scholarly journals Scalable population-level modelling of biological cells incorporating mechanics and kinetics in continuous time

2018 ◽  
Vol 5 (8) ◽  
pp. 180379 ◽  
Author(s):  
Stefan Engblom ◽  
Daniel B. Wilson ◽  
Ruth E. Baker
Keyword(s):  
Continuous Time ◽  
Computational Models ◽  
Coarse Graining ◽  
Population Level ◽  
Biomechanical Properties ◽  
Detailed Knowledge ◽  
Computational Framework ◽  
Rate Laws ◽  
Biological Phenomena ◽  
The Individual

The processes taking place inside the living cell are now understood to the point where predictive computational models can be used to gain detailed understanding of important biological phenomena. A key challenge is to extrapolate this detailed knowledge of the individual cell to be able to explain at the population level how cells interact and respond with each other and their environment. In particular, the goal is to understand how organisms develop, maintain and repair functional tissues and organs. In this paper, we propose a novel computational framework for modelling populations of interacting cells. Our framework incorporates mechanistic, constitutive descriptions of biomechanical properties of the cell population, and uses a coarse-graining approach to derive individual rate laws that enable propagation of the population through time. Thanks to its multiscale nature, the resulting simulation algorithm is extremely scalable and highly efficient. As highlighted in our computational examples, the framework is also very flexible and may straightforwardly be coupled with continuous-time descriptions of biochemical signalling within, and between, individual cells.

scholarly journals Comparative analysis of continuum angiogenesis models

2021 ◽  
Vol 82 (4) ◽  
Author(s):  
W. Duncan Martinson ◽  
Hirokazu Ninomiya ◽  
Helen M. Byrne ◽  
Philip K. Maini
Keyword(s):  
Mean Field ◽  
Cell Movement ◽  
Coarse Graining ◽  
Population Level ◽  
Coarse Grained ◽  
Continuum Models ◽  
Biological Phenomena ◽  
Complex Population ◽  
The Mean ◽  
Work Done

AbstractAlthough discrete approaches are increasingly employed to model biological phenomena, it remains unclear how complex, population-level behaviours in such frameworks arise from the rules used to represent interactions between individuals. Discrete-to-continuum approaches, which are used to derive systems of coarse-grained equations describing the mean-field dynamics of a microscopic model, can provide insight into such emergent behaviour. Coarse-grained models often contain nonlinear terms that depend on the microscopic rules of the discrete framework, however, and such nonlinearities can make a model difficult to mathematically analyse. By contrast, models developed using phenomenological approaches are typically easier to investigate but have a more obscure connection to the underlying microscopic system. To our knowledge, there has been little work done to compare solutions of phenomenological and coarse-grained models. Here we address this problem in the context of angiogenesis (the creation of new blood vessels from existing vasculature). We compare asymptotic solutions of a classical, phenomenological “snail-trail” model for angiogenesis to solutions of a nonlinear system of partial differential equations (PDEs) derived via a systematic coarse-graining procedure (Pillay et al. in Phys Rev E 95(1):012410, 2017. https://doi.org/10.1103/PhysRevE.95.012410). For distinguished parameter regimes corresponding to chemotaxis-dominated cell movement and low branching rates, both continuum models reduce at leading order to identical PDEs within the domain interior. Numerical and analytical results confirm that pointwise differences between solutions to the two continuum models are small if these conditions hold, and demonstrate how perturbation methods can be used to determine when a phenomenological model provides a good approximation to a more detailed coarse-grained system for the same biological process.

Optimal Consumption and Insurance: A Continuous-time Markov Chain Approach

2008 ◽  
Vol 38 (01) ◽  
pp. 231-257 ◽  
Author(s):  
Holger Kraft ◽  
Mogens Steffensen
Keyword(s):  
Continuous Time ◽  
Optimal Solution ◽  
Decision Problems ◽  
Optimal Consumption ◽  
Continuous Time Markov Chain ◽  
Financial Decision Making ◽  
Markov Chain Approach ◽  
Special Cases ◽  
Financial Decision ◽  
The Individual

Personal financial decision making plays an important role in modern finance. Decision problems about consumption and insurance are in this article modelled in a continuous-time multi-state Markovian framework. The optimal solution is derived and studied. The model, the problem, and its solution are exemplified by two special cases: In one model the individual takes optimal positions against the risk of dying; in another model the individual takes optimal positions against the risk of losing income as a consequence of disability or unemployment.

scholarly journals A methodological framework to predict the individual and population‐level distributions from tracking data

