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Tissues and Organs

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preprint2017arXiv

Misrepair mechanism: a mechanism essential for individual adaptation, species adaptation and species evolution

In Misrepair-accumulation theory, we have proposed a Misrepair mechanism for interpreting aging. However, Misrepair mechanism is also important in biological adaptation. Misrepair is a strategy of repair for increasing the surviving chance of an organism when it suffers from severe injuries. As a surviving strategy, Misrepair mechanism plays also an important role in individual adaptation, species survival, and species differentiation. Firstly, Misrepair of an injury is one of the manners of individual adaptation; and Misrepair mechanism gives an organism a great potential in adapting to changeable and destructive environment. Secondly, Misrepair mechanism is important in maintaining and enlarging the diversity of genome DNAs of a species; and a large diversity of genome DNAs is essential for the adaptation and the differentiation of a species in different environments. On one hand, somatic Misrepairs are essential for maintaining the sufficient number of individuals in a species, which are the vectors of different genome DNAs. On the other hand, Misrepair of DNA is a source of DNA mutations and the DNA Misrepairs in germ cells may contribute to the diversity of genome DNAs in a sp

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preprint2017arXiv

Cell transformation in tumor-development: a result of accumulation of Misrepairs of DNA through many generations of cells

Development of a tumor is known to be a result of accumulation of DNA changes in somatic cells. However, the processes of how DNA changes are produced and how they accumulate in somatic cells are not clear. DNA changes include two types: point DNA mutations and chromosome changes. However, point DNA mutations (DNA mutations) are the main type of DNA changes that can remain and accumulate in cells. Severe DNA injuries are the causes for DNA mutations. However, Misrepair of DNA is an essential process for transforming a DNA injury into a survivable and inheritable DNA mutation. In somatic cells, Misrepair of DNA is the main source of DNA mutations. Since the surviving chance of a cell by Misrepair of DNA is low, accumulation of DNA mutations can take place only possibly in the cells that can proliferate. Tumors can only develop in the tissues that are regenerable. The accumulation of Misrepairs of DNA needs to proceed in many generations of cells, and cell transformation from a normal cell into a tumor cell is a slow and long process. However, once a cell is transformed especially when it is malignantly transformed, the deficiency of DNA repair and the rapid cell proliferation will a

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preprint2017arXiv

Misrepair accumulation theory: a theory for understanding aging, cancer development, longevity, and adaptation

Misrepair accumulation theory is a novel theory in interpreting aging phenomena. With a new concept of Misrepair, this theory reaches a unified understanding of aging: aging of an organism is a result of accumulation of Misrepairs of its structure. Misrepair accumulation theory (MA theory) is distinct and it can improve our understanding of life on several aspects. I. MA theory is fundamentally different from other theories by: A. proposing a generalized concept of Misrepair; B. pointing out the evolutionary advantage of aging mechanism; and C. distinguishing between aging of a cell and aging of a tissue. II. MA theory overcomes the limitations of traditional theories on interpreting the phenomena of tissue fibrosis and cancer development. Tissue fibrosis, as a result of accumulation of Misrepairs with collagen fibers, is a powerful evidence for demonstrating the central role of Misrepairs in aging. Cancer development is a result of accumulation of DNA Misrepairs in somatic cells, which needs to proceed over many generations of cells in a regenerable tissue. III. MA theory improves also our understanding on longevity, premature aging, adaptation, and species evolution. The potentia

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preprint2016arXiv

Instability of spiral and scroll waves in the presence of a gradient in the fibroblast density: the effects of fibroblast-myocyte coupling

