Pei-Ying Chuang
University of Texas, USA
Title: Translational neuroscience trajectory-Big Data with bench evidence and clinical outcomes
Biography
Biography: Pei-Ying Chuang
Abstract
A wide-range of existing bench evidence and clinical outcome data has contributed to novel biological patterns and medical decisions in human health, disease and medicine. However, the lack of high-value phenotype vs. genetics interpretation between biological knowledge and clinical outcome still remains.
Purpose: To combine translational neuroscience studies with standardized-structure dataset and to establish significant brain-neuron protective knowledge with early medical intervention.
Method: 314 subjects enrolled in three prospective data sets were used. Clinical data were collected at neuro-trauma acute care units at two level-one trauma and stroke medical centers in the U.S. Inclusion criteria were basic characteristics, vital bedside and laboratory results, and neurological assessment tools (Glasgow Coma Scale, Glasgow Outcome Scale, and Disability Rankin Scale). Clinical diagnosis with cerebral hypoxia/ischemia was based on CT and MRI results. Bench evidence data were neuroglobin protein expression and neuroglobin genetic variation through peripheral blood and cerebro-spinal fluid during the first fourteen days after hospital admission.
Conclusion: Evidence-based medicine and personalized medicine were identified to provide a more effective health intervention approach and outcome prediction. Medical Bioinformatics technologies and main systematic concepts (biological mechanisms, physical condition, and functional outcomes) take into account the needs of the neurological survivors.
Future Direction: Health information technology systems and human genetics explore important advances in both basic science research and clinical care. A successful data analysis, trajectory will benefit robust clinical informatics systems and address the interaction of personalized genetic discoveries.