Can't tell the caterpillars from the trees: countershading enhances survival in a woodland

Perception of the body's outline and three-dimensional shape arises from visual cues such as shading, contour, perspective and texture. When a uniformly coloured prey animal is illuminated from above by sunlight, a shadow may be cast on the body, generating a brightness contrast between the dorsal and ventral surfaces. For animals such as caterpillars, which live among flat leaves, a difference in reflectance over the body surface may degrade the degree of background matching and provide cues to shape from shading. This may make otherwise cryptic prey more conspicuous to visually hunting predators. Cryptically coloured prey are expected to match their substrate in colour, pattern and texture (though disruptive patterning is an exception), but they may also abolish self-shadowing and therefore either reduce shape cues or maintain their degree of background matching through countershading: a gradation of pigment on the body of an animal so that the surface closest to illumination is darker. In this study, we report the results from a series of field experiments where artificial prey resembling lepidopteran larvae were presented on the upper surfaces of beech tree branches so that they could be viewed by free-living birds. We demonstrate that countershading is superior to uniform coloration in terms of reducing attack by free-living predators. This result persisted even when we fixed prey to the underside of branches, simulating the resting position of many tree-living caterpillars. Our experiments provide the first demonstration, in an ecologically valid visual context, that shadowing on bodies (such as lepidopteran larvae) provides cues that visually hunting predators use to detect potential prey species, and that countershading counterbalances shadowing to enhance cryptic protection.     

Visual shape representation with geometrically characterized contour partitions

This paper proposes a biologically plausible matching method to recognize general shapes based on contour curvature information. The human visual system recognizes general shapes flexibly in real-world scenes through the ventral pathway. The pathway is typically modeled using artificial neural networks. These network models, however, do not construct a shape representation that satisfies the following required constraints: (1) The original shape should be represented by a group of partitioned contours in order to retrieve the whole shape (global information) from the partial contours (local information). (2) Coarse and fine structures of the original shapes should be individually represented in order for the visual system to respond to shapes as quickly as possible based on the least number of their features, and to discriminate between shapes based on detailed information. (3) The shape recognition realized with an artificial visual system should be invariant to geometric transformation such as expansion, rotation, or shear. In this paper, we propose a visual shape representation with geometrically characterized contour partitions described on multiple spatial scales.     

A robust,high‐throughput method for computing maize ear,cob, and kernel attributes automatically from images

Grain yield of the maize plant depends on the sizes, shapes, and numbers of ears and the kernels they bear. An automated pipeline that can measure these components of yield from easily‐obtained digital images is needed to advance our understanding of this globally important crop. Here we present three custom algorithms designed to compute such yield components automatically from digital images acquired by a low‐cost platform. One algorithm determines the average space each kernel occupies along the cob axis using a sliding‐window Fourier transform analysis of image intensity features. A second counts individual kernels removed from ears, including those in clusters. A third measures each kernel's major and minor axis after a Bayesian analysis of contour points identifies the kernel tip. Dimensionless ear and kernel shape traits that may interrelate yield components are measured by principal components analysis of contour point sets. Increased objectivity and speed compared to typical manual methods are achieved without loss of accuracy as evidenced by high correlations with ground truth measurements and simulated data. Millimeter‐scale differences among ear, cob, and kernel traits that ranged more than 2.5‐fold across a diverse group of inbred maize lines were resolved. This system for measuring maize ear, cob, and kernel attributes is being used by multiple research groups as an automated Web service running on community high‐throughput computing and distributed data storage infrastructure. Users may create their own workflow using the source code that is staged for download on a public repository.     

Augmented reality for personalized nanomedicines

As our understanding of onset and progress of diseases at the genetic and molecular level rapidly progresses, the potential of advanced technologies, such as 3D-printing, Socially-Assistive Robots (SARs) or augmented reality (AR), that are applied to personalized nanomedicines (PNMs) to alleviate pathological conditions, has become more prominent. Among advanced technologies, AR in particular has the greatest potential to address those challenges and facilitate the translation of PNMs into formidable clinical application of personalized therapy.As AR is about to adapt additional new methods, such as speech, voice recognition, eye tracing and motion tracking, to enable interaction with host response or biological systems in 3-D space, a combination of multiple approaches to accommodate varying environmental conditions, such as public noise and atmosphere brightness, will be explored to improve its therapeutic outcomes in clinical applications. For instance, AR glasses still being developed by Facebook or Microsoft will serve as new platform that can provide people with the health information they are interested in or various measures through which they can interact with medical services.This review has addressed the current progress and impact of AR on PNMs and its application to the biomedical field. Special emphasis is placed on the application of AR based PNMs to the treatment strategies against senior care, drug addiction and medication adherence.     

