Coupled information networks drive honeybee (Apis mellifera) collective foraging

Collective behaviour by eusocial insect colonies is typically achieved through multiple communication networks that produce complex behaviour at the group level but often appear to provide redundant or even competing information. A classic example occurs in honeybee (Apis mellifera) colonies, where both the dance communication system and robust scent-based mechanisms contribute to the allocation of a colony's workforce by regulating the flow of experienced foragers among known food sources. Here we analysed social connectivity patterns during the reactivation of experienced foragers to familiar feeding sites to show that these social information pathways are not simply multiple means to achieve the same end but intersect to play complementary roles in guiding forager behaviour. Using artificial feeding stations, we mimicked a natural scenario in which two forager groups were simultaneously collecting from distinct patches containing different flowering species. We then observed the reactivation of these groups at their familiar feeding sites after interrupting their foraging. Social network analysis revealed that temporarily unemployed individuals interacted more often and for longer with foragers that advertised a familiar versus unfamiliar foraging site. Due to such resource-based assortative mixing, network-based diffusion analysis estimated that reactivation events primarily resulted from interactions among bees that had been trained to the same feeding station and less so from different-feeder interactions. Both scent- and dance-based interactions strongly contributed to reactivation decisions. However, each bout of dance-following had an especially strong effect on a follower's likelihood of reactivation, particularly when dances indicated locations familiar to followers. Our findings illustrate how honeybee foragers can alter their social connectivity in ways that are likely to enhance collective outcomes by enabling foragers to rapidly access up-to-date information about familiar foraging sites. In addition, our results highlight how reliance on multiple communication mechanisms enables social insect workers to utilise flexible information-use strategies that are robust to variation in the availability of social information

The Darkening Cloud of Diabetes: Do trends in cardiovascular risk management provide a silver lining?

OBJECTIVE—We aimed to evaluate the changes in cardiovascular-related health care utilization (drug therapies, hospitalizations) and mortality for the diabetic population during a 9-year period in Saskatchewan, Canada

Dynamics of Simple Balancing Models with State Dependent Switching Control

Time-delayed control in a balancing problem may be a nonsmooth function for a variety of reasons. In this paper we study a simple model of the control of an inverted pendulum by either a connected movable cart or an applied torque for which the control is turned off when the pendulum is located within certain regions of phase space. Without applying a small angle approximation for deviations about the vertical position, we see structurally stable periodic orbits which may be attracting or repelling. Due to the nonsmooth nature of the control, these periodic orbits are born in various discontinuity-induced bifurcations. Also we show that a coincidence of switching events can produce complicated periodic and aperiodic solutions.Comment: 36 pages, 12 figure

Center or Limit Cycle: Renormalization Group as a Probe

Based on our studies done on two-dimensional autonomous systems, forced non-autonomous systems and time-delayed systems, we propose a unified methodology - that uses renormalization group theory - for finding out existence of periodic solutions in a plethora of nonlinear dynamical systems appearing across disciplines. The technique will be shown to have a non-trivial ability of classifying the solutions into limit cycles and periodic orbits surrounding a center. Moreover, the methodology has a definite advantage over linear stability analysis in analyzing centers

Avalanches in self-organized critical neural networks: A minimal model for the neural SOC universality class

The brain keeps its overall dynamics in a corridor of intermediate activity and it has been a long standing question what possible mechanism could achieve this task. Mechanisms from the field of statistical physics have long been suggesting that this homeostasis of brain activity could occur even without a central regulator, via self-organization on the level of neurons and their interactions, alone. Such physical mechanisms from the class of self-organized criticality exhibit characteristic dynamical signatures, similar to seismic activity related to earthquakes. Measurements of cortex rest activity showed first signs of dynamical signatures potentially pointing to self-organized critical dynamics in the brain. Indeed, recent more accurate measurements allowed for a detailed comparison with scaling theory of non-equilibrium critical phenomena, proving the existence of criticality in cortex dynamics. We here compare this new evaluation of cortex activity data to the predictions of the earliest physics spin model of self-organized critical neural networks. We find that the model matches with the recent experimental data and its interpretation in terms of dynamical signatures for criticality in the brain. The combination of signatures for criticality, power law distributions of avalanche sizes and durations, as well as a specific scaling relationship between anomalous exponents, defines a universality class characteristic of the particular critical phenomenon observed in the neural experiments. The spin model is a candidate for a minimal model of a self-organized critical adaptive network for the universality class of neural criticality. As a prototype model, it provides the background for models that include more biological details, yet share the same universality class characteristic of the homeostasis of activity in the brain.Comment: 17 pages, 5 figure

