Research

Traumatic brain injury (TBI) is one of the world’s major causes of deaths and disability. Although laboratory models have successfully simulated TBI, the exact force magnitudes and directions that initiate TBI at the single cell level are still unknown. This information is critically important, since the clinical effects of TBI are rooted in molecular changes at the cellular level in direct response to the mechanical loading. To close this knowledge gap and to substantially improve current medical diagnostics and evaluation strategies of TBI, this project lays the foundation for the first, quantitative, cellular-based TBI criterion. Specifically, the injury criterion will be constructed by accounting for both primary and secondary injury incurred during a TBI.

Our approach integrates novel, state-of-the-art synergistic custom-developed mechanical loading devices with advanced 3D microscopy, 3D cell culture (polyculture) models, and advanced analyses tools. The use of deep learning convolution-based neural networks is aiding in the identification of important cellular phenotypes in regulating the secondary injury response, which is a key factor in being able to resolve an accurate, and predictive injury threshold criterion. Through this new criterion it will eventually be possible to objectively and immediately evaluate and screen military and civilian personnel for TBI at the point of care.

One of the major challenges in traumatic brain injury detection is the current dependency on measurable symptoms, yet many mild TBIs present themselves without discernible symptoms to the individual. Thus, significant effort is underway for establishing reliable, detectable biomarkers indicative of physical trauma during a TBI.  While some biomarkers including glial fibrillary acidic protein (GFAP) and a neuronal biomarker (UCHL1) have been thoroughly investigated and shown signs of promise for detecting TBI in peripheral blood or saliva samples, actual expression levels and time points of biomarker release due to injury remain only poorly understood and resolved and thus hampering any real translation into the clinical space.

To address this significant technological and scientific hurdle, this project is developing a unique micro mTBI platform and dynamically tracking the expression levels of several known soluble mTBI markers within a physiologically realistic model of brain tissue.  By integrating a novel, custom-designed TBI impact device with full 4D multiphoton imaging access capability with a state-of-the-art 3D cortical spheroid model, this project will directly correlate injury on neural tissue with soluble biomarker expression profiles at the point of release.

Besides physical alteration in cellular homeostasis during a traumatic brain injury (TBI) event, disturbances to electrical activity have been found to impair executive functions at potentially lower strain thresholds than are required to induce cell death. Excitotoxicity, excessive glutamate secretion, is hypothesized to be responsible for adverse alterations in Ca2+ dynamics post TBI. However, the literature shows inconsistencies in the event timeline, relevant mechanisms, and the underlying biochemical and electrophysiological responses. This study employs a stretchable in-vitro system and a comprehensive data analysis to delineate network disruption under varying mechanical loads at hyperacute and acute time points. The data will serve as the basis for determining a specific critical strain and strain rate threshold for Ca2+ signal dysfunction, which is vital for refining predictive models and devising protective strategies against TBI.

In order to study and understand the force propagation in highly compliant tissues and tissue surrogates, we are developing highly compliant, conforming force sensors capable of recording ultra-low forces.  Specifically, we design a multi-walled carbon nanotubes (MWCNTs), graphene, and elastomer polydimethylsiloxane (PDMS) based soft piezoresistive sensor. The sensor is fabricated using simple and cost-effective methods that provide significant form factor flexibility for the sensor to be employed on flat, curved, dry and/or wet surfaces.

A closed-loop time-frequency domain analysis shows that the sensor features a broadband detection range of 1-1000 Hz, stretchability up to 40%, and strain resolution of 0.1% making it a versatile sensor for the application of measuring mechanical loads in soft tissues as well as health monitoring in structural applications.

Blast exposure and impacts to the head can produce low pressure regions within the brain. It is hypothesized that sufficiently low, or tensile, pressures can generate cavitation within the brain parenchyma. However, detailed knowledge of critical cavitation pressure levels or thresholds are still missing, leaving us with an incomplete picture of cavitation as a possible mechanism of brain injury. This project is developing an optically clear skull-brain surrogate to investigate critical thresholds of cavitation nuclear under TBI impact conditions.

Continuous electromagnetic waves (EM) waves form the basis for today’s telecommunications technologies. Frequencies ranging from 300 MHz to 5 GHz are generated daily with devices such as cell phones, computers, and microwave ovens. Exposure to continuous waves is generally considered safe. However, the quantitative effects of pulsed waves at similar frequencies on biological tissues remain poorly understood. Short-pulsed EM waves, which have a pulse-width shorter than the characteristic wave speed of the material (or tissue) under investigation, have been shown capable of generating significant thermoelastic stresses, especially in soft materials. This carries a potential risk of cellular injury when imparted to vital soft tissues. As technology expands to utilize higher frequency and pulsed-EM sources to transfer information, the potential for harmful exposure increases.

Leveraging our expertise in cellular traumatic brain injury, cellular mechanics, quantitative imaging, and live cell and tissue culture we aim to quantify EM exposure on soft and biological materials to establish its cellular pathology and whether such exposure can cause brain injury.

Reliable predictions of biological soft tissue response to mechanical insults requires an appropriate resolution of the tissue’s constitutive behavior at a given loading rate. While determination of low, quasi-static strain rate properties is relatively straightforward and well-established, high-rate material characterization for blast, ballistic, and blunt exposure are difficult to acquire and therefore are still not well-defined in the literature. Computational head models, for example, are used to study traumatic brain injuries and can possess high geometric (anatomic) fidelity. However, uncertainties regarding the high-strain-rate constitutive response of brain tissue remain a significant limitation on the predictive capabilities of such models. To address and overcome these challenges, we employ a recently developed high to ultra-high-rate soft material rheology technique based on inertial microcavitation, termed Inertial Microcavitation Rheology (IMR), which is capable of constitutively characterizing soft tissues and gels at strain rates ranging between 10³ s^-1 and 10⁸ s^-1, to characterize the anatomically-relevant constitutive properties of porcine brain tissue.

We are part of PANTHER – an interdisciplinary research hub dedicated to advancing the understanding, detection, and prevention of traumatic brain injuries.

https://www.panther.engr.wisc.edu/