simmer : Discrete-Event Simulation for R Ucar, Iñaki; Smeets, Bart; Azcorra, Arturo
Journal of statistical software,
07/2019, Letnik:
90, Številka:
2
Journal Article
Recenzirano
Odprti dostop
The simmer package brings discrete-event simulation to R. It is designed as a generic yet powerful process-oriented framework. The architecture encloses a robust and fast simulation core written in ...C++ with automatic monitoring capabilities. It provides a rich and flexible R API (application programming interface) that revolves around the concept of trajectory, a common path in the simulation model for entities of the same type.
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 determining the emergent structures and dynamics of cell colonies.
We consider a cell as an elastic, contractile shell surrounding a liquid incompressible cytoplasm and with nonspecific adhesion. We perform numerical simulations of this model to study the mechanics ...of cell-cell separation. By variation of parameters, we are able to recover well-known limits of the Johnson-Kendall-Roberts theory, the Derjaguin-Muller-Toporov model, adhesive vesicles with surface tension (Brochard-Wyart and de Gennes derivation), and thin elastic shells. We further locate biological cells on this parameter space by comparison to existing experiments on S180 cells. Using this model, we show that mechanical parameters can be obtained that are consistent with both dual pipette aspiration and micropipette aspiration, a problem not successfully tackled so far. We estimate a cortex elastic modulus of Ec ≈ 15 kPa, an effective cortex thickness of tc ≈ 0.3 μm, and an active tension of γ ≈ 0.4 nN/μm. With these parameters, a Johnson-Kendall-Roberts-like scaling of the separation force is recovered. Finally, the change of contact radius with applied force in a pull-off experiment was investigated. For small forces, a scaling similar to both the Brochard-Wyart and de Gennes derivation and the Derjaguin-Muller-Toporov model is found.
Abstract
Motivation
Uncovering the cellular and mechanical processes that drive embryo formation requires an accurate read out of cell geometries over time. However, automated extraction of 3D cell ...shapes from time-lapse microscopy remains challenging, especially when only membranes are labeled.
Results
We present an image analysis framework for automated tracking and three-dimensional cell segmentation in confocal time lapses. A sphere clustering approach allows for local thresholding and application of logical rules to facilitate tracking and unseeded segmentation of variable cell shapes. Next, the segmentation is refined by a discrete element method simulation where cell shapes are constrained by a biomechanical cell shape model. We apply the framework on Caenorhabditis elegans embryos in various stages of early development and analyze the geometry of the 7- and 8-cell stage embryo, looking at volume, contact area and shape over time.
Availability and implementation
The Python code for the algorithm and for measuring performance, along with all data needed to recreate the results is freely available at 10.5281/zenodo.5108416 and 10.5281/zenodo.4540092. The most recent version of the software is maintained at https://bitbucket.org/pgmsembryogenesis/sdt-pics.
Supplementary information
Supplementary data are available at Bioinformatics online.
The development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized ...kidney tissue sections stained with periodic acid-Schiff (PAS).
We trained the network using multiclass annotations from 40 whole-slide images of stained kidney transplant biopsies and applied it to four independent data sets. We assessed multiclass segmentation performance by calculating Dice coefficients for ten tissue classes on ten transplant biopsies from the Radboud University Medical Center in Nijmegen, The Netherlands, and on ten transplant biopsies from an external center for validation. We also fully segmented 15 nephrectomy samples and calculated the network's glomerular detection rates and compared network-based measures with visually scored histologic components (Banff classification) in 82 kidney transplant biopsies.
The weighted mean Dice coefficients of all classes were 0.80 and 0.84 in ten kidney transplant biopsies from the Radboud center and the external center, respectively. The best segmented class was "glomeruli" in both data sets (Dice coefficients, 0.95 and 0.94, respectively), followed by "tubuli combined" and "interstitium." The network detected 92.7% of all glomeruli in nephrectomy samples, with 10.4% false positives. In whole transplant biopsies, the mean intraclass correlation coefficient for glomerular counting performed by pathologists versus the network was 0.94. We found significant correlations between visually scored histologic components and network-based measures.
This study presents the first convolutional neural network for multiclass segmentation of PAS-stained nephrectomy samples and transplant biopsies. Our network may have utility for quantitative studies involving kidney histopathology across centers and provide opportunities for deep learning applications in routine diagnostics.
WikiPathways (http://www.wikipathways.org) is an open, collaborative platform for capturing and disseminating models of biological pathways for data visualization and analysis. Since our last NAR ...update, 4 years ago, WikiPathways has experienced massive growth in content, which continues to be contributed by hundreds of individuals each year. New aspects of the diversity and depth of the collected pathways are described from the perspective of researchers interested in using pathway information in their studies. We provide updates on extensions and services to support pathway analysis and visualization via popular standalone tools, i.e. PathVisio and Cytoscape, web applications and common programming environments. We introduce the Quick Edit feature for pathway authors and curators, in addition to new means of publishing pathways and maintaining custom pathway collections to serve specific research topics and communities. In addition to the latest milestones in our pathway collection and curation effort, we also highlight the latest means to access the content as publishable figures, as standard data files, and as linked data, including bulk and programmatic access.