Treatment of Type 2 Diabetes and Outcomes in Patients With Heart Failure: A Nested Case–Control Study From the U.K. General Practice Research Database

OBJECTIVE - Diabetes and heart failure commonly coexist, and prior studies have suggested better outcomes with met formin than other antidiabetic agents. We designed this study to determine whether this association reflects a beneficial effect of metformin or a harmful effect of other agents. RESEARCH DESIGN AND METHODS - We performed a case-control study nested within the U.K. General Practice Research Database cohort in which diagnoses were assigned by each patient's primary care physician. Case subjects were patients 35 years or older, newly diagnosed with both heart failure and diabetes after January 1988, and who died prior to October 2007. Control subjects were matched to case subjects based on age, sex, clinic site, calendar year, and duration of follow-up. Analyses were adjusted for comorbidities, A1C, renal function, and BMI. RESULTS - The duration of concurrent diabetes and heart failure was 2.8 years (SD 2.6) in our 1,633 case subjects and 1,633 control subjects (mean age 78 years, 53% male). Compared with patients who were not exposed to antidiabetic drugs, the current use of metformin monotherapy (adjusted odds ratio 0.65 [0.48-0.87]) or metformin with or without other agents (0.72 [0.59-0.90]) was associated with lower mortality; however, use of other antidiabetic drugs or insulin was not associated with all-cause mortality. Conversely, the use of ACE inhibitors/angiotensin receptor blockers (0.55 [0.45-0.68]) and beta-blockers (0.76 [0.61-0.95]) were associated with reduced mortality. CONCLUSIONS - Our results confirm the benefits of trial-proven anti-failure therapies in patients with diabetes and support the use of metformin-based strategies to lower glucose

How spiking neurons give rise to a temporal-feature map

A temporal-feature map is a topographic neuronal representation of temporal attributes of phenomena or objects that occur in the outside world. We explain the evolution of such maps by means of a spike-based Hebbian learning rule in conjunction with a presynaptically unspecific contribution in that, if a synapse changes, then all other synapses connected to the same axon change by a small fraction as well. The learning equation is solved for the case of an array of Poisson neurons. We discuss the evolution of a temporal-feature map and the synchronization of the single cells’ synaptic structures, in dependence upon the strength of presynaptic unspecific learning. We also give an upper bound for the magnitude of the presynaptic interaction by estimating its impact on the noise level of synaptic growth. Finally, we compare the results with those obtained from a learning equation for nonlinear neurons and show that synaptic structure formation may profit from the nonlinearity

Development of a Cx46 Targeting Strategy for Cancer Stem Cells

Gap-junction-mediated cell-cell communication enables tumor cells to synchronize complex processes. We previously found that glioblastoma cancer stem cells (CSCs) express higher levels of the gap junction protein Cx46 compared to non-stem tumor cells (non-CSCs) and that this was necessary and sufficient for CSC maintenance. To understand the mechanism underlying this requirement, we use point mutants to disrupt specific functions of Cx46 and find that Cx46-mediated gap-junction coupling is critical for CSCs. To develop a Cx46 targeting strategy, we screen a clinically relevant small molecule library and identify clofazimine as an inhibitor of Cx46-specific cell-cell communication. Clofazimine attenuates proliferation, self-renewal, and tumor growth and synergizes with temozolomide to induce apoptosis. Although clofazimine does not cross the blood-brain barrier, the combination of clofazimine derivatives optimized for brain penetrance with standard-of-care therapies may target glioblastoma CSCs. Furthermore, these results demonstrate the importance of targeting cell-cell communication as an anti-cancer therapy

Macromolecular theory of solvation and structure in mixtures of colloids and polymers

The structural and thermodynamic properties of mixtures of colloidal spheres and non-adsorbing polymer chains are studied within a novel general two-component macromolecular liquid state approach applicable for all size asymmetry ratios. The dilute limits, when one of the components is at infinite dilution but the other concentrated, are presented and compared to field theory and models which replace polymer coils with spheres. Whereas the derived analytical results compare well, qualitatively and quantitatively, with mean-field scaling laws where available, important differences from ``effective sphere'' approaches are found for large polymer sizes or semi-dilute concentrations.Comment: 23 pages, 10 figure