How Can Dolphins Recognize Fish According to Their Echoes? A Statistical Analysis of Fish Echoes

Echo-based object classification is a fundamental task of animals that use a biosonar system. Dolphins and porpoises should be able to rely on echoes to discriminate a predator from a prey or to select a desired prey from an undesired object. Many studies have shown that dolphins and porpoises can discriminate between objects according to their echoes. All of these studies however, used unnatural objects that can be easily characterized in human terminologies (e.g., metallic spheres, disks, cylinders). In this work, we collected real fish echoes from many angles of acquisition using a sonar system that mimics the emission properties of dolphins and porpoises. We then tested two alternative statistical approaches in classifying these echoes. Our results suggest that fish species can be classified according to echoes returning from porpoise- and dolphin-like signals. These results suggest how dolphins and porpoises can classify fish based on their echoes and provide some insight as to which features might enable the classification.     

How Many Nucleotides Are Required to Resolve a Phylogenetic Problem? The Use of a New Statistical Method Applicable to Available Sequences

The evolution of bootstrap proportions (BP) with sequence length was studied using a 28S ribosomal RNA data set. For different sequence lengths, informative sites were jackknifed several times. Bootstrapping was subsequently performed on each of these subsamples. For each node, BPs so obtained were plotted against sequence length, showing the evolution of the robustness with increasing number of informative sites. For robust nodes (BP of 100%), the pattern of BPs is unvarying and is described by a simple function BP = 100(1− e^{−b(x − x′)}), where x is the number of informative sites and b and x′ are two parameters estimated using a nonlinear regression procedure. When a node has a BP <100% and the pattern of BPs fits this function, it is possible to estimate the number of informative sites required to obtain a given average BP. The method also identifies nonrobust nodes (nonascending clusters of BP dots), for which it seems to be more cost effective and fruitful to turn to other species and/or genes rather than to continue sequencing longer gene lengths from the same species to reach a BP of 95%.     

ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations

Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs–ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates.     

Deep Imaging: How Much of the Proteome Does Current Top-Down Technology Already Resolve?

Effective proteome analyses are based on interplay between resolution and detection. It had been claimed that resolution was the main factor limiting the use of two-dimensional gel electrophoresis. Improved protein detection now indicates that this is unlikely to be the case. Using a highly refined protocol, the rat brain proteome was extracted, resolved, and detected. In order to overcome the stain saturation threshold, high abundance protein species were excised from the gel following standard imaging. Gels were then imaged again using longer exposure times, enabling detection of lower abundance, less intensely stained protein species. This resulted in a significant enhancement in the detection of resolved proteins, and a slightly modified digestion protocol enabled effective identification by standard mass spectrometric methods. The data indicate that the resolution required for comprehensive proteome analyses is already available, can assess multiple samples in parallel, and preserve critical information concerning post-translational modifications. Further optimization of staining and detection methods promises additional improvements to this economical, widely accessible and effective top-down approach to proteome analysis.     

Prevalence of Endosymbionts in Bemisia tabaci Populations and Their In Vivo Sensitivity to Antibiotics

Bemisia tabaci can harbor both primary and secondary endosymbionts, and the specific endosymbionts can differ among different B. tabaci biotypes. This study determined (1) the prevalence of the primary endosymbiont Portiera aleyrodidarum and secondary endosymbionts Arsenophonus and Wolbachia in two invasive biotypes (B and Q) and one indigenous biotype (Cv) in China and (2) the in vivo effect of three antibiotics (tetracycline, ampicillin trihydrate, and rifampicin) against the endosymbionts; if an antibiotic substantially inhibits an endosymbiont, it could be used to determine the effect of that endosymbiont on B. tabaci. P. aleyrodidarum and Wolbachia were detected in all the three biotypes, while Arsenophonus was found only in the Q and Cv biotypes. P. aleyrodidarum was found in all tested individuals of the three biotypes. Infection rates of Wolbachia in the B, Cv, and Q biotypes were 58, 68, and 48%, respectively. The infection rate of Arsenophonus was 44% in the Q biotype but only 22% in the Cv biotype. The antibiotics failed to eliminate P. aleyrodidarum from any individual of the B, Cv, and Q biotypes but eliminated the secondary endosymbionts, Arsenophonus and Wolbachia, from 50 to 80% of the adult B. tabaci. The effect of the antibiotics depended on the species of endosymbiont, the antibiotic, the B. tabaci biotype, and various interactions between these factors. When used against Arsenophonus, the efficiency of rifampicin was better than ampicillin and tetracycline, regardless of B. tabaci biotype. When inactivating Wolbachia in Cv and Q biotypes, the efficiency tetracycline was better than ampicillin and rifampicin, and while the efficiency of tetracycline was better than rifampicin and ampicillin when they were used against Wolbachia in B biotype.     

