Modelling the niche space of desert annuals needs to include positive interactions

The niche is a necessary consideration when estimating habitable area and geographic range of a species. Modellers often examine the fundamental niche and the environmental requirements for plant species, ignoring interactions among species. In deserts, positive plant interactions are important drivers of biodiversity and structure communities through many mechanistic pathways including modifying environmental conditions. Thus, we tested the hypothesis that desert shrubs increase the geographical extent of some annual species because, through modifying the microclimate, they match the niche requirements of beneficiary species. We used the database of the Global Biodiversity Information Facility to construct MaxEnt species distribution models (SDM) with and without reported benefactor species within the Mojave Desert in California. We chose 20 annual species to be modeled including 10 species that had been previously reported in the literature as being facilitated (beneficiary) and 10 that had no record of being facilitated (unreported). Beneficiary annuals co‐occurred significantly more with benefactor shrubs than the unreported annual species. The inclusion of shrubs into SDMs significantly improved model predictability and geographic range for all the beneficiary annual species, but not for the unreported annual species. Thus, positive interactions are species specific and it is possible to determine annual species dependency on benefactor shrubs at the regional scale. The co‐occurrence of benefactor shrubs and annual species can be used as a proxy for facilitation and recent developments in SDM techniques encourage the inclusion of biotic interactions. Species distribution models should include estimates of facilitation because biotic interactions determine the niche of species and can have implications with a changing climate.     

Selective Vulnerability of Spinal and Cortical Motor Neuron Subpopulations in delta7 SMA Mice

Loss of the survival motor neuron gene (SMN1) is responsible for spinal muscular atrophy (SMA), the most common inherited cause of infant mortality. Even though the SMA phenotype is traditionally considered as related to spinal motor neuron loss, it remains debated whether the specific targeting of motor neurons could represent the best therapeutic option for the disease. We here investigated, using stereological quantification methods, the spinal cord and cerebral motor cortex of ∆7 SMA mice during development, to verify extent and selectivity of motor neuron loss. We found progressive post-natal loss of spinal motor neurons, already at pre-symptomatic stages, and a higher vulnerability of motor neurons innervating proximal and axial muscles. Larger motor neurons decreased in the course of disease, either for selective loss or specific developmental impairment. We also found a selective reduction of layer V pyramidal neurons associated with layer V gliosis in the cerebral motor cortex. Our data indicate that in the ∆7 SMA model SMN loss is critical for the spinal cord, particularly for specific motor neuron pools. Neuronal loss, however, is not selective for lower motor neurons. These data further suggest that SMA pathogenesis is likely more complex than previously anticipated. The better knowledge of SMA models might be instrumental in shaping better therapeutic options for affected patients.     

Phylogeny ofRubiaceae-Rubieae inferred from the sequence of a cpDNA intergene region

A phylogenetic analysis of 25 species, representing eight genera of theRubieae tribe (Rubiaceae), has been made using the DNA sequence of the chloroplastatp B-rbc L intergene region. Six tropical genera from other tribes ofRubiaceae have been used as outgroups. Whatever the method of analysis (distance, parsimony or maximum likelihood), five groups are clearly separated and described as informal clades. Their relative relationships are not clearly resolved by the parsimony analysis, resulting in eight equally parsimonious trees, 327 steps long, with a consistency index (CI) of 0.749 (excluding uninformative sites). TheRubieae tribe appears monophyletic from the data available. Some new and partly unexpected phylogenetic relationships are suggested. The genusRubia forms a separate clade and appears to be the relatively advanced sister group of the remaining taxa. TheSherardia clade also includes the generaCrucianella andPhuopsis. Galium sect.Aparinoides appears closely attached to theAsperula sect.Glabella clade. The remaining taxa ofGalium are paraphyletic:Galium sect.Platygalium (in theCruciata clade) is linked to the advanced generaCruciata andValantia; the more apomorphic groups ofGalium form theGalium sect.Galium clade, including the perennial sectionsGalium, Leiogalium, andLeptogalium as well as the annual (and possibly polyphyletic) sect.Kolgyda.     

Monomeric and Dimeric 9‐O Anthraquinone and Phenanthryl Derivatives of Cinchona Alkaloids as Chiral Solvating Agents for the NMR Enantiodiscrimination of Chiral Hemiesters

Mono‐ and bis‐alkaloid chiral auxiliaries with anthraquinone or phenanthryl cores were probed as chiral solvating agents (CSAs) for the enantiodiscrimination of chiral cyclic hemiesters. The dimeric anthraquinone derivative and the monomeric phenanthryl one showed remarkable efficiency in the nuclear magnetic resonance (NMR) differentiation of enantiomeric mixtures of hemiesters. An anthraquinone analogous with a single alkaloid unit was remarkably less effective. The conformational prevalence of the chiral auxiliaries were ascertained by NMR. Chirality 27:693–699, 2015. © 2015 Wiley Periodicals, Inc.     

