Landing together: how flocks arrive at a coherent action in time and space in the presence of perturbations

Collective motion is abundant in nature, producing a vast amount of phenomena which have been studied in recent years, including the landing of flocks of birds. We investigate the collective decision making scenario where a flock of birds decides the optimal time of landing in the absence of a global leader. We introduce a simple phenomenological model in the spirit of the statistical mechanics-based self-propelled particles (SPP-s) approach to interpret this process. We expect that our model is applicable to a larger class of spatiotemporal decision making situations than just the landing of flocks (which process is used as a paradigmatic case). In the model birds are only influenced by observable variables, like position and velocity. Heterogeneity is introduced in the flock in terms of a depletion time after which a bird feels increasing bias to move towards the ground. Our model demonstrates a possible mechanism by which animals in a large group can arrive at an egalitarian decision about the time of switching from one activity to another in the absence of a leader. In particular, we show the existence of a paradoxical effect where noise enhances the coherence of the landing process.Comment: 15 pages, 7 figure

Effects of anisotropic interactions on the structure of animal groups

This paper proposes an agent-based model which reproduces different structures of animal groups. The shape and structure of the group is the effect of simple interaction rules among individuals: each animal deploys itself depending on the position of a limited number of close group mates. The proposed model is shown to produce clustered formations, as well as lines and V-like formations. The key factors which trigger the onset of different patterns are argued to be the relative strength of attraction and repulsion forces and, most important, the anisotropy in their application.Comment: 22 pages, 9 figures. Submitted. v1-v4: revised presentation; extended simulations; included technical results. v5: added a few clarification

Optimization of organotypic cultures of mouse spleen for staining and functional assays

By preserving cell viability and three-dimensional localization, organotypic culture stands out among the newest frontiers of cell culture. It has been successfully employed for the study of diseases among which neoplasias, where tumoral cells take advantage of the surrounding stroma to promote their own proliferation and survival. Organotypic culture acquires major importance in the context of the immune system, whose cells cross-talk in a complex and dynamic fashion to elicit productive responses. However, organotypic culture has been as yet poorly developed for and applied to primary and secondary lymphoid organs. Here we describe in detail the development of a protocol suitable for the efficient cutting of mouse spleen, which overcomes technical difficulties related to the peculiar organ texture, and for optimized organotypic culture of spleen slices. Moreover, we used microscopy, immunofluorescence, flow cytometry and qRT-PCR to demonstrate that the majority of cells residing in spleen slices remain alive and maintain their original location in the organ architecture for several days after cutting. The development of this protocol represents a significant technical improvement in the study of the lymphoid microenvironment in both physiological and pathological conditions involving the immune system

CSF/serum matrix metallopeptidase-9 ratio discriminates neuro Behcet from multiple sclerosis

In neuro Behcet disease with multiple sclerosis-like features, diagnosis could be challenging. Here, we studied the cerebrospinal fluid and serum inflammatory profile of 11 neuro Behcet and 21 relapsing-remitting multiple sclerosis patients. Between the soluble factors analyzed (MMP9, TNF, IL6, CXCL13, CXCL10, CXCL8, IFN, IL10, IL17, IL23, and others) we found MMP9 increased in neuro Behcet serum compared to multiple sclerosis and decreased in cerebrospinal fluid. Furthermore, neuro Behcet analysis of circulating natural killer CD56(DIM) subset suggests their potential involvement in increased MMP9 production. We believe that these findings may have a translational utility in clinical practice

Dynamical modeling of collective behavior from pigeon flight data: flock cohesion and dispersion

Several models of flocking have been promoted based on simulations with qualitatively naturalistic behavior. In this paper we provide the first direct application of computational modeling methods to infer flocking behavior from experimental field data. We show that this approach is able to infer general rules for interaction, or lack of interaction, among members of a flock or, more generally, any community. Using experimental field measurements of homing pigeons in flight we demonstrate the existence of a basic distance dependent attraction/repulsion relationship and show that this rule is sufficient to explain collective behavior observed in nature. Positional data of individuals over time are used as input data to a computational algorithm capable of building complex nonlinear functions that can represent the system behavior. Topological nearest neighbor interactions are considered to characterize the components within this model. The efficacy of this method is demonstrated with simulated noisy data generated from the classical (two dimensional) Vicsek model. When applied to experimental data from homing pigeon flights we show that the more complex three dimensional models are capable of predicting and simulating trajectories, as well as exhibiting realistic collective dynamics. The simulations of the reconstructed models are used to extract properties of the collective behavior in pigeons, and how it is affected by changing the initial conditions of the system. Our results demonstrate that this approach may be applied to construct models capable of simulating trajectories and collective dynamics using experimental field measurements of herd movement. From these models, the behavior of the individual agents (animals) may be inferred

