Probing microwave fields and enabling in-situ experiments in a transmission electron microscope.

A technique is presented whereby the performance of a microwave device is evaluated by mapping local field distributions using Lorentz transmission electron microscopy (L-TEM). We demonstrate the method by measuring the polarisation state of the electromagnetic fields produced by a microstrip waveguide as a function of its gigahertz operating frequency. The forward and backward propagating electromagnetic fields produced by the waveguide, in a specimen-free experiment, exert Lorentz forces on the propagating electron beam. Importantly, in addition to the mapping of dynamic fields, this novel method allows detection of effects of microwave fields on specimens, such as observing ferromagnetic materials at resonance

Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?

The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed

Pre-Bilaterian Origins of the Hox Cluster and the Hox Code: Evidence from the Sea Anemone, Nematostella vectensis

BACKGROUND: Hox genes were critical to many morphological innovations of bilaterian animals. However, early Hox evolution remains obscure. Phylogenetic, developmental, and genomic analyses on the cnidarian sea anemone Nematostella vectensis challenge recent claims that the Hox code is a bilaterian invention and that no “true” Hox genes exist in the phylum Cnidaria. METHODOLOGY/PRINCIPAL FINDINGS: Phylogenetic analyses of 18 Hox-related genes from Nematostella identify putative Hox1, Hox2, and Hox9+ genes. Statistical comparisons among competing hypotheses bolster these findings, including an explicit consideration of the gene losses implied by alternate topologies. In situ hybridization studies of 20 Hox-related genes reveal that multiple Hox genes are expressed in distinct regions along the primary body axis, supporting the existence of a pre-bilaterian Hox code. Additionally, several Hox genes are expressed in nested domains along the secondary body axis, suggesting a role in “dorsoventral” patterning. CONCLUSIONS/SIGNIFICANCE: A cluster of anterior and posterior Hox genes, as well as ParaHox cluster of genes evolved prior to the cnidarian-bilaterian split. There is evidence to suggest that these clusters were formed from a series of tandem gene duplication events and played a role in patterning both the primary and secondary body axes in a bilaterally symmetrical common ancestor. Cnidarians and bilaterians shared a common ancestor some 570 to 700 million years ago, and as such, are derived from a common body plan. Our work reveals several conserved genetic components that are found in both of these diverse lineages. This finding is consistent with the hypothesis that a set of developmental rules established in the common ancestor of cnidarians and bilaterians is still at work today

Genome Sequence of the Pea Aphid Acyrthosiphon pisum

Aphids are important agricultural pests and also biological models for studies of insect-plant interactions, symbiosis, virus vectoring, and the developmental causes of extreme phenotypic plasticity. Here we present the 464 Mb draft genome assembly of the pea aphid Acyrthosiphon pisum. This first published whole genome sequence of a basal hemimetabolous insect provides an outgroup to the multiple published genomes of holometabolous insects. Pea aphids are host-plant specialists, they can reproduce both sexually and asexually, and they have coevolved with an obligate bacterial symbiont. Here we highlight findings from whole genome analysis that may be related to these unusual biological features. These findings include discovery of extensive gene duplication in more than 2000 gene families as well as loss of evolutionarily conserved genes. Gene family expansions relative to other published genomes include genes involved in chromatin modification, miRNA synthesis, and sugar transport. Gene losses include genes central to the IMD immune pathway, selenoprotein utilization, purine salvage, and the entire urea cycle. The pea aphid genome reveals that only a limited number of genes have been acquired from bacteria; thus the reduced gene count of Buchnera does not reflect gene transfer to the host genome. The inventory of metabolic genes in the pea aphid genome suggests that there is extensive metabolite exchange between the aphid and Buchnera, including sharing of amino acid biosynthesis between the aphid and Buchnera. The pea aphid genome provides a foundation for post-genomic studies of fundamental biological questions and applied agricultural problems

Toll-like receptor signaling and stages of addiction

Athina Markou and her colleagues discovered persistent changes in adult behavior following adolescent exposure to ethanol or nicotine consistent with increased risk for developing addiction. Building on Dr. Markou's important work and that of others in the field, researchers at the Bowles Center for Alcohol Studies have found that persistent changes in behavior following adolescent stress or alcohol exposure may be linked to induction of immune signaling in brain. This study aims to illuminate the critical interrelationship of the innate immune system (e.g., toll-like receptors [TLRs], high-mobility group box 1 [HMGB1]) in the neurobiology of addiction. This study reviews the relevant research regarding the relationship between the innate immune system and addiction. Emerging evidence indicates that TLRs in brain, particularly those on microglia, respond to endogenous innate immune agonists such as HMGB1 and microRNAs (miRNAs). Multiple TLRs, HMGB1, and miRNAs are induced in the brain by stress, alcohol, and other drugs of abuse and are increased in the postmortem human alcoholic brain. Enhanced TLR-innate immune signaling in brain leads to epigenetic modifications, alterations in synaptic plasticity, and loss of neuronal cell populations, which contribute to cognitive and emotive dysfunctions. Addiction involves progressive stages of drug binges and intoxication, withdrawal-negative affect, and ultimately compulsive drug use and abuse. Toll-like receptor signaling within cortical-limbic circuits is modified by alcohol and stress in a manner consistent with promoting progression through the stages of addiction

Novel methods improve prediction of species distributions from occurrence data

Prediction of species distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species’ distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species’ occurrence data. Presence-only data were effective for modelling species’ distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve