AMP-activated protein kinase plays an important evolutionary conserved role in the regulation of glucose metabolism in fish skeletal muscle cells

AMPK, a master metabolic switch, mediates the observed increase of glucose uptake in locomotory muscle of mammals during exercise. AMPK is activated by changes in the intracellular AMP:ATP ratio when ATP consumption is stimulated by contractile activity but also by AICAR and metformin, compounds that increase glucose transport in mammalian muscle cells. However, the possible role of AMPK in the regulation of glucose metabolism in skeletal muscle has not been investigated in other vertebrates, including fish. In this study, we investigated the effects of AMPK activators on glucose uptake, AMPK activity, cell surface levels of trout GLUT4 and expression of GLUT1 and GLUT4 as well as the expression of enzymes regulating glucose disposal and PGC1α in trout myotubes derived from a primary muscle cell culture. We show that AICAR and metformin significantly stimulated glucose uptake (1.6 and 1.3 fold, respectively) and that Compound C completely abrogated the stimulatory effects of the AMPK activators on glucose uptake. The combination of insulin and AMPK activators did not result in additive nor synergistic effects on glucose uptake. Moreover, exposure of trout myotubes to AICAR and metformin resulted in an increase in AMPK activity (3.8 and 3 fold, respectively). We also provide evidence suggesting that stimulation of glucose uptake by AMPK activators in trout myotubes may take place, at least in part, by increasing the cell surface and mRNA levels of trout GLUT4. Finally, AICAR increased the mRNA levels of genes involved in glucose disposal (hexokinase, 6-phosphofructokinase, pyruvate kinase and citrate synthase) and mitochondrial biogenesis (PGC-1α) and did not affect glycogen content or glycogen synthase mRNA levels in trout myotubes. Therefore, we provide evidence, for the first time in non-mammalian vertebrates, suggesting a potentially important role of AMPK in stimulating glucose uptake and utilization in the skeletal muscle of fish.

Question Waves: A multicast query routing algorithm for social search

This paper describes Question Waves, an algorithm that can be applied to social search protocols, such as Asknext or Sixearch. In this model, the queries are propagated through the social network, with faster propagation through more trustable acquaintances. Question Waves uses local information to make decisions and obtain an answer ranking. With Question Waves, the answers that arrive first are the most likely to be relevant, and we computed the correlation of answer relevance with the order of arrival to demonstrate this result. We obtained correlations equivalent to the heuristics that use global knowledge, such as profile similarity among users or the expertise value of an agent. Because Question Waves is compatible with the social search protocol Asknext, it is possible to stop a search when enough relevant answers have been found; additionally, stopping the search early only introduces a minimal risk of not obtaining the best possible answer. Furthermore, Question Waves does not require a re-ranking algorithm because the results arrive sorted

Functional and evolutionary analysis of DXL1, a non-essential gene encoding a 1-deoxy-D-xylulose 5-phosphate synthase like protein in Arabidopsis thaliana

The synthesis of 1-deoxy-D-xylulose 5-phosphate (DXP), catalyzed by the enzyme DXP synthase (DXS), represents a key regulatory step of the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway for isoprenoid biosynthesis. In plants DXS is encoded by small multigene families that can be classified into, at least, three specialized subfamilies. Arabidopsis thaliana contains three genes encoding proteins with similarity to DXS, including the well-known DXS1/CLA1 gene, which clusters within subfamily I. The remaining proteins, initially named DXS2 and DXS3, have not yet been characterized. Here we report the expression and functional analysis of A. thaliana DXS2. Unexpectedly, the expression of DXS2 failed to rescue Escherichia coli and A. thaliana mutants defective in DXS activity. Coherently, we found that DXS activity was negligible in vitro, being renamed as DXL1 following recent nomenclature recommendation. DXL1 is targeted to plastids as DXS1, but shows a distinct expression pattern. The phenotypic analysis of a DXL1 defective mutant revealed that the function of the encoded protein is not essential for growth and development. Evolutionary analyses indicated that DXL1 emerged from DXS1 through a recent duplication apparently specific of the Brassicaceae lineage. Divergent selective constraints would have affected a significant fraction of sites after diversification of the paralogues. Furthermore, amino acids subjected to divergent selection and likely critical for functional divergence through the acquisition of a novel, although not yet known, biochemical function, were identified. Our results provide with the first evidences of functional specialization at both the regulatory and biochemical level within the plant DXS family.

Complex patterns of global spread in invasive insects: eco-evolutionary and management consequences

The advent of simple and affordable tools for molecular identification of novel insect invaders and assessment of population diversity has changed the face of invasion biology in recent years. The widespread application of these tools has brought with it an emerging understanding that patterns in biogeography, introduction history and subsequent movement and spread of many invasive alien insects are far more complex than previously thought. We reviewed the literature and found that for a number of invasive insects, there is strong and growing evidence that multiple introductions, complex global movement, and population admixture in the invaded range are commonplace. Additionally, historical paradigms related to species and strain identities and origins of common invaders are in many cases being challenged. This has major consequences for our understanding of basic biology and ecology of invasive insects and impacts quarantine, management and biocontrol programs. In addition, we found that founder effects rarely limit fitness in invasive insects and may benefit populations (by purging harmful alleles or increasing additive genetic variance). Also, while phenotypic plasticity appears important post-establishment, genetic diversity in invasive insects is often higher than expected and increases over time via multiple introductions. Further, connectivity among disjunct regions of global invasive ranges is generally far higher than expected and is often asymmetric, with some populations contributing disproportionately to global spread. We argue that the role of connectivity in driving the ecology and evolution of introduced species with multiple invasive ranges has been historically underestimated and that such species are often best understood in a global context.

