1,436 research outputs found
A multiscale mechanobiological model of bone remodelling predicts site-specific bone loss in the femur during osteoporosis and mechanical disuse
We propose a multiscale mechanobiological model of bone remodelling to
investigate the site-specific evolution of bone volume fraction across the
midshaft of a femur. The model includes hormonal regulation and biochemical
coupling of bone cell populations, the influence of the microstructure on bone
turnover rate, and mechanical adaptation of the tissue. Both microscopic and
tissue-scale stress/strain states of the tissue are calculated from macroscopic
loads by a combination of beam theory and micromechanical homogenisation.
This model is applied to simulate the spatio-temporal evolution of a human
midshaft femur scan subjected to two deregulating circumstances: (i)
osteoporosis and (ii) mechanical disuse. Both simulated deregulations led to
endocortical bone loss, cortical wall thinning and expansion of the medullary
cavity, in accordance with experimental findings. Our model suggests that these
observations are attributable to a large extent to the influence of the
microstructure on bone turnover rate. Mechanical adaptation is found to help
preserve intracortical bone matrix near the periosteum. Moreover, it leads to
non-uniform cortical wall thickness due to the asymmetry of macroscopic loads
introduced by the bending moment. The effect of mechanical adaptation near the
endosteum can be greatly affected by whether the mechanical stimulus includes
stress concentration effects or not.Comment: 25 pages, 10 figure
Astrocytic Ion Dynamics: Implications for Potassium Buffering and Liquid Flow
We review modeling of astrocyte ion dynamics with a specific focus on the
implications of so-called spatial potassium buffering, where excess potassium
in the extracellular space (ECS) is transported away to prevent pathological
neural spiking. The recently introduced Kirchoff-Nernst-Planck (KNP) scheme for
modeling ion dynamics in astrocytes (and brain tissue in general) is outlined
and used to study such spatial buffering. We next describe how the ion dynamics
of astrocytes may regulate microscopic liquid flow by osmotic effects and how
such microscopic flow can be linked to whole-brain macroscopic flow. We thus
include the key elements in a putative multiscale theory with astrocytes
linking neural activity on a microscopic scale to macroscopic fluid flow.Comment: 27 pages, 7 figure
Opportunities for multiscale computational modelling of serotonergic drug effects in Alzheimer’s disease
Alzheimer's disease (AD) is an age-specific neurodegenerative disease that
compromises cognitive functioning and impacts the quality of life of an
individual. Pathologically, AD is characterised by abnormal accumulation of
beta-amyloid (A) and hyperphosphorylated tau protein. Despite research
advances over the last few decades, there is currently still no cure for AD.
Although, medications are available to control some behavioural symptoms and
slow the disease's progression, most prescribed medications are based on
cholinesterase inhibitors. Over the last decade, there has been increased
attention towards novel drugs, targeting alternative neurotransmitter pathways,
particularly those targeting serotonergic (5-HT) system. In this review, we
focused on 5-HT receptor (5-HTR) mediated signalling and drugs that target
these receptors. These pathways regulate key proteins and kinases such as GSK-3
that are associated with abnormal levels of A and tau in AD. We then
review computational studies related to 5-HT signalling pathways with the
potential for providing deeper understanding of AD pathologies. In particular,
we suggest that multiscale and multilevel modelling approaches could
potentially provide new insights into AD mechanisms, and towards discovering
novel 5-HTR based therapeutic targets.Comment: Accepted manuscript in Neuropharmacolog
Data-driven modelling of biological multi-scale processes
Biological processes involve a variety of spatial and temporal scales. A
holistic understanding of many biological processes therefore requires
multi-scale models which capture the relevant properties on all these scales.
In this manuscript we review mathematical modelling approaches used to describe
the individual spatial scales and how they are integrated into holistic models.
We discuss the relation between spatial and temporal scales and the implication
of that on multi-scale modelling. Based upon this overview over
state-of-the-art modelling approaches, we formulate key challenges in
mathematical and computational modelling of biological multi-scale and
multi-physics processes. In particular, we considered the availability of
analysis tools for multi-scale models and model-based multi-scale data
integration. We provide a compact review of methods for model-based data
integration and model-based hypothesis testing. Furthermore, novel approaches
and recent trends are discussed, including computation time reduction using
reduced order and surrogate models, which contribute to the solution of
inference problems. We conclude the manuscript by providing a few ideas for the
development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and
Multiscale Dynamics (American Scientific Publishers
Waves and patterning in developmental biology: vertebrate segmentation and feather bud formation as case studies
In this article we will discuss the integration of developmental patterning mechanisms with waves of competency that control the ability of a homogeneous field of cells to react to pattern forming cues and generate spatially heterogeneous patterns. We base our discussion around two well known patterning events that take place in the early embryo: somitogenesis and feather bud formation. We outline mathematical models to describe each patterning mechanism, present the results of numerical simulations and discuss the validity of each model in relation to our example patterning processes
Version control of pathway models using XML patches
<p>Background: Computational modelling has become an important tool in understanding biological systems such as signalling pathways. With an increase in size complexity of models comes a need for techniques to manage model versions and their relationship to one another. Model version control for pathway models shares some of the features of software version control but has a number of differences that warrant a specific solution.</p>
<p>Results: We present a model version control method, along with a prototype implementation, based on XML patches. We show its application to the EGF/RAS/RAF pathway.</p>
<p>Conclusion: Our method allows quick and convenient storage of a wide range of model variations and enables a thorough explanation of these variations. Trying to produce these results without such methods results in slow and cumbersome development that is prone to frustration and human error.</p>
Partial differential equations for self-organization in cellular and developmental biology
Understanding the mechanisms governing and regulating the emergence of structure and heterogeneity within cellular systems, such as the developing embryo, represents a multiscale challenge typifying current integrative biology research, namely, explaining the macroscale behaviour of a system from microscale dynamics. This review will focus upon modelling how cell-based dynamics orchestrate the emergence of higher level structure. After surveying representative biological examples and the models used to describe them, we will assess how developments at the scale of molecular biology have impacted on current theoretical frameworks, and the new modelling opportunities that are emerging as a result. We shall restrict our survey of mathematical approaches to partial differential equations and the tools required for their analysis. We will discuss the gap between the modelling abstraction and biological reality, the challenges this presents and highlight some open problems in the field
Statistical mechanics of neocortical interactions: large-scale EEG influences on molecular processes
Recent calculations further supports the premise that large-scale synchronous
firings of neurons may affect molecular processes. The context is scalp
electroencephalography (EEG) during short-term memory (STM) tasks. The
mechanism considered is (SI units)
coupling, where is the momenta of free waves
the charge of in units of the electron charge, and
the magnetic vector potential of current from
neuronal minicolumnar firings considered as wires, giving rise to EEG. Data has
processed using multiple graphs to identify sections of data to which
spline-Laplacian transformations are applied, to fit the statistical mechanics
of neocortical interactions (SMNI) model to EEG data, sensitive to synaptic
interactions subject to modification by waves.Comment: Accepted for publication in Journal of Theoretical Biolog
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