Food-web structure in relation to environmental gradients and predator-prey ratios in tank-bromeliad ecosystems

Little is known of how linkage patterns between species change along environmental gradients. The small, spatially discrete food webs inhabiting tank-bromeliads provide an excellent opportunity to analyse patterns of community diversity and food-web topology (connectance, linkage density, nestedness) in relation to key environmental variables (habitat size, detrital resource, incident radiation) and predators: prey ratios. We sampled 365 bromeliads in a wide range of understorey environments in French Guiana and used gut contents of invertebrates to draw the corresponding 365 connectance webs. At the bromeliad scale, habitat size (water volume) determined the number of species that constitute food-web nodes, the proportion of predators, and food-web topology. The number of species as well as the proportion of predators within bromeliads declined from open to forested habitats, where the volume of water collected by bromeliads was generally lower because of rainfall interception by the canopy. A core group of microorganisms and generalist detritivores remained relatively constant across environments. This suggests that (i) a highly-connected core ensures food-web stability and key ecosystem functions across environments, and (ii) larger deviations in food-web structures can be expected following disturbance if detritivores share traits that determine responses to environmental changes. While linkage density and nestedness were lower in bromeliads in the forest than in open areas, experiments are needed to confirm a trend for lower food-web stability in the understorey of primary forests

Horizontal patterns of water temperature and salinity in an estuarine tidal channel: Ria de Aveiro

This work presents results from two complementary and interconnected approaches to study water temperature and salinity patterns in an estuarine tidal channel. This channel is one of the four main branches of the Ria de Aveiro, a shallow lagoon located in the Northwest coast of the Iberian Peninsula. Longitudinal and cross-sectional fields of water temperature and salinity were determined by spatial interpolation of field measurements. A numerical model (Mohid) was used in a 2D depth-integrated mode in order to compute water temperature and salinity patterns. The main purpose of this work was to determine the horizontal patterns of water temperature and salinity in the study area, evaluating the effects of the main forcing factors. The field results were depth-integrated and compared to numerical model results. These results obtained using extreme tidal and river runoff forcing, are also presented. The field results reveal that, when the river flow is weak, the tidal intrusion is the main forcing mechanism, generating saline and thermal fronts which migrate with the neap/spring tidal cycle. When the river flow increases, the influence of the freshwater extends almost as far as the mouth of the lagoon and vertical stratification is established. Results of numerical modelling reveal that the implemented model reproduces quite well the observed horizontal patterns. The model was also used to study the hydrology of the study area under extreme forcing conditions. When the model is forced with a low river flow (1 m3 s−1) the results confirm that the hydrology is tidally dominated. When the model is forced with a high river flow (1,000 m3 s−1) the hydrology is dominated by freshwater, as would be expected in such an area

High-resolution transcriptional profiling of Anopheles gambiae spermatogenesis reveals mechanisms of sex chromosome regulation

Abstract: Although of high priority for the development of genetic tools to control malaria-transmitting mosquitoes, only a few germline-specific regulatory regions have been characterised to date and the presence of global regulatory mechanisms, such as dosage compensation and meiotic sex chromosome inactivation (MSCI), are mostly assumed from transcriptomic analyses of reproductive tissues or whole gonads. In such studies, samples include a significant portion of somatic tissues inevitably complicating the reconstruction of a defined transcriptional map of gametogenesis. By exploiting recent advances in transgenic technologies and gene editing tools, combined with fluorescence-activated cell sorting and RNA sequencing, we have separated four distinct cell lineages from the Anopheles gambiae male gonads: premeiotic, meiotic (primary and secondary spermatocytes) and postmeiotic. By comparing the overall expression levels of X-linked and autosomal genes across the four populations, we revealed a striking transcriptional repression of the X chromosome coincident with the meiotic phase, classifiable as MSCI, and highlighted genes that may evade silencing. In addition, chromosome-wide median expression ratios of the premeiotic population confirmed the absence of dosage compensation in the male germline. Applying differential expression analysis, we highlighted genes and transcript isoforms enriched at specific timepoints and reconstructed the expression dynamics of the main biological processes regulating the key stages of sperm development and maturation. We generated the first transcriptomic atlas of A. gambiae spermatogenesis that will expand the available toolbox for the genetic engineering of vector control technologies. We also describe an innovative and multidimensional approach to isolate specific cell lineages that can be used for the targeted analysis of other A. gambiae organs or transferred to other medically relevant species and model organisms

