A multiscale hybrid model for pro-angiogenic calcium signals in a vascular endothelial cell

Cytosolic calcium machinery is one of the principal signaling mechanisms by which endothelial cells (ECs) respond to external stimuli during several biological processes, including vascular progression in both physiological and pathological conditions. Low concentrations of angiogenic factors (such as VEGF) activate in fact complex pathways involving, among others, second messengers arachidonic acid (AA) and nitric oxide (NO), which in turn control the activity of plasma membrane calcium channels. The subsequent increase in the intracellular level of the ion regulates fundamental biophysical properties of ECs (such as elasticity, intrinsic motility, and chemical strength), enhancing their migratory capacity. Previously, a number of continuous models have represented cytosolic calcium dynamics, while EC migration in angiogenesis has been separately approached with discrete, lattice-based techniques. These two components are here integrated and interfaced to provide a multiscale and hybrid Cellular Potts Model (CPM), where the phenomenology of a motile EC is realistically mediated by its calcium-dependent subcellular events. The model, based on a realistic 3-D cell morphology with a nuclear and a cytosolic region, is set with known biochemical and electrophysiological data. In particular, the resulting simulations are able to reproduce and describe the polarization process, typical of stimulated vascular cells, in various experimental conditions.Moreover, by analyzing the mutual interactions between multilevel biochemical and biomechanical aspects, our study investigates ways to inhibit cell migration: such strategies have in fact the potential to result in pharmacological interventions useful to disrupt malignant vascular progressio

Real-Time Profiling of Respiratory Motion: Baseline Drift, Frequency Variation and Fundamental Pattern Change

To precisely ablate tumor in radiation therapy, it is important to locate the tumor position in real time during treatment. However, respiration-induced tumor motions are difficult to track. They are semi-periodic and exhibit variations in baseline, frequency and fundamental pattern (oscillatory amplitude and shape). In this study, we try to decompose the above-mentioned components from discrete observations in real time. Baseline drift, frequency (equivalently phase) variation and fundamental pattern change characterize different aspects of respiratory motion and have distinctive clinical indications. Furthermore, smoothness is a valid assumption for each one of these components in their own spaces, and facilitates effective extrapolation for the purpose of estimation and prediction. We call this process 'profiling' to reflect the integration of information extraction, decomposition, processing and recovery. The proposed method has three major ingredients: (1) real-time baseline and phase estimation based on elliptical shape tracking in augmented state space and Poincaré sectioning principle; (2) estimation of the fundamental pattern by unwarping the observation with phase estimate from the previous step; (3) filtering of individual components and assembly in the original temporal-displacement signal space. We tested the proposed method with both simulated and clinical data. For the purpose of prediction, the results are comparable to what one would expect from a human operator. The proposed approach is fully unsupervised and data driven, making it ideal for applications requiring economy, efficiency and flexibility.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85908/1/Fessler14.pd

Effect of spatial concentration fluctuations on effective kinetics in diffusion-reaction systems

International audienceThe effect of spatial concentration fluctuations on the reaction of two solutes, A þ B* C, is considered. In the absence of fluctuations, the concentration of solutes decays as Adet ¼ Bdet t 1. Contrary to this, experimental and numerical studies suggest that concentrations decay significantly slower. Existing theory suggests a t d/4 scaling in the asymptotic regime (d is the dimensionality of the problem). Here we study the effect of fluctuations using the classical diffusion-reaction equation with random initial conditions. Initial concentrations of the reactants are treated as correlated random fields.We use the method of moment equations to solve the resulting stochastic diffusion-reaction equation and obtain a solution for the average concentrations that deviates from t 1 to t d/4 behavior at characteristic transition time t . We also derive analytical expressions for t as a function of Damköhler number and the coefficient of variation of the initial concentration

Breathing adapted radiotherapy: a 4D gating software for lung cancer

<p>Abstract</p> <p>Purpose</p> <p>Physiological respiratory motion of tumors growing in the lung can be corrected with respiratory gating when treated with radiotherapy (RT). The optimal respiratory phase for beam-on may be assessed with a respiratory phase optimizer (RPO), a 4D image processing software developed with this purpose.</p> <p>Methods and Materials</p> <p>Fourteen patients with lung cancer were included in the study. Every patient underwent a 4D-CT providing ten datasets of ten phases of the respiratory cycle (0-100% of the cycle). We defined two morphological parameters for comparison of 4D-CT images in different respiratory phases: tumor-volume to lung-volume ratio and tumor-to-spinal cord distance. The RPO automatized the calculations (200 per patient) of these parameters for each phase of the respiratory cycle allowing to determine the optimal interval for RT.</p> <p>Results</p> <p>Lower lobe lung tumors not attached to the diaphragm presented with the largest motion with breathing. Maximum inspiration was considered the optimal phase for treatment in 4 patients (28.6%). In 7 patients (50%), however, the RPO showed a most favorable volumetric and spatial configuration in phases other than maximum inspiration. In 2 cases (14.4%) the RPO showed no benefit from gating. This tool was not conclusive in only one case.</p> <p>Conclusions</p> <p>The RPO software presented in this study can help to determine the optimal respiratory phase for gated RT based on a few simple morphological parameters. Easy to apply in daily routine, it may be a useful tool for selecting patients who might benefit from breathing adapted RT.</p

