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At least 253 records · Page 14Linked to original sources

arXiv2014

Two-dimension tissue growth model based on circular granular cells for cells with small overlap

Tissue growth can be modeled in two dimension by only using circular granular cells, which can grow and produce child. Linear spring-dashpot model is used to bind the cells with a cut-off interaction range of 1.1 times sum of radii of interacted cells. Simulation steps must be divided into explicit and implicit ones due to cell growing stage and cell position rearrangement. This division is aimed to avoid simulation problem. Only in the explicit steps time changes is performed. Large cells overlap is chosen as termination condition of tissue growth. Only some cells configuration can growth to infinite time without encountering the large cells overlap. These configurations, and the other also, are presented in this work. Simulation time $t$ increases as cell number $N$ increases due to raise of interaction number between two cells. Linear and network configurations tend to aligned with different asymtotic function, that relates $N$ and $t$, for large $N$.

physics.bio-ph↗

arXiv2014

Joint fitting reveals hidden interactions in tumor growth

Tumor growth is often the result of the simultaneous development of two or more cancer cell populations. Their interaction between them characterizes the system evolution. To obtain information about these interactions we apply the recently developed vector universality (VUN) formalism to various instances of competition between tumor populations. The formalism allows us: (a) to quantify the growth mechanisms of a HeLa cell colony, describing the phenotype switching responsible for its fast expansion, (b) to reliably reconstruct the evolution of the necrotic and viable fractions in both in vitro and in vivo tumors using data for the time dependences of the total masses, and (c) to show how the shedding of cells leading to subspheroid formation is beneficial to both the spheroid and subspheroid populations, suggesting that shedding is a strong positive influence on cancer dissemination.

q-bio.TO↗

arXiv2014

Niche inheritance: a cooperative pathway to enhance cancer cell fitness though ecosystem engineering

Cancer cells can be described as an invasive species that is able to establish itself in a new environment. The concept of niche construction can be utilized to describe the process by which cancer cells terraform their environment, thereby engineering an ecosystem that promotes the genetic fitness of the species. Ecological dispersion theory can then be utilized to describe and model the steps and barriers involved in a successful diaspora as the cancer cells leave the original host organ and migrate to new host organs to successfully establish a new metastatic community. These ecological concepts can be further utilized to define new diagnostic and therapeutic areas for lethal cancers.

q-bio.TO↗

arXiv2014

Thesis: The Effects of Hypoxia, Metabolic Restriction and Magnetic Fields on Chromosome Instability and Karyotype Contraction in Cancer Cell Lines

Background: Biological effects of extra-low-frequency (ELF) magnetic fields (MFs) have lacked a credible mechanism of interaction between MFs and living material. Objectives: To examine the effect of ELF-MFs on cancer cells. Methods: Five cancer cell lines were exposed to ELF-MFs within the range of 0.025-5 microTesla, and the cells were examined for karyotype changes after 6 days. Results: All cancer cells lines lost chromosomes from MF exposure, with a mostly flat dose-response. Constant MF exposures for three weeks allow a rising return to the baseline, unperturbed karyotypes. From this point, small MF increases or decreases are again capable of inducing karyotype contractions (KCs). Our data suggest that the KCs are caused by MF interference with mitochondria's adenosine triphosphate synthase (ATPS), compensated by the action of adenosine monophosphate-activated protein kinase (AMPK). The effects of MFs are similar to those of the ATPS inhibitor, oligomycin. They are amplified by metformin, an AMPK stimulator, and attenuated by resistin, an AMPK inhibitor. Over environmental MFs, KCs of various cancer cell lines show exceptionally wide and flat dose-responses, except for those of erythroleukemia cells, which display a progressive rise from 0.025 to 0.4 microTesla. Conclusions: The biological effects of MFs are connected to an alteration in the structure of water that impedes the flux of protons in ATPS channels. These results may be environment ally important, in view of the central roles played in human physiology by ATPS and AMPK, particularly in their links to diabetes, cancer and longevity.