Analysis of multi-decadal wetland changes,and cumulative impact of multiple storms 1984 to 2017

Land-cover classification analysis using Landsat satellite imagery acquired between 1984 and 2017 quantified short- (post-Hurricane Sandy) and long-term wetland-change trends along the Maryland and Virginia coasts between Metompkin Bay, VA and Ocean City, MD. Although there are limited options for upland migration of wetlands in the study area, regression analysis showed that wetland area increased slightly between 1984 and 2011, indicating that marsh aggradation rates were sufficient to maintain wetland elevation relative to mean sea level. Following Hurricane Irene (August 2011), the Halloween Nor’Easter (October 2011), and Hurricane Sandy (October 2012), wetland area decreased by more than 7 km² compared with average pre-storm extents. We assume that Hurricane Sandy had the greatest impact due to the size and intensity of the storm. However, the cumulative effects of multiple storms within a short time period likely contributed to the greater observed losses in coastal wetlands relative to earlier periods. Five years after Hurricane Sandy, wetland area had not significantly recovered, but more time may be necessary to assess if the observed wetland losses will persist or if new growth within flooded marsh areas will be sufficient for the wetlands to recover to pre-storm extents. Comparisons of long-term and storm-driven wetland changes can lead to improved accuracy of habitat vulnerability models and greater understanding of potential impacts of future storms and SLR to coastal wetlands.     

The “Intrinsic” Thermal Conductivity of Some Wet Proteins in Relation to Their Hydrophobicity: Analysis on Gelatin Gel

Since the intrinsic thermal conductivity of protein cannot be measured directly, the apparent “intrinsic” thermal conductivity of gelatin was estimated on the basis of the most suitable heat conduction model. Among four models of heat conduction through heterogeneous material, the series layers model best described the experimental results for frozen gelatin gels of different concentrations. Then, the “intrinsic” thermal conductivity of frozen wet gelatin was estimated to be 0.61 [W/m·°C]. The “intrinsic” thermal conductivity of unfrozen wet gelatin was estimated on the basis of Filippov’s equation to be 0.38 [W/m·°C], since the unfrozen gelating gel seemed to be as homogeneous as the solution.     

Phylogenetic Analysis: How Old are the Parts of Your Body?

According to the National Academy of Sciences, biology students in the USA are not being adequately prepared for successful futures. Of paramount concern is a lack of sufficient training in quantitative and computational skills, which are needed to compete effectively for an array of educational and occupational opportunities. In this paper, we introduce a classroom exercise that invites students to solve a simple biological problem and illustrates the need for a computer-assisted strategy to arrive at a solution. The exercise invites students to consider the question “How old are the parts of your body?” Some features of the human body are more ancient than others. For example, our bodies have both hair and backbones, but backbones arose much earlier in evolutionary history. Our exercise relies upon MEGA 4.0, a free, visually appealing, and intuitive computer program that allows students to gather DNA or protein sequences from electronic databases, then use them to infer phylogenetic trees. Student-inferred phylogenies are used to explore the relative order in which diverse aspects of the human form evolved. In the process, students are trained to use powerful features of MEGA and encouraged through group discussion to consider additional applications of the technology they have learned. Our lesson plan includes a brief video, a web site with essential terminology and links for further exploration, a hands-on experience using MEGA, and a follow-up discussion.     

A Statistical Test of Network Analysis: Can it Detect Differences in Food Web Properties?

Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a statistical evaluation of ENA is lacking. The major objectives of this study, therefore, were to evaluate statistically the effectiveness of ENA in detecting differences in food web properties and to compare ENA output with established community level indices. Quantitative trophic networks (n = 12) representing four high salt marsh ponds during three times (corresponding to low stress, high stress, and post-disturbance) were constructed from an extensive field sampling program augmented by literature values. Food webs of salt marsh ponds were used because these systems contain relatively simple food webs, have well defined boundaries, and allow for adequate replication. A null hypothesis was tested to determine how values of 12 indices from ENA output differed among the three stress/disturbance conditions (H _o: low stress = high stress = post-disturbance). Results of both ANOVA and Friedman’s tests indicated most ENA indices were significantly different among the three stress/disturbance conditions. The amount of covariance among the indices was relatively low (7 of 66 were significant). Results were compared to differences in community indices (richness, evenness, and diversity) among the three stress/disturbance conditions. ENA output identified differences beyond those recognized by the community indices. Overall, networks were unique enough under different environmental conditions to provide statistically significant differences in ENA results. Our findings are supportive of the use of carefully constructed networks in food web analysis and for decision making in ecosystem-based management. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613–621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. In particular, we examine the conditions under which stable spatial patterns can emerge with this model, focusing on the influence of mechanical stimuli and the interplay of non-local phenomena. To this end, we have performed a linear stability analysis and numerical simulations based on a mixed finite element formulation, which have allowed us to study the dynamical behaviour of the system in terms of the qualitative shape of the dispersion relation. We show that the consideration of mechanotaxis, namely changes in migration speeds and directions in response to mechanical stimuli alters the conditions for pattern formation in a singular manner. Furthermore without non-local effects, responses to mechanical stimuli are observed to result in dispersion relations with positive growth rates at arbitrarily large wavenumbers, in turn yielding heterogeneity at the cellular level in model predictions. This highlights the sensitivity and necessity of non-local effects in mechanically influenced biological pattern formation models and the ultimate failure of the continuum approximation in their absence.     