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Evolutionary Ecology of Mountain Birch in Subarctic Stress Gradients: Interplay of Biotic and Abiotic Factors in Plant-Plant Interactions and Evolutionary Processes

In nature, variation for example in herbivory, wind exposure, moisture and pollution impact often creates variation in physiological stress and plant productivity. This variation is seldom clear-cut, but rather results in clines of decreasing growth and productivity towards the high-stress end. These clines of unidirectionally changing stress are generally known as ‘stress gradients’. Through its effect on plant performance, stress has the capacity to fundamentally alter the ecological relationships between individuals, and through variation in survival and reproduction it also causes evolutionary change, i.e. local adaptations to stress and eventually speciation. In certain conditions local adaptations to environmental stress have been documented in a matter of just a few generations. In plant-plant interactions, intensities of both negative interactions (competition) and positive ones (facilitation) are expected to vary along stress gradients. The stress-gradient hypothesis (SGH) suggests that net facilitation will be strongest in conditions of high biotic and abiotic stress, while a more recent ‘humpback’ model predicts strongest net facilitation at intermediate levels of stress. Plant interactions on stress gradients, however, are affected by a multitude of confounding factors, making studies of facilitation-related theories challenging. Among these factors are plant ontogeny, spatial scale, and local adaptation to stress. The last of these has very rarely been included in facilitation studies, despite the potential co-occurrence of local adaptations and changes in net facilitation in stress gradients. Current theory would predict both competitive effects and facilitative responses to be weakest in populations locally adapted to withstand high abiotic stress. This thesis is based on six experiments, conducted both in greenhouses and in the field in Russia, Norway and Finland, with mountain birch (Betula pubescens subsp. czerepanovii) as the model species. The aims were to study potential local adaptations in multiple stress gradients (both natural and anthropogenic), changes in plant-plant interactions under conditions of varying stress (as predicted by SGH), potential mechanisms behind intraspecific facilitation, and factors confounding plant-plant facilitation, such as spatiotemporal, ontogenetic, and genetic differences. I found rapid evolutionary adaptations (occurring within a time-span of 60 to 70 years) towards heavy-metal resistance around two copper-nickel smelters, a phenomenon that has resulted in a trade-off of decreased performance in pristine conditions. Heavy-metal-adapted individuals had lowered nickel uptake, indicating a possible mechanism behind the detected resistance. Seedlings adapted to heavy-metal toxicity were not co-resistant to others forms of abiotic stress, but showed co-resistance to biotic stress by being consumed to a lesser extent by insect herbivores. Conversely, populations from conditions of high natural stress (wind, drought etc.) showed no local adaptations, despite much longer evolutionary time scales. Due to decreasing emissions, I was unable to test SGH in the pollution gradients. In natural stress gradients, however, plant performance was in accordance with SGH, with the strongest host-seedling facilitation found at the high-stress sites in two different stress gradients. Factors confounding this pattern included (1) plant size / ontogenetic status, with seedling-seedling interactions being competition dominated and host-seedling interactions potentially switching towards competition with seedling growth, and (2) spatial distance, with competition dominating at very short planting distances, and facilitation being strongest at a distance of circa ¼ benefactor height. I found no evidence for changes in facilitation with respect to the evolutionary histories of plant populations. Despite the support for SGH, it may be that the ‘humpback’ model is more relevant when the main stressor is resource-related, while what I studied were the effects of ‘non-resource’ stressors (i.e. heavy-metal pollution and wind). The results have potential practical applications: the utilisation of locally adapted seedlings and plant facilitation may increase the success of future restoration efforts in industrial barrens as well as in other wind-exposed sites. The findings also have implications with regard to the effects of global change in subarctic environments: the documented potential by mountain birch for rapid evolutionary change, together with the general lack of evolutionary ‘dead ends’, due to not (over)specialising to current natural conditions, increase the chances of this crucial forest-forming tree persisting even under the anticipated climate change.

