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.

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.

Data-Parallel Techniques for Agent-Based Tissue Modeling on Graphics Processing Units

2008 ◽  
Author(s):  
Ryan S. Richards ◽  
Mikola Lysenko ◽  
Roshan M. D’Souza ◽  
Gary An
Keyword(s):  
Real Time ◽  
Graphics Processing Units ◽  
Large Scale ◽  
Experimental Studies ◽  
Test Case ◽  
Cell Systems ◽  
Von Neumann ◽  
Agent Based ◽  
Cell Behaviors ◽  
Graphics Processing

Agent-Based Modeling has been recently recognized as a method for in-silico multi-scale modeling of biological cell systems. Agent-Based Models (ABMs) allow results from experimental studies of individual cell behaviors to be scaled into the macro-behavior of interacting cells in complex cell systems or tissues. Current generation ABM simulation toolkits are designed to work on serial von-Neumann architectures, which have poor scalability. The best systems can barely handle tens of thousands of agents in real-time. Considering that there are models for which mega-scale populations have significantly different emergent behaviors than smaller population sizes, it is important to have the ability to model such large scale models in real-time. In this paper we present a new framework for simulating ABMs on programmable graphics processing units (GPUs). Novel algorithms and data-structures have been developed for agent-state representation, agent motion, and replication. As a test case, we have implemented an abstracted version of the Systematic Inflammatory Response System (SIRS) ABM. Compared to the original implementation on the NetLogo system, our implementation can handle an agent population that is over three orders of magnitude larger with close to 40 updates/sec. We believe that our system is the only one of its kind that is capable of efficiently handling realistic problem sizes in biological simulations.

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 Leisure Time Sports Activities and Life Satisfaction: Deeper Insights Based on a Representative Survey from Germany

2020 ◽  
Author(s):  
Michael Mutz ◽  
Anne K. Reimers ◽  
Yolanda Demetriou
Keyword(s):  
Life Satisfaction ◽  
Large Scale ◽  
Leisure Time ◽  
Organizational Context ◽  
Experimental Studies ◽  
Well Being ◽  
Activity Level ◽  
Leisure Satisfaction ◽  
General Life Satisfaction ◽  
Sports Activities

Abstract Observational and experimental studies show that leisure time sporting activity (LTSA) is associated with higher well-being. However, scholars often seem to assume that 1) LTSA fosters “general” life satisfaction, thereby ignoring effects on domain satisfaction; 2) the effect of LTSA on well-being is linear and independent of a person’s general activity level; 3) the amount of LTSA is more important than the repertoire of LTSA, i.e. the number of different activities; 4) all kinds of LTSA are equal in their effects, irrespective of spatial and organisational context conditions. Using data from the German SALLSA-Study (“Sport, Active Lifestyle and Life Satisfaction”), a large-scale CAWI-Survey (N = 1008) representing the population ≥ 14 years, the paper takes a closer look on these assumptions. Findings demonstrate that LTSA is associated with general life satisfaction and domain-specific satisfaction (concerning relationships, appearance, leisure, work and health), but that the relationship is most pronounced for leisure satisfaction. Associations of sport with life satisfaction, leisure satisfaction and subjective health are non-linear, approaching an injection point from which on additional LTSA is no longer beneficial. Moreover, findings lend support to the notion that diversity in LTSA matters, as individuals with higher variation in sports activities are more satisfied. Finally, results with regard to spatial and organizational context suggest that outdoor sports and club-organized sports have additional benefits.

scholarly journals Why does the spread of COVID-19 vary greatly in different countries? Revealing the efficacy of face masks in epidemic prevention

2021 ◽  
Vol 149 ◽  
Author(s):  
Jincheng Wei ◽  
Shurui Guo ◽  
Enshen Long ◽  
Li Zhang ◽  
Bizhen Shu ◽  
...  
Keyword(s):  
Social Isolation ◽  
Large Scale ◽  
Experimental Studies ◽  
Weighted Average ◽  
Filtration Efficiency ◽  
Volume Distribution ◽  
Particle Sizes ◽  
Economic Activities ◽  
Protection Measure ◽  
Source Of Infection