A randomized controlled trial to assess the clinical and cost effectiveness of a nurse-led Antenatal Asthma Management Service in South Australia (AAMS study)

Background: Pregnancy presents a unique situation for the management of asthma as it can alter the course of asthma severity and its treatment, which in turn can affect pregnancy outcomes. Despite awareness of the substantial adverse effects associated with asthma during pregnancy, little has been done to improve its management and reduce associated perinatal morbidity and mortality. The aim of this randomized controlled trial is to evaluate the clinical and cost effectiveness of an Antenatal Asthma Management Service. Methods/design: Design: Multicentre, randomized controlled trial. Inclusion criteria: Women with physician diagnosed asthma, which is not currently in remission, who are less than 20 weeks gestation with a singleton pregnancy and do not have a chronic medical condition. Trial entry and randomization: Eligible women with asthma, stratified by treatment site, disease severity and parity, will be randomized into either the ‘Standard Care Group’ or the ‘Intervention Group’. Study groups: Both groups will be followed prospectively throughout pregnancy. Women in the ‘Standard Care Group’ will receive routine obstetric care reflecting current clinical practice in Australian hospitals. Women in the ‘Intervention Group’ will receive additional care through the nurse-led Antenatal Asthma Management Service, based in the antenatal outpatient clinic. Women will receive asthma education with a full assessment of their asthma at 18, 24, 30 and 36 weeks gestation. Each antenatal visit will include a 60 min session where asthma management skills are assessed including: medication adherence and knowledge, inhaler device technique, recognition of asthma deterioration and possession of a written asthma action plan. Furthermore, subjects will receive education about asthma control and management skills including trigger avoidance and smoking cessation counseling when appropriate. Primary study outcome: Asthma exacerbations during pregnancy. Sample size: A sample size of 378 women will be sufficient to show an absolute reduction in asthma exacerbations during pregnancy of 20% (alpha 0.05 two-tailed, 90% power, 5% loss to follow-up). Discussion: The integration of an asthma education program within the antenatal clinic setting has the significant potential to improve the participation of pregnant women in the self-management of their asthma, reduce asthma exacerbations and improve perinatal health outcomes.Luke E Grzeskowiak, Gustaaf Dekker, Karen Rivers, Kate Roberts-Thomson, Anil Roy, Brian Smith, Jeffery Bowden, Robert Bryce, Michael Davies, Justin Beilby, Anne Wilson, Philippa Middleton, Richard Ruffin, Jonathan Karnon, Vicki L Clifton and for the AAMS study grou

Staphylococcus aureus Survives with a Minimal Peptidoglycan Synthesis Machine but Sacrifices Virulence and Antibiotic Resistance

Many important cellular processes are performed by molecular machines, composed of multiple proteins that physically interact to execute biological functions. An example is the bacterial peptidoglycan (PG) synthesis machine, responsible for the synthesis of the main component of the cell wall and the target of many contemporary antibiotics. One approach for the identification of essential components of a cellular machine involves the determination of its minimal protein composition. Staphylococcus aureus is a Gram-positive pathogen, renowned for its resistance to many commonly used antibiotics and prevalence in hospitals. Its genome encodes a low number of proteins with PG synthesis activity (9 proteins), when compared to other model organisms, and is therefore a good model for the study of a minimal PG synthesis machine. We deleted seven of the nine genes encoding PG synthesis enzymes from the S. aureus genome without affecting normal growth or cell morphology, generating a strain capable of PG biosynthesis catalyzed only by two penicillin-binding proteins, PBP1 and the bi-functional PBP2. However, multiple PBPs are important in clinically relevant environments, as bacteria with a minimal PG synthesis machinery became highly susceptible to cell wall-targeting antibiotics, host lytic enzymes and displayed impaired virulence in a Drosophila infection model which is dependent on the presence of specific peptidoglycan receptor proteins, namely PGRP-SA. The fact that S. aureus can grow and divide with only two active PG synthesizing enzymes shows that most of these enzymes are redundant in vitro and identifies the minimal PG synthesis machinery of S. aureus. However a complex molecular machine is important in environments other than in vitro growth as the expendable PG synthesis enzymes play an important role in the pathogenicity and antibiotic resistance of S. aureus

