scholarly journals Self-* properties through gossiping

2008 ◽  
Vol 366 (1881) ◽  
pp. 3747-3757 ◽  
Author(s):  
Ozalp Babaoglu ◽  
Márk Jelasity
Keyword(s):  
Cell Sorting ◽  
Mobile Agents ◽  
Large Scale ◽  
Overlay Networks ◽  
Biological Mechanism ◽  
Human Intervention ◽  
Differential Adhesion ◽  
Novel Approach ◽  
Large Numbers ◽  
Ubiquitous Systems

As computer systems have become more complex, numerous competing approaches have been proposed for these systems to self-configure, self-manage, self-repair, etc. such that human intervention in their operation can be minimized. In ubiquitous systems, this has always been a central issue as well. In this paper, we overview techniques to implement self-* properties in large-scale, decentralized networks through bio-inspired techniques in general, and gossip-based algorithms in particular. We believe that gossip-based algorithms could be an important inspiration for solving problems in ubiquitous computing as well. As an example, we outline a novel approach to arrange large numbers of mobile agents (e.g. vehicles, rescue teams carrying mobile devices) into different formations in a totally decentralized manner. The approach is inspired by the biological mechanism of cell sorting via differential adhesion, as well as by our earlier work in self-organizing peer-to-peer overlay networks.

scholarly journals Large-scale simulations of biological cell sorting driven by differential adhesion follow diffusion-limited domain coalescence regime

2020 ◽  
Author(s):  
Marc Durand
Keyword(s):  
Cell Sorting ◽  
Large Scale ◽  
Experimental Studies ◽  
Finite Size ◽  
Domain Size ◽  
Cellular Potts Model ◽  
Mixture Ratio ◽  
Cell Behaviors ◽  
Differential Adhesion ◽  
Initial Cluster

Cell sorting, whereby a heterogeneous cell mixture segregates and forms distinct homogeneous tissues, is one of the main collective cell behaviors at work during development. Although differences in interfacial energies are recognized to be a possible driving source for cell sorting, no clear consensus has emerged on the kinetic law of cell sorting driven by differential adhesion. Using a modified Cellular Potts Model algorithm that allows for efficient simulations while preserving the connectivity of cells, we numerically explore cell-sorting dynamics over unprecedentedly large scales in space and time. For a binary mixture of cells surrounded by a medium, increase of domain size follows a power-law with exponent n = 1/4 independently of the mixture ratio, revealing that the kinetics is dominated by the diffusion and coalescence of rounded domains. We compare these results with recent numerical and experimental studies on cell sorting, and discuss the importance of boundary conditions, space dimension, initial cluster geometry, and finite size effects on the observed scaling.

A FUNCTIONAL DIFFERENTIAL EQUATION MODEL FOR BIOLOGICAL CELL SORTING DUE TO DIFFERENTIAL ADHESION

2012 ◽  
Vol 23 (01) ◽  
pp. 93-126 ◽  
Author(s):  
GREG LEMON ◽  
JOHN R. KING
Keyword(s):  
Mathematical Model ◽  
Cell Sorting ◽  
Biological Tissue ◽  
Numerical Solutions ◽  
Functional Differential Equations ◽  
Cell Types ◽  
Equation Model ◽  
Differential Adhesion ◽  
Novel Approach ◽  
Functional Differential

This paper presents a mathematical model to describe the sorting of two different types of cells, arising from differential adhesion mechanisms within biological tissue. The model is based on a continuum approach that takes into account individual cell behavior including aspects of the cell-migration process, dynamics of the adhesions between contacting cells, and finite cell size. Numerical solutions and bifurcation analyses for the case of a collection of two different cell types show a variety of behaviors observed in experiments, including spatially uniform mixing of cells and the formation of two distinct, containing both types of cells or just one. The mathematical model, which is in the form of a set of functional differential equations, represents a novel approach to continuum modeling of cell sorting and migration within biological tissue.

Large-scale mutagenesis directed at specific chromosomes in wheat

Genome ◽  
2001 ◽  
Vol 44 (1) ◽  
pp. 45-49 ◽  
Author(s):  
Robert Koebner ◽  
James Hadfield
Keyword(s):  
Disease Resistance ◽  
Large Scale ◽  
Target Gene ◽  
Yellow Rust ◽  
Chemical Mutagenesis ◽  
Loss Of Function ◽  
Novel Approach ◽  
Large Numbers ◽  
Resistance Pathway ◽  
Order Of Magnitude

A novel approach has been developed to allow for the efficient selection of loss-of-function wheat mutants in the M1 generation, following either physical or chemical mutagenesis. This has generated an order of magnitude increase in the efficiency of identification of mutants, and also greatly increases the likelihood that selected individuals reflect mutation events at the target locus, rather than at genes acting elsewhere in the disease resistance pathway. The approach relies only on prior knowledge of the chromosomal location of the target gene, and uses the polyploidy of wheat to construct populations for mutagenesis in which large numbers of individuals are hemizygous for the target gene. The idea is illustrated with the mass identification of mutants at three independent genes for race-specific resistance to yellow rust, and one gene for resistance to powdery mildew.Key words: disease resistance mutant, hemizygotes, loss-of-function mutant.

