Distribution and Specificity of Helminths in Microtine Rodents: Evolutionary Implications

The taxonomic status of anoplocephaline cestodes of microtine rodents has been reviewed. Of the genus Andrya Railliet, 1883, five species are considered valid: A. macrocephala Douthitt, 1915; A. primordialis Douthitt, 1915; A. montana Kirshenblat, 1941 ; A. arctica Rausch, 1952; A. bairdi Schad, 1954. Of the genus Paranoplocephala Luehe, 1910, six species are regarded as valid: P. omphalodes (Hermann, 1783); P. blanchardi (Moniez, 1891); P. infrequens (Douthitt, 1915); P. variabilis (Douthitt, 1915); P. lemmi Rausch, 1952; P. neofibrinus Rausch, 1952. Andrya caucasica Kirshenblat, 1938, and A. bialowizensis Soltys, 1949, are regarded as synonyms of A. macrocephala. Paranoplocephala brevis Kirshenblat, 1938, is regarded as a synonym of P. infrequens. Three species, A. macrocephala, P. omphalodes, and P. infrequens, are holarctic in distribution, occurring mainly in species of Microtus. The uniformity of microtine rodents as hosts for various helminths has been discussed. It is concluded that Dicrostonyx is the most isolated genus from this standpoint, having two nematodes which have not been recorded from members of other genera, and harboring few helminths in common with others. This agrees with Hinton's conclusions, based on morphological characters of Dicrostonyx. From the present concept of Pleistocene glaciations, it is concluded that P. omphalodes and P. infrequens reached the St. Matthew Islands, in Bering Sea, as parasites of a vole from which Microtus abbreviatus has evolved. It appears that this vole arrived on these islands before North America was invaded, in the late Pleistocene, by the palearctic M. oeconomus and Clethrionomys rutilus,/i>. The present known distribution of P. omphalodes in North America corresponds about to that of M. oeconomus on the continent.

EVOLUTIONARY AESTHETICS AND SEXUAL SELECTION IN THE EVOLUTION OF ROCK ART AESTHETICS

This theoretical proposal applies evolutionary aesthetic, animal signalling and sexual selection to understand our artistic cognition, especially rock art aesthetics. Iconographic motifs, universally found in rock art, indicate which set of pre-artistic aesthetic psychological bias has been co-opted to catch the viewer`s attention. The co-evolutionary process of sexual selection could have shaped the design features of both rock art images and their aesthetic cognition by conferring mutual benefits on both producers, via manipulation, and receivers, via information extraction. We show some strategic techniques identified in rock art and art that indicate the occurrence of this co-evolution between producers and receivers.

Evolutionary Diversification of Banded Tube-Dwelling Anemones (Cnidaria; Ceriantharia; Isarachnanthus) in the Atlantic Ocean

The use of molecular data for species delimitation in Anthozoa is still a very delicate issue. This is probably due to the low genetic variation found among the molecular markers (primarily mitochondrial) commonly used for Anthozoa. Ceriantharia is an anthozoan group that has not been tested for genetic divergence at the species level. Recently, all three Atlantic species described for the genus Isarachnanthus of Atlantic Ocean, were deemed synonyms based on morphological simmilarities of only one species: Isarachnanthus maderensis. Here, we aimed to verify whether genetic relationships (using COI, 16S, ITS1 and ITS2 molecular markers) confirmed morphological affinities among members of Isarachnanthus from different regions across the Atlantic Ocean. Results from four DNA markers were completely congruent and revealed that two different species exist in the Atlantic Ocean. The low identification success and substantial overlap between intra and interspecific COI distances render the Anthozoa unsuitable for DNA barcoding, which is not true for Ceriantharia. In addition, genetic divergence within and between Ceriantharia species is more similar to that found in Medusozoa (Hydrozoa and Scyphozoa) than Anthozoa and Porifera that have divergence rates similar to typical metazoans. The two genetic species could also be separated based on micromorphological characteristics of their cnidomes. Using a specimen of Isarachnanthus bandanensis from Pacific Ocean as an outgroup, it was possible to estimate the minimum date of divergence between the clades. The cladogenesis event that formed the species of the Atlantic Ocean is estimated to have occured around 8.5 million years ago (Miocene) and several possible speciation scenarios are discussed.