A Cretaceous origin for fire adaptations in the Cape flora

Fire has had a profound effect on the evolution of worldwide biotas. The Cape Floristic Region is one of the world's most species-rich regions, yet it is highly prone to recurrent fires and fire-adapted species contribute strongly to the overall flora. It is hypothesized that the current fire regimes in the Cape could be as old as 6-8 million years (My), while indirect evidence indicates that the onset of fire could have reached 18 million years ago (Ma). Here, we trace the origin of fire-dependent traits in two monocot families that are significant elements in the fire-prone Cape flora. Our analysis shows that fire-stimulated flowering originated in the Cape Haemodoraceae 81 Ma, while fire-stimulated germination arose in the African Restionaceae at least 70 Ma, implying that wildfires have been a significant force in the evolution of the Cape flora at least 60 My earlier than previous estimates. Our results provide strong evidence for the presence of fire adaptations in the Cape from the Cretaceous, leading to the extraordinary persistence of a fire-adapted flora in this biodiversity hotspot, and giving support to the hypothesis that Cretaceous fire was a global phenomenon that shaped the evolution of terrestrial floras

A Feature-Driven Active Framework for Ultrasound-Based Brain Shift Compensation

A reliable Ultrasound (US)-to-US registration method to compensate for brain shift would substantially improve Image-Guided Neurological Surgery. Developing such a registration method is very challenging, due to factors such as missing correspondence in images, the complexity of brain pathology and the demand for fast computation. We propose a novel feature-driven active framework. Here, landmarks and their displacement are first estimated from a pair of US images using corresponding local image features. Subsequently, a Gaussian Process (GP) model is used to interpolate a dense deformation field from the sparse landmarks. Kernels of the GP are estimated by using variograms and a discrete grid search method. If necessary, the user can actively add new landmarks based on the image context and visualization of the uncertainty measure provided by the GP to further improve the result. We retrospectively demonstrate our registration framework as a robust and accurate brain shift compensation solution on clinical data acquired during neurosurgery

A Platform for Processing Expression of Short Time Series (PESTS)

<p>Abstract</p> <p>Background</p> <p>Time course microarray profiles examine the expression of genes over a time domain. They are necessary in order to determine the complete set of genes that are dynamically expressed under given conditions, and to determine the interaction between these genes. Because of cost and resource issues, most time series datasets contain less than 9 points and there are few tools available geared towards the analysis of this type of data.</p> <p>Results</p> <p>To this end, we introduce a platform for Processing Expression of Short Time Series (PESTS). It was designed with a focus on usability and interpretability of analyses for the researcher. As such, it implements several standard techniques for comparability as well as visualization functions. However, it is designed specifically for the unique methods we have developed for significance analysis, multiple test correction and clustering of short time series data. The central tenet of these methods is the use of biologically relevant features for analysis. Features summarize short gene expression profiles, inherently incorporate dependence across time, and allow for both full description of the examined curve and missing data points.</p> <p>Conclusions</p> <p>PESTS is fully generalizable to other types of time series analyses. PESTS implements novel methods as well as several standard techniques for comparability and visualization functions. These features and functionality make PESTS a valuable resource for a researcher's toolkit. PESTS is available to download for free to academic and non-profit users at <url>http://www.mailman.columbia.edu/academic-departments/biostatistics/research-service/software-development</url>.</p

Bayesian Multimodel Inference for Geostatistical Regression Models

The problem of simultaneous covariate selection and parameter inference for spatial regression models is considered. Previous research has shown that failure to take spatial correlation into account can influence the outcome of standard model selection methods. A Markov chain Monte Carlo (MCMC) method is investigated for the calculation of parameter estimates and posterior model probabilities for spatial regression models. The method can accommodate normal and non-normal response data and a large number of covariates. Thus the method is very flexible and can be used to fit spatial linear models, spatial linear mixed models, and spatial generalized linear mixed models (GLMMs). The Bayesian MCMC method also allows a priori unequal weighting of covariates, which is not possible with many model selection methods such as Akaike's information criterion (AIC). The proposed method is demonstrated on two data sets. The first is the whiptail lizard data set which has been previously analyzed by other researchers investigating model selection methods. Our results confirmed the previous analysis suggesting that sandy soil and ant abundance were strongly associated with lizard abundance. The second data set concerned pollution tolerant fish abundance in relation to several environmental factors. Results indicate that abundance is positively related to Strahler stream order and a habitat quality index. Abundance is negatively related to percent watershed disturbance