Dissolution Anisotropy of Pyroxenes: Role of Edges and Corners Inferred from Stochastic Simulations of Enstatite Dissolution

Simulations of dynamically cross-linked actin networks: Morphology, rheology, and hydrodynamic interactions

PLoS Computational Biology ◽

10.1371/journal.pcbi.1009240 ◽

2021 ◽

Vol 17 (12) ◽

pp. e1009240

Author(s):

Ondrej Maxian ◽

Raúl P. Peláez ◽

Alex Mogilner ◽

Aleksandar Donev

Keyword(s):

Time Scale ◽

Stochastic Simulations ◽

Hydrodynamic Interactions ◽

Short Time Scale ◽

Slender Body Theory ◽

Small Amplitude Oscillatory Shear ◽

Actin Networks ◽

Cross Links ◽

The Cross

Cross-linked actin networks are the primary component of the cell cytoskeleton and have been the subject of numerous experimental and modeling studies. While these studies have demonstrated that the networks are viscoelastic materials, evolving from elastic solids on short timescales to viscous fluids on long ones, questions remain about the duration of each asymptotic regime, the role of the surrounding fluid, and the behavior of the networks on intermediate timescales. Here we perform detailed simulations of passively cross-linked non-Brownian actin networks to quantify the principal timescales involved in the elastoviscous behavior, study the role of nonlocal hydrodynamic interactions, and parameterize continuum models from discrete stochastic simulations. To do this, we extend our recent computational framework for semiflexible filament suspensions, which is based on nonlocal slender body theory, to actin networks with dynamic cross linkers and finite filament lifetime. We introduce a model where the cross linkers are elastic springs with sticky ends stochastically binding to and unbinding from the elastic filaments, which randomly turn over at a characteristic rate. We show that, depending on the parameters, the network evolves to a steady state morphology that is either an isotropic actin mesh or a mesh with embedded actin bundles. For different degrees of bundling, we numerically apply small-amplitude oscillatory shear deformation to extract three timescales from networks of hundreds of filaments and cross linkers. We analyze the dependence of these timescales, which range from the order of hundredths of a second to the actin turnover time of several seconds, on the dynamic nature of the links, solvent viscosity, and filament bending stiffness. We show that the network is mostly elastic on the short time scale, with the elasticity coming mainly from the cross links, and viscous on the long time scale, with the effective viscosity originating primarily from stretching and breaking of the cross links. We show that the influence of nonlocal hydrodynamic interactions depends on the network morphology: for homogeneous meshworks, nonlocal hydrodynamics gives only a small correction to the viscous behavior, but for bundled networks it both hinders the formation of bundles and significantly lowers the resistance to shear once bundles are formed. We use our results to construct three-timescale generalized Maxwell models of the networks.

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A One-Dimensional Stochastic Model of Diamond Growth

MRS Proceedings ◽

10.1557/proc-399-83 ◽

1995 ◽

Vol 399 ◽

Author(s):

Michael Frenklach

Keyword(s):

Critical Role ◽

Diamond Films ◽

Chemical Vapor ◽

Stochastic Simulations ◽

Diamond Growth ◽

Elementary Processes ◽

One Dimensional ◽

Surface Migration ◽

Kinetic Rates

ABSTRACT(1+1)-dimensional stochastic simulations were performed representing elementary processes underlying chemical vapor deposition of diamond films. The results exhibit different growth regimes, depending on the values assigned to kinetic rates, and generally support the critical role of surface migration suggested earlier for the growth of diamond.

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The Role of Type 4 Phosphodiesterases in Generating Microdomains of cAMP: Large Scale Stochastic Simulations

PLoS ONE ◽

10.1371/journal.pone.0011725 ◽

2010 ◽

Vol 5 (7) ◽

pp. e11725 ◽

Cited By ~ 86

Author(s):

Rodrigo F. Oliveira ◽

Anna Terrin ◽

Giulietta Di Benedetto ◽

Robert C. Cannon ◽

Wonryull Koh ◽

...

