Visceral pain in the large bowel is a defining symptom of irritable bowel syndrome (IBS) and the primary reason that patients visit gastroenterologists. This pain is reliably triggered by mechanical distension of the ...
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Visceral pain in the large bowel is a defining symptom of irritable bowel syndrome (IBS) and the primary reason that patients visit gastroenterologists. This pain is reliably triggered by mechanical distension of the distal colon and rectum (colorectum). Consequently, the process of mechanotransduction by sensory afferents, responsible for translating mechanical colorectal stimuli into neural action potentials, plays a central role in IBS-related bowel pain. In this study, we aim to enhance our understanding of colorectal mechanotransduction by combining experimental findings in colorectal biomechanics and afferent neural encoding within a comprehensive computational simulation framework. To achieve this, we implemented a three-layered, fiber-reinforced finite element model that accurately replicates the nonlinear, heterogeneous, and anisotropic mechanical characteristics of the mouse colorectum. This model facilitates the computation of local mechanical stresses and strains around individual afferent endings, which have diameters on the micron-scale. We then integrated a neural membrane model to simulate the encoding of action potentials by afferent nerves in response to microscopic stresses and strains along the afferent endings. Our multiscale simulation framework enables the assessment of three hypotheses regarding the mechanical gating of action potential generation: (1) axial stress dominates mechanical gating of mechanosensitive channels, (2) both axial and circumferential stresses contribute, and (3) membrane shear stress dominates. Additionally, we explore how the orientation of afferent endings impacts neural encoding properties. This computational framework not only allows for the virtual investigation of colorectal mechanotransduction in the context of prolonged visceral hypersensitivity but can also guide the development of new experimental studies aimed at uncovering the neural and biomechanical mechanisms underlying IBS-related bowel pain.
Corrosion is a serious problem, which reduces the efficiency and lifespan of various technologies, such as thermal power plants, aviation, nuclear reactors, etc. It starts from the interactions of corrosive species wi...
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Corrosion is a serious problem, which reduces the efficiency and lifespan of various technologies, such as thermal power plants, aviation, nuclear reactors, etc. It starts from the interactions of corrosive species with alloys to various subsequent processes, such as oxide-formation, growth, and delamination, void and crevices-formation, etc., which all have different lengths and time- spans. Resolving such a problem requires a complete understanding of these processes, necessitating multi-scale computationalmodeling (MSCM). Available literature focuses mainly on single aspects of corrosion, such as the adsorption of corrosive agents on alloy or cracking, which requires the application of single computationalmodeling (SCM). Applying SCM is inadequate for addressing and describing some essential corrosion processes as spatial and temporal scales increase, as well as designing corrosion-resistant alloys, which also requires MSCM to couple various properties along their hierarchical structures. Thus, this paper critically and comprehensively reviews the MSCM of high-temperature corrosion and its control. The structure-property relationships during alloy design were discussed. Also, challenges and hot spots for further research directions were identified. We foresee that, in the future, there will be wide applications of MSCM to uncover the hitherto unknown corrosion processes, and alloys will be designed from atomic/molecular structures. Hence, this review paper will provide several computational options for corrosion investigation and connecting alloy structures to properties during alloy designing.
Materials with features at the nanoscale can provide unique mechanical properties and increased functionality when included as part of a nanocomposite. This dissertation utilizes computational methods at multiple scal...
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Materials with features at the nanoscale can provide unique mechanical properties and increased functionality when included as part of a nanocomposite. This dissertation utilizes computational methods at multiple scales, including molecular dynamics (MD) and density functional theory (DFT), and the coupled atomistic and discrete dislocation multiscale method (CADD), to predict the mechanical properties of nanocomposites possessing nanomaterials that are either 1-D (carbyne chains), 2-D (graphene sheets), or 3-D (Al/amorphous-Si core-shell nanorod). The MD method is used to model Ni-graphene nanocomposites. The strength of a Ni-graphene nanocomposite is found to improve by increasing the gap between the graphene sheet and a crack embedded in the Ni matrix. Ni-graphene nanocomposites also show substantially greater strength than pure Ni, depending on the loading direction and crack orientation relative to the graphene sheet. Moreover, polycrystalline graphene may serve as a better reinforce in Ni-graphene nanocomposites due to its improved interfacial shear stress with the Ni matrix compared to pristine graphene. This work develops a patchwork quilt method for generating polycrystalline graphene sheets for use in MD models. Carbyne-based nanocomposites are modeled from first principles using DFT. This research finds that carbyne can only serve as an effective reinforcement in Ni-based nanocomposites when it is dielectrically screened from the Ni matrix, otherwise the carbyne structure is lost. When graphene is used as a dielectric screen, the local stiffness of the nanocomposite improves with the number of carbyne chains present. Specific stiffness is introduced as an alternative to elastic stiffness for characterizing low-dimensional materials because it is not dependent on volume when derived using an energy vs. strain relation. A two-material formulation of CADD is developed to model Al/a-Si core-shell nanorods under indentation/retraction. The structural deformati
Cardiac optogenetics is an emergent research area involving the delivery of light-sensitive proteins (opsins) to excitable heart tissue to enable optical modulation of cardiac electrical function. Optogenetic stimulat...
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Cardiac optogenetics is an emergent research area involving the delivery of light-sensitive proteins (opsins) to excitable heart tissue to enable optical modulation of cardiac electrical function. Optogenetic stimulation has many noteworthy advantages over conventional electrical methods, including selective electrophysiological modulation in specifically targeted cell subpopulations, high-resolution spatiotemporal control via patterned illumination, and use of different opsins to elicit inward or outward transmembrane current. This review summarizes developments achieved since the inception of cardiac optogenetics research, which has spanned nearly a decade. The authors first provide an overview of recent methodological advances in opsin engineering, light sensitization of cardiac tissue, strategies for illuminating the heart, and frameworks for simulating optogenetics in realistic computational models of patient hearts. They then review recent cardiac optogenetics applications, including: 1) all-optical, high-throughput, contactless assays for quantification of electrophysiological properties;2) optogenetic perturbation of cardiac tissue to unveil mechanistic insights on the initiation, perpetuation, and termination of arrhythmia;and 3) disruptive translational innovations such as light-based pacemaking and defibrillation. (c) 2018 by the American College of Cardiology Foundation.
We present a new numerical method for particle interactions in polymer-fluid models of DNA-laden flows. The DNA is represented by a bead-rod polymer model and is fully-coupled to the fluid. The main objective in this ...
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We present a new numerical method for particle interactions in polymer-fluid models of DNA-laden flows. The DNA is represented by a bead-rod polymer model and is fully-coupled to the fluid. The main objective in this work is to properly model polymer-polymer and polymersurface interactions by enforcing the physical rod-rod and rod-surface non-crossing constraints. Our new method is based on a rigid constraint algorithm whereby rods elastically bounce off one another to prevent crossing, similar to our previous algorithm used to model polymer-surface interactions.
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