Cellular biomechanics of central nervous system injury

Meaney, David F.; Smith, Douglas H.

doi:10.1016/b978-0-444-52892-6.00007-6

Cited by 18 publications

(17 citation statements)

References 68 publications

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“…In contrast, the same region of increased FA can be found in both the in vivo and ex vivo mouse brain 12 weeks after CCI (b). The observations depicted in this figure demonstrate several of the key points described in the text neurocircuitry become evident during the chronic period following injury (Meaney & Smith, 2015).…”

Section: Sprouting Remodeling and Regenerationmentioning

confidence: 52%

“…For instance, observations in a model of focal cortical ischemia (Pierpaoli et al, 1993) have demonstrated increased diffusivity in nonischemic brain regions with edema adjacent to regions of decreased diffusivity where ischemic damage was later confirmed by histology. The implication of this for TBI research is that acutely increased diffusivity may indicate brain regions that undergo edema without cellular disruption, and possibly these areas will not progress to degenerative outcomes, while regions with acutely decreased diffusivity are more likely to have metabolic or Sato et al, 2001;Chen et al, 2003;Coleman, 2005;Stoica & Faden, 2010Assaf et al, 1997Van Putten et al, 2005;Immonen et al, 2009;Laitinen et al, 2015 axonal injury axon morphology changes including beading and varicosities reduction in anisotropy and reduction in diffusion, especially in the axial direction Johnson et al, 2013Budde et al, 2009;Jiang et al, 2011;Li et al, 2011;Bennett et al, 2012; van de Looij et al, 2012 neural plasticity sprouting, arborization increased number of coherent processes and new collaterals increased anisotropy and/or changed orientation Bach-y-Rita, 2003;Yiu & He, 2006;Werner & Stevens, 2015;Meaney & Smith, 2015Kharatishvili et al, 2007Hutchinson et al, 2012;Sierra et al, 2015 Oligodendrocytes demyelination direct damage, chronic pathology degenerating or lost decreased anisotropy Armstrong et al, 2016Jiang et al, 2011Budde et al, 2011;Li et al, 2014;Mac Donald, Dikranian, Song, et al, 2007 myelination repair remyelination regenerating normalized anisotropy…”

Section: Significancementioning

confidence: 99%

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Diffusion MRI and the detection of alterations following traumatic brain injury

Hutchinson

Schwerin

Avram

et al. 2017

J of Neuroscience Research

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This article provides a review of brain tissue alterations that may be detectable using diffusion MRI (dMRI) approaches and an overview and perspective on the modern dMRI toolkits for characterizing alterations that follow traumatic brain injury (TBI). Non-invasive imaging is a cornerstone of clinical treatment of TBI and has become increasingly used for pre-clinical and basic research studies. In particular, quantitative MRI methods have the potential to distinguish and evaluate the complex collection of neurobiological responses to TBI arising from pathology, neuroprotection and recovery. Diffusion MRI provides unique information about the physical environment in tissue and can be used to probe physiological, architectural and microstructural features. While well-established approaches such as diffusion tensor imaging (DTI) are known to be highly sensitive to changes in the tissue environment, more advanced diffusion MRI techniques have been developed that may offer increased specificity or new information for describing abnormalities. These tools are promising, but incompletely understood in the context of TBI. Furthermore, model dependencies and relative limitations may impact the implementation of these approaches and the interpretation of abnormalities in their metrics. The objective of this paper is to present a basic review and comparison across diffusion MRI methods as they pertain to the detection of the most commonly observed tissue and cellular alterations following TBI.

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Section: Sprouting Remodeling and Regenerationmentioning

confidence: 52%

Section: Significancementioning

confidence: 99%

Diffusion MRI and the detection of alterations following traumatic brain injury

Hutchinson

Schwerin

Avram

et al. 2017

J of Neuroscience Research

View full text Add to dashboard Cite

show abstract

“…While the whole brain undergoes dynamic tissue deformation at all levels of TBI, the white matter is at greatest risk of damage, possibly due to its highly organized, highly directional anisotropic structure. In particular, axon tracts have been shown to suffer selective damage in several unique ways due to a viscoelastic response at the cellular level . The resulting diffuse axonal injury (DAI) has long been identified as common neuropathological feature of higher levels of TBI where post‐mortem histopathological analyses have been possible.…”

Section: Human Pathology Of Ctementioning

confidence: 99%

“…In particular, axon tracts have been shown to suffer selective damage in several unique ways due to a viscoelastic response at the cellular level [25,26]. The resulting diffuse axonal injury (DAI) has long been identified as common neuropathological feature of higher levels of TBI where post-mortem histopathological analyses have been possible.…”

Section: Introductionmentioning

confidence: 99%

Modelling human pathology of traumatic brain injury in animal models

et al. 2019

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Traumatic brain injury (TBI) is caused by a head impact with a force exceeding regular exposure from normal body movement which the brain normally can accommodate. People affected include, but are not restricted to, sport athletes in American football, ice hockey, boxing as well as military personnel. Both single and repetitive exposures may affect the brain acutely and can lead to chronic neurodegenerative changes including chronic traumatic encephalopathy associated with the development of dementia. The changes in the brain following TBI include neuroinflammation, white matter lesions, and axonal damage as well as hyperphosphorylation and aggregation of tau protein. Even though the human brain gross anatomy is different from rodents implicating different energy transfer upon impact, especially rotational forces, animal models of TBI are important tools to investigate the changes that occur upon TBI at molecular and cellular levels. Importantly, such models may help to increase the knowledge of how the pathologies develop, including the spreading of tau pathologies, and how to diagnose the severity of the TBI in the clinic. In addition, animal models are helpful in the development of novel biomarkers and can also be used to test potential disease‐modifying compounds in a preclinical setting.

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“…These works identified several structures termed ‘mechanosensors’ that include the voltage-gated sodium channel, or NMDA receptor that responds to the mechanical forces induced by cell deformation with altered channel activation [87]. Data from these experiments are used to build in silico models of TBI [90–92].…”

Section: Cellular Biomechanics In Vitro and In Vivo Modelingmentioning

confidence: 99%

Big Data in traumatic brain injury; promise and challenges

Agoston

Langford

2017

Concussion

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Traumatic brain injury (TBI) is a spectrum disease of overwhelming complexity, the research of which generates enormous amounts of structured, semi-structured and unstructured data. This resulting big data has tremendous potential to be mined for valuable information regarding the “most complex disease of the most complex organ”. Big data analyses require specialized big data analytics applications, machine learning and artificial intelligence platforms to reveal associations, trends, correlations and patterns not otherwise realized by current analytical approaches. The intersection of potential data sources between experimental TBI and clinical TBI research presents inherent challenges for setting parameters for the generation of common data elements and to mine existing legacy data that would allow highly translatable big data analyses. In order to successfully utilize big data analyses in TBI, we must be willing to accept the messiness of data, collect and store all data and give up causation for correlation. In this context, coupling the big data approach to established clinical and pre-clinical data sources will transform current practices for triage, diagnosis, treatment and prognosis into highly integrated evidence-based patient care.

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Cellular biomechanics of central nervous system injury

Cited by 18 publications

References 68 publications

Diffusion MRI and the detection of alterations following traumatic brain injury

Diffusion MRI and the detection of alterations following traumatic brain injury

Modelling human pathology of traumatic brain injury in animal models

Big Data in traumatic brain injury; promise and challenges

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