Fibroblast-myocyte coupling can modulate electrical-wave dynamics in cardiac tissue. In diseased hearts, the distribution of fibroblasts is heterogeneous, so there can be gradients in the fibroblast density (henceforth we call this GFD) especially from highly injured regions, like infarcted or ischemic zones, to less-wounded regions of the tissue. Fibrotic hearts are known to be prone to arrhythmias, so it is important to understand the effects of GFD in the formation and sustenance of arrhythmic re- entrant waves, like spiral or scroll waves. Therefore, we investigate the effects of GFD on the stability of spiral and scroll waves of electrical activation in a state-of-the- art mathematical model for cardiac tissue in which we also include fibroblasts. By introducing GFD in controlled ways, we show that spiral and scroll waves can be unstable in the presence of GFDs because of regions with varying spiral or scroll-wave frequency ω, induced by the GFD. We examine the effects of the resting membrane potential of the fibroblast and the number of fibroblasts attached to the myocytes on the stability of these waves. Finally, we show that the presence of GFDs can lead to the formation of

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preprint2016arXiv

Automatic labeling of molecular biomarkers of whole slide immunohistochemistry images using fully convolutional networks

This paper addresses the problem of quantifying biomarkers in multi-stained tissues, based on color and spatial information. A deep learning based method that can automatically localize and quantify the cells expressing biomarker(s) in a whole slide image is proposed. The deep learning network is a fully convolutional network (FCN) whose input is the true RGB color image of a tissue and output is a map of the different biomarkers. The FCN relies on a convolutional neural network (CNN) that classifies each cell separately according to the biomarker it expresses. In this study, images of immunohistochemistry (IHC) stained slides were collected and used. More than 4,500 RGB images of cells were manually labeled based on the expressing biomarkers. The labeled cell images were used to train the CNN (obtaining an accuracy of 92% in a test set). The trained CNN is then extended to an FCN that generates a map of all biomarkers in the whole slide image acquired by the scanner (instead of classifying every cell image). To evaluate our method, we manually labeled all nuclei expressing different biomarkers in two whole slide images and used theses as the ground truth. Our proposed method for i

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preprint2016arXiv

Effects of non-physiological blood pressure artefacts on measures of cerebral autoregulation

Cerebral autoregulation refers to regulation mechanisms that aim to maintain cerebral blood flow approximately constant. It is often assessed by autoregulation index (ARI), which uses arterial blood pressure and cerebral blood flow velocity time series to produce a ten-scale index of autoregulation performance (0 denoting the absence of and 9 the strongest autoregulation). Unfortunately, data are rarely free from various artefacts. Here, we consider four of the most common non-physiological blood pressure artefacts (saturation, square wave, reduced pulse pressure and impulse) and study their effects on ARI for a range of different artefact sizes. We show that a sufficiently large saturation and square wave always result in ARI reaching the maximum value of 9. The pulse pressure reduction and impulse artefact lead to a more diverse behaviour. Finally, we characterised the critical size of artefacts, defined as the minimum artefact size that, on average, leads to a 10\% deviation of ARI

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preprint2017arXiv

Aging as a process of accumulation of Misrepairs

We recently introduced Misrepair-accumulation theory as an interpretation on aging mechanism. For better understanding this theory, we discuss here in more details the new concept of Misrepair and the concept of accumulation of Misrepairs. I. Aging takes place uniquely on the systems that have a well-defined structure: an organization of its sub-structures. Aging of a non-living system is a result of accumulation of injuries (damage) of its structure. II. A generalized concept of Misrepair is important for reaching to a unified understanding of aging changes. In the situation of a severe injury, incorrect repair is a repair essential for maintaining structural integrity for increasing the surviving chance of an organism. With the same mechanism as that in "Misrepair of DNA" , the term of "Misrepair" can be used for describing all kinds of incorrect repairs on different types of living structures, including molecules, cells and tissues. A new concept of Misrepair is therefore proposed and defined as incorrect reconstruction of an injured living structure. Misrepair mechanism is beneficial for the survival of an organism, and it is essential for the survival of a spec

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preprint2016arXiv

Bone fusion in normal and pathological development is constrained by the network architecture of the human skull

