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Glial Model for Traumatic Brain Injury: Network Strain Field and Inflammation Induced by Repeated Mechanical Impacts In Vitro

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Abstract

Traumatic brain injury (TBI) is a form of acquired brain trauma in which sudden external mechanical insults damage brain structures and cells. With a wide range of severities, TBI induces inflammatory responses with neurodegeneration and dysfunction. To develop new treatments, reproducible models of implementation are needed. Moreover, these models need to exhibit high biological and mechanical fidelity to the injurious event that they are trying to mimic. Here, the Highly Automated Mechanical Impactor (HAMr) is used to deliver 64 controlled pressure-pulses of known magnitude and duration to mixed glia cultures as a model for repetitive TBI. The mechanical response of those glial networks was quantified in terms of induced strain histories using Digital Image Correlation (DIC) under high-speed microscopic imaging. Four hours post-impact, glial network shearing and gene expression increases of TNFα and IL-1α were observed. However, select microglia and astrocyte markers were unchanged. These findings validate HAMr as a tool that enables quantification of the cell-substrate strain history during impact loading while reproducibly inducing inflammation and damaging glial network integrity, which are both common consequences of TBI.

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Authors and Affiliations

  1. Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA

    S. Koumlis & V. Eliasson

  2. Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA

    H. Cheng, T. E. Morgan & C. E. Finch

  3. Structural Engineering Department, University of California San Diego, San Diego, CA, USA

    V. Eliasson

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  1. S. Koumlis
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  2. H. Cheng
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  5. V. Eliasson
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Correspondence to V. Eliasson.

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Koumlis, S., Cheng, H., Morgan, T.E. et al. Glial Model for Traumatic Brain Injury: Network Strain Field and Inflammation Induced by Repeated Mechanical Impacts In Vitro . Exp Mech 58, 125–135 (2018). https://doi.org/10.1007/s11340-017-0338-3

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