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Poster Session II - DIGITAL TRANSFORMATION, AI AND ROBOTICS 07.00 - DIGITAL TRANSFORMATION, AI AND ROBOTICS - 07.01 - TECHNOLOGY INNOVATIONS: ROBOTS, VIRTUAL REALITY, ARTIFICIAL INTELLIGENCE AND MORE P911 - ESOC25-2156 NOVEL AI-POWERED, TIME-ADJUSTED NET WATER UPTAKE IMAGING BIOMARKER DERIVED FROM NON-CONTRAST COMPUTED TOMOGRAPHY TO VISUALIZE EARLY INFARCTED TISSUE AND PREDICT REVERSAL POTENTIAL Jonathon Cummock 1,2,3 , Timea Hodics 4 , Rahul Ghosh 1,2,3,5 , John Volpi 4 , Stephen Wong 2,3,6 , Kelvin Wong 2,3,6 1 Texas A&M University College of Medicine, Bryan, United States, 2 Houston Methodist Hospital, Department of Systems Medicine and Bioengineering, Houston, United States, 3 Houston Methodist Academic Institute, The Ting Tsung and Wei Fong Chao Center for BRAIN, Houston, United States, 4 Houston Methodist Hospital, Department of Neurological Surgery and Neurological Institute, Houston, United States, 5 Texas A&M University College of Engineering, Department of Biomedical Engineering, College Station, United States, 6 Houston Methodist Hospital, Department of Radiology, Houston, United States Background and Aims: In acute ischemic stroke (AIS), net water uptake (NWU) is a method to quantify tissue edema to detect and visualize ischemia
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Thus, BPC 157, along with Nab2 , could serve as a controlling feedback mechanism and guarantee transient and controlled Egr1 activity (Tkalcevic et al., 2007) (consequently, Egr1 decreases later in the 24 hr period in the inferior caval vein while remaining increased in ovarian veins (Vukojevic et al., 2018), similar to its presentation in the hippocampus of ischemia/reperfusion rats)