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Ashfaq Adnan

Publications and source records attributed to Ashfaq Adnan.

7 recordsLinked to original sources
arXiv2026

Head Impact Characterization and Cellular Response of a Live-neuron cell-integrated Biomechanical Full-body Surrogate Model

In this study, we develop a novel integrated framework that links the impact response with cellular dynamics using a live-neuron cell-integrated biomechanical full-body surrogate model. The impact event is simulated by allowing the surrogate model to fall from controlled seated release angles of 30-degree, 60-degree, and 90-degree. Three vertically stacked cell-culture Petri dishes, each containing live SH-SY5Y neuroblastoma cells, were placed inside the head of a commercially available surrogate model. The dynamic response of the impact event was evaluated using acceleration measurements from six accelerometers, comprising three sensors mounted on the head surface and three embedded in series with the cell stacks, along with kinematic measurements of the fall and deformation of the head model. In parallel, an OpenSim-based modified musculoskeletal model was used to simulate the fall experiment. We found that variation in contact stiffness produced the largest change in the predicted head acceleration in the simulation. When the cellular response and the measured accelerations are compared, oxidative stress and cell viability showed trends consistent with the regional acceleration and angle of fall. At the 90-degree fall, where median peak linear accelerations ranged from 170-258g, and the maximum headform deformation was approximately 9.4 mm, oxidative stress increased to approximately twice that of the control sample. We also quantified the cellular drift of SH-SY5Y cells, which is focal in nature for the 90-degree impact condition. The corresponding fall scenarios were also simulated in OpenSim and a preliminary calibration relationship was developed to compare the kinematic responses of the physical surrogate and musculoskeletal model. Finally, the framework provides a basis for relating experimental surrogate measurements to human head-neck response during impact.

q-bio.TO↗
arXiv2026

A Validated Data-driven Subject and Vehicle Specific Nonlinear Biodynamic Model for Predicting Upper-Body Response in Vehicle Ride

A six-degree-of-freedom (6-DOF) nonlinear lumped-parameter biodynamic model of the seated human upper body is formulated to predict human response under different unknown loading conditions. The model consists of six anatomically partitioned cascade body segments: pelvis, lower torso, central torso, upper torso, neck, and head. The joints are connected through nonlinear viscoelastic joints incorporating strain-stiffening restoring forces consistent with the nonlinear constitutive behavior of biological soft tissue. Fifteen subject-specific mechanical parameters are considered as design variables. The design variables are six joint natural frequencies, six viscous damping ratios, one Rayleigh coefficient, one nonlinear stiffening scale, and one mass scale. The subject-specific design variables are identified from three distinct vehicular loading cases using a hybrid two-phase optimization strategy. Particle Swarm Optimization (PSO) globally searches on a frequency-domain surrogate and seeds a bounded Nelder-Mead refinement for the full nonlinear Ordinary Differential Equation (ODE) response. A rigorous parameter idealization methodology, based on error-weighted geometric mean in log space, was implemented to fuse the multi-case optima into a single subject-representative consensus parameter set. The idealized model retains physical interpretability across loading scenarios and is subsequently used in forward dynamics to predict and validate the subject's experimental response. The framework constitutes a complete subject-specific biodynamic pipeline, from experimental data through optimization, idealization, and forward prediction, suitable for occupational health assessment and protective equipment design across diverse loading scenarios.

q-bio.TO↗
arXiv2024

A biomechanical study of neck strength and impact dynamics on head and neck injury parameters

Traumatic brain injuries (TBI) are considered a silent epidemic. It affects many people, from automobiles to sports to service members. In this study, we employed a musculoskeletal head-neck model to understand the effect of impact locations, characteristics, and neck strength on head and neck injury severity. Three types of impact forces were studied: low-velocity impact (LVI), intermediate-velocity impact (IVI), and high-velocity impact (HVI). We investigated six parameters: linear and rotational accelerations, the Generalized Acceleration Model For Brain Injury Threshold (GAMBIT), neck force, neck moment, and Neck Injury Criteria (NIC). We consider seven impact locations, three neck strengths, and three impact characteristics. We studied a total of 63 cases. It was found that the linear accelerations do not change much with different neck strengths and impact locations. The impact locations have a significant effect on head and neck injury parameters, and anterolateral impact is the most risky impact location for both head and neck. The maximum average rotational acceleration is for anterolateral eccentric impact which is 4.75 times more than the average anterior central impact. The lateral impacts generate about 10% more linear accelerations than anterior and posterior impacts. Neck forces do not vary more than 20% with impact locations and neck strength. The average head and neck injury parameters do not vary more than 10% based on neck strength. Impact characteristics have a significant role in GAMBIT and NIC. The average GAMBIT for IVI and HVI were 1.44 and 1.54 times higher than LVI. In summary, the anterolateral eccentric impact has a higher probability of head and neck injury than the other six impact locations. These findings provide objective evidence that can inform injury prevention strategies as well as aid tissue and cellular level studies.

