Asynchrony rescues statistically optimal group decisions from information cascades through emergent leaders.

It is usually assumed that information cascades are most likely to occur when an early but incorrect opinion spreads through the group. Here, we analyse models of confidence-sharing in groups and reveal the opposite result: simple but plausible models of naive-Bayesian decision-making exhibit information cascades when group decisions are synchronous; however, when group decisions are asynchronous, the early decisions reached by Bayesian decision-makers tend to be correct and dominate the group consensus dynamics. Thus early decisions actually rescue the group from making errors, rather than contribute to it. We explore the likely realism of our assumed decision-making rule with reference to the evolution of mechanisms for aggregating social information, and known psychological and neuroscientific mechanisms.

Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.

Collective behaviour is of fundamental importance in the life sciences, where it appears at levels of biological complexity from single cells to superorganisms, in demography and the social sciences, where it describes the behaviour of populations, and in the physical and engineering sciences, where it describes physical phenomena and can be used to design distributed systems. Reasoning about collective behaviour is inherently difficult, as the non-linear interactions between individuals give rise to complex emergent dynamics. Mathematical techniques have been developed to analyse systematically collective behaviour in such systems, yet these frequently require extensive formal training and technical ability to apply. Even for those with the requisite training and ability, analysis using these techniques can be laborious, time-consuming and error-prone. Together these difficulties raise a barrier-to-entry for practitioners wishing to analyse models of collective behaviour. However, rigorous modelling of collective behaviour is required to make progress in understanding and applying it. Here we present an accessible tool which aims to automate the process of modelling and analysing collective behaviour, as far as possible. We focus our attention on the general class of systems described by reaction kinetics, involving interactions between components that change state as a result, as these are easily understood and extracted from data by natural, physical and social scientists, and correspond to algorithms for component-level controllers in engineering applications. By providing simple automated access to advanced mathematical techniques from statistical physics, nonlinear dynamical systems analysis, and computational simulation, we hope to advance standards in modelling collective behaviour. At the same time, by providing expert users with access to the results of automated analyses, sophisticated investigations that could take significant effort are substantially facilitated. Our tool can be accessed online without installing software, uses a simple programmatic interface, and provides interactive graphical plots for users to develop understanding of their models.

Inhibition and Excitation Shape Activity Selection: Effect of Oscillations in a Decision-Making Circuit.

Decision making is a complex task, and its underlying mechanisms that regulate behavior, such as the implementation of the coupling between physiological states and neural networks, are hard to decipher. To gain more insight into neural computations underlying ongoing binary decision-making tasks, we consider a neural circuit that guides the feeding behavior of a hypothetical animal making dietary choices. We adopt an inhibition motif from neural network theory and propose a dynamical system characterized by nonlinear feedback, which links mechanism (the implementation of the neural circuit and its coupling to the animal's nutritional state) and function (improving behavioral performance). A central inhibitory unit influences evidence-integrating excitatory units, which in our terms correspond to motivations competing for selection. We determine the parameter regime where the animal exhibits improved decision-making behavior and explain different behavioral outcomes by making the link between accessible states of the nonlinear neural circuit model and decision-making performance. We find that for given deficits in nutritional items, the variation of inhibition strength and ratio of excitation and inhibition strengths in the decision circuit allows the animal to enter an oscillatory phase that describes its internal motivational state. Our findings indicate that this oscillatory phase may improve the overall performance of the animal in an ongoing foraging task and underpin the importance of an integrated functional and mechanistic study of animal activity selection.

Psychophysical Laws and the Superorganism.

Through theoretical analysis, we show how a superorganism may react to stimulus variations according to psychophysical laws observed in humans and other animals. We investigate an empirically-motivated honeybee house-hunting model, which describes a value-sensitive decision process over potential nest-sites, at the level of the colony. In this study, we show how colony decision time increases with the number of available nests, in agreement with the Hick-Hyman law of psychophysics, and decreases with mean nest quality, in agreement with Piéron's law. We also show that colony error rate depends on mean nest quality, and difference in quality, in agreement with Weber's law. Psychophysical laws, particularly Weber's law, have been found in diverse species, including unicellular organisms. Our theoretical results predict that superorganisms may also exhibit such behaviour, suggesting that these laws arise from fundamental mechanisms of information processing and decision-making. Finally, we propose a combined psychophysical law which unifies Hick-Hyman's law and Piéron's law, traditionally studied independently; this unified law makes predictions that can be empirically tested.

Model of the best-of-N nest-site selection process in honeybees.

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N-1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

Macrophage type modulates osteogenic differentiation of adipose tissue MSCs.