The premature fusion of cranial bones, craniosynostosis, affects the correct development of the skull producing morphological malformations in newborns. To assess the susceptibility of each craniofacial articulation to close prematurely, we used a network model of the skull to quantify the link reliability (an index based on stochastic block modeling and Bayesian inference) of each articulation. We show that, of the 93 human skull articulations at birth, the few articulations that are associated with nonsyndromic craniosynostosis conditions have statistically significant lower reliability scores than the others. In a similar way, articulations that close during the normal postnatal development of the skull have also lower reliability scores than those articulations that persist through adult live. These results indicate a relationship between the architecture of the skull network and the specific articulations that close during normal development and in pathological conditions. Our findings suggest that the topological arrangement of skull bones might act as an epigenetic factor, predisposing some articulations to closure, both in normal and pathological development, and also affec

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preprint2016arXiv

Emergent structures and dynamics of cell colonies by contact inhibition of locomotion

Cells in tissues can organize into a broad spectrum of structures according to their function. Drastic changes of organization, such as epithelial-mesenchymal transitions or the formation of spheroidal aggregates, are often associated either to tissue morphogenesis or to cancer progression. Here, we study the organization of cell colonies by means of simulations of self-propelled particles with generic cell-like interactions. The interplay between cell softness, cell-cell adhesion, and contact inhibition of locomotion (CIL) yields structures and collective dynamics observed in several existing tissue phenotypes. These include regular distributions of cells, dynamic cell clusters, gel-like networks, collectively migrating monolayers, and 3D aggregates. We give analytical predictions for transitions between noncohesive, cohesive, and 3D cell arrangements. We explicitly show how CIL yields an effective repulsion that promotes cell dispersal, thereby hindering the formation of cohesive tissues. Yet, in continuous monolayers, CIL leads to collective cell motion, ensures tensile intercellular stresses, and opposes cell extrusion. Thus, our work highlights the prominent role of CIL in det

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preprint2016arXiv

Scroll-wave dynamics in the presence of ionic and conduction inhomogeneities in an anatomically realistic mathematical model for the pig heart

Nonlinear waves of the reaction-diffusion (RD) type occur in many biophysical systems, including the heart, where they initiate cardiac contraction. Such waves can form vortices called scroll waves, which result in the onset of life-threatening cardiac arrhythmias. The dynamics of scroll waves is affected by the presence of inhomogeneities, which, in a very general way, can be of \textit{(i)} ionic type, i.e., they affect the reaction part, or \textit{(ii)} conduction type, i.e., they affect the diffusion part of an RD equation. We demostrate, for the first time, by using a state-of-the-art, anatomically realistic model of the pig heart, how differences in the geometrical and biophysical nature of such inhomogeneities can influence scroll-wave dynamics in different ways. Our study reveals that conduction-type inhomogeneities become increasingly important at small length scales, i.e., in the case of multiple, randomly distributed, obstacles in space at the cellular scale ($0.2-0.4{\rm mm}$). Such configurations can lead to scroll-wave break up. In contrast, ionic inhomogeneities, affect scroll-wave dynamics significantly at large length scales, when these inhomogeneities are localiz

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Structure, Function, and Control of the Musculoskeletal Network

The human body is a complex organism whose gross mechanical properties are enabled by an interconnected musculoskeletal network controlled by the nervous system. The nature of musculoskeletal interconnection facilitates stability, voluntary movement, and robustness to injury. However, a fundamental understanding of this network and its control by neural systems has remained elusive. Here we utilize medical databases and mathematical modeling to reveal the organizational structure, predicted function, and neural control of the musculoskeletal system. We construct a whole-body musculoskeletal network in which single muscles connect to multiple bones via both origin and insertion points. We demonstrate that a muscle's role in this network predicts susceptibility of surrounding components to secondary injury. Finally, we illustrate that sets of muscles cluster into network communities that mimic the organization of motor cortex control modules. This novel formalism for describing interactions between the muscular and skeletal systems serves as a foundation to develop and test therapeutic responses to injury, inspiring future advances in clinical treatments.

