Trapline foraging by bumble bees: II. Definition and detection from sequence data

Trapline foraging—repeated sequential visits to a seriesof feeding locations—presents interesting problems seldomtreated in foraging models. Work on traplining is hampered bythe lack of statistical, operational approaches for detectingits existence and measuring its strength. We propose severalstatistical procedures, illustrating them with records of interplantflight sequences by bumble bees visiting penstemon flowers.An asymmetry test detects deviations from binomial expectationin the directionality of visits between pairs of plants. Severaltests compare data from one bee to another frequencies of visitsto plants and frequencies of departures to particular destinationsare compared using contingency tables; similarities of repeatedsequences within bees are compared to those between bees bymeans of sequence alignment and Mantel tests. We also comparedobserved movement patterns to those generated by null modelsdesigned to represent realistic foraging by non-traplining bees,examining: temporal patterns of the bee's spatial displacementfrom its starting point using spectral analysis; the varianceof return times to particular plants; and the sequence alignmentof repeated cycles within sequences. We discuss the differentindications and the relative strengths of these approaches     

Innovative biomechanics for directional hearing in small flies

In humans and animals alike, the localization of sound constitutes a fundamental processing task of the auditory system. Directional hearing relies on acoustic cues such as the interaural amplitude and time differences and also, sometimes, the signal spectral composition. In small animals, such as insects, the auditory receptors are forcibly set close together, a design constraint imposing very short interaural distances. Due to the physics of sound propagation, the close proximity of the sound receivers results in vanishingly small amplitude and time cues. Yet, because of their directionality, small auditory systems embed original and innovative solutions that can be of inspirational value to some acute problems of technological miniaturization. Such ears are found in a parasitoid fly that acoustically locates its singing cricket host. Anatomically rather unconventional, the fly's auditory system is endowed with a directional sensitivity that is based on the mechanical coupling between its two hemilateral tympanal membranes. The functional principle permitting this directionality may be of particular relevance for technological applications necessitating sensors that are low cost, low weight, and low energy. Based on silicon-etching technology, early prototypes of sub-millimeter acoustic sensors provide evidence for directional mechanical responses. Further developments hold the promise of applications in hearing aid technology, vibration sensors, and miniature video-acoustic surveillance systems.     

Three-dimensional arrangement of F-actin in the contractile ring of fission yeast

The contractile ring, which is required for cytokinesis in animal and yeast cells, consists mainly of actin filaments. Here, we investigate the directionality of the filaments in fission yeast using myosin S1 decoration and electron microscopy. The contractile ring is composed of around 1,000 to 2,000 filaments each around 0.6 mum in length. During the early stages of cytokinesis, the ring consists of two semicircular populations of parallel filaments of opposite directionality. At later stages, before contraction, the ring filaments show mixed directionality. We consider that the ring is initially assembled from a single site in the division plane and that filaments subsequently rearrange before contraction initiates.     

Microfluidics Approaches in Modern Developmental Biology

Modern automated microsystems based on microhydrodynamic (microfluidic) technologies— labs on chips—make it possible to solve various basic and applied research problems. In the last 15 years, the development of these approaches in application to the problems of modern quantitative (systems) development biology has been observed. In this field, high-throughput experiments aimed at accumulating ample quantitative data for their subsequent computer analysis are important. In this review, the main directions in the development and application of microfluidics approaches for solving problems of modern developmental biology using the classical model object, Drosophila embryo, as an example is discussed. Microfluidic systems provide an opportunity to perform experiments that can hardly be performed using other approaches. These systems allow automated, rapid, reliable, and proper placing of many live embryos on a substrate for their simultaneous confocal scanning, sorting them, or injecting them with various agents. Such systems make it possible, in particular, to create controlled gradients of microenvironmental parameters along a series of developing embryos or even to introduce discontinuity in parameters within the microenvironment of one embryo, so that the head half is under other conditions compared to the tail half (at continuous scanning). These approaches are used both in basic research of the functions of gene ensembles that control early development, including the problems of resistance of early patterns to disturbances, and in test systems for screening chemical agents on developing embryos. The problems of integration of microfluidic devices in systems for automated performance of experiments simultaneously on many developing embryos under conditions of their continuous scanning using modern fluorescence microscopy instruments will be discussed. The methods and approaches developed for Drosophila are also applicable to other model objects, even mammalian embryos.     

