scholarly journals Spatial structure arising from chase-escape interactions with crowding

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Anudeep Surendran ◽  
Michael J. Plank ◽  
Matthew J. Simpson
Keyword(s):  
Spatial Structure ◽  
Cell Biology ◽  
Scale Up ◽  
Interaction Strength ◽  
Distinct Species ◽  
Interspecies Interactions ◽  
Individual Based Model ◽  
Directional Bias ◽  
Spatial Moments ◽  
Individual Level

Abstract Movement of individuals, mediated by localised interactions, plays a key role in numerous processes including cell biology and ecology. In this work, we investigate an individual-based model accounting for various intraspecies and interspecies interactions in a community consisting of two distinct species. In this framework we consider one species to be chasers and the other species to be escapees, and we focus on chase-escape dynamics where the chasers are biased to move towards the escapees, and the escapees are biased to move away from the chasers. This framework allows us to explore how individual-level directional interactions scale up to influence spatial structure at the macroscale. To focus exclusively on the role of motility and directional bias in determining spatial structure, we consider conservative communities where the number of individuals in each species remains constant. To provide additional information about the individual-based model, we also present a mathematically tractable deterministic approximation based on describing the evolution of the spatial moments. We explore how different features of interactions including interaction strength, spatial extent of interaction, and relative density of species influence the formation of the macroscale spatial patterns.

scholarly journals Spatial structure arising from chase-escape interactions with crowding

2018 ◽  
Author(s):  
Anudeep Surendran ◽  
Michael J Plank ◽  
Matthew J Simpson
Keyword(s):  
Spatial Structure ◽  
Cell Biology ◽  
Scale Up ◽  
Interaction Strength ◽  
Distinct Species ◽  
Interspecies Interactions ◽  
Individual Based Model ◽  
Directional Bias ◽  
Spatial Moments ◽  
Individual Level

ABSTRACTMovement of individuals, mediated by localised interactions, plays a key role in numerous processes including cell biology and ecology. In this work, we investigate an individual-based model accounting for various intraspecies and interspecies interactions in a community consisting of two distinct species. In this framework we consider one species to be chasers and the other species to be escapees, and we focus on chase-escape dynamics where the chasers are biased to move towards the escapees, and the escapees are biased to move away from the chasers. This framework allows us to explore how individual-level directional interactions scale up to influence spatial structure at the macroscale. To focus exclusively on the role of motility and directional bias in determining spatial structure, we consider conservative communities where the number of individuals in each species remains constant. To provide additional information about the individual-based model, we also present a mathematically tractable deterministic approximation based on describing the evolution of the spatial moments. We explore how different features of interactions including interaction strength, spatial extent of interaction, and relative density of species influence the formation of the macroscale spatial patterns.

scholarly journals Spatial structure arising from neighbour-dependent bias in collective cell movement

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1689 ◽  
Author(s):  
Rachelle N. Binny ◽  
Parvathi Haridas ◽  
Alex James ◽  
Richard Law ◽  
Matthew J. Simpson ◽  
...  
Keyword(s):  
Spatial Structure ◽  
Cell Population ◽  
Cell Movement ◽  
Average Density ◽  
Imaging Data ◽  
Spatial Correlations ◽  
Directional Bias ◽  
Spatial Moments ◽  
Spatial Moment

Mathematical models of collective cell movement often neglect the effects of spatial structure, such as clustering, on the population dynamics. Typically, they assume that individuals interact with one another in proportion to their average density (the mean-field assumption) which means that cell–cell interactions occurring over short spatial ranges are not accounted for. However,in vitrocell culture studies have shown that spatial correlations can play an important role in determining collective behaviour. Here, we take a combined experimental and modelling approach to explore how individual-level interactions give rise to spatial structure in a moving cell population. Using imaging data fromin vitroexperiments, we quantify the extent of spatial structure in a population of 3T3 fibroblast cells. To understand how this spatial structure arises, we develop a lattice-free individual-based model (IBM) and simulate cell movement in two spatial dimensions. Our model allows an individual’s direction of movement to be affected by interactions with other cells in its neighbourhood, providing insights into how directional bias generates spatial structure. We consider how this behaviour scales up to the population level by using the IBM to derive a continuum description in terms of the dynamics of spatial moments. In particular, we account for spatial correlations between cells by considering dynamics of the second spatial moment (the average density of pairs of cells). Our numerical results suggest that the moment dynamics description can provide a good approximation to averaged simulation results from the underlying IBM. Using ourin vitrodata, we estimate parameters for the model and show that it can generate similar spatial structure to that observed in a 3T3 fibroblast cell population.