Quantitative analysis of radiation-induced changes in sperm morphology

When developing spermatogenic cells are exposed to radiation, chemical carcinogens or mutagens, the transformation in the morphology of the mature sperm can be used to determine the severity of the exposure. In this study five groups of mice with three mice per group received testicular doses of X irradiation at dosage levels ranging from 0 rad to 120 rad. A random sample of 100 mature sperm per mouse was analyzed five weeks later for the quantitative morphologic transformation as a function of dosage level. The cells were stained with gallocyanin chrome alum (GCA) so that only the DNA in the sperm head was visible. The ACUity quantitative microscopy system at Lawrence Livermore National Laboratory was used to scan the sperm at a sampling density of 16 points per linear micrometer and with 256 brightness levels per point. The contour of each cell was extracted using conventional thresholding techniques on the high-contrast images. For each contour a variety of shape features was then computed to characterize the morphology of that cell. Using the control group and the distribution of their shape features to establish the variability of a normal sperm population, the 95% limits on normal morphology were established. Using only four shape features, a doubling dose of approximately 39 rad was determined. That is, at 39 rad exposure the percentage of abnormal cells was twice that occurring in the control population. This compared to a doubling dose of approximately 70 rad obtained from a concurrent visual procedure.     

Detection of temporary lateral confinement of membrane proteins using single-particle tracking analysis.

Techniques such as single-particle tracking allow the characterization of the movements of single or very few molecules. Features of the molecular trajectories, such as confined diffusion or directed transport, can reveal interesting biological interactions, but they can also arise from simple Brownian motion. Careful analysis of the data, therefore, is necessary to identify interesting effects from pure random movements. A method was developed to detect temporary confinement in the trajectories of membrane proteins that cannot be accounted for by Brownian motion. This analysis was applied to trajectories of two lipid-linked members of the immunoglobulin superfamily, Thy-1 and a neural cell adhesion molecule (NCAM 125), and the results were compared with those for simulated random walks. Approximately 28% of the trajectories for both proteins exhibited periods of transient confinement, which were < 0.07% likely to arise from random movements. In contrast to these results, only 1.5% of the simulated trajectories showed confined periods. Transient confinement for both proteins lasted on average 8 s in regions that were approximately 280 nm in diameter.     

Saccadic tracking of a light grey target in the mantis,Tenodera aridifolia

I presented a horizontally moving square on a computer display to the mantis, Tenodera aridifolia, and examined the effects of target brightness and velocity, and background brightness on its tracking behavior. The mantis tracked a light grey square with more saccadic head movements than a black square, although these squares moved on a homogeneous background. The amplitude of saccades was larger when the light grey square moved at a lower velocity. The background brightness had little effect on the type (smooth or saccadic) of tracking behavior. These results suggest that the saccadic tracking of light grey objects on a homogeneous background may not be caused by low contrast, i.e., the difficulty in discriminating the object from the background. The possible biological significance of saccadic tracking on a homogenous background is discussed.     

Evaluating Cell Processes,Quality, and Biomarkers in Pluripotent Stem Cells Using Video Bioinformatics

There is a foundational need for quality control tools in stem cell laboratories engaged in basic research, regenerative therapies, and toxicological studies. These tools require automated methods for evaluating cell processes and quality during in vitro passaging, expansion, maintenance, and differentiation. In this paper, an unbiased, automated high-content profiling toolkit, StemCellQC, is presented that non-invasively extracts information on cell quality and cellular processes from time-lapse phase-contrast videos. Twenty four (24) morphological and dynamic features were analyzed in healthy, unhealthy, and dying human embryonic stem cell (hESC) colonies to identify those features that were affected in each group. Multiple features differed in the healthy versus unhealthy/dying groups, and these features were linked to growth, motility, and death. Biomarkers were discovered that predicted cell processes before they were detectable by manual observation. StemCellQC distinguished healthy and unhealthy/dying hESC colonies with 96% accuracy by non-invasively measuring and tracking dynamic and morphological features over 48 hours. Changes in cellular processes can be monitored by StemCellQC and predictions can be made about the quality of pluripotent stem cell colonies. This toolkit reduced the time and resources required to track multiple pluripotent stem cell colonies and eliminated handling errors and false classifications due to human bias. StemCellQC provided both user-specified and classifier-determined analysis in cases where the affected features are not intuitive or anticipated. Video analysis algorithms allowed assessment of biological phenomena using automatic detection analysis, which can aid facilities where maintaining stem cell quality and/or monitoring changes in cellular processes are essential. In the future StemCellQC can be expanded to include other features, cell types, treatments, and differentiating cells.     