Accounting for diffusion in agent based models of reaction-diffusion systems with application to cytoskeletal diffusion

Diffusion plays a key role in many biochemical reaction systems seen in nature. Scenarios where diffusion behavior is critical can be seen in the cell and subcellular compartments where molecular crowding limits the interaction between particles. We investigate the application of a computational method for modeling the diffusion of molecules and macromolecules in three-dimensional solutions using agent based modeling. This method allows for realistic modeling of a system of particles with different properties such as size, diffusion coefficients, and affinity as well as the environment properties such as viscosity and geometry. Simulations using these movement probabilities yield behavior that mimics natural diffusion. Using this modeling framework, we simulate the effects of molecular crowding on effective diffusion and have validated the results of our model using Langevin dynamics simulations and note that they are in good agreement with previous experimental data. Furthermore, we investigate an extension of this framework where single discrete cells can contain multiple particles of varying size in an effort to highlight errors that can arise from discretization that lead to the unnatural behavior of particles undergoing diffusion. Subsequently, we explore various algorithms that differ in how they handle the movement of multiple particles per cell and suggest an algorithm that properly accommodates multiple particles of various sizes per cell that can replicate the natural behavior of these particles diffusing. Finally, we use the present modeling framework to investigate the effect of structural geometry on the directionality of diffusion in the cell cytoskeleton with the observation that parallel orientation in the structural geometry of actin filaments of filopodia and the branched structure of lamellipodia can give directionality to diffusion at the filopodia-lamellipodia interface.     

The influence of coastal topography, circulation patterns, and rafting in structuring populations of an intertidal alga

Understanding the dispersal processes that influence genetic structure in marine species requires estimating gene flow in a dynamic, fluid environment that is often poorly characterized at scales relevant to multiple dispersive stages (e.g. spores, gametes, zygotes, larvae, adults). We examine genetic structure in the marine alga Fucus vesiculosus L., which inhabits moderately exposed shores in the northern Atlantic but releases gametes only under sunny, calm conditions. We predicted genetic structure would correlate with coastal topography because weather frequently varies across coastal promontories on the Maine shore when F. vesiculosus is reproductive, which causes one side to experience high levels of water motion (= no gamete release) while one side is calm (= gamete release). Furthermore, we expected that the effect of low dispersal capacities of gametes and zygotes would result in spatial genetic structure over short distances. Using surface drifters, we characterized near-shore circulation patterns around the study sites to investigate whether directionality of gene flow was correlated with directionality of currents. We found significant genetic differentiation among sites sampled at two different peninsulas, but patterns of differentiation were unrelated to coastal topography and there was no within-site spatial structuring. Our genetic and near-shore circulation data, combined with an examination of gamete longevity, support the dependency of gene flow on storm-detached, rafting, reproductive adults. This study highlights the significance of rafting as a mechanism for structuring established populations of macroalgae and associated biota and demonstrates the importance of coupling population genetics' research with relevant hydrodynamic studies.     

Analysis of fragmented images perception: local features and global description

Analysis of experimental investigations of the perception of incomplete images is presented. It illustrates two different approaches to work of the brain mechanisms involved: one approach is based on the perception of whole images and another on local informative features. These approaches describe two different mechanisms, which are possibly used by brain systems for incomplete image recognition. Performance on the Gollin test (measuring recognition thresholds for fragmented line drawings of everyday objects and animals) depends upon recognition based on image informational-statistical characteristics. We suggest that recognition thresholds for Gollin stimuli in part reflect the extraction of signal from noise. The brain uses local informative features as an additional source of information about them. We have suggested that fragmented images in the Gollin-test are perceived as whole structures. This structure is compared with a template in memory which is extracted with the help of selective attention mechanism in accordance with a matched filtration model. The Gollin-test is a tool for differential diagnosis of a various forms of cognitive disorders.     

Dynamic Service Discovery for Mobile Computing: Intelligent Agents Meet Jini in the Aether

The emergence of ad-hoc pervasive connectivity for devices based on Bluetooth-like systems provides a new way to create applications for mobile systems. We seek to realize ubiquitous computing systems based on the cooperation of autonomous, dynamic and adaptive components (hardware as well as software) which are located in vicinity of one another. In this paper we present this vision. We also describe a prototype system we have developed that implements parts of this vision – in particular a system that combines agent oriented and service oriented approaches and provides dynamic service discovery. We point out why existing systems such as Jini are not suited for this task, and how our system improves on them.     

Foraging behavior of bee pollinators on the tropical weed Triumfetta semitriloba: flight distance and directionality

We studied flight distance and directionality of bee pollinators on the tropical shrub weed Triumfetta semitriloba Jacq. (Tiliaceae), addressing (1) within- and between-plant movement pattern; (2) distances flown between plants; (3) flight directionality. Flowering plants were distributed in well-delimited clumps, in each of two pasture areas (A1 and A2) and one area of forest gap (A3), in Vi?osa, southeastern Brazil. Five solitary bee species, Augochlorella michaelis, Augochloropsis cupreola, Pseudocentron paulistana, Ceratinula sp., Melissodes sexcincta, and two social bee, Plebeia droryana, P. cf. nigriceps were observed. All species moved mainly to the nearest flower on the same individual plant and, in between-plant movements, to the first or second nearest neighbor. All species moved non-randomly, presenting a flight directionality in departures (maintenance of flight direction), but with a high frequency of turn angles. It is suggested that this foraging behavior pattern occurred because of the resource quantity and quality (pollen or nectar), and environmental characteristics such as flower density and resource distribution.     

