KAIST metabolic engineers presented the bio-based production of multiple short-chain primary amines that have a wide range of applications in chemical industries for the first time. The research team designed the novel biosynthetic pathways for short-chain primary amines by combining retrobiosynthesis and a precursor selection step.
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ATLANTA Compared to standard machine learning models, deep learning models are largely superior at discerning patterns and discriminative features in brain imaging, despite being more complex in their architecture, according to a new study in
Nature Communications led by Georgia State University.
Advanced biomedical technologies such as structural and functional magnetic resonance imaging (MRI and fMRI) or genomic sequencing have produced an enormous volume of data about the human body. By extracting patterns from this information, scientists can glean new insights into health and disease. This is a challenging task, however, given the complexity of the data and the fact that the relationships among types of data are poorly understood.
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IMAGE: A research participant wearing the BrainQ System, an AI-powered device that delivers electromagnetic stimulation to the upper extremity of individuals with impaired motor abilities. view more
Credit: BrainQ Technologies
East Hanover, NJ. January 14, 2021. Ghaith Androwis, PhD, and Steven Kirshblum, MD, received a grant from BrainQ Technologies to study a potential treatment for arm and hand dysfunction in individuals with chronic spinal cord injury. The study is titled, The safety and effectiveness of the use of a brain-computer interface-based electromagnetic field treatment in the management of patients with chronic spinal cord injury: A pilot study.
Dr. Androwis is a research scientist in the Center for Mobility and Rehabilitation Engineering Research at Kessler Foundation. Dr. Kirshblum is senior medical officer and director of the Spinal Cord Injury Program for Kessler Institute for Rehabilitation, chief academic officer for the Select Medical R
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IMAGE: Shell Scientist Christian A. Davies, Ph.D., has been named the recipient of the 2021 Edith and Peter O Donnell Award in Technology Innovation from TAMEST (The Academy of Medicine, Engineering and. view more
Credit: TAMEST (The Academy of Medicine, Engineering and Science of Texas)
(Embargoed until Wednesday, January 13, 2021, 12:00 a.m. CT)
HOUSTON - Shell Scientist Christian A. Davies, Ph.D., has been named the recipient of the 2021 Edith and Peter O Donnell Award in Technology Innovation from TAMEST (The Academy of Medicine, Engineering and Science of Texas). He was chosen for his development of a broad suite of alternative carbon management technologies to reduce emissions for a lower carbon future.
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Our immune system is never idle. Their task is to detect and eliminate invasive pathogens, and they have no time to lose. The adaptive immune system identifies infectious organisms by recognizing foreign proteins on the surfaces of bacteria, viruses and unicellular protozoans. The interaction of these antigens with immune cells triggers a series of downstream events, which in most cases leads to the elimination of the pathogen.
But pathogenic organisms have developed strategies that enable them to escape detection by the immune system, and the strategies employed by remotely related organisms are often remarkably similar to each other. One way of confusing the immune system is to increase the structural heterogeneity of the antigens it encounters. In bacteria,pathogenic yeast and parasites this can be done by randomly activating different members of gene families, which code for non-identical versions of the proteins expressed on their surfaces. This strategy essentially a