Differential detection of phospholipid fluidity, order, and spacing by fluorescence spectroscopy of bis-pyrene, prodan, nystatin, and merocyanine 540

The properties of liquid-ordered, solid-ordered, and liquid-disordered phases were investigated by steady-state fluorescence spectroscopy in liposomes composed of mixtures of dipalmitoylphosphatidylcholine and cholesterol (0-40 mol %) as a function of temperature (24-51 degrees C). The fluorescent probes used (bis-pyrene, nystatin, prodan, and merocyanine) were chosen because they differ in the location they occupy in the membrane and in the types of properties they sense. Comparison of phase diagrams with contour plots of the fluorescence data suggested that bis-pyrene is sensitive primarily to lipid order. In contrast, nystatin fluorescence intensity responded to changes in lipid fluidity. The shape of the prodan emission spectrum detected both liquid-solid and order-disorder transitions in the phase diagram. Merocyanine's behavior was more complex. First, it was more sensitive than any of the other probes to the membrane pretransition that occurs in the absence of cholesterol. Second, regardless of whether emission intensity, anisotropy, or spectral shape was observed, the probe appeared to distinguish two types of liquid-ordered phases, one with tightly packed lipids and one in which the apparent spacing among lipids was increased. The prodan data supported these results by displaying modest versions of these two observations. Together, the results identify eight regions within the phase diagram of distinguishable combinations of these physical properties. As an example of how this combined analysis can be applied to biological membranes, human erythrocytes were treated similarly. Temperature variation at constant cholesterol content revealed three of the eight combinations identified in our analysis of liposomes.     

Detecting circular and rectangular particles based on geometric feature detection in electron micrographs

Accurate and automatic particle detection from cryo-electron microscopy (cryo-EM images) is very important for high-resolution reconstruction of large macromolecular structures. In this paper, we present a method for particle picking based on shape feature detection. Two fundamental concepts of computational geometry, namely, the distance transform and the Voronoi diagram, are used for detection of critical features as well as for accurate location of particles from the images or micrographs. Unlike the conventional template-matching methods, our approach detects the particles based on their boundary features instead of intensities. The geometric features derived from the boundaries provide an efficient way for locating particles quickly and accurately, which avoids a brute-force searching for the best position/orientation. Our approach is fully automatic and has been successfully applied to detect particles with approximately circular or rectangular shapes (e.g., KLH particles). Particle detection can be enhanced by multiple sets of parameters used in edge detection and/or by anisotropic filtering. We also discuss the extension of this approach to other types of particles with certain geometric features.     

Bio-microrheology: a frontier in microrheology

Cells continuously adapt to changing conditions through coordinated molecular and mechanical responses. This adaptation requires the transport of molecules and signaling through intracellular regions with differing material properties, such as variations in viscosity or elasticity. To determine the impact of regional variations on cell structure and physiology, an approach, termed bio-microrheology, or the study of deformation and flow of biological materials at small length scales has emerged. By tracking the thermal and driven motion of probe particles, organelles, or molecules, the local physical environment in distinct subcellular regions can be explored. On the surface or inside cells, tracking the motion of particles can reveal the rheological properties that influence cell features, such as shape and metastatic potential. Cellular microrheology promises to improve our concepts of regional and integrated properties, structures, and transport in live cells. Since bio-microrheology is an evolving methodology, many specific details, such as how to interpret complex combinations of thermally mediated and directed probe transport, remain to be fully explained. This work reviews the current state of the field and discusses the utility and challenges of this emerging approach.     

Wing shape changes: a morphological view of the <Emphasis Type="Italic">Diabrotica virgifera virgifera</Emphasis> European invasion

An analysis of the hind wing morphology (size and shape) within and among western corn rootworm, Diabrotica virgifera virgifera LeConte, populations over a large geographic scale in Europe was conducted. The changes in hind wing shape and size detected were related to identifiable invasion processes (i.e. multiple introduction events into Europe), first characterised using genetic markers. Overall implications from this work suggest that geometric morphometric techniques can be used to detect population changes related to invasions and could therefore serve as a cheaper and more accessible alternative ‘biomarker’ to more expensive and specialised-use genetic markers, such as microsatellites or SNPs, when investigating biological invasions.     

Stereo vision and isoluminance.

