Objective: Despite treatments which reduce relapses in multiple sclerosis (MS), many patients continue to experience progressive disability accumulation. MS is associated with metabolic disruptions and cerebral metabolic stress predisposes to tissue injury and possibly impaired remyelination. Additionally, myelin homeostasis is metabolically expensive and reliant on glycolysis.
View Article and Find Full Text PDFChronic kidney disease mineral bone disorder (CKD-MBD) is a complex clinical syndrome responsible for the accelerated cardiovascular mortality seen in individuals afflicted with CKD. Current approaches to therapy have failed to improve clinical outcomes adequately, likely due to targeting surrogate biochemical parameters as articulated by the guideline developer, Kidney Disease: Improving Global Outcomes (KDIGO). We hypothesized that using a Systems Biology Approach combining machine learning with mathematical modeling, we could test a novel approach to therapy targeting the abnormal movement of mineral out of bone and into soft tissue that is characteristic of CKD-MBD.
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