q-bio.TO↗

arXiv2014

Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks

In this review we summarize our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions.

q-bio.TO↗

arXiv2014

Functional optimization of the arterial network

We build an evolutionary scenario that explains how some crucial physiological constraints in the arterial network of mammals - i.e. hematocrit, vessels diameters and arterial pressure drops - could have been selected by evolution. We propose that the arterial network evolved while being constrained by its function as an organ. To support this hypothesis, we focus our study on one of the main function of blood network: oxygen supply to the organs. We consider an idealized organ with a given oxygen need and we optimize blood network geometry and hematocrit with the constraint that it must fulfill the organ oxygen need. Our model accounts for the non-Newtonian behavior of blood, its maintenance cost and Fåhræus effects (decrease in average concentration of red blood cells as the vessel diameters decrease). We show that the mean shear rates (relative velocities of fluid layers) in the tree vessels follow a scaling law related to the multi-scale property of the tree network, and we show that this scaling law drives the behavior of the optimal hematocrit in the tree. We apply our scenario to physiological data and reach results fully compatible with the physiology: we found an optimal hematocrit of 0.43 and an optimal ratio for diameter decrease of about 0.79. Moreover our results show that pressure drops in the arterial network should be regulated in order for oxygen supply to remain optimal, suggesting that the amplitude of the arterial pressure drop may have co-evolved with oxygen needs.

physics.bio-ph↗

arXiv2014

Correlation of multiple sclerosis (MS) incidence trends with solar and geomagnetic indices: time to revise the method of reporting MS epidemiological data

Background: Recently, we introduced solar related geomagnetic disturbances (GMD) as a potential environmental risk factor for multiple sclerosis (MS). The aim of this study was to test probable correlation between solar activities and GMD with long-term variations of MS incidence. Methods: After a systematic review, we studied the association between alterations in solar wind velocity (Vsw) and planetary A index (Ap, a GMD index) with MS incidence in Tehran and western Greece, during the 23rd solar cycle (1996-2008), by an ecological-correlational study. Results: We found moderate to strong correlations among MS incidence of Tehran with Vsw (Rs=0.665, p=0.013), with one year delay, and also with Ap (Rs=0.864, p=0.001) with 2 year delay. There were very strong correlations among MS incidence data of Greece with Vsw (R=0.906, p<0.001) and with Ap (R=0.844, p=0.001), both with one year lag. Conclusion: It is the first time that a hypothesis has introduced an environmental factor that may describe MS incidence alterations; however, it should be reminded that correlation does not mean necessarily the existence of a causal relationship. Important message of these findings for researchers is to provide MS incidence reports with higher resolution for consecutive years, based on the time of disease onset and relapses, not just the time of diagnosis. Then, it would be possible to further investigate the validity of GMD hypothesis or any other probable environmental risk factors. Keywords: Correlation analysis, Multiple sclerosis, Incidence, Geomagnetic disturbance, Geomagnetic activity, Solar wind velocity, Environmental risk factor.

q-bio.TO↗

arXiv2014

Glomerular protein separation as a mechanism for powering renal concentrating processes

Various models have been proposed to explain the urine concentrating mechanism in mammals, however uncertainty remains regarding the origin of the energy required for the production of concentrated urine. We propose a novel mechanism for concentrating urine. We postulate that the energy for the concentrating process is derived from the osmotic potentials generated by the separation of afferent blood into protein-rich efferent blood and protein-deplete filtrate. These two streams run in mutual juxtaposition along the length of the nephron and are thus suitably arranged to provide the osmotic potential to concentrate the urine. The proposed model is able to qualitatively explain the production of various urine concentrations under different clinical conditions. An approach to testing the feasibility of the hypothesis is proposed.

q-bio.TO↗

arXiv2014

A computational study of the effects of remodelled electrophysiology and mechanics on initiation of ventricular fibrillation in human heart failure

