Persistence Parameter: a Reliable Measurement for Behavioral Responses of Medaka (Oryzias latipes) to Environmental Stress

Online monitoring systems provided a significant evidence for feasibility of the stepwise behavioral response model in detecting the effects of organophosphorus pesticides on movements of medaka (Oryzias latipes), being able to determine the state of indicator organisms, "no effect," "stimulation," "acclimation," "adjustment (readjustment)," and "toxic effect." Though the stepwise behavioral response model postulated that an organism displays a time-dependent sequence of compensatory stepwise behavioral response during exposure to pollutants above their respective thresholds of resistance, it was still a conceptual model based on tendency only in analysis. In this study, the phenomenon of bacterial persistence was used to interpret the relationship between the stepwise behavioral response model and the environmental stress caused by both exposure time and different treatments. Quantitative measurements of the stepwise behavioral response model led to a simple mathematical description of the threshold switch, which evaluated the effects of environmental stress on behavioral responses to decide the tendency. The adjustment ability correlated to "persisters (p)" is very important for test individuals to overcome the "threshold" from the outside environmental stress. The computational modeling results suggested that "persister (p)," as described in the general equations of bacterial persistence model in changing environments, illustrated behavior acclimation and adjustment (or readjustment) clearly. Consequently, the persistence parameter, p, was critical in addressing for medaka to be adapted to fluctuating environments under different environmental stress

Physical and land-cover variables influence ant functional groups and species diversity along elevational gradients

Of particular importance in shaping species assemblages is the spatial heterogeneity of the environment. The aim of our study was to investigate the influence of spatial heterogeneity and environmental complexity on the distribution of ant functional groups and species diversity along altitudinal gradients in a temperate ecosystem (Pyrenees Mountains). During three summers, we sampled 20 sites distributed across two Pyrenean valleys ranging in altitude from 1,009 to 2,339 m by using pitfall traps and hand collection. The environment around each sampling points was characterized by using both physical and land-cover variables. We then used a self-organizing map algorithm (SOM, neural network) to detect and characterize the relationship between the spatial distribution of ant functional groups, species diversity, and the variables measured. The use of SOM allowed us to reduce the apparent complexity of the environment to five clusters that highlighted two main gradients: an altitudinal gradient and a gradient of environmental closure. The composition of ant functional groups and species diversity changed along both of these gradients and was differently affected by environmental variables. The SOM also allowed us to validate the contours of most ant functional groups by highlighting the response of these groups to the environmental and land-cover variables

Three-Dimensional Neurophenotyping of Adult Zebrafish Behavior

The use of adult zebrafish (Danio rerio) in neurobehavioral research is rapidly expanding. The present large-scale study applied the newest video-tracking and data-mining technologies to further examine zebrafish anxiety-like phenotypes. Here, we generated temporal and spatial three-dimensional (3D) reconstructions of zebrafish locomotion, globally assessed behavioral profiles evoked by several anxiogenic and anxiolytic manipulations, mapped individual endpoints to 3D reconstructions, and performed cluster analysis to reconfirm behavioral correlates of high- and low-anxiety states. The application of 3D swim path reconstructions consolidates behavioral data (while increasing data density) and provides a novel way to examine and represent zebrafish behavior. It also enables rapid optimization of video tracking settings to improve quantification of automated parameters, and suggests that spatiotemporal organization of zebrafish swimming activity can be affected by various experimental manipulations in a manner predicted by their anxiolytic or anxiogenic nature. Our approach markedly enhances the power of zebrafish behavioral analyses, providing innovative framework for high-throughput 3D phenotyping of adult zebrafish behavior

