Journal of neurotrauma
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Journal of neurotrauma · Nov 2020
Multidimensional mapping of brain-derived extracellular vesicle (EV) miRNA biomarker for traumatic brain injury diagnostics.
The diagnosis and prognosis of traumatic brain injury (TBI) is complicated by variability in the type and severity of injuries and the multiple endophenotypes that describe each patient's response and recovery to the injury. It has been challenging to capture the multiple dimensions that describe an injury and its recovery to provide clinically useful information. To address this challenge, we have performed an open-ended search for panels of microRNA (miRNA) biomarkers, packaged inside of brain-derived extracellular vesicles (EVs), that can be combined algorithmically to accurately classify various states of injury. ⋯ Many of these pathways are shared between the pre-clinical model and the clinical samples, and present distinct signatures across different injury models and times elapsed after injury. Using this map of EV miRNA, we applied machine learning to define a panel of biomarkers to successfully classify specific states of injury, paving the way for a prognostic blood test for TBI. We generated a panel of eight miRNAs (miR-150-5p, miR-669c-5p, miR-488-3p, miR-22-5p, miR-9-5p, miR-6236, miR-219a.2-3p, miR-351-3p) for injured mice versus sham mice and four miRNAs (miR-203b-5p, miR-203a-3p, miR-206, miR-185-5p) for TBI patients versus healthy controls.
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Journal of neurotrauma · Nov 2020
ReviewPaths to successful translation of new therapies for severe TBI in the golden age of traumatic brain injury research: A Pittsburgh vision.
New neuroprotective therapies for severe traumatic brain injury (TBI) have not translated from pre-clinical to clinical success. Numerous explanations have been suggested in both the pre-clinical and clinical arenas. Coverage of TBI in the lay press has reinvigorated interest, creating a golden age of TBI research with innovative strategies to circumvent roadblocks. ⋯ TBI research from concussion to coma can cross-pollinate and further advancement of new therapies. Misconceptions can stifle/misdirect TBI research and deserve special attention. Finally, we synthesize an approach to deliver therapeutic breakthroughs in this golden age of TBI research.
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Journal of neurotrauma · Nov 2020
ReviewThe Clinical Relevance of Behavior Testing in Animal Models of Traumatic Brain Injury.
Traumatic brain injury (TBI) is a leading cause of morbidity worldwide, with patients often suffering from consequences such as cognitive deficits, social abnormalities, anxiety, depression, pain, and motor dysfunction. Given that these impairments often have a significant impact on the patient's quality of life, a key aim of therapeutic intervention in TBI is to mitigate these effects. Translational strategies to develop such interventions have heavily featured animal models of TBI. ⋯ However, in light of the past translational failures that have plagued the TBI field, the clinical relevance of these preclinical behavioral tests is now being scrutinized. This article will summarize the behavioral consequences of TBI in humans; describe common methods available for testing cognition, social function, motor ability, pain, as well as depression- and anxiety-like behaviors in animal models of TBI; provide an overview of the results from TBI animal model studies that have utilized these methods; and discuss these pre-clinical behavior methods and findings in terms of their relevance to the clinical TBI setting. We conclude that there is translational value in these methods and their related findings, but also suggest strategies and future research to improve the clinical relevance of behavior testing in animal models of TBI.
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Journal of neurotrauma · Nov 2020
ReviewPharmacological Optimization for Successful Traumatic Brain Injury Drug Development.
The purpose of this review is to highlight the pharmacological barrier to drug development for traumatic brain injury (TBI) and to discuss best practice strategies to overcome such barriers. Specifically, this article will review the pharmacological considerations of moving from the disease target "hit" to the "lead" compound with drug-like and central nervous system (CNS) penetrant properties. In vitro assessment of drug-like properties will be detailed, followed by pre-clinical studies to ensure adequate pharmacokinetic and pharmacodynamic characteristics of response. ⋯ This review will detail the important considerations in determining in vivo pre-clinical dose selection, as well as cross-species and human equivalent dose selection. Specific use of allometric scaling, pharmacokinetic and pharmacodynamic criteria, as well as incorporation of biomarker assessments in human dose selection for clinical trial design will also be discussed. The overarching goal of this review is to detail the pharmacological considerations in the drug development process as a method to improve both pre-clinical and clinical study design as we evaluate novel therapies to improve outcomes in patients with TBI.
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Journal of neurotrauma · Nov 2020
ReviewData Dissemination: Shortening the Long Tail of Traumatic Brain Injury Dark Data.
Translation of traumatic brain injury (TBI) research findings from bench to bedside involves aligning multi-species data across diverse data types including imaging and molecular biomarkers, histopathology, behavior, and functional outcomes. In this review we argue that TBI translation should be acknowledged for what it is: a problem of big data that can be addressed using modern data science approaches. We review the history of the term big data, tracing its origins in Internet technology as data that are "big" according to the "4Vs" of volume, velocity, variety, veracity and discuss how the term has transitioned into the mainstream of biomedical research. ⋯ Throughout our discussion we highlight the need to pull data from diverse sources including unpublished data ("dark data") and "long-tail data" (small, specialty TBI datasets undergirding the published literature). We review a few early examples of published articles in both the pre-clinical and clinical TBI research literature to demonstrate how data reuse can drive new discoveries leading into translational therapies. Making TBI data resources more Findable, Accessible, Interoperable, and Reusable (FAIR) through better data stewardship has great potential to accelerate discovery and translation for the silent epidemic of TBI.