scholarly journals Spatial moment description of birth-death-movement processes incorporating the effects of crowding and obstacles

2018 ◽  
Author(s):  
Anudeep Surendran ◽  
Michael J. Plank ◽  
Matthew J. Simpson
Keyword(s):  
Spatial Structure ◽  
Cell Biology ◽  
Mean Field ◽  
Population Level ◽  
Individual Level ◽  
Spatial Moment ◽  
Motile Cells ◽  
Stationary Obstacles ◽  
Birth Death

AbstractBirth-death-movement processes, modulated by interactions between individuals, are fundamental to many cell biology processes. A key feature of the movement of cells within in vivo environments are the interactions between motile cells and stationary obstacles. Here we propose a multi-species model of individual-level motility, proliferation and death. This model is a spatial birth-death-movement stochastic process, a class of individual-based model (IBM) that is amenable to mathematical analysis. We present the IBM in a general multi-species framework, and then focus on the case of a population of motile, proliferative agents in an environment populated by stationary, non-proliferative obstacles. To analyse the IBM, we derive a system of spatial moment equations governing the evolution of the density of agents and the density of pairs of agents. This approach avoids making the usual mean-field assumption so that our models can be used to study the formation of spatial structure, such as clustering and aggregation, and to understand how spatial structure influences population-level outcomes. Overall the spatial moment model provides a reasonably accurate prediction of the system dynamics, including important effects such as how varying the properties of the obstacles leads to different spatial patterns in the population of agents.

scholarly journals MiSiC, a general deep learning-based method for the high-throughput cell segmentation of complex bacterial communities

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Swapnesh Panigrahi ◽  
Dorothée Murat ◽  
Antoine Le Gall ◽  
Eugénie Martineau ◽  
Kelly Goldlust ◽  
...  
Keyword(s):  
Deep Learning ◽  
Bacterial Communities ◽  
Cell Biology ◽  
Imaging Modality ◽  
Interaction Model ◽  
Cell Segmentation ◽  
Bacterial Cells ◽  
Interspecies Interactions ◽  
Prey Interaction ◽  
Simple Implementation

Studies of bacterial communities, biofilms and microbiomes, are multiplying due to their impact on health and ecology. Live imaging of microbial communities requires new tools for the robust identification of bacterial cells in dense and often inter-species populations, sometimes over very large scales. Here, we developed MiSiC, a general deep-learning-based 2D segmentation method that automatically segments single bacteria in complex images of interacting bacterial communities with very little parameter adjustment, independent of the microscopy settings and imaging modality. Using a bacterial predator-prey interaction model, we demonstrate that MiSiC enables the analysis of interspecies interactions, resolving processes at subcellular scales and discriminating between species in millimeter size datasets. The simple implementation of MiSiC and the relatively low need in computing power make its use broadly accessible to fields interested in bacterial interactions and cell biology.

scholarly journals Opposite outcomes of coinfection at individual and population scales

2018 ◽  
Vol 115 (29) ◽  
pp. 7545-7550 ◽  
Author(s):  
Erin E. Gorsich ◽  
Rampal S. Etienne ◽  
Jan Medlock ◽  
Brianna R. Beechler ◽  
Johannie M. Spaan ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Negative Impact ◽  
Scale Up ◽  
Population Level ◽  
Clear Understanding ◽  
African Buffalo ◽  
Global Public Health ◽  
Individual Level ◽  
Secondary Infections ◽  
The Individual