Recent experiments have shown that stereo depth is given by fusion of illusory ('cognitive') contours. They occur across quite large gaps in figures, when these gaps are unlikely and form the shape of a probable (nearer) masking object or masking feature. Implications are that: (a) clearly defined contours and regions of brightness difference can be produced as postulates from sensory evidence, which may be surprising absence of stimulation; (b) each eye-system can derive its own postulates, or hypotheses, which (c) can be combined to give stereo vision. It has been shown that random-dot stereo depth does not occur when there is colour contrast but no brightness difference between the dots and their background. This we have confirmed by using a new technique for producing isoluminant pictures, of any complexity, with exact registration for any two colours. With this technique, we find large displacements of narrow borders bounding regions that are shifted across isoluminance. These displacements, which are clearly seen as movements, occur with or without colour differences. The direction of shift depends on whether the narrow border is light or dark. It is found that these dramatic shifts do not - when produced in opposite directions to the two eyes and fused - produce stereo depth. It is concluded, following Julesz's paradigm, that these contour displacements have their neural orgin not retinally, but after stereo fusion. Experiments combining the 'cognitive contours' stereo depth with isoluminance are described.     

Mammobarography: a possible method of mass breast screening

Preliminary details are given of a novel method of detecting breast lumps. The technique relies on the fact that such a lump will cause a perturbation in the pressure distribution when the breast is loaded against a flat plate. The pressure distribution is monitored by using the principle of frustrated total internal reflection to generate a brightness distribution which can then be presented as a contour map in synthesized colour. Using this technique, simulated lumps in breast prostheses have been detected down to a diameter of 6 mm. It is argued that this represents the basis of a method of mass breast screening.     

Detection of multiple QTL with epistatic effects under a mixed inheritance model in an outbred population

A quantitative trait depends on multiple quantitative trait loci (QTL) and on the interaction between two or more QTL, named epistasis. Several methods to detect multiple QTL in various types of design have been proposed, but most of these are based on the assumption that each QTL works independently and epistasis has not been explored sufficiently. The objective of the study was to propose an integrated method to detect multiple QTL with epistases using Bayesian inference via a Markov chain Monte Carlo (MCMC) algorithm. Since the mixed inheritance model is assumed and the deterministic algorithm to calculate the probabilities of QTL genotypes is incorporated in the method, this can be applied to an outbred population such as livestock. Additionally, we treated a pair of QTL as one variable in the Reversible jump Markov chain Monte Carlo (RJMCMC) algorithm so that two QTL were able to be simultaneously added into or deleted from a model. As a result, both of the QTL can be detected, not only in cases where either of the two QTL has main effects and they have epistatic effects between each other, but also in cases where neither of the two QTL has main effects but they have epistatic effects. The method will help ascertain the complicated structure of quantitative traits.     

Bone surface mapping method

Bone shape is an important factor to determine the bone's structural function. For the asymmetrically shaped and anisotropically distributed bone in vivo, a surface mapping method is proposed on the bases of its geometric transformation invariance and its uniqueness of the principal axes of inertia. Using spiral CT scanning, we can make precise measurements to bone in vivo. The coordinate transformations lead to the principal axes of inertia, with which the prime meridian and the contour can be set. Methods such as tomographic reconstruction and boundary development are employed so that the surface of bone in vivo can be mapped. Experimental results show that the surface mapping method can reflect the shape features and help study the surface changes of bone in vivo. This method can be applied to research into the surface characteristics and changes of organ, tissue or cell whenever its digitalized surface is obtained.     

Investigating the status of biological stimuli as objects of attention in multiple object tracking

Background

Humans are able to track multiple simultaneously moving objects. A number of factors have been identified that can influence the ease with which objects can be attended and tracked. Here, we explored the possibility that object tracking abilities may be specialized for tracking biological targets such as people.

Methodology/Principal Findings

We used the Multiple Object Tracking (MOT) paradigm to explore whether the high-level biological status of the targets affects the efficiency of attentional selection and tracking. In Experiment 1, we assessed the tracking of point-light biological motion figures. As controls, we used either the same stimuli or point-light letters, presented in upright, inverted or scrambled configurations. While scrambling significantly affected performance for both letters and point-light figures, there was an effect of inversion restricted to biological motion, inverted figures being harder to track. In Experiment 2, we found that tracking performance was equivalent for natural point-light walkers and ‘moon-walkers’, whose implied direction was incongruent with their actual direction of motion. In Experiment 3, we found higher tracking accuracy for inverted faces compared with upright faces. Thus, there was a double dissociation between inversion effects for biological motion and faces, with no inversion effect for our non-biological stimuli (letters, houses).

Conclusions/Significance

MOT is sensitive to some, but not all naturalistic aspects of biological stimuli. There does not appear to be a highly specialized role for tracking people. However, MOT appears constrained by principles of object segmentation and grouping, where effectively grouped, coherent objects, but not necessarily biological objects, are tracked most successfully.