Since the reconstruction of large bone defects remains a challenge, knowledge about the biology of bone healing is desirable to develop novel strategies for improving the treatment of bone defects. In osteoimmunology, macrophages are the central component in the early stage of physiological response after bone injury and bone remodeling in the late stage. During this process, a switch of macrophage phenotype from pro-inflammatory (M1) to anti-inflammatory (M2) is observed. An appealing option for bone regeneration would be to exploit this regulatory role for the benefit of osteogenic differentiation of osteoprogenitor cells (e.g., mesenchymal stem cells; MSCs) and to eventually utilize this knowledge to improve the therapeutic outcome of bone regenerative treatment. In view of this, we focused on the in vitro interaction of different macrophage subtypes with adipose tissue MSCs to monitor the behavior (i.e. proliferation, differentiation and mineralization) of the latter in dedicated co-culture models. Our data show that co-culture of MSCs with M2 macrophages, but not with M1 macrophages or M0 macrophages, results in significantly increased MSC mineralization caused by soluble factors. Specifically, M2 macrophages promoted the proliferation and osteogenic differentiation of MSCs, while M0 and M1 macrophages solely stimulated the osteogenic differentiation of MSCs in the early and middle stages during co-culture. Secretion of the soluble factors oncostatin M (OSM) and bone morphogenetic protein 2 (BMP-2) by macrophages showed correlation with MSC gene expression levels for OSM-receptor and BMP-2, suggesting the involvement of both signaling pathways in the osteogenic differentiation of MSCs.

First-principles study of the Fe | MgO(0 0 1) interface: magnetic anisotropy.

We present a systematic first-principles study of Fe | MgO bilayer systems emphasizing the influence of the iron layer thickness on the geometry, the electronic structure and the magnetic properties. Our calculations ensure the unconstrained structural relaxation at scalar relativistic level for various numbers of iron layers placed on the magnesium oxide substrate. Our results show that due to the formation of the interface the electronic structure of the interface iron atoms is significantly modified involving charge transfer within the iron subsystem. In addition, we find that the magnetic anisotropy energy increases from 1.9 mJ m(-2) for 3 Fe layers up to 3.0 mJ m(-2) for 11 Fe layers.

Enzyme-responsive nanocomposites for wound infection prophylaxis in burn management: in vitro evaluation of their compatibility with healing processes.

Responsive, theranostic nanosystems, capable of both signaling and treating wound infections, is a sophisticated approach to reduce the most common and potentially traumatizing side effects of burn wound treatment: slowed wound healing due to prophylactic anti-infective drug exposure as well as frequent painful dressing changes. Antimicrobials as well as dye molecules have been incorporated into biodegradable nanosystems that release their content only in the presence of pathogens. Following nanocarrier degradation by bacterial enzymes, any infection will thus emit a visible signal and be effectively treated at its source. In this study, we investigated the effect of fluorescent-labeled hyaluronan nanocapsules containing polyhexanide biguanide and poly-L-lactic acid nanoparticles loaded with octenidine on primary human dermal microvascular endothelial cells, which play a major role in cutaneous wound healing. Microscopic and flow cytometric analysis indicated a time-dependent uptake of both the nanocapsules and the nanoparticles. However, enzyme immunoassays showed no significant influence on the expression of pro-inflammatory cell adhesion molecules and cytokines by the endothelial cells. Under angiogenic-stimulating conditions, the potential to form capillary-like structures in co-culture with dermal fibroblasts was not inhibited. Furthermore, cytotoxicity studies (the MTS and crystal violet assay) after short- and long-term exposure to the materials demonstrated that both systems exhibited less toxicity than solutions of the antiseptic agents alone in comparable concentrations. The results indicate that responsive antimicrobial nanocomposites could be used as an advanced drug delivery system and a promising addition to current best practice wound infection prophylaxis with few side effects.

Mild heat stress enhances angiogenesis in a co-culture system consisting of primary human osteoblasts and outgrowth endothelial cells.

The repair and regeneration of large bone defects, including the formation of functional vasculature, represents a highly challenging task for tissue engineering and regenerative medicine. Recent studies have shown that vascularization and ossification can be stimulated by mild heat stress (MHS), which would offer the option to enhance the bone regeneration process by relatively simple means. However, the mechanisms of MHS-enhanced angiogenesis and osteogenesis, as well as potential risks for the treated cells are unclear. We have investigated the direct effect of MHS on angiogenesis and osteogenesis in a co-culture system of human outgrowth endothelial cells (OECs) and primary osteoblasts (pOBs), and assessed cytotoxic effects, as well as the levels of various heat shock proteins (HSPs) synthesized under these conditions. Enhanced formation of microvessel-like structures was observed in co-cultures exposed to MHS (41°C, 1 h), twice per week, over a time period of 7-14 days. As shown by real-time polymerase chain reaction (PCR), the expression of vascular endothelial growth factor (VEGF), angiopoietin-1 (Ang-1), angiopoietin-2 (Ang-2), and tumor necrosis factor-alpha was up-regulated in MHS-treated co-cultures 24 h post-treatment. At the protein level, significantly elevated VEGF and Ang-1 concentrations were observed in MHS-treated co-cultures and pOB mono-cultures compared with controls, indicating paracrine effects associated with MHS-induced angiogenesis. MHS-stimulated co-cultures and OEC mono-cultures released higher levels of Ang-2 than untreated cultures. On the other hand MHS treatment of co-cultures did not result in a clear effect regarding osteogenesis. Nevertheless, real-time PCR demonstrated that MHS increased the expression of mitogen-activated protein kinase, interleukin-6, and bone morphogenetic protein 2, known as HSP-related molecules in angiogenic and osteogenic regulation pathways. In agreement with these observations, the expression of some selected HSPs also increased at both the mRNA and protein levels in MHS-treated co-cultures.