scholarly journals High-throughput microfluidic cell sorting platform (MICS)

2019 ◽  
Author(s):  
David Philpott ◽  
Peter Aldridge ◽  
Barbara Mair ◽  
Randy Atwal ◽  
Sanna Masud ◽  
...  
Keyword(s):  
Protein Expression ◽  
Cell Viability ◽  
High Throughput ◽  
Cell Sorting ◽  
Mammalian Cells ◽  
Large Scale ◽  
Genetic Screens ◽  
Large Numbers ◽  
Conventional Cell ◽  
Set Up

Abstract Genome-scale functional genetic screens can be used to interrogate determinants of protein expression modulation of a target of interest. Such phenotypic screening approaches typically require sorting of large numbers of cells (>108). In conventional cell sorting techniques (i.e. fluorescence-activated cell sorting), sorting time, associated with high instrument and operating costs and loss of cell viability, are limiting to the scalability and throughput of these screens. We recently established a rapid and scalable high-throughput microfluidic cell sorting platform (MICS) using immunomagnetic nanoparticles to sort cells in parallel capable of sorting more than 108 HAP1 cells in under one hour while maintaining high levels of cell viability (Ref. 1). This protocol outlines how to set-up MICS for large-scale phenotypic screens in mammalian cells. We anticipate this platform being used for genome-wide functional genetic screens as well as other applications requiring the sorting of large numbers of cells based on protein expression.

scholarly journals Large-scale simulations of biological cell sorting driven by differential adhesion follow diffusion-limited domain coalescence regime

2021 ◽  
Vol 17 (8) ◽  
pp. e1008576
Author(s):  
Marc Durand
Keyword(s):  
Cell Sorting ◽  
Large Scale ◽  
Domain Size ◽  
Cellular Potts Model ◽  
Mixture Ratio ◽  
Cell Behaviors ◽  
Differential Adhesion ◽  
Interfacial Energies ◽  
Diffusion Limited ◽  
Medium Increase

Cell sorting, whereby a heterogeneous cell mixture segregates and forms distinct homogeneous tissues, is one of the main collective cell behaviors at work during development. Although differences in interfacial energies are recognized to be a possible driving source for cell sorting, no clear consensus has emerged on the kinetic law of cell sorting driven by differential adhesion. Using a modified Cellular Potts Model algorithm that allows for efficient simulations while preserving the connectivity of cells, we numerically explore cell-sorting dynamics over very large scales in space and time. For a binary mixture of cells surrounded by a medium, increase of domain size follows a power-law with exponent n = 1/4 independently of the mixture ratio, revealing that the kinetics is dominated by the diffusion and coalescence of rounded domains. We compare these results with recent numerical studies on cell sorting, and discuss the importance of algorithmic differences as well as boundary conditions on the observed scaling.

Computer Analyses in Preventive Health Research

1967 ◽  
Vol 06 (01) ◽  
pp. 8-14 ◽  
Author(s):  
M. F. Collen
Keyword(s):  
Medical Research ◽  
Preventive Medicine ◽  
Health Research ◽  
Large Scale ◽  
Preventive Health ◽  
New Era ◽  
Large Numbers ◽  
Normal Test ◽  
Computer Analyses

The utilization of an automated multitest laboratory as a data acquisition center and of a computer for trie data processing and analysis permits large scale preventive medical research previously not feasible. Normal test values are easily generated for the particular population studied. Long-term epidemiological research on large numbers of persons becomes practical. It is our belief that the advent of automation and computers has introduced a new era of preventive medicine.

Green synthesis, characterization of silver sulfide nanoparticles and antibacterial activity evaluation

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Antibacterial Activity ◽  
Large Scale ◽  
Research Work ◽  
Silver Sulfide ◽  
Morphological Properties ◽  
Effective Diameter ◽  
Novel Approach ◽  
Transmission Electron ◽  
Green Route ◽  
Silver Sulfide Nanoparticles

This research work presents a facile and green route for synthesis silver sulfide (Ag2SNPs) nanoparticles from silver nitrate (AgNO3) and sodium sulfide nonahydrate (Na2S.9H2O) in the presence of rosemary leaves aqueous extract at ambient temperature (27 oC). Structural and morphological properties of Ag2SNPs nanoparticles were analyzed by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The surface Plasmon resonance for Ag2SNPs was obtained around 355 nm. Ag2SNPs was spherical in shape with an effective diameter size of 14 nm. Our novel approach represents a promising and effective method to large scale synthesis of eco-friendly antibacterial activity silver sulfide nanoparticles.

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