• Albert Hyllested posted an update a month ago

    Mitochondria play a critical role in regulating cellular processes including ATP production, intracellular calcium signaling and generation of reactive oxidative species (ROS). Neurons rely on mitochondrial function to perform a range of complex processes, and mitochondrial dysfunctions have been shown to have an impact in pathologies of the nervous system. Yet, neurons contain a finite number of mitochondria, and their location is known to change in response to a number of factors including age and cellular activity, thereby impacting neuronal response. In this paper, we introduce a novel computational model of mitochondria motility that focuses on their movements along the axon. We describe the biological processes involved and the main parameters of the model. We use the model to investigate how some of these parameters affect the ability of mitochondria to position themselves in regions of high energy demand. Finally, we discuss the significance of our work and its downstream applications in further understanding pathologies of the nervous system such as Alzheimer’s disease, and help identify potential novel therapeutic targets.In this work we evaluated the maximum temperature reached by the head tissues and transducers during TTFields treatment when the thermal parameters were changed. ODM208 cost We used Pennes’ equation to obtain the temperature distribution and we ran our studies using COMSOL Multiphysics. We observed that, among the parameters we tested, changes in the scalp thermal conductivity and grey matter blood perfusion were the ones that led to the highest temperature variations.Clinical Relevance- This work shows that the uncertainty regarding the thermal parameters of biological tissues might lead to significant changes in the temperature distribution when modeling heat transfer during TTFields therapy.Simulations that are meant to determine the steady-state distribution of a diffusible solute such as oxygen in tissues have typically used finite difference methods to solve the diffusion equation. Finite difference methods require a tissue mesh with enough points to resolve oxygen gradients near and between discrete blood vessels. The large number of points that are typically required can make these calculations very slow. In this paper, we investigate a numerical method known as the Green’s function method which is not bound by the same constraint. The Green’s function method is expected to yield an accurate oxygen distribution more quickly by requiring fewer mesh points. Both methods were applied to calculate the steady state oxygen distribution in a model simulation region. When the Green’s function calculation used meshes with 1/2, 1/4 and, 1/8 of the resolution required for the finite-difference mesh, there was good agreement with the finite difference calculation in all cases. When the volume of the domain was increased 8-fold the Green’s function method was able to calculate the O2 field in 22 minutes, whereas the finite difference calculation is expected to take approximately 1 week. The number of steps required for the Green’s function calculation increases quadratically with the number of points in the tissue mesh. As a result, small meshes are calculated very quickly using Green’s functions, while for larger mesh sizes this method experiences a significant decrease in efficiency.We have refactored the Pulse Physiology Engine respiratory software with enhanced parameterization for improved simulation functionality and results. Realistic patient variability can be applied using discretized lumped-parameters that define lung volumes, compliances, and resistances. A new sigmoid compliance waveform helps meet validation of compartment pressures, flows, volumes, and substance values. Further parameterization and enhanced logic for the application of pathophysiology allows for more accurate modeling of both restrictive and obstructive diseases for mild, moderate, and severe cases.Clinical Relevance- This free and open model provides a well-validated respiratory system for integration with medical simulations and research. It improves the Pulse modeling software and allows for new, low-cost training and in silico testing use-cases. Applications include virtual/augmented environments, manikin-based simulations, and clinical explorations.Iron plays important roles in healthy brain but altered homeostasis and concentration have been correlated to aging and neurodegenerative diseases. Iron enters the central nervous system by crossing the brain barrier systems the Blood- Brain Barrier separating blood and brain and the Blood-Cerebrospinal Fluid Barrier (BCSFB) between blood and CSF, which is in contact with the brain by far less selective barriers. Herein, we develop a two-compartmental model for the BCSFB, based on first-order ordinary differential equations, performing numerical simulations and sensitivity analysis. Furthermore, as input parameters of the model, experimental data from patients affected by Alzheimer’s disease, frontotemporal dementia, mild cognitive impairment and matched neurological controls were used, with the aim of investigating the differences between physiological and pathological conditions in the regulation of iron passage between blood and CSF which can be possibly targeted by therapy.This paper describes a method for deciphering major drivers of bacterial stress response using an empirically informed computational approach. We develop a working model of iron flux regulation and concomitant oxidative stress response in Escherichia coli. The integrated model is used to investigate the temporal effects of iron and hydrogen peroxide stress on bacterial growth and metabolism. We employ a sensitivity analysis platform and, using various measures, probe for major mechanistic drivers of the bacterial response to iron stress.Cardiac muscle cells are the fundamental building blocks of the heart, yet little is known about their mechanical properties in either healthy or diseased states. While many have explored unloaded myocyte behavior under a variety of interventions, methods for force measurements are limited due to cell fragility. Here, we present a custom device for manipulation and mechanical testing of hydrogels embedded with delicate cardiac muscle cells. Consisting of a custom disposable flexure, which is easily interchangeable, the device has the potential for high throughput testing of cell-gel constructs. Additionally, the mechanical testing device is the size of a microscope slide – appropriate for use in most microscopes, for simultaneous imaging of the sample. The mechanical properties of a gelatin-methacryloyl hydrogel sample were assessed, and 3D volumes of gel imaged using a confocal microscope. The Young’s modulus of the gel was found to be 33kPa.Clinical Relevance- High-throughput testing provides the potential to gain insight into cardiac cell mechanics.

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