Ecography ◽  
2021 ◽  
Author(s):  
Philippine Chambault ◽  
Tarek Hattab ◽  
Pascal Mouquet ◽  
Touria Bajjouk ◽  
Claire Jean ◽  
...  
Keyword(s):  
Population Level ◽  
Tracking Data ◽  
Methodological Framework ◽  
The Individual

scholarly journals Phenotypic plasticity of labile traits in the wild

2013 ◽  
Vol 59 (4) ◽  
pp. 485-505 ◽  
Author(s):  
Jon E. Brommer
Keyword(s):  
Life History ◽  
Phenotypic Plasticity ◽  
Statistical Approach ◽  
Scale Up ◽  
Population Level ◽  
Wild Populations ◽  
Quantitative Genetic ◽  
In The Wild ◽  
The Individual ◽  
Quantitative Genetic Parameters

Abstract Individual-based studies allow quantification of phenotypic plasticity in behavioural, life-history and other labile traits. The study of phenotypic plasticity in the wild can shed new light on the ultimate objectives (1) whether plasticity itself can evolve or is constrained by its genetic architecture, and (2) whether plasticity is associated to other traits, including fitness (selection). I describe the main statistical approach for how repeated records of individuals and a description of the environment (E) allow quantification of variation in plasticity across individuals (IxE) and genotypes (GxE) in wild populations. Based on a literature review of life-history and behavioural studies on plasticity in the wild, I discuss the present state of the two objectives listed above. Few studies have quantified GxE of labile traits in wild populations, and it is likely that power to detect statistically significant GxE is lacking. Apart from the issue of whether it is heritable, plasticity tends to correlate with average trait expression (not fully supported by the few genetic estimates available) and may thus be evolutionary constrained in this way. Individual-specific estimates of plasticity tend to be related to other traits of the individual (including fitness), but these analyses may be anti-conservative because they predominantly concern stats-on-stats. Despite the increased interest in plasticity in wild populations, the putative lack of power to detect GxE in such populations hinders achieving general insights. I discuss possible steps to invigorate the field by moving away from simply testing for presence of GxE to analyses that ‘scale up’ to population level processes and by the development of new behavioural theory to identify quantitative genetic parameters which can be estimated.

scholarly journals Healthy ageing, resilience and wellbeing

2017 ◽  
Vol 26 (6) ◽  
pp. 579-583 ◽  
Author(s):  
T. D. Cosco ◽  
K. Howse ◽  
C. Brayne
Keyword(s):  
Population Level ◽  
Healthy Ageing ◽  
Ageing Population ◽  
Environmental Resources ◽  
Great Achievement ◽  
Health Concept ◽  
Ageing Model ◽  
The Face ◽  
The Individual ◽  
High Level

The extension of life does not appear to be slowing, representing a great achievement for mankind as well as a challenge for ageing populations. As we move towards an increasingly older population we will need to find novel ways for individuals to make the best of the challenges they face, as the likelihood of encountering some form of adversity increases with age. Resilience theories share a common idea that individuals who manage to navigate adversity and maintain high levels of functioning demonstrate resilience. Traditional models of healthy ageing suggest that having a high level of functioning across a number of domains is a requirement. The addition of adversity to the healthy ageing model via resilience makes this concept much more accessible and more amenable to the ageing population. Through asset-based approaches, such as the invoking of individual, social and environmental resources, it is hoped that greater resilience can be fostered at a population level. Interventions aimed at fostering greater resilience may take many forms; however, there is great potential to increase social and environmental resources through public policy interventions. The wellbeing of the individual must be the focus of these efforts; quality of life is an integral component to the enjoyment of additional years and should not be overlooked. Therefore, it will become increasingly important to use resilience as a public health concept and to intervene through policy to foster greater resilience by increasing resources available to older people. Fostering wellbeing in the face of increasing adversity has significant implications for ageing individuals and society as a whole.

scholarly journals On the modeling of the interaction between tumor growth and the immune system using some new fractional and fractional-fractal operators

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Behzad Ghanbari
Keyword(s):  
Immune System ◽  
Infectious Diseases ◽  
Tumor Growth ◽  
Computational Models ◽  
Recent Literature ◽  
Approximate Solutions ◽  
Biological Phenomena ◽  
Uniqueness Of The Solution ◽  
Biological Concepts ◽  
New Research

Abstract Humans are always exposed to the threat of infectious diseases. It has been proven that there is a direct link between the strength or weakness of the immune system and the spread of infectious diseases such as tuberculosis, hepatitis, AIDS, and Covid-19 as soon as the immune system has no the power to fight infections and infectious diseases. Moreover, it has been proven that mathematical modeling is a great tool to accurately describe complex biological phenomena. In the recent literature, we can easily find that these effective tools provide important contributions to our understanding and analysis of such problems such as tumor growth. This is indeed one of the main reasons for the need to study computational models of how the immune system interacts with other factors involved. To this end, in this paper, we present some new approximate solutions to a computational formulation that models the interaction between tumor growth and the immune system with several fractional and fractal operators. The operators used in this model are the Liouville–Caputo, Caputo–Fabrizio, and Atangana–Baleanu–Caputo in both fractional and fractal-fractional senses. The existence and uniqueness of the solution in each of these cases is also verified. To complete our analysis, we include numerous numerical simulations to show the behavior of tumors. These diagrams help us explain mathematical results and better describe related biological concepts. In many cases the approximate results obtained have a chaotic structure, which justifies the complexity of unpredictable and uncontrollable behavior of cancerous tumors. As a result, the newly implemented operators certainly open new research windows in further computational models arising in the modeling of different diseases. It is confirmed that similar problems in the field can be also be modeled by the approaches employed in this paper.