Planck 2015 results I. Overview of products and scientific results

The European Space Agency's Planck satellite, which is dedicated to studying the early Universe and its subsequent evolution, was launched on 14 May 2009. It scanned the microwave and submillimetre sky continuously between 12 August 2009 and 23 October 2013. In February 2015, ESA and the Planck Collaboration released the second set of cosmology products based on data from the entire Planck mission, including both temperature and polarization, along with a set of scientific and technical papers and a web-based explanatory supplement. This paper gives an overview of the main characteristics of the data and the data products in the release, as well as the associated cosmological and astrophysical science results and papers. The data products include maps of the cosmic microwave background (CMB), the thermal Sunyaev-Zeldovich effect, diffuse foregrounds in temperature and polarization, catalogues of compact Galactic and extragalactic sources (including separate catalogues of Sunyaev-Zeldovich clusters and Galactic cold clumps), and extensive simulations of signals and noise used in assessing uncertainties and the performance of the analysis methods. The likelihood code used to assess cosmological models against the Planck data is described, along with a CMB lensing likelihood. Scientific results include cosmological parameters derived from CMB power spectra, gravitational lensing, and cluster counts, as well as constraints on inflation, non-Gaussianity, primordial magnetic fields, dark energy, and modified gravity, and new results on low-frequency Galactic foregrounds

Inferring variance and invariance in multi-individual behavior of zebrafish (Danio rerio) responding to chemical stress

Variance and invariance residing in multi-individual movement of zebrafish under chemical stress were addressed concurrently before and after treatment with formaldehyde. Variance was observed in movement parameters. Without treatment, linear speed was highest in groups with two-individuals, followed by those with one- and four-individuals. Following treatment, linear speed decreased significantly in groups with one- and two-individuals, but not in those with four-individuals. Inter-distances between two-individuals in groups with two-individuals decreased markedly after treatment, whereas inter-distances between two randomly selected individuals in the groups with four-individuals were not affected. The zero- and peak-values in the time-lag of autocorrelation of inter-distances decreased further after treatment in groups of two individuals relative to those in groups of four individuals. However, the empirical transition probability matrix between predefined behavioral patterns remained invariant among groups with different numbers of individuals as well as before and after treatment. Variance and invariance in multi-individual behaviors are suitable in expressing complex behaviors under chemical stress and could be a reference for detecting contaminants in the environment using indicator species

Characterizing response behavior of medaka (Oryzias latipes) under chemical stress based on self-organizing map and filtering by integration

Behavioral responses (BRs) of medaka (Oryzias latipes) were observed after exposure to low concentrations (0.1 TU (Toxic Unit, TU), 1 TU, 5 TU, and 10 TU) of trichlorfon, parathion and malathion. Overall response patterns of test organisms were reflected from surface shapes of BS (Behavior Strength) values in 3-D: parathion appeared to be most variable in presenting response behaviors whereas trichlorfon showed relatively simple response patterns. The self-organizing map (SOM) addressed the time and toxic effects efficiently. An evident circadian rhythm observed in the control diminished at a low concentration of toxic unit, and variability of toxic effects was accordingly observed according to chemicals and concentrations. Subsequently filtering by integration was conducted to time series BS values. The highly fluctuating nature of original BS values was filtered efficiently to produce linear fitting closely. Slopes of regression decreased monotonically as toxic concentrations increased. Residual curves of integral BS values from linear fitting were further used for determining different BS phases proposed by empirical observations; the positive and negative phases were in accordance with acclimation, adjustment and toxic effects in behavior response modes. According to inclination and declination periods observed in residual curves, new states of test organisms were further defined to present intoxicating and recovering tendencies Profiles based on residual curves of integral BS values were able to show landscape of response patterns across toxic concentrations in different chemicals. Computational methods for defining behavior states provide an objective ground for analyzing complex stress response and could be suitable in referencing toxic behavior modes of test organisms quantitatively. (C) 2014 Elsevier B.V. All rights reserved

Implementation of computational methods to pattern recognition of movement behavior of Blattella germanica (Blattaria : Blattellidae) treated with Ca2+ signal inducing chemicals