Optimization methods to solve adaptive management problems

Determining the best management actions is challenging when critical information is missing. However, urgency and limited resources require that decisions must be made despite this uncertainty. The best practice method for managing uncertain systems is adaptive management, or learning by doing. Adaptive management problems can be solved optimally using decision-theoretic methods; the challenge for these methods is to represent current and future knowledge using easy-to-optimize representations. Significant methodological advances have been made since the seminal adaptive management work was published in the 1980s, but despite recent advances, guidance for implementing these approaches has been piecemeal and study-specific. There is a need to collate and summarize new work. Here, we classify methods and update the literature with the latest optimal or near-optimal approaches for solving adaptive management problems. We review three mathematical concepts required to solve adaptive management problems: Markov decision processes, sufficient statistics, and Bayes’ theorem. We provide a decision tree to determine whether adaptive management is appropriate and then group adaptive management approaches based on whether they learn only from the past (passive) or anticipate future learning (active). We discuss the assumptions made when using existing models and provide solution algorithms for each approach. Finally, we propose new areas of development that could inspire future research. For a long time, limited by the efficiency of the solution methods, recent techniques to efficiently solve partially observable decision problems now allow us to solve more realistic adaptive management problems such as imperfect detection and non-stationarity in systems.     

Analysis of control strategies for VIVA OpenHBM with active reflexive neck muscles

Modeling muscle activity in the neck muscles of a finite element (FE) human body model can be based on two biological reflex systems. One approach is to approximate the Vestibulocollic reflex (VCR) function, which maintains the head orientation relative to a fixed reference in space. The second system tries to maintain the head posture relative to the torso, similar to the Cervicocolic reflex (CCR). Strategies to combine these two neck muscle controller approaches in a single head-neck FE model were tested, optimized, and compared to rear-impact volunteer data. The first approach, Combined-Control, assumed that both controllers simultaneously controlled all neck muscle activations. In the second approach, Distributed-Control, one controller was used to regulate activation of the superficial muscles while a different controller acted on deep neck muscles. The results showed that any muscle controller that combined the two approaches was less effective than only using one of VCR- or CCR-based systems on its own. A passive model had the best objective rating for cervical spine kinematics, but the addition of a single active controller provided the best response for both head and cervical spine kinematics. The present study demonstrates the difficulty in completely capturing representative head and cervical spine responses to rear-impact loading and identified a controller capturing the VCR reflex as the best candidate to investigate whiplash injury mechanisms through FE modeling.

     

Hyperbolic and kinetic models for self-organized biological aggregations and movement: a brief review

We briefly review hyperbolic and kinetic models for self-organized biological aggregations and traffic-like movement. We begin with the simplest models described by an advection-reaction equation in one spatial dimension. We then increase the complexity of models in steps. To this end, we begin investigating local hyperbolic systems of conservation laws with constant velocity. Next, we proceed to investigate local hyperbolic systems with density-dependent speed, systems that consider population dynamics (i.e., birth and death processes), and nonlocal hyperbolic systems. We conclude by discussing kinetic models in two spatial dimensions and their limiting hyperbolic models. This structural approach allows us to discuss the complexity of the biological problems investigated, and the necessity for deriving complex mathematical models that would explain the observed spatial and spatiotemporal group patterns.     

Preservation of dynamic properties in qualitative modeling frameworks for gene regulatory networks

Mathematical modeling often helps to provide a systems perspective on gene regulatory networks. In particular, qualitative approaches are useful when detailed kinetic information is lacking. Multiple methods have been developed that implement qualitative information in different ways, e.g., in purely discrete or hybrid discrete/continuous models. In this paper, we compare the discrete asynchronous logical modeling formalism for gene regulatory networks due to R. Thomas with piecewise affine differential equation models. We provide a local characterization of the qualitative dynamics of a piecewise affine differential equation model using the discrete dynamics of a corresponding Thomas model. Based on this result, we investigate the consistency of higher-level dynamical properties such as attractor characteristics and reachability. We show that although the two approaches are based on equivalent information, the resulting qualitative dynamics are different. In particular, the dynamics of the piecewise affine differential equation model is not a simple refinement of the dynamics of the Thomas model     

ROS-DET: robust detector of switching mechanisms in gene expression

A switching mechanism in gene expression, where two genes are positively correlated in one condition and negatively correlated in the other condition, is a key to elucidating complex biological systems. There already exist methods for detecting switching mechanisms from microarrays. However, current approaches have problems under three real cases: outliers, expression values with a very small range and a small number of examples. ROS-DET overcomes these three problems, keeping the computational complexity of current approaches. We demonstrated that ROS-DET outperformed existing methods, under that all these three situations are considered. Furthermore, for each of the top 10 pairs ranked by ROS-DET, we attempted to identify a pathway, i.e. consecutive biological phenomena, being related with the corresponding two genes by checking the biological literature. In 8 out of the 10 pairs, we found two parallel pathways, one of the two genes being in each of the two pathways and two pathways coming to (or starting with) the same gene. This indicates that two parallel pathways would be cooperatively used under one experimental condition, corresponding to the positive correlation, and the two pathways might be alternatively used under the other condition, corresponding to the negative correlation. ROS-DET is available from http://www.bic.kyoto-u.ac.jp/pathway/kayano/ros-det.htm.