ridge National Laboratory analyzed data from published medical studies to reveal the potential of direct and indirect impacts of bullying.

Oak Ridge National Laboratory is using artificial intelligence to analyze data from published medical studies associated with bullying to reveal the potential of broader impacts, such as mental illness or disease. 

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.

ORNL researcher Karren More has been elected fellow of the Microscopy Society of America.

OAK RIDGE, Tenn., March 22, 2019 – Karren Leslie More, a researcher at the Department of Energy’s Oak Ridge National Laboratory, has been elected fellow of the Microscopy Society of America (MSA) professional organization.

Illustration of the intricate organization of the PKA structure, wherein different parts of the protein are connected through elaborate hydrogen bonding networks (dashed yellow lines), glued together by the hydrophobic assemblies (light blue and orange volumes)—all working together to build the functional active site. Insert shows protonation of the transferred phosphoryl group (cyan mesh) and its many interactions with water and the active site amino acid residues. Credit: Jill Hemman/ORNL

OAK RIDGE, Tenn., March 20, 2019—Direct observations of the structure and catalytic mechanism of a prototypical kinase enzyme—protein kinase A or PKA—will provide researchers and drug developers with significantly enhanced abilities to understand and treat fatal diseases and neurological disorders such as cancer, diabetes, and cystic fibrosis.

Neutron scattering allowed direct observation of how aurein induces lateral segregation in the bacteria membranes, which creates instability in the membrane structure. This instability causes the membranes to fail, making harmful bacteria less effective.

As the rise of antibiotic-resistant bacteria known as superbugs threatens public health, Oak Ridge National Laboratory’s Shuo Qian and Veerendra Sharma from the Bhaba Atomic Research Centre in India are using neutron scattering to study how an antibacterial peptide interacts with and fights harmful bacteria.

(From left) ORNL Associate Laboratory Director for Computing and Computational Sciences Jeff Nichols; ORNL Health Data Sciences Institute Director Gina Tourassi; DOE Deputy Under Secretary for Science Thomas Cubbage; ORNL Task Lead for Biostatistics Blair Christian; and ORNL Research Scientist Ioana Danciu were invited to the White House to showcase an ORNL-developed digital tool aimed at better matching cancer patients with clinical trials.

OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.

carbon nanospikes

OAK RIDGE, Tenn., March 1, 2019—ReactWell, LLC, has licensed a novel waste-to-fuel technology from the Department of Energy’s Oak Ridge National Laboratory to improve energy conversion methods for cleaner, more efficient oil and gas, chemical and

To develop complex materials with superior properties, Vera Bocharova uses diverse methods including broadband dielectric spectroscopy. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Jason Richards

Vera Bocharova at the Department of Energy’s Oak Ridge National Laboratory investigates the structure and dynamics of soft materials—polymer nanocomposites, polymer electrolytes and biological macromolecules—to advance materials and technologies for energy, medicine and other applications.

ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La

Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.

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While studying the genes in poplar trees that control callus formation, scientists at Oak Ridge National Laboratory have uncovered genetic networks at the root of tumor formation in several human cancers.