The study of pathological cardiac conditions such as arrhythmias, a major cause of mortality in heart failure, is becoming increasingly informed by computational simulation, numerically modelling the governing equations. This can provide insight where experimental work is constrained by technical limitations and/or ethical issues. As the models become more realistic, the construction of efficient and accurate computational models becomes increasingly challenging. In particular, recent developments have started to couple the electrophysiology models with mechanical models in order to investigate the effect of tissue deformation on arrhythmogenesis, thus introducing an element of nonlinearity into the mathematical representation. This paper outlines a biophysically-detailed computational model of coupled electromechanical cardiac activity which uses the finite element method to approximate both electrical and mechanical systems on unstructured, deforming, meshes. An ILU preconditioner is applied to improve performance of the solver. This software is used to examine the role of electrophysiology, fibrosis and mechanical deformation on the stability of spiral wave dynamics in human ventricular tissue by applying it to models of both healthy and failing tissue. The latter was simulated by modifying (i) cellular electrophysiological properties, to generate an increased action potential duration and altered intracellular calcium handling, and (ii) tissue-level properties, to simulate the gap junction remodelling, fibrosis and increased tissue stiffness seen in heart failure. The resulting numerical experiments suggest that, for the chosen mathematical models of electrophysiology and mechanical response, introducing tissue level fibrosis can have a destabilising effect on the dynamics, while the net effect of the electrophysiological remodelling stabilises the system.

cs.CE↗

arXiv2014

Image-based Parameter Inference for Spatio-temporal models of Organogenesis

Advances in imaging technology now provide us with detailed 3D data on gene expression patterns in developing embryos. This information can be used to build predictive mathematical models of embryogenesis. Current modelling approaches are, however, limited by lack of methods to automatically infer the regulatory networks and the parameter values from the image-based information. Here we make a first step to the development of such methods. We use limb bud development as a model system. For a given regulatory network we developed a decision tree based algorithm to automatically determine parameter values for which the model reproduces the expression patterns. Starting from this parameter set, local optimization was performed to further reduce the chosen goodness-of-fit measure. This approach allowed us to recover the target expression patterns, as judged by eye, and thus provides a first step towards the automated inference of parameter values for a given regulatory network.

q-bio.QM↗

arXiv2014

Effect of low-intensity pulsed ultrasound on biocompatibility and cellular uptake of chitosan-TPP nanoparticles

Using low molecular weight chitosan nanoparticles (CNPs) prepared by an ionic gelation method, we report the effect of low-intensity pulsed ultrasound (US) on cell viability and nanoparticle uptake in cultured murine pre-osteoblasts. Particle size and zeta potential are measured using Dynamic Light Scattering (DLS), and cell viability is evaluated using the MTS assay. Results show that 30 min delivery of CNPs at 0.5 mg/mL is able to prevent loss of cell viability due to either serum starvation or subsequent exposure to US (1 W/cm2 or 2 W/cm2, up to 1 min). Additionally, flow cytometry data suggest that there is a close association between cellular membrane integrity and the presence of CNPs when US at 2 W/cm2 is administered.

q-bio.BM↗

arXiv2014

Low-level laser irradiation-induced changes in bovine spermatozoa

Some biochemical and metabolic characteristics of bovine sperm cells irradiated with low-level laser were probed and correlated to the irradiation parameters. Bovine spermatozoa were exposed to spatially filtered light from a He-Ne laser (633 nm) with fluences from 150 to 600 mJ/cm2. General biochemical alterations were assessed by vibrational spectroscopy (micro-Fourier-Transform Infrared technique). The mitochondrial membrane potential was assessed by flow cytometry. Lipid peroxidation due to reactive oxygen species (ROS) production was assessed by thiobarbituric acid reactive substances (TBARS) assay. Sperm morphologic characteristics changes were probed by atomic force microscopy (AFM) technique. LLLI was able to induce, at different fluences, changes in lipid, DNA and protein contents. Moreover, LLLI also induced changes in TBARS production, suggesting an irradiation effect on lipid peroxidation. Acrosomal reaction induction evidences was found based on changes in protein structure (Amides I and II bands) and AFM characterization. The most interesting result, however, was the changes in methyl and DNA groups, which strongly suggests that LLLI can modify DNA methylation patterns, important for pregnancy establishment. The observed changes in the above-cited parameters have direct impact on sperm quality. The low-level laser irradiation has the potential to improve the fertilizing capacity of bovine sperm cells.