In situ ¹⁰Be modeling and terrain analysis constrain subglacial quarrying and abrasion rates at Sermeq Kujalleq (Jakobshavn Isbræ), Greenland

Glacial erosion creates diagnostic landscapes and vast amounts of sediment. However, knowledge about the rate at which glaciers erode and sculpt bedrock and the proportion of quarried (plucked) versus abraded material is limited. To address this, we quantify subglacial erosion rates and constrain the ratio of quarrying to abrasion during a recent, ∼ 200-year long overriding of a bedrock surface fronting, Sermeq Kujalleq (Jakobshavn Isbræ), Greenland, by combining 10Be analyses, a digital terrain model, and field observations. Cosmogenic 10Be measurements along a 1.2 m tall quarried bedrock step reveal a triangular wedge of quarried rock. Using individual 10Be measurements from abraded surfaces across the study area, we derive an average abrasion rate of 0.13 ± 0.08 mm yr−1. By applying this analysis across a ∼ 1.33 km2 study area, we estimate that the Greenland Ice Sheet quarried 378 ± 45 m3 and abraded 322 ± 204 m3 of material at this site. These values result in an average total erosion rate of 0.26 ± 0.16 mm yr−1, with abrasion and quarrying contributing in roughly equal proportions within uncertainty. Additional cosmogenic 10Be analysis and surface texture mapping indicate that many lee steps are relicts from the prior glaciation and were not re-quarried during the recent overriding event. These new observations of glacier erosion in a recently exposed landscape provide one of the first direct measurements of quarrying rates and indicate that quarrying accounts for roughly half of the total glacial erosion in representative continental shield lithologies.</p

A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning

Progress in biomechanical modelling of human soft tissue is the basis for the development of new clinical applications capable of improving the diagnosis and treatment of some diseases (e.g. cancer), as well as the surgical planning and guidance of some interventions. The finite element method (FEM) is one of the most popular techniques used to predict the deformation of the human soft tissue due to its high accuracy. However, FEM has an associated high computational cost, which makes it difficult its integration in real-time computer-aided surgery systems. An alternative for simulating the mechanical behaviour of human organs in real time comes from the use of machine learning (ML) techniques, which are much faster than FEM. This paper assesses the feasibility of ML methods for modelling the biomechanical behaviour of the human liver during the breathing process, which is crucial for guiding surgeons during interventions where it is critical to track this deformation (e.g. some specific kind of biopsies) or for the accurate application of radiotherapy dose to liver tumours. For this purpose, different ML regression models were investigated, including three tree-based methods (decision trees, random forests and extremely randomised trees) and other two simpler regression techniques (dummy model and linear regression). In order to build and validate the ML models, a labelled data set was constructed from modelling the deformation of eight ex-vivo human livers using FEM. The best prediction performance was obtained using extremely randomised trees, with a mean error of 0.07 mm and all the samples with an error under 1 mm. The achieved results lay the foundation for the future development of some real-time software capable of simulating the human liver deformation during the breathing process during clinical interventions.This work has been funded by the Spanish Ministry of Economy and Competitiveness (MINECO) through research projects TIN2014-52033-R and DPI2013-40859-R, both also supported by European FEDER funds. The authors acknowledge the kind collaboration of the personnel from the hospital involved in the research.Lorente, D.; Martínez-Martínez, F.; Rupérez Moreno, MJ.; Lago, MA.; Martínez-Sober, M.; Escandell-Montero, P.; Martínez-Martínez, JM.... (2017). A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning. Expert Systems with Applications. 71:342-357. doi:10.1016/j.eswa.2016.11.037S3423577