Keyword(s):

Large Scale ◽

Stochastic Simulations

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Evaluation of Current Amikacin Dosing Recommendations and Development of an Interactive Nomogram: The Role of Albumin

Pharmaceutics ◽

10.3390/pharmaceutics13020264 ◽

2021 ◽

Vol 13 (2) ◽

pp. 264

Author(s):

Jonás Samuel Pérez-Blanco ◽

Eva María Sáez Fernández ◽

María Victoria Calvo ◽

José M. Lanao ◽

Ana Martín-Suárez

Keyword(s):

Initial Dosage ◽

Stochastic Simulations ◽

Efficacy And Safety ◽

Target Attainment ◽

Minimum Concentration ◽

Time Period ◽

Potential Efficacy ◽

Clinical Scenarios ◽

Potential Impact

This study aimed to evaluate the potential efficacy and safety of the amikacin dosage proposed by the main guidelines and to develop an interactive nomogram, especially focused on the potential impact of albumin on initial dosage recommendation. The probability of target attainment (PTA) for each of the different dosing recommendations was calculated through stochastic simulations based on pharmacokinetic/pharmacodynamic (PKPD) criteria. Large efficacy and safety differences were observed for the evaluated amikacin dosing guidelines together with a significant impact of albumin concentrations on efficacy and safety. For all recommended dosages evaluated, efficacy and safety criteria of amikacin dosage proposed were not achieved simultaneously in most of the clinical scenarios evaluated. Furthermore, a significant impact of albumin was identified: The higher is the albumin, (i) the higher will be the PTA for maximum concentration/minimum inhibitory concentration (Cmax/MIC), (ii) the lower will be the PTA for the time period with drug concentration exceeding MIC (T>MIC) and (iii) the lower will be the PTA for toxicity (minimum concentration). Thus, accounting for albumin effect might be of interest for future amikacin dosing guidelines updates. In addition, AMKnom, an amikacin nomogram builder based on PKPD criteria, has been developed and is freely available to help evaluating dosing recommendations.

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Imperfect strategy transmission can reverse the role of population viscosity on the evolution of altruism

10.1101/609818 ◽

2019 ◽

Author(s):

F. Débarre

Keyword(s):

Life Cycle ◽

Social Interactions ◽

Side Effect ◽

Life Cycles ◽

Stochastic Simulations ◽

Altruistic Behavior ◽

Weak Selection ◽

Related Individuals ◽

Population Viscosity

AbstractPopulation viscosity, i.e., low emigration out of the natal deme, leads to high within-deme relatedness, which is beneficial to the evolution of altruistic behavior when social interactions take place among deme-mates. However, a detrimental side-effect of low emigration is the increase in competition among related individuals. The evolution of altruism depends on the balance between these opposite effects. This balance is already known to be affected by details of the life cycle; we show here that it further depends on the fidelity of strategy transmission from parents to their offspring. We consider different life cycles and identify thresholds of parent-offspring strategy transmission inaccuracy, above which higher emigration can increase the frequency of altruists maintained in the population. Predictions were first obtained analytically assuming weak selection and equal deme sizes, then confirmed with stochastic simulations relaxing these assumptions. Contrary to what happens with perfect strategy transmission from parent to off-spring, our results show that higher emigration can be favorable to the evolution of altruism.

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Mechanistic Model of Telomere Length Homeostasis in Yeast

10.1101/2021.10.02.462846 ◽

2021 ◽

Author(s):

Ghanendra Singh ◽

Sriram K

Keyword(s):

Telomere Length ◽

Molecular Mechanisms ◽

Global Analysis ◽

Mechanistic Model ◽

Stochastic Simulations ◽

Phase Plane Analysis ◽

Plane Analysis ◽

Length Regulation ◽

Telomere Length Homeostasis

Cells maintain homeostatic telomere length, and this homeostatic disruption leads to various types of diseases. Presently, it is not clear how telomeres achieve homeostasis. One of the prevailing hypotheses is a protein-counting model with a built-in sensor mechanism that counts proteins that directly regulate the telomeric length. However, it does not explain telomere length regulation at the mechanistic level. Here, we present a mathematical model based on the underlying molecular mechanisms of length regulation needed to establish telomere length homeostasis in yeast. We perform both deterministic and stochastic simulations to validate the models with the experimental data of Teixeira et al., rate-balance plot, and phase plane analysis to understand the nature of dynamics exhibited by the models. For global analysis, we constructed bifurcation diagrams. The model explains the role of negative and positive feedback loops and a delay between telomerase and telomere-bound proteins, leading to oscillations in telomere length. We map these in-silico results to proposition by Teixeira of telomeres making a transition between extendible and non-extendible states.