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preprint2016arXiv

Mechanisms of stochastic onset and termination of atrial fibrillation episodes: Insights using a cellular automaton model

Mathematical models of cardiac electrical excitation are increasingly complex, with multiscale models seeking to represent and bridge physiological behaviours across temporal and spatial scales. The increasing complexity of these models makes it computationally expensive to both evaluate long term (>60 seconds) behaviour and determine sensitivity of model outputs to inputs. This is particularly relevant in models of atrial fibrillation (AF), where individual episodes last from seconds to days, and inter-episode waiting times can be minutes to months. Potential mechanisms of transition between sinus rhythm and AF have been identified but are not well understood, and it is difficult to simulate AF for long periods of time using state-of-the-art models. In this study, we implemented a Moe-type cellular automaton on a novel, topologically correct surface geometry of the left atrium. We used the model to simulate stochastic initiation and spontaneous termination of AF, arising from bursts of spontaneous activation near pulmonary veins. The simplified representation of atrial electrical activity reduced computational cost, and so permitted us to investigate AF mechanisms in a probabilist

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preprint2016arXiv

Multi-Organ Cancer Classification and Survival Analysis

Accurate and robust cell nuclei classification is the cornerstone for a wider range of tasks in digital and Computational Pathology. However, most machine learning systems require extensive labeling from expert pathologists for each individual problem at hand, with no or limited abilities for knowledge transfer between datasets and organ sites. In this paper we implement and evaluate a variety of deep neural network models and model ensembles for nuclei classification in renal cell cancer (RCC) and prostate cancer (PCa). We propose a convolutional neural network system based on residual learning which significantly improves over the state-of-the-art in cell nuclei classification. Finally, we show that the combination of tissue types during training increases not only classification accuracy but also overall survival analysis.

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preprint2016arXiv

Lipidomic approach for stratification of Acute Myeloid Leukemia patients

The pathogenesis and progression of many tumors, including hematologic malignancies is highly dependent on enhanced lipogenesis. De novo fatty-acid synthesis permits accelerated proliferation of tumor cells by providing structural components to build the membranes. It may also lead to alterations of physicochemical properties of the formed membranes, which can have an impact on signaling or even increase resistance to drugs in cancer cells. Cancer type-specific lipid profiles would allow understanding the actual effects of lipid changes and therefore could potentially serve as fingerprints for individual tumors and be explored as diagnostic markers. We have used shotgun MS approach to identify lipid patterns in different types of acute myeloid leukemia (AML) patients that either show no karyotype changes or belong to t(8;21) or inv16 types. The observed differences in lipidomes of t(8;21) and inv(16) patients, as compared to AML patients without karyotype changes, concentrate mostly on substantial modulation of ceramides/sphingolipids synthesis. Also significant changes in the physicochemical properties of the membranes, between the t(8;21) and the other patients, were noted that w

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preprint2016arXiv

Uncertainty of current understanding regarding OBT formation in plants

Radiological impact models are important tools that support nuclear safety. For tritium, a special radionuclide that readily enters the life cycle, the processes involved in its transport into the environment are complex and inadequately understood. For example, tritiated water (HTO) enters plants by leaf and root uptake and is converted to organically bound tritium (OBT) in exchangeable and non-exchangeable forms; however, the observed OBT/HTO ratios in crops exhibit large variability and contradict the current models for routine releases. Non-routine or spike releases of tritium further complicate the prediction of OBT formation. The experimental data for a short and intense atmospheric contamination of wheat are presented together with various models predictions. The experimental data on wheat demonstrate that the OBT formation is a long process, it is dependent on receptor location and stack dynamics, there are differences between night and day releases, and the HTO dynamics in leaf and ear is a very important contributor to OBT formation.