A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data

In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a user-defined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Efficient Placement of Fault Indicators in an Actual Distribution System Using Evolutionary Computing

This paper proposes an evolutionary computing strategy to solve the problem of fault indicator (FI) placement in primary distribution feeders. More specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions on the main feeder of a real-life distribution system. Thus, the problem is modeled as one of optimization, aimed at improving the distribution reliability indices, while, at the same time, finding the least expensive solution. Based on actual data, the results confirm the efficiency of the GA approach to the FI placement problem.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

A complex networks approach for data clustering

This work proposes a method for data clustering based on complex networks theory. A data set is represented as a network by considering different metrics to establish the connection between each pair of objects. The clusters are obtained by taking into account five community detection algorithms. The network-based clustering approach is applied in two real-world databases and two sets of artificially generated data. The obtained results suggest that the exponential of the Minkowski distance is the most suitable metric to quantify the similarities between pairs of objects. In addition, the community identification method based on the greedy optimization provides the best cluster solution. We compare the network-based clustering approach with some traditional clustering algorithms and verify that it provides the lowest classification error rate. (C) 2012 Elsevier B.V. All rights reserved.

A novel linkage map of sugarcane with evidence for clustering of retrotransposon-based markers

Background: The development of sugarcane as a sustainable crop has unlimited applications. The crop is one of the most economically viable for renewable energy production, and CO2 balance. Linkage maps are valuable tools for understanding genetic and genomic organization, particularly in sugarcane due to its complex polyploid genome of multispecific origins. The overall objective of our study was to construct a novel sugarcane linkage map, compiling AFLP and EST-SSR markers, and to generate data on the distribution of markers anchored to sequences of scIvana_1, a complete sugarcane transposable element, and member of the Copia superfamily. Results: The mapping population parents ('IAC66-6' and 'TUC71-7') contributed equally to polymorphisms, independent of marker type, and generated markers that were distributed into nearly the same number of co-segregation groups (or CGs). Bi-parentally inherited alleles provided the integration of 19 CGs. The marker number per CG ranged from two to 39. The total map length was 4,843.19 cM, with a marker density of 8.87 cM. Markers were assembled into 92 CGs that ranged in length from 1.14 to 404.72 cM, with an estimated average length of 52.64 cM. The greatest distance between two adjacent markers was 48.25 cM. The scIvana_1-based markers (56) were positioned on 21 CGs, but were not regularly distributed. Interestingly, the distance between adjacent scIvana_1-based markers was less than 5 cM, and was observed on five CGs, suggesting a clustered organization. Conclusions: Results indicated the use of a NBS-profiling technique was efficient to develop retrotransposon-based markers in sugarcane. The simultaneous maximum-likelihood estimates of linkage and linkage phase based strategies confirmed the suitability of its approach to estimate linkage, and construct the linkage map. Interestingly, using our genetic data it was possible to calculate the number of retrotransposonscIvana_1 (similar to 60) copies in the sugarcane genome, confirming previously reported molecular results. In addition, this research possibly will have indirect implications in crop economics e. g., productivity enhancement via QTL studies, as the mapping population parents differ in response to an important fungal disease.

Multicentric Carpotarsal Osteolysis Is Caused by Mutations Clustering in the Amino-Terminal Transcriptional Activation Domain of MAFB

Multicentric carpotarsal osteolysis (MCTO) is a rare skeletal dysplasia characterized by aggressive osteolysis, particularly affecting the carpal and tarsal bones, and is frequently associated with progressive renal failure. Using exome capture and next-generation sequencing in five unrelated simplex cases of MCTO, we identified previously unreported missense mutations clustering within a 51 base pair region of the single exon of MAFB, validated by Sanger sequencing. A further six unrelated simplex cases with MCTO were also heterozygous for previously unreported mutations within this same region, as were affected members of two families with autosomal-dominant MCTO. MAFB encodes a transcription factor that negatively regulates RANKL-induced osteoclastogenesis and is essential for normal renal development. Identification of this gene paves the way for development of novel therapeutic approaches for this crippling disease and provides insight into normal bone and kidney development.

A survey of evolutionary algorithms for decision-tree induction

This paper presents a survey of evolutionary algorithms that are designed for decision-tree induction. In this context, most of the paper focuses on approaches that evolve decision trees as an alternate heuristics to the traditional top-down divide-and-conquer approach. Additionally, we present some alternative methods that make use of evolutionary algorithms to improve particular components of decision-tree classifiers. The paper's original contributions are the following. First, it provides an up-to-date overview that is fully focused on evolutionary algorithms and decision trees and does not concentrate on any specific evolutionary approach. Second, it provides a taxonomy, which addresses works that evolve decision trees and works that design decision-tree components by the use of evolutionary algorithms. Finally, a number of references are provided that describe applications of evolutionary algorithms for decision-tree induction in different domains. At the end of this paper, we address some important issues and open questions that can be the subject of future research.