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Simulations of dynamically cross-linked actin networks: morphology, rheology, and hydrodynamic interactions

10.1101/2021.07.07.451453 ◽

2021 ◽

Author(s):

Ondrej Maxian ◽

Raúl P Peláez ◽

Alex Mogilner ◽

Aleksandar Donev

Keyword(s):

Time Scale ◽

Stochastic Simulations ◽

Hydrodynamic Interactions ◽

Short Time Scale ◽

Slender Body Theory ◽

Small Amplitude Oscillatory Shear ◽

Actin Networks ◽

Cross Links ◽

The Cross

Cross-linked actin networks are the primary component of the cell cytoskeleton and have been the subject of numerous experimental and modeling studies. While these studies have demonstrated that the networks are viscoelastic materials, evolving from elastic solids on short timescales to viscous fluids on long ones, questions remain about the duration of each asymptotic regime, the role of the surrounding fluid, and the behavior of the networks on intermediate timescales. Here we perform detailed simulations of passively cross-linked actin networks to quantify the principal timescales involved in the elastoviscous behavior, study the role of nonlocal hydrodynamic interactions, and derive continuum models from discrete stochastic simulations. To do this, we extend our recent computational framework for semiflexible filament suspensions, which is based on nonlocal slender body theory, to actin networks with dynamic cross linkers. We introduce a model where the cross linkers are elastic springs with sticky ends stochastically binding to and unbinding from the elastic filaments, which randomly turn over at a characteristic rate. We show that, depending on the parameters, the network evolves to a steady state morphology that is either an isotropic actin mesh or a mesh with embedded actin bundles. For different degrees of bundling, we numerically apply small-amplitude oscillatory shear deformation to extract three timescales from networks of hundreds of filaments and cross linkers. We analyze the dependence of these timescales, which range from the order of hundredths of a second to several seconds, on the dynamic nature of the links, solvent viscosity, and filament bending stiffness. We show that the network is mostly elastic on the short time scale, with the elasticity coming mainly from the cross links, and viscous on the long time scale, with the effective viscosity originating primarily from stretching and breaking of the cross links. We show that the influence of nonlocal hydrodynamic interactions depends on the network morphology: for homogeneous meshworks, nonlocal hydrodynamics gives only a small correction to the viscous behavior, but for bundled networks it both hinders the formation of bundles and significantly lowers the resistance to shear once bundles are formed. We use our results to construct continuum Maxwell-type models of the networks.

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Evaluation of the potential incidence of COVID-19 and effectiveness of contention measures in Spain: a data-driven approach

10.1101/2020.03.01.20029801 ◽

2020 ◽

Cited By ~ 7

Author(s):

Alberto Aleta ◽

Yamir Moreno

Keyword(s):

Order Effect ◽

Stochastic Simulations ◽

Data Driven ◽

World Health ◽

Metapopulation Model ◽

Spatial Spread ◽

Data Driven Approach ◽

History Of ◽

Health Organization

Our society is currently experiencing an unprecedented challenge, managing and containing an outbreak of a new coronavirus disease known as COVID-19. While China - where the outbreak started - seems to have been able to contain the growth of the epidemic, different outbreaks are nowadays being detected in multiple countries. Much is currently unknown about the natural history of the disease, such as a possible asymptomatic spreading or the role of age in both the susceptibility and mortality of the disease. Nonetheless, authorities have to take action and implement contention measures, even if not everything is known. To facilitate this task, we have studied the effect of different containment strategies that can be put into effect. Our work specifically refers to the situation in Spain as of February 28th, 2020, where a few dozens of cases have been detected. We implemented an SEIR-metapopulation model that allows tracing explicitly the spatial spread of the disease through data-driven stochastic simulations. Our results are in line with the most recent recommendations from the World Health Organization, namely, that the best strategy is the early detection and isolation of individuals with symptoms, followed by interventions and public recommendations aimed at reducing the transmissibility of the disease, which although not efficacious for disease eradication, would produce as a second order effect a delay of several days in the raise of the number of infected cases.

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