Coinfecting parasites and pathogens remain a leading challenge for global public health due to their consequences for individual-level infection risk and disease progression. However, a clear understanding of the population-level consequences of coinfection is lacking. Here, we constructed a model that includes three individual-level effects of coinfection: mortality, fecundity, and transmission. We used the model to investigate how these individual-level consequences of coinfection scale up to produce population-level infection patterns. To parameterize this model, we conducted a 4-y cohort study in African buffalo to estimate the individual-level effects of coinfection with two bacterial pathogens, bovine tuberculosis (bTB) and brucellosis, across a range of demographic and environmental contexts. At the individual level, our empirical results identified bTB as a risk factor for acquiring brucellosis, but we found no association between brucellosis and the risk of acquiring bTB. Both infections were associated with reductions in survival and neither infection was associated with reductions in fecundity. The model reproduced coinfection patterns in the data and predicted opposite impacts of coinfection at individual and population scales: Whereas bTB facilitated brucellosis infection at the individual level, our model predicted the presence of brucellosis to have a strong negative impact on bTB at the population level. In modeled populations where brucellosis was present, the endemic prevalence and basic reproduction number (R0) of bTB were lower than in populations without brucellosis. Therefore, these results provide a data-driven example of competition between coinfecting pathogens that occurs when one pathogen facilitates secondary infections at the individual level.

Online Mindfulness Interventions

2018 ◽  
pp. 1-27 ◽  
Author(s):  
Farah Ahmad ◽  
Jamie Jianmin Wang ◽  
Christo El Morr
Keyword(s):  
Positive Impact ◽  
Scale Up ◽  
Virtual Community ◽  
Cost Effective ◽  
Mental Wellbeing ◽  
Individual Level ◽  
Symptoms Of Depression ◽  
The Social ◽  
Mindfulness Interventions ◽  
The Individual

The current chapter systematically reviewed literature on online mindfulness interventions. Electronic databases were searched from 2005 to July 2016. The aim was to examine the nature of online mindfulness interventions, design features, and their effectiveness in improving symptoms of depression, anxiety, and stress. The review of selected studies shows that online delivery of mindfulness psycho-education and practice is an area in its infancy. There is evidence that online mindfulness interventions can have a positive impact on mental health in terms of stress, depression, and anxiety; however, large sample studies are needed in order to have conclusive results. Moreover, the extension of online mindfulness interventions beyond the individual level to include a community dimension, such as virtual community features, and a focus on the social determinants of health, needs to be explored in future. The online mindfulness intervention could be a cost-effective way to scale up the promotion of mental wellbeing.

scholarly journals Understanding the evolution of interspecies interactions in microbial communities

2020 ◽  
Vol 375 (1798) ◽  
pp. 20190256 ◽  
Author(s):  
Florien A. Gorter ◽  
Michael Manhart ◽  
Martin Ackermann
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Interaction Strength ◽  
Quantitative Model ◽  
Systematic Effect ◽  
Interspecies Interactions ◽  
Fitness Effects ◽  
Indirect Fitness ◽  
Beneficial Traits ◽  
Selection Of

Microbial communities are complex multi-species assemblages that are characterized by a multitude of interspecies interactions, which can range from mutualism to competition. The overall sign and strength of interspecies interactions have important consequences for emergent community-level properties such as productivity and stability. It is not well understood how interspecies interactions change over evolutionary timescales. Here, we review the empirical evidence that evolution is an important driver of microbial community properties and dynamics on timescales that have traditionally been regarded as purely ecological. Next, we briefly discuss different modelling approaches to study evolution of communities, emphasizing the similarities and differences between evolutionary and ecological perspectives. We then propose a simple conceptual model for the evolution of interspecies interactions in communities. Specifically, we propose that to understand the evolution of interspecies interactions, it is important to distinguish between direct and indirect fitness effects of a mutation. We predict that in well-mixed environments, traits will be selected exclusively for their direct fitness effects, while in spatially structured environments, traits may also be selected for their indirect fitness effects. Selection of indirectly beneficial traits should result in an increase in interaction strength over time, while selection of directly beneficial traits should not have such a systematic effect. We tested our intuitions using a simple quantitative model and found support for our hypotheses. The next step will be to test these hypotheses experimentally and provide input for a more refined version of the model in turn, thus closing the scientific cycle of models and experiments. This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.

