Geometrical nonlinear elasticity of axon under tension: A coarse-grained computational study.

Axon bundles cross-linked by microtubule (MT) associate proteins and bounded by a shell skeleton are critical for normal function of neurons. Understanding effects of the complexly geometrical parameters on their mechanical properties can help gain a biomechanical perspective on the neurological functions of axons and thus brain disorders caused by the structural failure of axons. Here, the tensile mechanical properties of MT bundles cross-linked by tau proteins are investigated by systematically tuning MT length, axonal cross-section radius, and tau protein spacing in a bead-spring coarse-grained model.

Mechanical Ventilator Parameter Estimation for Lung Health through Machine Learning.

Patients whose lungs are compromised due to various respiratory health concerns require mechanical ventilation for support in breathing. Different mechanical ventilation settings are selected depending on the patient's lung condition, and the selection of these parameters depends on the observed patient response and experience of the clinicians involved. To support this decision-making process for clinicians, good prediction models are always beneficial in improving the setting accuracy, reducing treatment error, and quickly weaning patients off the ventilation support.

Identification of predictive MRI and functional biomarkers in a pediatric piglet traumatic brain injury model.

Traumatic brain injury (TBI) at a young age can lead to the development of long-term functional impairments. Severity of injury is well demonstrated to have a strong influence on the extent of functional impairments; however, identification of specific magnetic resonance imaging (MRI) biomarkers that are most reflective of injury severity and functional prognosis remain elusive. Therefore, the objective of this study was to utilize advanced statistical approaches to identify clinically relevant MRI biomarkers and predict functional outcomes using MRI metrics in a translational large animal piglet TBI model.

Mimicking Sub-Structures Self-Organization in Microtubules.

Microtubules (MTs) are highly dynamic polymers distributed in the cytoplasm of a biological cell. Alpha and beta globular proteins constituting the heterodimer building blocks combine to form these tubules through polymerization, controlled by the concentration of Guanosine-triphosphate (GTPs) and other Microtubule Associated Proteins (MAPs). MTs play a crucial role in many intracellular processes, predominantly in mitosis, organelle transport and cell locomotion.

Physiochemical Effects of Nanoparticles on Cell Nuclear Complex Pore Transport: A Coarse-Grained Computational Model.

Understanding and controlling the interaction between nanoparticles and cell nuclei is critical to the development of the biomedical applications such as gene delivery, cellular imaging, and tumor therapy. Recent years have witnessed growing evidence that the size, shape, and the grafting density of the karyopherins ligands of nanoparticles provide a significant influence on the uptake mechanism of nanoparticles into cells; however, there is a lack of investigation into how these physical factors play a role in cellular nuclear uptake and how the nanoparticle enters the nucleus. Here, we build a computational framework to parametrically evaluate the effects of the size, shape, and the grafting density of the karyopherins ligands of designed nanoparticles on their transport through the nuclear pore complex of a cell nucleus so as to provide a novel scheme for nanoparticle design and precise nucleus-targeted therapy.