Bringing Computational Models of Word Naming Down to the Item Level

1997 ◽  
Vol 8 (6) ◽  
pp. 411-416 ◽  
Author(s):  
Daniel H. Spieler ◽  
David A. Balota
Keyword(s):  
Word Recognition ◽  
Computational Models ◽  
Predictive Power ◽  
Neighborhood Density ◽  
Word Naming ◽  
Connectionist Models ◽  
Item Level ◽  
The Individual ◽  
Level Performance ◽  
Naming Latencies

Early noncomputational models of word recognition have typically attempted to account for effects of categorical factors such as word frequency (high vs low) and spelling-to-sound regularity (regular vs irregular) More recent computational models that adhere to general connectionist principles hold the promise of being sensitive to underlying item differences that are only approximated by these categorical factors In contrast to earlier models, these connectionist models provide predictions of performance for individual items In the present study, we used the item-level estimates from two connectionist models (Plaut, McClelland, Seidenberg, & Patterson, 1996, Seidenberg & McClelland, 1989) to predict naming latencies on the individual items on which the models were trained The results indicate that the models capture, at best, slightly more variance than simple log frequency and substantially less than the combined predictive power of log frequency, neighborhood density, and orthographic length. The discussion focuses on the importance of examining the item-level performance of word-naming models and possible approaches that may improve the models' sensitivity to such item differences

scholarly journals Migration, acculturation, and the maintenance of between-group cultural variation

2017 ◽  
Author(s):  
Alex Mesoudi
Keyword(s):  
Social Learning ◽  
Cultural Values ◽  
Cultural Evolution ◽  
Population Level ◽  
Empirical Literature ◽  
Cultural Variation ◽  
Individual Level ◽  
And Migration ◽  
The Individual ◽  
Social Learning Processes

AbstractHow do migration and acculturation (i.e. psychological or behavioral change resulting from migration) affect within- and between-group cultural variation? Here I answer this question by drawing analogies between genetic and cultural evolution. Population genetic models show that migration rapidly breaks down between-group genetic structure. In cultural evolution, however, migrants or their descendants can acculturate to local behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. An analysis of the empirical literature on migration suggests that acculturation is common, with second and subsequent migrant generations shifting, sometimes substantially, towards the cultural values of the adopted society. Yet there is little understanding of the individual-level dynamics that underlie these population-level shifts. To explore this formally, I present models quantifying the effect of migration and acculturation on between-group cultural variation, for both neutral and costly cooperative traits. In the models, between-group cultural variation, measured using F statistics, is eliminated by migration and maintained by conformist acculturation. The extent of acculturation is determined by the strength of conformist bias and the number of demonstrators from whom individuals learn. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Unlike neutral traits, cooperative traits can additionally be maintained by payoff-biased social learning, but only in the presence of strong sanctioning institutions. Overall, the models show that surprisingly little conformist acculturation is required to maintain realistic amounts of between-group cultural diversity. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.

scholarly journals Nonlinear visuoauditory integration in the mouse superior colliculus

2021 ◽  
Author(s):  
Shinya Ito ◽  
Yufei Si ◽  
Alan M. Litke ◽  
David A. Feldheim
Keyword(s):  
Superior Colliculus ◽  
Sensory Integration ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Critical Role ◽  
Sensory Information ◽  
Population Level ◽  
Object Identification ◽  
Response Properties ◽  
The Individual

AbstractSensory information from different modalities is processed in parallel, and then integrated in associative brain areas to improve object identification and the interpretation of sensory experiences. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual, auditory, and somatosensory input to assess saliency and promote action. Although the response properties of the individual SC neurons to visuoauditory stimuli have been characterized, little is known about the spatial and temporal dynamics of the integration at the population level. Here we recorded the response properties of SC neurons to spatially restricted visual and auditory stimuli using large-scale electrophysiology. We then created a general, population-level model that explains the spatial, temporal, and intensity requirements of stimuli needed for sensory integration. We found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. We show that nonlinear integration depends on properties of auditory but not visual stimuli. We also find that a heuristically derived nonlinear modulation function reveals conditions required for sensory integration that are consistent with previously proposed models of sensory integration such as spatial matching and the principle of inverse effectiveness.

Sign in / Sign up

Export Citation Format

Share Document