Response behavior of specimens of the German cockroach (Blattella germanica) exposed to the Ca2+ signal inducing chemicals was characterized through implementation of two computational methods: the Fourier transform analysis and artificial neural networks. lonomycin, thapsigargin, and their solvent (dimethyl sulfoxide) were topically applied to male German cockroaches, and the movement tracks were continuously observed through the image processing system under semi-natural conditions for 4-5 days. The specimens treated with the chemicals revealed different movement patterns: 1) shaky advancement and entanglement of the movement tracks with the ionomycin treatments; 2) continuous, circular movements with the thapsigargin treatments; and 3) shaky turning movements with the dimethyl sulfoxide treatments. The movement tracks in time domain were further analyzed with the two-dimensional fast Fourier transform (2-D FFT). The coefficients of the 2-D FFT efficiently revealed characteristics that resided in the two-dimensional data of the movement tracks in the frequency domain. Subsequently the magnitudes of the coefficients were trained by self-organizing map (SOM) through unsupervised learning. Classification of the different movement patterns was possible with the trained network. The combined use of the 2-D FFT and the SOM could be an alternative tool to automatically monitor behavioral changes in specimens exposed to stimulating chemicals.X1125sciescopu

SERS-based immunoassay of tumor marker VEGF using DNA aptamers and silica-encapsulated hollow gold nanospheres.pdf

We propose an in situ detection method of multiple leaves with overlapping and occlusion in greenhouse conditions. Initially a multilayer perceptron (MLP) is used to classify partial boundary images of pepper leaves. After the partial leaf boundary detection, active shape models (ASMs) are subsequently built to employ the images of entire leaves based on a priori knowledge using landmark. Two deformable models were developed with pepper leaves: Boundary-ASM and MLP-ASM. Matching processes are carried out by deforming the trained leaf models to fit real leaf images collected in the greenhouse. MLP-ASM detected 76.7 and 87.8% of overlapping and occluded pepper leaves respectively, while Boundary-ASM showed detection rates of 63.4 and 76.7%. The detection rates by the conventional ASM were 23.3 and 29.3%. The leaf models trained with pepper leaves were further tested with leaves of paprika, in the same family but with more complex shapes (e.g., holes and rolling). Although the overall detection rates were somewhat lower than those for pepper, the rates for the occluded and overlapping leaves of paprika were still higher with MLP-ASM (ranging from 60.4 to 76.7%) and Boundary-ASM (ranging from 50.5 to 63.3%) than using the conventional active shape model (from 21.6 to 30.0%). The modified active shape models with the boundary classifier could be an efficient means for detecting multiple leaves in field conditions. (c) 2013 IAgrE. Published by Elsevier Ltd. All rights reserved.We propose an in situ detection method of multiple leaves with overlapping and occlusion in greenhouse conditions. Initially a multilayer perceptron (MLP) is used to classify partial boundary images of pepper leaves. After the partial leaf boundary detection, active shape models (ASMs) are subsequently built to employ the images of entire leaves based on a priori knowledge using landmark. Two deformable models were developed with pepper leaves: Boundary-ASM and MLP-ASM. Matching processes are carried out by deforming the trained leaf models to fit real leaf images collected in the greenhouse. MLP-ASM detected 76.7 and 87.8% of overlapping and occluded pepper leaves respectively, while Boundary-ASM showed detection rates of 63.4 and 76.7%. The detection rates by the conventional ASM were 23.3 and 29.3%. The leaf models trained with pepper leaves were further tested with leaves of paprika, in the same family but with more complex shapes (e.g., holes and rolling). Although the overall detection rates were somewhat lower than those for pepper, the rates for the occluded and overlapping leaves of paprika were still higher with MLP-ASM (ranging from 60.4 to 76.7%) and Boundary-ASM (ranging from 50.5 to 63.3%) than using the conventional active shape model (from 21.6 to 30.0%). The modified active shape models with the boundary classifier could be an efficient means for detecting multiple leaves in field conditions. (c) 2013 IAgrE. Published by Elsevier Ltd. All rights reserved