How Close Do We Live to Water? A Global Analysis of Population Distance to Freshwater Bodies

Traditionally, people have inhabited places with ready access to fresh water. Today, over 50% of the global population lives in urban areas, and water can be directed via tens of kilometres of pipelines. Still, however, a large part of the world''s population is directly dependent on access to natural freshwater sources. So how are inhabited places related to the location of freshwater bodies today? We present a high-resolution global analysis of how close present-day populations live to surface freshwater. We aim to increase the understanding of the relationship between inhabited places, distance to surface freshwater bodies, and climatic characteristics in different climate zones and administrative regions. Our results show that over 50% of the world''s population lives closer than 3 km to a surface freshwater body, and only 10% of the population lives further than 10 km away. There are, however, remarkable differences between administrative regions and climatic zones. Populations in Australia, Asia, and Europe live closest to water. Although populations in arid zones live furthest away from freshwater bodies in absolute terms, relatively speaking they live closest to water considering the limited number of freshwater bodies in those areas. Population distributions in arid zones show statistically significant relationships with a combination of climatic factors and distance to water, whilst in other zones there is no statistically significant relationship with distance to water. Global studies on development and climate adaptation can benefit from an improved understanding of these relationships between human populations and the distance to fresh water.     

Carbohydrate and Protein-based Inhibitors of Porcine Pancreatic α-Amylase: Structure Analysis and Comparison of Their Binding Characteristics

The crystal structures of porcine pancreatic α-amylase isozyme II (PPA II) in its free form and complexed with the trestatin A derived pseudo-octasaccharide V-1532 have been determined using Patterson search techniques at resolutions of 2.3 and 2.2 Å, respectively. Seven rings of the competitive inhibitor V-1532 could be detected in the active site region as well as two maltose units in secondary binding sites on the surface.V-1532 occupies the five central sugar binding subsites similar to the PPA/acarbose structure. A sixth ring exists at the reducing end, connecting two symmetry related PPA molecules. The seventh moiety, a 6-hydroxymethylconduritol ring, is located at the non-reducing end. The electron density for this ring is relatively weak, indicating considerable disorder.This study shows that PPA is able to accommodate more than five rings in the active site region, but that additional rings would increase the binding affinity only slightly, which is in accordance with kinetic experiments.A comparison of the structures of free PPA, PPA/V-1532 and PPA/Tendamistat shows the characteristic conformational changes that accompany inhibitor binding and distinguish pseudo-oligosaccharide inhibitors from proteinaceous inhibitors. Although both classes of inhibitors block the sugar binding subsites in the active site region, the extreme specificity and binding affinity of the proteinaceous inhibitors is probably due to an intricate interaction pattern involving areas further away from the catalytic center.     

Genetic Analysis of Resistance to Benzimidazoles in Physarum: Differential Expression of β-Tubulin Genes

Physarum displays two vegetative cell types, uninucleate myxamoebae and multinucleate plasmodia. Mutant myxamoebae of Physarum resistant to the antitubulin drug methylbenzimidazole-2-yl-carbamate (MBC) were isolated. All mutants tested were cross-resistant to other benzimidazoles but not to cycloheximide or emetine. Genetic analysis showed that mutation to MBC resistance can occur at any one of four unlinked loci, benA, benB, benC or benD. MBC resistance of benB and benD mutants was expressed in plasmodia, but benA and benC mutant plasmodia were MBC sensitive, suggesting that benA and benC encode myxamoeba-specific products. Myxamoebae carrying the recessive benD210 mutation express a β-tubulin with noval electrophoretic mobility, in addition to a β-tubulin with wild-type mobility. This and other evidence indicates that benD is a structural gene for β-tubulin, and that at least two β-tubulin genes are expressed in myxamoebae. Comparisons of the β-tubulins of wildtype and benD210 strains by gel electrophoresis revealed that, of the three (or more) β-tubulin genes expressed in Physarum, one, benD, is expressed in both myxamoebae and plasmodia, one is expressed specifically in myxamoebae and one is expressed specifically in plasmodia. However, mutation in only one gene, benD, is sufficient to confer MBC resistance on both myxamoebae and plasmodia.     

Response of Tumor Spheroids to Radiation: Modeling and Parameter Estimation

We propose a spatially distributed continuous model for the spheroid response to radiation, in which the oxygen distribution is represented by means of a diffusion-consumption equation and the radiosensitivity parameters depend on the oxygen concentration. The induction of lethally damaged cells by a pulse of radiation, their death, and the degradation of dead cells are included. The compartments of lethally damaged cells and of dead cells are subdivided into different subcompartments to simulate the delays that occur in cell death and cell degradation, with a gain in model flexibility. It is shown that, for a single irradiation and under the hypothesis of a sufficiently small spheroid radius, the model can be reformulated as a linear stationary ordinary differential equation system. For this system, the parameter identifiability has been investigated, showing that the set of unknown parameters can be univocally identified by exploiting the response of the model to at least two different radiation doses. Experimental data from spheroids originated from different cell lines are used to identify the unknown parameters and to test the predictive capability of the model with satisfactory results.