Simultaneous electrophysiological and morphological assessment of functional damage to neural networks in vitro after 30-300 g impacts

Opening the black box of traumatic brain injury: a holistic approach combining human 3D neural tissue and an in vitro traumatic brain injury induction device

Traumatic brain injury (TBI) is caused by a wide range of physical events and can induce an even larger spectrum of short- to long-term pathophysiologies. Neuroscientists have relied on animal models to understand the relationship between mechanical damages and functional alterations of neural cells. These in vivo and animal-based in vitro models represent important approaches to mimic traumas on whole brains or organized brain structures but are not fully representative of pathologies occurring after traumas on human brain parenchyma. To overcome these limitations and to establish a more accurate and comprehensive model of human TBI, we engineered an in vitro platform to induce injuries via the controlled projection of a small drop of liquid onto a 3D neural tissue engineered from human iPS cells. With this platform, biological mechanisms involved in neural cellular injury are recorded through electrophysiology measurements, quantification of biomarkers released, and two imaging methods [confocal laser scanning microscope (CLSM) and optical projection tomography (OPT)]. The results showed drastic changes in tissue electrophysiological activities and significant releases of glial and neuronal biomarkers. Tissue imaging allowed us to reconstruct the injured area spatially in 3D after staining it with specific nuclear dyes and to determine TBI resulting in cell death. In future experiments, we seek to monitor the effects of TBI-induced injuries over a prolonged time and at a higher temporal resolution to better understand the subtleties of the biomarker release kinetics and the cell recovery phases.

Human-Derived Cortical Neurospheroids Coupled to Passive, High-Density and 3D MEAs: A Valid Platform for Functional Tests

With the advent of human-induced pluripotent stem cells (hiPSCs) and differentiation protocols, methods to create in-vitro human-derived neuronal networks have been proposed. Although monolayer cultures represent a valid model, adding three-dimensionality (3D) would make them more representative of an in-vivo environment. Thus, human-derived 3D structures are becoming increasingly used for in-vitro disease modeling. Achieving control over the final cell composition and investigating the exhibited electrophysiological activity is still a challenge. Thence, methodologies to create 3D structures with controlled cellular density and composition and platforms capable of measuring and characterizing the functional aspects of these samples are needed. Here, we propose a method to rapidly generate neurospheroids of human origin with control over cell composition that can be used for functional investigations. We show a characterization of the electrophysiological activity exhibited by the neurospheroids by using micro-electrode arrays (MEAs) with different types (i.e., passive, C-MOS, and 3D) and number of electrodes. Neurospheroids grown in free culture and transferred on MEAs exhibited functional activity that can be chemically and electrically modulated. Our results indicate that this model holds great potential for an in-depth study of signal transmission to drug screening and disease modeling and offers a platform for in-vitro functional testing.

Utilizing novel TBI-on-a-chip device to link physical impacts to neurodegeneration and decipher primary and secondary injury mechanisms

While clinical observations have confirmed a link between the development of neurodegenerative diseases and traumatic brain injuries (TBI), there are currently no treatments available and the underlying mechanisms remain elusive. In response, we have developed an in vitro pendulum trauma model capable of imparting rapid acceleration injuries to neuronal networks grown on microelectrode arrays within a clinically relevant range of g forces, with real-time electrophysiological and morphological monitoring. By coupling a primary physical insult with the quantification of post-impact levels of known biochemical pathological markers, we demonstrate the capability of our system to delineate and investigate the primary and secondary injury mechanisms leading to post-impact neurodegeneration. Specifically, impact experiments reveal significant, force-dependent increases in the pro-inflammatory, oxidative stress marker acrolein at 24 h post-impact. The elevation of acrolein was augmented by escalating g force exposures (30–200 g), increasing the number of rapidly repeated impacts (4–6 s interval, 3, 5 and 10×), and by exposing impacted cells to 40 mM ethanol, a known comorbidity of TBI. The elevated levels of acrolein following multiple impacts could be reduced by increasing time-intervals between repeated hits. In addition, we show that conditioned media from maximally-impacted cultures can cause cellular acrolein elevation when introduced to non-impact, control networks, further solidifying acrolein’s role as a diffusive-factor in post-TBI secondary injuries. Finally, morphological data reveals post-impact acrolein generation to be primarily confined to soma, with some emergence in cellular processes. In conclusion, this novel technology provides accurate, physical insults with a unique level of structural and temporal resolution, facilitating the investigation of post-TBI neurodegeneration.

An interdisciplinary computational model for predicting traumatic brain injury: Linking biomechanics and functional neural networks

The brain is a complex network consisting of neuron cell bodies in the gray matter and their axonal projections, forming the white matter tracts. These neurons are supported by an equally complex vascular network as well as glial cells. Traumatic brain injury (TBI) can lead to the disruption of the structural and functional brain networks due to disruption of both neuronal cell bodies in the gray matter as well as their projections and supporting cells. To explore how an impact can alter the function of brain networks, we integrated a finite element (FE) brain mechanics model with linked models of brain dynamics (Kuramoto oscillator) and vascular perfusion (Balloon-Windkessel) in this study. We used empirical resting-state functional magnetic resonance imaging (MRI) data to optimize the fit of our brain dynamics and perfusion models to clinical data. Results from the FE model were used to mimic injury in these optimized brain dynamics models: injury to the nodes (gray matter) led to a decrease in the nodal oscillation frequency, while damage to the edges (axonal connections/white matter) progressively decreased coupling among connected nodes. A total of 53 cases, including 33 non-injurious and 20 concussive head impacts experienced by professional American football players were simulated using this integrated model. We examined the correlation of injury outcomes with global measures of structural connectivity, neural dynamics, and functional connectivity of the brain networks when using different lesion methods. Results show that injurious head impacts cause significant alterations in global network topology regardless of lesion methods. Changes between the disrupted and healthy functional connectivity (measured by Pearson correlation) consistently correlated well with injury outcomes (AUC≥0.75), although the predictive performance is not significantly different (p>0.05) to that of traditional kinematic measures (angular acceleration). Intriguingly, our lesion model for gray matter damage predicted increases in global efficiency and clustering coefficient with increases in injury risk, while disrupting axonal connections led to lower network efficiency and clustering. When both injury mechanisms were combined into a single injury prediction model, the injury prediction performance depended on the thresholds used to determine neurodegeneration and mechanical tolerance for axonal injury. Together, these results point towards complex effects of mechanical trauma to the brain and provide a new framework for understanding brain injury at a causal mechanistic level and developing more effective diagnostic methods and therapeutic interventions.

Current advances in in vitro models of central nervous system trauma

CNS trauma is a prominent cause of mortality and morbidity, and although much effort has focused on developing treatments for CNS trauma-related pathologies, little progress has been made. Pre-clinical models of TBI and SCI suffer from significant drawbacks, which result in substantial failures during clinical translation of promising pre-clinical therapies. Here, we review recent advances made in the development of in vitro models of CNS trauma, the promises and drawbacks of current in vitro CNS injury models, and the attributes necessary for future models to accurately mimic the trauma microenvironment and facilitate CNS trauma drug discovery. The goal is to provide insight for the development of future CNS injury models and to aid researchers in selecting effective models for pre-clinical research of trauma therapeutics.