q-bio.TO↗

arXiv2014

Mathematical modeling applied to the left ventricle of heart

Background: How can mathematics help us to understand the mechanism of the cardiac motion? The best known approach is to take a mathematical model of the fibered structure, insert it into a more-or-less complex model of cardiac architecture, and then study the resulting fibers of activation that propagate through the myocardium. In our paper, we have attempted to create a novel software capable of demonstrate left ventricular (LV) model in normal hearts. Method: Echocardiography was performed on 70 healthy volunteers. Data evaluated included: velocity (radial, longitudinal, rotational and vector point), displacement (longitudinal and rotational), strain rate (longitudinal and circumferential) and strain (radial, longitudinal and circumferential) of all 16 LV myocardial segments. Using these data, force vectors of myocardial samples were estimated by MATLAB software, interfaced in the echocardiograph system. Dynamic orientation contraction (through the cardiac cycle) of every individual myocardial fiber could be created by adding together the sequential steps of the multiple fragmented sectors of that fiber. This way we attempted to mechanically illustrate the global LV model. Result: Our study shows that in normal cases myocardial fibers initiate from the posterior basal region of the heart, continues through the LV free wall, reaches the septum, loops around the apex, ascends, and ends at the superior-anterior edge of LV. Conclusion: We were able to define the whole LV myocardial model mathematically, by MATLAB software in normal subjects. This will enable physicians to diagnose and follow up many cardiac diseases when this software is interfaced within echocardiographic machines.

physics.med-ph↗

arXiv2014

Investigating the development of chemotherapeutic drug resistance in cancer: A multiscale computational study

Chemotherapy is one of the most important therapeutic options used to treat human cancers, either alone or in combination with radiation therapy and surgery. Recent studies have indicated that intra-tumoural heterogeneity has a significant role in driving resistance to chemotherapy in many human malignancies. Multiple factors including the internal cell-cycle dynamics and the external microenvironement contribute to the intra-tumoural heterogeneity. In this paper we present a hybrid, multiscale, individual-based mathematical model, incorporating internal cell-cycle dynamics and changes in oxygen concentration, to study the effects of delivery of several different chemotherapeutic drugs on the heterogeneous subpopulations of cancer cells with varying cell-cycle dynamics. The computational simulation results from the multiscale model are in good agreement with available experimental data and support the hypothesis that slow-cycling sub-populations of tumour cells within a growing tumour mass can induce drug resistance to chemotherapy and thus the use of conventional chemotherapy may actually result in the emergence of dominant, therapy-resistant, slow-cycling subpopulations of tumour cells. Our results indicate that the appearance of this chemotherapeutic resistance is mainly due to the inability of the administered drug to target all cancer cells irrespective of the stage in the cell-cycle they are in i.e. most chemotherapeutic drugs target cells in a particular phase/phases of the cell-cycle, and hence always spare some cancer cells that are not in the targeted cell-cycle phase/phases. The results also suggest that this cell-cycle-mediated drug resistance may be overcome by using multiple doses of cell-cycle, phase-specific chemotherapy that targets cells in all phases and its appropriate sequencing and scheduling.

