Biology subjects

Alshareef, A.

Publications and source records attributed to Alshareef, A..

3 recordsLinked to original sources

bioRxiv2026

Age and Gender-Dependent Group-Average Brain Biomechanics Models for Traumatic Brain Injury

Experimental studies involving mechanical loading of the human head and brain in vivo are necessarily limited, making computational modeling essential for advancing our understanding of brain biomechanics. Demographic factors such as age and gender are known to influence brain anatomical structures, material properties, and potentially vulnerability to injurious loading. To address this, we construct six group-average brain models stratified by age and gender from a total of 135 subjects, and investigate the mechanical responses of these "group-average brains" using computational simulations. We use Pearson correlations to assess to what degree the group-average models represent individuals within each demographic category, showing strong correlations. Further, our p-value hypothesis test of the first principal strain across the six groups shows significant differences. This study demonstrates that age- and gender-stratified group-average models can effectively represent biomechanical responses of the individuals within the groups, and can reveal meaningful demographic differences that may influence susceptibility to traumatic brain injury. We show that the age-dependent change in material properties plays a greater role than anatomical changes in driving differences in the deformations. We hope to see increased utilization of these group-average models in both research and clinical applications.

biophysics↗

bioRxiv2022

Absorbable Conductive Electrotherapeutic Scaffolds (ACES) for Enhanced Peripheral Nerve Regeneration and Stimulation

While peripheral nerve stimulation (PNS) has shown promise in applications ranging from peripheral nerve regeneration after injury to therapeutic organ stimulation, clinical implementation has been impeded by various technological limitations, including surgical placement, lead migration, and atraumatic removal. Here, we describe the design and validation of a new platform for nerve regeneration and interfacing: Absorbable, Conductive, Electrotherapeutic Scaffolds (ACES). ACES are comprised of an alginate/poly-acrylamide interpenetrating network hydrogel optimized for both open and minimally invasive percutaneous approaches. In a rodent model of sciatic nerve repair, ACES significantly improved motor and sensory recovery (p < 0.05), increased muscle mass (p < 0.05), and increased axonogenesis (p < 0.05). Triggered dissolution of ACES enabled atraumatic, percutaneous removal of leads at forces significantly lower than controls (p < 0.05). In a porcine model, ultrasound-guided percutaneous placement of leads with an injectable ACES near the femoral and cervical vagus nerves facilitated stimulus conduction at significantly greater lengths than saline controls (p < 0.05). Overall, ACES facilitated lead placement, stabilization, stimulation and atraumatic removal enabling therapeutic PNS as demonstrated in small and large animal models.

bioengineering↗

bioRxiv2021

Development and Validation of Subject-Specific 3D Human Head Models Based on a Nonlinear Visco-Hyperelastic Constitutive Framework

Computational models of the human head are promising tools for the study and prediction of traumatic brain injuries (TBIs). Most available head models are developed using inputs (i.e., head geometry, material properties, and boundary conditions) derived from ex-vivo experiments on cadavers or animals and employ linear viscoelasticity (LVE)-based constitutive models, which leads to high uncertainty and poor accuracy in capturing the nonlinear response of brain tissue under impulsive loading conditions. To resolve these issues, a framework for the development of fully subject-specific 3D human head models is proposed, in which model inputs are derived from the same living human subject using a comprehensive in-vivo brain imaging protocol, and the viscous dissipation-based visco-hyperelastic constitutive modeling framework is employed. Specifically, brain tissue material properties are derived from in-vivo magnetic resonance elastography (MRE), and full-field strain-response of brain under rapid rotational acceleration is obtained from tagged MRI, which is used for model validation. The constitutive model comprises the Ogden hyperelastic strain energy density and the Upadhyay-Subhash-Spearot viscous dissipation potential. The simulated strain-response is compared with experimental data and with predictions from subject-specific models employing two commonly used LVE-based constitutive models, using a rigorous validation procedure that evaluates agreement in spatial strain distribution, temporal strain evolution, and differences in maximum values of peak and average strain. Results show that the head model developed in this work reasonably captures 3D brain dynamics, and when compared to LVE-based models, provides improvements in the prediction of peak strains and temporal strain evolution.

bioengineering↗