Biocompatible coating of encapsulated cells using ionotropic gelation.

The technique of immunoisolated transplantation has seen in the last twenty years improvements in biocompatibility, long term stability and methods for avoidance of fibrosis in alginate capsules. However, two major problems are not yet solved: living cellular material that is not centered in the capsule is not properly protected from the hosts' immune system and the total transplant volume needs to be reduced. To solve these problems, we present a method for applying fully biocompatible alginate multilayers to a barium-alginate core without the use of polycations. We report on the factors that influence layer formation and stability and can therefore provide data for full adjustability of the additional layer. Although known for yeast and plant cells, this technique has not previously been demonstrated with mammalian cells or ultra-high viscous alginates. Viability of murine insulinoma cells was investigated by live-dead staining and live cell imaging, for murine Langerhans' islets viability and insulin secretion have been measured. No hampering effects of the second alginate layer were found. This multi-layer technique therefore has great potential for clinical and in vitro use and is likely to be central in alginate matrix based immunoisolated cell therapy.

Mesenchymal stem cell proliferation and differentiation on load-bearing trabecular Nitinol scaffolds.

Bone tissue regeneration in load-bearing regions of the body requires high-strength porous scaffolds capable of supporting angiogenesis and osteogenesis. 70% porous Nitinol (NiTi) scaffolds with a regular 3-D architecture resembling trabecular bone were produced from Ni foams using an original reactive vapor infiltration technique. The "trabecular Nitinol" scaffolds possessed a high compressive strength of 79 MPa and high permeability of 6.9×10(-6) cm2. The scaffolds were further modified to produce a near Ni-free surface layer and evaluated in terms of Ni ion release and human mesenchymal stem cell (hMSC) proliferation (AlamarBlue), differentiation (alkaline phosphatase activity, ALP) and mineralization (Alizarin Red S staining). Scanning electron microscopy was employed to qualitatively corroborate the results. hMSCs were able to adhere and proliferate on both as-produced and surface-modified trabecular NiTi scaffolds, to acquire an osteoblastic phenotype and produce a mineralized extracellular matrix. Both ALP activity and mineralization were increased on porous scaffolds compared to control polystyrene plates. Experiments in a model coculture system of microvascular endothelial cells and hMSCs demonstrated the formation of prevascular structures in trabecular NiTi scaffolds. These data suggest that load-bearing trabecular Nitinol scaffolds could be effective in regenerating damaged or lost bone tissue.

Noise-assisted interactions of tumor and immune cells.

We consider a three-state model comprising tumor cells, effector cells, and tumor-detecting cells under the influence of noises. It is demonstrated that inevitable stochastic forces existing in all three cell species are able to suppress tumor cell growth completely. Whereas the deterministic model does not reveal a stable tumor-free state, the auto-correlated noise combined with cross-correlation functions can either lead to tumor-dormant states, tumor progression, as well as to an elimination of tumor cells. The auto-correlation function exhibits a finite correlation time τ, while the cross-correlation functions shows a white-noise behavior. The evolution of each of the three kinds of cells leads to a multiplicative noise coupling. The model is investigated by means of a multivariate Fokker-Planck equation for small τ. The different behavior of the system is, above all, determined by the variation of the correlation time and the strength of the cross-correlation between tumor and tumor-detecting cells. The theoretical model is based on a biological background discussed in detail, and the results are tested using realistic parameters from experimental observations.

Stochastic model for tumor growth with immunization.

We analyze a stochastic model for tumor cell growth with both multiplicative and additive colored noises as well as nonzero cross correlations in between. Whereas the death rate within the logistic model is altered by a deterministic term characterizing immunization, the birth rate is assumed to be stochastically changed due to biological motivated growth processes leading to a multiplicative internal noise. Moreover, the system is subjected to an external additive noise which mimics the influence of the environment of the tumor. The stationary probability distribution P_{s} is derived depending on the finite correlation time, the immunization rate, and the strength of the cross correlation. P_{s} offers a maximum which becomes more pronounced for increasing immunization rate. The mean-first-passage time is also calculated in order to find out under which conditions the tumor can suffer extinction. Its characteristics are again controlled by the degree of immunization and the strength of the cross correlation. The behavior observed can be interpreted in terms of a biological model of tumor evolution.