q-bio.TO↗

arXiv2014

Parameter Synthesis for Cardiac Cell Hybrid Models Using Delta-Decisions

A central problem in systems biology is to identify parameter values such that a biological model satisfies some behavioral constraints (\eg, time series). In this paper we focus on parameter synthesis for hybrid (continuous/discrete) models, as many biological systems can possess multiple operational modes with specific continuous dynamics in each mode. These biological systems are naturally modeled as hybrid automata, most often with nonlinear continuous dynamics. However, hybrid automata are notoriously hard to analyze --- even simple reachability for hybrid systems with linear differential dynamics is an undecidable problem. In this paper we present a parameter synthesis framework based on $δ$-complete decision procedures that sidesteps undecidability. We demonstrate our method on two highly nonlinear hybrid models of the cardiac cell action potential. The results show that our parameter synthesis framework is convenient and efficient, and it enabled us to select a suitable model to study and identify crucial parameter ranges related to cardiac disorders.

cs.LO↗

arXiv2014

Emerging Allee effect in tumor growth

Tumor cells develop different features to adapt to environmental conditions. A prominent example is the ability of tumor cells to switch between migratory and proliferative phenotypes, a phenomenon known as go-or-grow mechanism. It is however unclear how this particular phenotypic plasticity affects overall tumor growth. To address this problem, we formulate and study a mathematical model of spatio-temporal tumor dynamics where different responses to local cell density mediate the go-or-grow dichotomy. Our analysis reveals that two dynamic regimes can be distinguished. If cell motility is allowed to increase with local cell density, any tumor cell population will persist in time, irrespective of its initial size. On the contrary, if cell motility is assumed to decrease with respect to local cell density, an Allee effect emerges, so that any tumor population below a certain size threshold eventually extinguishes. These results suggest that strategies aimed at hindering migration, for instance by enhancing contact inhibition, are worth to be explored as alternatives to those mainly focused at checking tumor proliferation.

q-bio.TO↗

arXiv2014

Competition driven cancer immunoediting

It is a well-established fact that tumors up-regulate glucose consumption to meet increasing demands for rapidly available energy by switching to purely glycolytic mode of glucose metabolism. What is often neglected is that cytotoxic cells of the immune system also have increased energy demands and also switch to pure glycolysis when they are in an activated state. Moreover, while cancer cells can revert back to aerobic metabolism, rapidly proliferating cytotoxic lymphocytes are incapable of performing their function when adequate resources are lacking. Consequently, in the tumor microenvironment there must exist competition for the common resources between cancer cells and the cells of the immune system, which may drive a lot of the tumor-immune dynamics. Proposed here is a model of tumor-immune-glucose interactions, formulated as a predator-prey-common resource type system, which allows to investigate possible dynamical behaviors that may arise as a result of competition for glucose, including tumor elimination, tumor dormancy and unrestrained tumor growth.

q-bio.TO↗

arXiv2014

Immune Evasion through Competitive Inhibition: the Shielding Effect of non-Stem Cancer Cells

It has been recently proposed that the two "emerging" hallmarks of cancer, namely altered glucose metabolism and immune evasion, may in fact be fundamentally linked (Kareva and Hahnfeldt, 2013). This connection comes from up-regulation of glycolysis by tumor cells, which can lead to active competition for resources in the tumor microenvironment between tumor and immune cells. Here it is further proposed that cancer stem cells (CSCs) can circumvent the anti-tumor immune response by creating a 'protective shield' of non-stem cancer cells around them. This shield can protect the CSCs both by creating a physical barrier between them and cytotoxic lymphocytes (CTLs), and by promoting competition for the common resources, such as glucose, between non-stem cancer cells and CTLs. The implications of this hypothesis are investigate using an agent-based model, leading to a prediction that relative CSC to non-CSC ratio will vary with the strength of the host immune response, with the highest occurring at an intermediate state of immune activation. A discussion of possible therapeutic approaches concludes the paper, suggesting that a chemotherapeutic regimen consisting of regular pulsed doses, i.e., metronomic chemotherapy, would yield the best clinical outcome by allowing CTLs to most effectively reach and eliminate CSCs.

q-bio.TO↗