q-bio.TO↗
arXiv2021

Shock Induced Damage Mechanism Of Perineuronal Net

ECM components, such as the Perineuronal net (PNN), one of the most prevalent parts surrounding the neuronal cell. PNN is a protective net-like structure regulating neuronal activity such as neurotransmission, charge balance and generates an action potential. Shock induced damage of this essential component may cause neuronal cell death and potentially leads to CTE, AD diseases, PTSD, etc. The shock generated possibly during an accident, improvised devie explosion or collision between NFL players may lead to damage to this safety net. The goal is to investigate the mechanics of PNN under shock wave. To understand the mechanics of PNN, mechanical properties of different PNN components such as glycan, GAG, and protein need to be evaluated. In this study, we evaluated the mechanical strength of PNN molecules and the interfacial strength between the components of PNN. Afterward, we have assessed the PNN molecules' damage efficiency at various conditions such as shock speed, preexisting bubble, and boundary conditions. The secondary structure altercation of the protein molecules of the PNN has been analyzed to evaluate damage intensity under varying shock loading. At higher shock speed, damage intensity is more elevated, and hyaluronan is most likely to break at the rigid junction. The primary structure of the protein molecules is most unlikely to fail. Instead, the molecules' secondary bonds will be altered. Our study suggests that the number of hydrogen bonds during the shock wave propagation decreased.

physics.bio-ph↗
arXiv2021

Mechanical Behavior of Axonal Actin, Spectrin, and Their Periodic Structure: A Brief Review

Actin and spectrin are important constituents of axonal cytoskeleton. Periodic actin and spectrin structures are found in dendrites, initial segment of axon, and main axon. Actin and spectrin periodicity has been hypothesized to be manipulating the axon stability and mechanical behavior. Several experimental and computational studies have been performed focusing on the mechanical behavior of actin, spectrin, and actin and spectrin network. However, most of the actin studies focus on typical long F actin and do not provide quantitative comparison between the mechanical behavior of short and long actin filaments. Also, most of the spectrin studies focus on erythrocytic spectrin and do not shed light on the behavior of structurally different axonal spectrin. Only a few studies have highlighted forced unfolding of axonal spectrin which are relevant to brain injury scenario. A comprehensive, strain rate dependent mechanical study is still absent in the literature. Moreover, the current opinions regarding periodic actin and spectrin network structure in axon are disputed due to conflicting results on actin ring organization as argued by recent superresolution microscopy studies. This review summarizes the ongoing limitations in this regard and provides insights on possible approaches to address them. This study will invoke further investigation into relevant high strain rate response of actin, spectrin, and actin and spectrin network shedding light into brain pathology scenario such as traumatic brain injury.

physics.bio-ph↗
arXiv2020

Effect of Random Fiber Network and Fracture Toughness on the Onset of Cavitation in Soft Materials

Experimental and theoretical observations have agreed that the onset of cavitation in soft materials requires higher tensile pressure than pure water. The extra tensile pressure is required since the cavitating bubble needs to overcome the elastic energy in soft materials. In this manuscript, we have developed two models to study and quantify the extra tensile pressure. In the first approach, we proposed a strain energy based random fiber network (RFN) failure criteria in which interaction between the cavitating bubble and RFN is considered. Gelatin samples are prepared for different concentrations, and SEM images are used to study the microstructural properties of the RFN. A unit-cell model is introduced to evaluate the geometrical and mechanical properties of the RFN. The network strain energy formulation is then coupled with the bubble growth, and the critical condition is set as the fibers ultimate failure strain. We considered soft materials as homogeneous hyper-elastic Ogden material, and fracture-based failure criteria are proposed in the second approach. The critical energy release rate is considered for quantifying the extra tensile pressure. Both the models are then compared with the existing cavitation onset criteria of rubber like materials. The validation is done with the experimental results of threshold tensile pressure for different gelatin concentrations. We have found that due to the large distribution of the pore size in the network, the nucleation pressure is similar to water. Both models can moderately predict the extra tensile pressure within the intermediate range of gelatin concentrations. For low concentration, the network's non-affinity plays a significant role and must be incorporated. On the other hand, for higher concentrations, the entropic deformation dominates, and strain energy formulation is not adequate.

cond-mat.soft↗