Journal of neurotrauma
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Journal of neurotrauma · Mar 2017
A Mouse Model of Bilateral Cervical Contusion-Compression Spinal Cord Injury.
Cervical spinal cord injury (cSCI) occurs in over half of all cases of traumatic spinal cord injury (SCI), yet we lack therapies that can generate significant functional recovery in these patients. The development of animal models of cSCI will aid in the pre-clinical assessment of therapies and in understanding basic pathophysiological mechanisms. Here, we describe a clinically relevant model of cervical contusion-compression injury in the mouse. ⋯ Volumetric analysis of protein kinase C gamma (PKCgamma)-stained axons revealed that this injury results in significant damage to the corticospinal tract caudal to the injury site. Finally, we used quantitative real-time polymerase chain reaction to show that genes associated with inflammation and glial scarring are upregulated as a result of injury. This study confirms that we can effectively model bilateral cervical injury in the mouse and provides a framework for future studies using this model to assess therapies.
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Journal of neurotrauma · Mar 2017
Altered wiring of the human structural connectome in adults with mild traumatic brain injury.
In this study, structural connectivity after mild traumatic brain injury (mTBI) was examined from a network perspective, with a particular focus on post-traumatic complaints. Fifty-three patients with and without self-reported complaints at 2 weeks after uncomplicated mTBI were included, in addition to 20 matched healthy controls. Diffusion weighted imaging was performed at 4 weeks post-injury, and neuropsychological tests measuring processing speed and verbal memory were administered at 3 months post-injury to determine cognitive outcome. ⋯ Additionally, significant correlations were found between higher betweenness centrality values of language areas and lower verbal memory scores in patients with mTBI. In conclusion, our findings may indicate that global graph measures of the structural connectome are associated with pre- and/or non-injury-related factors that determine the susceptibility to developing (persistent) complaints after mTBI. Further, correlations between graph measures and neuropsychological test scores could suggest early compensatory mechanisms to maintain adequate cognitive performance.
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Journal of neurotrauma · Mar 2017
[18F]FDG-PET Combined with MRI Elucidates the Pathophysiology of Traumatic Brain Injury in Rats.
Non-invasive measurements of brain metabolism using 18F-fluorodeoxyglucose (FDG) with positron emission tomography (PET) may provide important information about injury severity following traumatic brain injury (TBI). There is growing interest in the potential of combining functional PET imaging with anatomical and functional magnetic resonance imaging (MRI). This study aimed to investigate the effectiveness of combining clinically available FDG-PET with T2 and diffusion MR imaging, with a particular focus on inflammation and the influence of glial alterations after injury. ⋯ Glial activation was not detected in the amygdala but neuronal damage was evident, as the amygdala was the only region to show a reduction in both FDG uptake and ADC at sub-acute time-points. Overall, FDG-PET detected glial activation but was confounded by the presence of cell damage, whereas MRI consistently detected cell damage but was confounded by glial activation. These results demonstrate that FDG-PET and MRI can be used together to improve our understanding of the complex alterations in the brain after TBI.
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Journal of neurotrauma · Mar 2017
Detection of Mild Traumatic Brain Injury by Machine Learning Classification using Resting State Functional Network Connectivity and Fractional Anisotropy.
Traumatic brain injury (TBI) may adversely affect a person's thinking, memory, personality, and behavior. While mild TBI (mTBI) diagnosis is challenging, there is a risk for long-term psychiatric, neurologic, and psychosocial problems in some patients that motivates the search for new and better biomarkers. Recently, diffusion magnetic resonance imaging (dMRI) has shown promise in detecting mTBI, but its validity is still being investigated. ⋯ A t test analysis revealed significant increase in rsFNC between cerebellum versus sensorimotor networks and between left angular gyrus versus precuneus in subjects with mTBI. These outcomes suggest that inclusion of both common and unique information is important for classification of mTBI. Results also suggest that rsFNC can yield viable biomarkers that might outperform dMRI and points to connectivity to the cerebellum as an important region for the detection of mTBI.