Inhibition of Immune Synapse by Altered Dendritic Cell Actin Distribution: A New Pathway of Mesenchymal Stem Cell Immune Regulation

n/

Bayesian Inference for Identifying Interaction Rules in Moving Animal Groups

The emergence of similar collective patterns from different self-propelled particle models of animal groups points to a restricted set of “universal” classes for these patterns. While universality is interesting, it is often the fine details of animal interactions that are of biological importance. Universality thus presents a challenge to inferring such interactions from macroscopic group dynamics since these can be consistent with many underlying interaction models. We present a Bayesian framework for learning animal interaction rules from fine scale recordings of animal movements in swarms. We apply these techniques to the inverse problem of inferring interaction rules from simulation models, showing that parameters can often be inferred from a small number of observations. Our methodology allows us to quantify our confidence in parameter fitting. For example, we show that attraction and alignment terms can be reliably estimated when animals are milling in a torus shape, while interaction radius cannot be reliably measured in such a situation. We assess the importance of rate of data collection and show how to test different models, such as topological and metric neighbourhood models. Taken together our results both inform the design of experiments on animal interactions and suggest how these data should be best analysed

Polystyrene Nanopillars with Inbuilt Carbon Nanotubes Enable Synaptic Modulation and Stimulation in Interfaced Neuronal Networks

The use of nanostructured materials and nanosized-topographies has the potential to impact the performance of implantable biodevices, including neural interfaces, enhancing their sensitivity and selectivity, while reducing tissue reactivity. As a result, current trends in biosensor technology require the effective ability to improve devices with controlled nanostructures. Nanoimprint lithography to pattern surfaces with high-density and high aspect ratio nanopillars (NPs) made of polystyrene (PS-NP, insulating), or of a polystyrene/carbon-nanotube nanocomposite (PS-CNT-NP, electrically conductive) are exploited. Both substrates are challenged with cultured primary neurons. They are demonstrated to support the development of suspended synaptic networks at the NPs’ interfaces characterized by a reduction in proliferating neuroglia, and a boost in neuronal emergent electrical activity when compared to flat controls. The authors successfully exploit their conductive PS-CNT-NPs to stimulate cultured cells electrically. The ability of both nanostructured surfaces to interface tissue explants isolated from the mouse spinal cord is then tested. The integration of the neuronal circuits with the NP topology, the suspended nature of the cultured networks, the reduced neuroglia formation, and the higher network activity together with the ability to deliver electrical stimuli via PS-CNT-NP reveal such platforms as promising designs to implement on neuro-prosthetic or neurostimulation devices

Robust model-based indicators of regional differences in food-web structure in the Southern Ocean

Efforts to model marine food-webs are generally undertaken by small teams working separately on specific regions (<106 km2) and making independent decisions about how to deal with data gaps and uncertainties. Differences in these largely arbitrary decisions (which we call ‘model personality’) can potentially obscure true differences between regional food-webs or lead to spurious differences. Here we explore the influence of model personality on a comparison of four Southern Ocean regional food-web models. We construct alternative model versions which sequentially remove aspects of personality (alternative model ‘currencies’, schemes for aggregating organisms into functional groups, and energetic parameter values). These alternative versions preserve regional differences in biomass and feeding relationships. Variation in a set of model metrics that are insensitive to absolute biomass and production identifies multiple regional contrasts, a subset of which are robust to differences in model personality. These contrasts imply real differences in ecosystem structure which, in conjunction with differences in primary production and consumer biomass (spanning two and four orders of magnitude respectively), underpin differences in function. Existing regional models are therefore a useful resource for comparing ecosystem structure, function and response to change if comparative studies assess and report the influence of model personality