Abstract The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is highly contagious, and the coronavirus disease 2019 (COVID-19) pandemic caused by it has forced many countries to adopt ‘lockdown’ measures to prevent the spread of the epidemic through social isolation of citizens. Some countries proposed universal mask wearing as a protection measure of public health to strengthen national prevention efforts and to limit the wider spread of the epidemic. In order to reveal the epidemic prevention efficacy of masks, this paper systematically evaluates the experimental studies of various masks and filter materials, summarises the general characteristics of the filtration efficiency of isolation masks with particle size, and reveals the actual efficacy of masks by combining the volume distribution characteristics of human exhaled droplets with different particle sizes and the SARS-CoV-2 virus load of nasopharynx and throat swabs from patients. The existing measured data show that the filtration efficiency of all kinds of masks for large particles and extra-large droplets is close to 100%. From the perspective of filtering the total number of pathogens discharged in the environment and protecting vulnerable individuals from breathing live viruses, the mask has a higher protective effect. If considering the weighted average filtration efficiency with different particle sizes, the filtration efficiencies of the N95 mask and the ordinary mask are 99.4% and 98.5%, respectively. The mask can avoid releasing active viruses to the environment from the source of infection, thus maximising the protection of vulnerable individuals by reducing the probability of inhaling a virus. Therefore, if the whole society strictly implements the policy of publicly wearing masks, the risk of large-scale spread of the epidemic can be greatly reduced. Compared with the overall cost of social isolation, limited personal freedoms and forced suspension of economic activities, the inconvenience for citizens caused by wearing masks is perfectly acceptable.

scholarly journals Interventions to optimize medication use in nursing homes: a narrative review

2021 ◽  
Author(s):  
Anne Spinewine ◽  
Perrine Evrard ◽  
Carmel Hughes
Keyword(s):  
Nursing Homes ◽  
Large Scale ◽  
Adverse Drug Events ◽  
Experimental Studies ◽  
Medication Use ◽  
Nursing Home Residents ◽  
Qualitative Studies ◽  
Patient Centered ◽  
Barriers And Enablers ◽  
Specific Medication

Abstract Purpose Polypharmacy, medication errors and adverse drug events are frequent among nursing home residents. Errors can occur at any step of the medication use process. We aimed to review interventions aiming at optimization of any step of medication use in nursing homes. Methods We narratively reviewed quantitative as well as qualitative studies, observational and experimental studies that described interventions, their effects as well as barriers and enablers to implementation. We prioritized recent studies with relevant findings for the European setting. Results Many interventions led to improvements in medication use. However, because of outcome heterogeneity, comparison between interventions was difficult. Prescribing was the most studied aspect of medication use. At the micro-level, medication review, multidisciplinary work, and more recently, patient-centered care components dominated. At the macro-level, guidelines and legislation, mainly for specific medication classes (e.g., antipsychotics) were employed. Utilization of technology also helped improve medication administration. Several barriers and enablers were reported, at individual, organizational, and system levels. Conclusion Overall, existing interventions are effective in optimizing medication use. However there is a need for further European well-designed and large-scale evaluations of under-researched intervention components (e.g., health information technology, patient-centered approaches), specific medication classes (e.g., antithrombotic agents), and interventions targeting medication use aspects other than prescribing (e.g., monitoring). Further development and uptake of core outcome sets is required. Finally, qualitative studies on barriers and enablers for intervention implementation would enable theory-driven intervention design.

scholarly journals Opportunistic Large Array Propagation Models: A Comprehensive Survey

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4206
Author(s):  
Farhan Nawaz ◽  
Hemant Kumar ◽  
Syed Ali Hassan ◽  
Haejoon Jung
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Performance Metrics ◽  
Experimental Studies ◽  
Cooperative Transmission ◽  
Analytical Models ◽  
Future Research ◽  
Large Array ◽  
Propagation Models ◽  
Comprehensive Survey

Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

scholarly journals Computer Simulations of Cell Sorting Due to Differential Adhesion

PLoS ONE ◽  
2011 ◽  
Vol 6 (10) ◽  
pp. e24999 ◽  
Author(s):  
Ying Zhang ◽  
Gilberto L. Thomas ◽  
Maciej Swat ◽  
Abbas Shirinifard ◽  
James A. Glazier
Keyword(s):  
Computer Simulations ◽  
Cell Sorting ◽  
Differential Adhesion
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