A Cellular Potts Model simulating cell migration on and in matrix environments

Cell migration on and through extracellular matrix plays a critical role in a wide variety of physiological and pathological phenomena, and in scaffold-based tissue engineering. Migration is regulated by a number of extracellular matrix- or cell-derived biophysical parameters, such as matrix fiber orientation, gap size, and elasticity, or cell deformation, proteolysis, and adhesion. We here present an extended Cellular Potts Model (CPM) able to qualitatively and quantitatively describe cell migratory phenotype on both two-dimensional substrates and within three-dimensional environments, in a close comparison with experimental evidence. As distinct features of our approach, the cells are represented by compartmentalized discrete objects, differentiated in the nucleus and in the cytosolic region, while the extracellular matrix is composed of a fibrous mesh and of a homogeneous fluid. Our model provides a strong correlation of the directionality of migration with the topological ECM distribution and, further, a biphasic dependence of migration on the matrix density, and in part adhesion, in both two-dimensional and three-dimensional settings. Moreover, we demonstrate that the directional component of cell movement is strongly correlated with the topological distribution of the ECM fibrous network. In the three-dimensional networks, we also investigate the effects of the matrix mechanical microstructure, observing that, at a given distribution of fibers, cell motility has a subtle bimodal relation with the elasticity of the scaffold. Finally, cell locomotion requires deformation of the cell's nucleus and/or cell-derived proteolysis of steric fibrillar obstacles within rather rigid matrices characterized by small pores, not, however, for sufficiently large pores. In conclusion, we here propose a mathematical modeling approach that serves to characterize cell migration as a biological phenomen in health, disease and tissue engineering applications. The research that led to the present paper was partially supported by a grant of the group GNFM of INdA

3D Multi-Cell Simulation of Tumor Growth and Angiogenesis

We present a 3D multi-cell simulation of a generic simplification of vascular tumor growth which can be easily extended and adapted to describe more specific vascular tumor types and host tissues. Initially, tumor cells proliferate as they take up the oxygen which the pre-existing vasculature supplies. The tumor grows exponentially. When the oxygen level drops below a threshold, the tumor cells become hypoxic and start secreting pro-angiogenic factors. At this stage, the tumor reaches a maximum diameter characteristic of an avascular tumor spheroid. The endothelial cells in the pre-existing vasculature respond to the pro-angiogenic factors both by chemotaxing towards higher concentrations of pro-angiogenic factors and by forming new blood vessels via angiogenesis. The tumor-induced vasculature increases the growth rate of the resulting vascularized solid tumor compared to an avascular tumor, allowing the tumor to grow beyond the spheroid in these linear-growth phases. First, in the linear-spherical phase of growth, the tumor remains spherical while its volume increases. Second, in the linear-cylindrical phase of growth the tumor elongates into a cylinder. Finally, in the linear-sheet phase of growth, tumor growth accelerates as the tumor changes from cylindrical to paddle-shaped. Substantial periods during which the tumor grows slowly or not at all separate the exponential from the linear-spherical and the linear-spherical from the linear-cylindrical growth phases. In contrast to other simulations in which avascular tumors remain spherical, our simulated avascular tumors form cylinders following the blood vessels, leading to a different distribution of hypoxic cells within the tumor. Our simulations cover time periods which are long enough to produce a range of biologically reasonable complex morphologies, allowing us to study how tumor-induced angiogenesis affects the growth rate, size and morphology of simulated tumors

Corticosteroid suppression of lipoxin A4 and leukotriene B4from alveolar macrophages in severe asthma

<p>Abstract</p> <p>Background</p> <p>An imbalance in the generation of pro-inflammatory leukotrienes, and counter-regulatory lipoxins is present in severe asthma. We measured leukotriene B₄(LTB₄), and lipoxin A₄(LXA₄) production by alveolar macrophages (AMs) and studied the impact of corticosteroids.</p> <p>Methods</p> <p>AMs obtained by fiberoptic bronchoscopy from 14 non-asthmatics, 12 non-severe and 11 severe asthmatics were stimulated with lipopolysaccharide (LPS,10 μg/ml) with or without dexamethasone (10^-6M). LTB₄and LXA₄were measured by enzyme immunoassay.</p> <p>Results</p> <p>LXA₄biosynthesis was decreased from severe asthma AMs compared to non-severe (p < 0.05) and normal subjects (p < 0.001). LXA₄induced by LPS was highest in normal subjects and lowest in severe asthmatics (p < 0.01). Basal levels of LTB₄were decreased in severe asthmatics compared to normal subjects (p < 0.05), but not to non-severe asthma. LPS-induced LTB₄was increased in severe asthma compared to non-severe asthma (p < 0.05). Dexamethasone inhibited LPS-induced LTB₄and LXA₄, with lesser suppression of LTB₄in severe asthma patients (p < 0.05). There was a significant correlation between LPS-induced LXA₄and FEV₁(% predicted) (r_s= 0.60; p < 0.01).</p> <p>Conclusions</p> <p>Decreased LXA₄and increased LTB₄generation plus impaired corticosteroid sensitivity of LPS-induced LTB₄but not of LXA₄support a role for AMs in establishing a pro-inflammatory balance in severe asthma.</p