Scaling Up Social Problems

2016 ◽  
Vol 27 (2) ◽  
pp. 139-149 ◽  
Author(s):  
Maria Y. Rodriguez ◽  
Laysha Ostrow ◽  
Susan P. Kemp
Keyword(s):  
Social Work ◽  
Progressive Era ◽  
Social Problems ◽  
Scale Up ◽  
Work Practice ◽  
Scaling Up ◽  
Social Work Practice ◽  
Individual Level ◽  
Social Work Research ◽  
Meaningful Engagement

The Grand Challenges for Social Work Initiative aims to focus the profession’s attention on how social work can play a larger role in mitigating contemporary social problems. Yet a central issue facing contemporary social work is its seeming reticence to engage with social problems, and their solutions, beyond individual-level interventions. Social work research, we contend, must more consistently link case and cause, iteratively developing processes for bringing micro-, mezzo-, and macrostreams of information together. We further argue that meaningful engagement with the initiative requires social work scholars and practitioners to actively scale up practice and research inquiry. We detail two key strategies for employing a scaled-up social work practice and research ethos: (a) employing a critical economic lens and (b) engaging with diverse publics. As proof of concept for these arguments, we offer an early example of progressive era social workers scaling up responses to a pressing social issue: infant mortality.

scholarly journals Tuberculosis care cascade in Zambia - identifying the gaps in order to improve outcomes: a population-based analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. e044867
Author(s):  
Patrick Lungu ◽  
Andrew D Kerkhoff ◽  
Clara C Kasapo ◽  
Judith Mzyece ◽  
Sulani Nyimbili ◽  
...  
Keyword(s):  
National Level ◽  
Scale Up ◽  
Drug Susceptibility ◽  
Population Based ◽  
Health Systems Strengthening ◽  
People Living With Hiv ◽  
Individual Level ◽  
Engagement Strategies ◽  
Care Cascade ◽  
Total Burden

ObjectiveTuberculosis (TB) remains a leading cause of morbidity and mortality in Zambia, especially for people living with HIV (PLHIV). We undertook a care cascade analysis to quantify gaps in care and align programme improvement measures with areas of need.DesignRetrospective, population-based analysis.SettingWe derived national-level estimates for each step of the TB care cascade in Zambia. Estimates were informed by WHO incidence estimates, nationally aggregated laboratory and notification registers, and individual-level programme data from four provinces.ParticipantsParticipants included all individuals with active TB disease in Zambia in 2018. We characterised the overall TB cascade and disaggregated by drug susceptibility results and HIV status.ResultsIn 2018, the total burden of TB in Zambia was estimated to be 72 495 (range, 40 495–111 495) cases. Of these, 43 387 (59.8%) accessed TB testing, 40 176 (55.4%) were diagnosed with TB, 36 431 (50.3%) were started on treatment and 32 700 (45.1%) completed treatment. Among all persons with TB lost at any step along the care cascade (n=39 795), 29 108 (73.1%) were lost prior to accessing diagnostic services, 3211 (8.1%) prior to diagnosis, 3745 (9.4%) prior to initiating treatment and 3731 (9.4%) prior to treatment completion. PLHIV were less likely than HIV-negative individuals to successfully complete the care cascade (42.8% vs 50.2%, p<0.001). Among those with rifampicin-resistant TB, there was substantial attrition at each step of the cascade and only 22.8% were estimated to have successfully completed treatment.ConclusionsLosses throughout the care cascade resulted in a large proportion of individuals with TB not completing treatment. Ongoing health systems strengthening and patient-centred engagement strategies are needed at every step of the care cascade; however, scale-up of active case finding strategies is particularly critical to ensure individuals with TB in the population reach initial stages of care. Additionally, a renewed focus on PLHIV and individuals with drug-resistant TB is urgently needed to improve TB-related outcomes in Zambia.

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