Lattice structures offer enhanced stiffness-to-weight characteristics for structures in highly mass sensitive applications like aviation and aerospace. The adaptability of composite materials allows ...for further optimisation of the structural layout of the lattice to reduce mass for primary aerospace structures. The attachment point on the lattice is a key structural feature, defining the interaction between the payload and the primary structure. The present work investigates an attachment point design for a lattice satellite central cylinder approximately 1.5 m in diameter, manufactured using composite prepreg fibre placement. This work presents the design, experimental testing and numerical analysis of attachment points consisting of filled patches in the lattice. The points were loaded in shear and the responses of the surrounding helical and hoop ribs of the lattice were monitored using strain gauges, LVDTs and a digital image correlation system. The measured response of the structure validated numerical predictions and the numerical design methodology.
Many real-life applications of the Discrete Element Method (DEM) require a particle description which accounts for irregular and arbitrary shapes. In this work, a novel method is presented for ...calculating contact force interactions between polyhedral particles. A contact between two polyhedra is decomposed as a set of contacts between individual polygonal facets. For each polygon–polygon contact, an individual contact force is obtained by integrating a linear pressure over the area of its intersection. Both convex as well as partially concave polyhedra can be accurately represented. The proposed algorithm is validated by comparing to previously published experimental and computational gravitational particle depositions of identical cubes. Finally, the model is demonstrated in simulations of gravitational packing of various other polyhedral shapes.
Actin protrusion dynamics plays an important role in the regulation of three-dimensional (3D) cell migration. Cells form protrusions that adhere to the surrounding extracellular matrix (ECM), ...mechanically probe the ECM and contract in order to displace the cell body. This results in cell migration that can be directed by the mechanical anisotropy of the ECM. However, the subcellular processes that regulate protrusion dynamics in 3D cell migration are difficult to investigate experimentally and therefore not well understood. Here, we present a computational model of cell migration through a degradable viscoelastic ECM. This model is a 2D representation of 3D cell migration. The cell is modeled as an active deformable object that captures the viscoelastic behavior of the actin cortex and the subcellular processes underlying 3D cell migration. The ECM is regarded as a viscoelastic material, with or without anisotropy due to fibrillar strain stiffening, and modeled by means of the meshless Lagrangian smoothed particle hydrodynamics (SPH) method. ECM degradation is captured by local fluidization of the material and permits cell migration through the ECM. We demonstrate that changes in ECM stiffness and cell strength affect cell migration and are accompanied by changes in number, lifetime and length of protrusions. Interestingly, directly changing the total protrusion number or the average lifetime or length of protrusions does not affect cell migration. A stochastic variability in protrusion lifetime proves to be enough to explain differences in cell migration velocity. Force-dependent adhesion disassembly does not result in faster migration, but can make migration more efficient. We also demonstrate that when a number of simultaneous protrusions is enforced, the optimal number of simultaneous protrusions is one or two, depending on ECM anisotropy. Together, the model provides non-trivial new insights in the role of protrusions in 3D cell migration and can be a valuable contribution to increase the understanding of 3D cell migration mechanics.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Acute kidney injury (AKI) is associated with high morbidity and mortality. Recent genetic fate mapping studies demonstrated that recovery from AKI occurs from intrinsic tubular cells. It is ...unresolved whether these intrinsic cells (so-called “scattered tubular cells”) represent fixed progenitor cells or whether recovery involves any surviving tubular cell. Here, we show that the doxycycline-inducible parietal epithelial cell (PEC)–specific PEC–reverse-tetracycline transactivator (rtTA) transgenic mouse also efficiently labels the scattered tubular cell population. Proximal tubular cells labeled by the PEC–rtTA mouse coexpressed markers for scattered tubular cells (kidney injury molecule 1, annexin A3, src-suppressed C-kinase substrate, and CD44) and showed a higher proliferative index. The PEC–rtTA mouse labeled more tubular cells upon different tubular injuries but was independent of cellular proliferation as determined in physiological growth of the kidney. To resolve whether scattered tubular cells are fixed progenitors, cells were irreversibly labeled before ischemia reperfusion injury (genetic cell fate mapping). During recovery, the frequency of labeled tubular cells remained constant, arguing against a fixed progenitor population. In contrast, when genetic labeling was induced during ischemic injury and subsequent recovery, the number of labeled cells increased significantly, indicating that scattered tubular cells arise from any surviving tubular cell. In summary, scattered tubular cells do not represent a fixed progenitor population but rather a phenotype that can be adopted by almost any proximal tubular cell upon injury. Understanding and modulating these phenotypic changes using the PEC–rtTA mouse may lead to more specific therapies in AKI.
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