Shout and Act: an Algorithm for Digital Objects Preservation Inspired from Rescue Robots

We adapt the Shout and Act algorithm to Digital Objects Preservation where agents explore file systems looking for digital objects to be preserved (victims). When they find something they “shout” so that agent mates can hear it. The louder the shout, the urgent or most important the finding is. Louder shouts can also refer to closeness. We perform several experiments to show that this system works very scalably, showing that heterogeneous teams of agents outperform homogeneous ones over a wide range of tasks complexity. The target at-risk documents are MS Office documents (including an RTF file) with Excel content or in Excel format. Thus, an interesting conclusion from the experiments is that fewer heterogeneous (varying skills) agents can equal the performance of many homogeneous (combined super-skilled) agents, implying significant performance increases with lower overall cost growth. Our results impact the design of Digital Objects Preservation teams: a properly designed combination of heterogeneous teams is cheaper and more scalable when confronted with uncertain maps of digital objects that need to be preserved. A cost pyramid is proposed for engineers to use for modeling the most effective agent combinations

An energy efficient vertical handover decision algorithm

As wireless communications evolve towards heterogeneousnetworks, mobile terminals have been enabled tohandover seamlessly from one network to another. At the sametime, the continuous increase in the terminal power consumptionhas resulted in an ever-decreasing battery lifetime. To that end,the network selection is expected to play a key role on howto minimize the energy consumption, and thus to extend theterminal lifetime. Hitherto, terminals select the network thatprovides the highest received power. However, it has been provedthat this solution does not provide the highest energy efficiency.Thus, this paper proposes an energy efficient vertical handoveralgorithm that selects the most energy efficient network thatminimizes the uplink power consumption. The performance of theproposed algorithm is evaluated through extensive simulationsand it is shown to achieve high energy efficiency gains comparedto the conventional approach.

Evolutionary analysis of mitogenomes from parasitic and free-living flatworms

Mitochondrial genomes (mitogenomes) are useful and relatively accessible sources of molecular data to explore and understand the evolutionary history and relationships of eukaryotic organisms across diverse taxonomic levels. The availability of complete mitogenomes from Platyhelminthes is limited; of the 40 or so published most are from parasitic flatworms (Neodermata). Here, we present the mitogenomes of two free-living flatworms (Tricladida): the complete genome of the freshwater species Crenobia alpina (Planariidae) and a nearly complete genome of the land planarian Obama sp. (Geoplanidae). Moreover, we have reanotated the published mitogenome of the species Dugesia japonica (Dugesiidae). This contribution almost doubles the total number of mtDNAs published for Tricladida, a species-rich group including model organisms and economically important invasive species. We took the opportunity to conduct comparative mitogenomic analyses between available free-living and selected parasitic flatworms in order to gain insights into the putative effect of life cycle on nucleotide composition through mutation and natural selection. Unexpectedly, we did not find any molecular hallmark of a selective relaxation in mitogenomes of parasitic flatworms; on the contrary, three out of the four studied free-living triclad mitogenomes exhibit higher A+T content and selective relaxation levels. Additionally, we provide new and valuable molecular data to develop markers for future phylogenetic studies on planariids and geoplanids.

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

Lautanauhaohjeen muodostus tavoitekuviosta geneettisellä algoritmilla

Lautanauhatekniikka on monipuolinen menetelmä esimerkiksi kuvioitujen nauhojen kutomiseen, mutta uusien kuvioaiheiden suunnittelu, tai aloittelijalle jo valmiiden ohjeettomien kuviomallien jäljittely, voi helposti käydä työlääksi menetelmän ominaispiirteiden johdosta. Tämän työn tavoitteena oli kehittää ohjelmallinen työkalu auttamaan näissä ongelmissa automatisoimalla kudontaohjeen etsintä käyttäjän laatimalle tavoitekuviolle. Ratkaisumenetelmän perustaksi valittiin geneettinen algoritmi, minkä johdosta työn keskeisintutkimusongelma oli kartoittaa algoritmin perusoperaatioiden parametrien ja tavoitekuvion kompleksisuuden keskinäisiä riippuvuuksia riittävästi toimivien arvosuositusten antamiseen ohjelman tulevassa käytännön käytössä. Työssä ei kehitetty sovellusalueeseen mukautettuja evoluutiooperaatioita, vaan keskityttiin luomaan hyvin tunnetuista elementeistä perusta, jota voi myöhemmin kehittää eteenpäin.

Brain size and evolutionary diversification in birds

The role of behavior in evolution remains controversial, despite that some ideas are over 100 years old. Changes in behavior are generally believed to enhance evolution by exposing individuals to new selective pressures and by facilitating range expansions. However, this hypothesis lacks firm empirical evidence. Moreover, behavioral changes can also inhibit evolution by hiding heritable variation from natural selection. Taking advantage of the complete phylogeny of extant birds, a new species-level measure of past diversification rate and the best existing measures of brain size (n = 1326 species), I show here that relative brain size is associated (albeit weakly) with diversification rates. Assuming that brain relative size reflects behavioral flexibility, an assumption well-supported by evidence, this finding supports the idea that behavior can enhance evolutionary diversification. This view is further supported by the discovery that the most important factor influencing diversification rates is ecological generalism, which is believed to require behavioral flexibility. Thus, behavioral changes that expose animals to a variety of environments can have played an important role in the evolution of birds.

Analysis of metabolites from plants of the Swartzia genus using chemical indexes: evolutionary tendencies

The chemical indexes, suggested by Gottlieb et al., have not been used before regarding evolutionary tendency of species in the Swartzia genus. However, the importance of this work encouraged for an analysis of the Swartzia genus using the metabolites isolated from nine species. The analysis, based on calculated chemical indexes, provided an evolutionary tendency for these plants, which correlates with the classification based on morphological analysis.