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preprint2016arXiv

One-dimensional Arterial Network Model for Bypass Grafts Assessment

We propose an arterial network model based on 1D blood hemodynamic equations to study the behavior of different vascular surgical bypass grafts in case of an arterial occlusive pathology: an obliteration or stenosis of the iliac artery. We investigate the performances of three different bypass grafts (Aorto-Femoral, Axillo-Femoral and cross-over Femoral) depending on the degree of obliteration of the stenosis. Numerical simulations show that all bypass grafts are efficient since we retrieve in all cases the normal hemodynamics in the stenosed region while ensuring at the same time a global healthy circulation. We analyze in particular the Axillo-Femoral bypass graft by performing hundreds of simulations by varying the values of the Young's modulus [0.1--50 MPa] and the radius [0.01--5 cm] of the bypass graft. We show that the Young's modulus and radius of commercial bypass grafts are optimal in terms of hemodynamic considerations. The numerical findings prove that this approach could be used to optimize or plan surgeries for specific patients, to perform parameter's statistics and error propagation evaluations by running extensive simulations, or to characterize numeric

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preprint2016arXiv

Hydrolytic and lysozymic degradability of chitosan systems with heparin-mimicking pendant groups

Chitosan (CT) is an antibacterial polysaccharide that has been investigated for drug carriers, haemostats and wound dressings. For these applications, customised CT devices can often be obtained with specific experimental conditions, which can irreversibly alter native biopolymer properties and functions and lead to unreliable material behaviour. In order to investigate the structure-function relationships in CT covalent networks, monosodium 5-sulfoisophthalate (PhS) was selected as heparin-mimicking, growth factor-binding crosslinking segment, whilst 1,4-phenylenediacetic acid (4Ph) and poly(ethylene glycol) bis(carboxymethyl) ether (PEG) were employed as sulfonic acid-free diacids of low and high crosslinker length respectively. Hydrogels based on short crosslinkers (PhS and 4Ph) displayed increased crosslink density, decreased swelling ratio as well as minimal hydrolytic and lysozymic degradation, whilst addition of lysozymes to PEG based networks resulted in 70 wt.-% mass loss. PhS-crosslinked CT hydrogels displayed the highest loss (40 +/- 6 CFU%) of antibacterial activity upon incubation with Porphyromonas gingivalis, whilst respective extracts were tolerated by L929 mouse fi

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preprint2016arXiv

Perspectives on the mathematics of biological patterning and morphogenesis

A central question in developmental biology is how size and position are determined. The genetic code carries instructions on how to control these properties in order to regulate the pattern and morphology of structures in the developing organism. Transcription and protein translation mechanisms implement these instructions. However, this cannot happen without some manner of sampling of epigenetic information on the current patterns and morphological forms of structures in the organism. Any rigorous description of space- and time-varying patterns and morphological forms reduces to one among various classes of spatio-temporal partial differential equations. Reaction-transport equations represent one such class. Starting from simple Fickian diffusion, the incorporation of reaction, phase segregation and advection terms can represent many of the patterns seen in the animal and plant kingdoms. Morphological form, requiring the development of three-dimensional structure, also can be represented by these equations of mass transport, albeit to a limited degree. The recognition that physical forces play controlling roles in shaping tissues leads to the conclusion that (nonlinear) elasticit

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preprint2016arXiv

Multi-Constituent Simulation of Thrombus Deposition

In this paper, we present a spatio-temporal mathematical model for simulating the formation and growth of a thrombus. Blood is treated as a multi-constituent mixture comprised of a linear fluid phase and a thrombus (solid) phase. The transport and reactions of 10 chemical and biological species are incorporated using a system of coupled convection-reaction-diffusion (CRD) equations to represent three processes in thrombus formation: initiation, propagation and stabilization. Computational fluid dynamic (CFD) simulations using the libraries of OpenFOAM were performed for two illustrative benchmark problems: in vivo thrombus growth in an injured blood vessel and in vitro thrombus deposition in micro-channels (1.5mm x 1.6mm x 0.1mm) with small crevices (125μm x 75μm and 125μm x 137μm). For both problems, the simulated thrombus deposition agreed very well with experimental observations, both spatially and temporally. Based on the success with these two benchmark problems, which have very different flow conditions and biological environments, we believe that the current model will provide useful insight into the genesis of thrombosis in blood-wetted devices, and provide a tool for the d