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

A model to explain spermatophore implantation in cephalopods (Mollusca: Cephalopoda) and a discussion on its evolutionary origins and significance

Male coleoid cephalopods produce spermatophores that can attach autonomously on the female's body during a complex process of evagination called the spermatophoric reaction, during which the ejaculatory apparatus and spiral filament of the spermatophore are everted and exposed to the external milieu. In some deepwater cephalopods, the reaction leads to the intradermal implantation of the spermatophore, a hitherto enigmatic phenomenon. The present study builds upon several lines of evidence to propose that spermatophore implantation is probably achieved through the combination of (1) an evaginating-tube mechanism performed by the everting ejaculatory apparatus and (2) the anchorage provided by the spiral filament's stellate particles. The proposed theoretical model assumes that, as it is exposed to the external milieu, each whorl of the spiral filament anchors to the surrounding tissue by means of its sharp stellate particles. As the ejaculatory apparatus tip continues evaginating, it grows in diameter and stretches lengthwise, enlarging the diameter of the whorl and propelling it, consequently tearing and pushing the anchored tissue outward and backward, and opening space for the next whorl to attach. After the ejaculatory apparatus has been everted and has perforated tissue, the cement body is extruded, possibly aiding in final attachment, and the sperm mass comes to lie inside the female tissue, encompassed by the everted ejaculatory apparatus tube. It is proposed that this unique, efficient spermatophore attachment mechanism possibly evolved in intimate relationship with the adoption of an active mode of life by coleoids. The possible roles of predation pressure and sperm competition in the evolution of this mechanism are also discussed. (c) 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 105, 711726.

The Ecological Basis for Biogeographic Classification: an Example in Orchid Bees (Apidae: Euglossini)

Biogeography has been difficult to apply as a methodological approach because organismic biology is incomplete at levels where the process of formulating comparisons and analogies is complex. The study of insect biogeography became necessary because insects possess numerous evolutionary traits and play an important role as pollinators. Among insects, the euglossine bees, or orchid bees, attract interest because the study of their biology allows us to explain important steps in the evolution of social behavior and many other adaptive tradeoffs. We analyzed the distribution of morphological characteristics in Colombian orchid bees from an ecological perspective. The aim of this study was to observe the distribution of these attributes on a regional basis. Data corresponding to Colombian euglossine species were ordered with a correspondence analysis and with subsequent hierarchical clustering. Later, and based on community proprieties, we compared the resulting hierarchical model with the collection localities to seek to identify a biogeographic classification pattern. From this analysis, we derived a model that classifies the territory of Colombia into 11 biogeographic units or natural clusters. Ecological assumptions in concordance with the derived classification levels suggest that species characteristics associated with flight performance, nectar uptake, and social behavior are the factors that served to produce the current geographical structure.

Evolutionary history of exon shuffling

Exon shuffling has been characterized as one of the major evolutionary forces shaping both the genome and the proteome of eukaryotes. This mechanism was particularly important in the creation of multidomain proteins during animal evolution, bringing a number of functional genetic novelties. Here, genome information from a variety of eukaryotic species was used to address several issues related to the evolutionary history of exon shuffling. By comparing all protein sequences within each species, we were able to characterize exon shuffling signatures throughout metazoans. Intron phase (the position of the intron regarding the codon) and exon symmetry (the pattern of flanking introns for a given exon or block of adjacent exons) were features used to evaluate exon shuffling. We confirmed previous observations that exon shuffling mediated by phase 1 introns (1-1 exon shuffling) is the predominant kind in multicellular animals. Evidence is provided that such pattern was achieved since the early steps of animal evolution, supported by a detectable presence of 1-1 shuffling units in Trichoplax adhaerens and a considerable prevalence of them in Nematostella vectensis. In contrast, Monosiga brevicollis, one of the closest relatives of metazoans, and Arabidopsis thaliana, showed no evidence of 1-1 exon or domain shuffling above what it would be expected by chance. Instead, exon shuffling events are less abundant and predominantly mediated by phase 0 introns (0-0 exon shuffling) in those non-metazoan species. Moreover, an intermediate pattern of 1-1 and 0-0 exon shuffling was observed for the placozoan T. adhaerens, a primitive animal. Finally, characterization of flanking intron phases around domain borders allowed us to identify a common set of symmetric 1-1 domains that have been shuffled throughout the metazoan lineage.