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preprint2016arXiv

Modelling the effect of curvature on the collective behaviour of cells growing new tissue

The growth of several biological tissues is known to be controlled in part by local geometrical features, such as the curvature of the tissue interface. This control leads to changes in tissue shape that in turn can affect the tissue's evolution. Understanding the cellular basis of this control is highly significant for bioscaffold tissue engineering, the evolution of bone microarchitecture, wound healing, and tumour growth. While previous models have proposed geometrical relationships between tissue growth and curvature, the role of cell density and cell vigor remains poorly understood. We propose a cell-based mathematical model of tissue growth to investigate the systematic influence of curvature on the collective crowding or spreading of tissue-synthesising cells induced by changes in local tissue surface area during the motion of the interface. Depending on the strength of diffusive damping, the model exhibits complex growth patterns such as undulating motion, efficient smoothing of irregularities, and the generation of cusps. We compare this model with in-vitro experiments of tissue deposition in bioscaffolds of different geometries. By accounting for the depletion of acti

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preprint2016arXiv

A Mathematical Model of Mechanotransduction

This article reviews the mechanical bidomain model, a mathematical description how the extracellular matrix and intracellular cytoskeleton are coupled by integrin proteins. The fundamental hypothesis is that differences between intracellular and extracellular displacements drive mechanotransduction. A one-dimensional example illustrates the model, which is then extended to two dimensions. In several cases the equations are solved analytically, illustrating how displacements divide into two parts: monodomain displacements are identical in both spaces and therefore do not contribute to mechanotransduction, whereas bidomain displacements cause mechanotransduction. A new length constant depends on the intracellular and extracellular shear moduli and the integrin spring constant, and bidomain effects often occur within a few length constants of the tissue edge. Numerical methods for solving the model equations are being developed. Precursors to the model and potential applications are discussed. The bidomain model may be applicable to cardiac remodeling, blood vessel regulation, tissue engineering, stem cell differentiation, cancer biology, and development.

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preprint2012arXiv

Velocity distribution of neutral particles ejected from biological material under ultra short laser radiation

Neutral particles ejected from biological material under ultra short laser ablation have been investigated by laser post-ionization time-of-flight mass spectrometry. It could be shown, that beside ionized species, a substantial amount of neutral particles is ejected. A temporal study of the ablation plume is carried out by recording neutral particle time-of- flight mass spectra as a function of delay time between the ablation and post-ionization pulse. Close the ablation threshold, the mechanism of ejection is found to be of predominantely mechanical nature, driven by the relaxation of the laser-induced pressure. In this regime of stress confinement, the ejection results in very broad velocity distributions and extremely low velocities.

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preprint2016arXiv

Multiple Sclerosis and Geomagnetic Disturbances: Investigating a Potentially Important Environmental Risk Factor

Multiple sclerosis (MS) is the most common disabling neurological disorders in the young adults. In spite of many researches, the cause of the disease has remained mainly not understood. All evidences indicate that environmental risk factors play key roles in this disease etiology. Various hypotheses have been posited up to now on the presumed disease risk factors, however, they were not successful in explaining all MS features. The aim of this article is to introduce the concept of the newly proposed "geomagnetic disturbance hypothesis of MS" and its abilities in explaining the special features of the disease to encourage medical geologist and other biomedical researchers to contribute to this area of research.

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preprint2016arXiv

Pruning to Increase Taylor Dispersion in Physarum polycephalum Networks

How do the topology and geometry of a tubular network affect the spread of particles within fluid flows? We investigate patterns of effective dispersion in the hierarchical, biological transport network formed by Physarum polycephalum. We demonstrate that a change in topology - pruning in the foraging state - causes a large increase in effective dispersion throughout the network. By comparison, changes in the hierarchy of tube radii result in smaller and more localized differences. Pruned networks capitalize on Taylor dispersion to increase the dispersion capability.

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