Introducing “best single template” models as reference baseline for the Continuous Automated Model Evaluation (CAMEO)

Critical blind assessment of structure prediction techniques is crucial for the scientific community to establish the state of the art, identify bottlenecks, and guide future developments. In Critical Assessment of Techniques in Structure Prediction (CASP), human experts assess the performance of participating methods in relation to the difficulty of the prediction task in a biennial experiment on approximately 100 targets. Yet, the development of automated computational modeling methods requires more frequent evaluation cycles and larger sets of data. The “Continuous Automated Model EvaluatiOn (CAMEO)” platform complements CASP by conducting fully automated blind prediction evaluations based on the weekly pre-release of sequences of those structures, which are going to be published in the next release of the Protein Data Bank (PDB). Each week, CAMEO publishes benchmarking results for predictions corresponding to a set of about 20 targets collected during a 4-day prediction window. CAMEO benchmarking data are generated consistently for all methods at the same point in time, enabling developers to cross-validate their method's performance, and referring to their results in publications. Many successful participants of CASP have used CAMEO—either by directly benchmarking their methods within the system or by comparing their own performance to CAMEO reference data. CAMEO offers a variety of scores reflecting different aspects of structure modeling, for example, binding site accuracy, homo-oligomer interface quality, or accuracy of local model confidence estimates. By introducing the "bestSingleTemplate" method based on structure superpositions as a reference for the accuracy of 3D modeling predictions, CAMEO facilitates objective comparison of techniques and fosters the development of advanced methods.     

Mesoscopic Segregation of Excitation and Inhibition in a Brain Network Model

Neurons in the brain are known to operate under a careful balance of excitation and inhibition, which maintains neural microcircuits within the proper operational range. How this balance is played out at the mesoscopic level of neuronal populations is, however, less clear. In order to address this issue, here we use a coupled neural mass model to study computationally the dynamics of a network of cortical macrocolumns operating in a partially synchronized, irregular regime. The topology of the network is heterogeneous, with a few of the nodes acting as connector hubs while the rest are relatively poorly connected. Our results show that in this type of mesoscopic network excitation and inhibition spontaneously segregate, with some columns acting mainly in an excitatory manner while some others have predominantly an inhibitory effect on their neighbors. We characterize the conditions under which this segregation arises, and relate the character of the different columns with their topological role within the network. In particular, we show that the connector hubs are preferentially inhibitory, the more so the larger the node''s connectivity. These results suggest a potential mesoscale organization of the excitation-inhibition balance in brain networks.     

Clinical Efficacy and Safety of Ezetimibe on Major Cardiovascular Endpoints: Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background

Randomized clinical trials (RCTs) about Ezetimibe''s efficacy on patient-oriented outcomes have given discordant results. The aim of this study was to determine the net effect of Ezetimibe and of the widely marketed combination, Ezetimibe+simvastatin, on mortality and morbidity outcomes.

Methods and Findings

We searched for RCT on Ezetimibe using MEDLINE, CCTR, EMBASE, ClinicalTrials.gov databases up to December 2013, Merck and Novartis online registers, and personal communications. Two authors independently selected trials fulfilling these criteria: RCTs comparing Ezetimibe±statin or another lipid-lowering drug against placebo, or against the same lipid-lowering drug at the same dosage, with a follow-up at least 24 weeks and one or more of these outcomes: all-cause mortality, cardiovascular (CV) mortality, stroke, myocardial infarction (MI), cancer, serious adverse events (SAEs); we assessed the risk of bias using the Cochrane checklist. We extracted the data for major clinical events as a dichotomous measure, with the patient the unit of analysis. Pooled analysis was done with random and fixed effect based models. Trials comparing Ezetimibe plus a lipid-lowering drug against the same lipidlowering drug representing the net effect of Ezetimibe, showed a nonsignificant tendency toward damage for cancer, MI, stroke and SAEs. Ezetimibe+simvastatin vs. simvastatin alone showed a stronger tendency towards a higher risk for all-cause death (2.52; 0.65-9.74), CV death (3.04; 0.48-19.21), non-CV death (3.03; 0.12-73.50), MI (1.91; 0.42-8.70), stroke (2.38; 0.46-12.35), cancer (RR 11.11; 0.62-198.29), and SAEs (1.45; 0.95-2.23). Limitations include small numbers of events and inadequate power of the pooling. Trials comparing Ezetimibe+simvastatin vs placebo showed non-significant effects: MI (0.81; 0.66-1.00 p = 0.051), all-cause death (1.02; 0.95-1.09), CV death (0.91; 0.80-1.04), non-CV death (108; 0.99-1.18), stroke (0.86; 0.72-1.04), cancer (1.18; 0.80-1.74), SAEs (1.01; 0.96-1.06).

Conclusions

Ezetimibe±simvastatin had inconsistent effects on important outcomes. No firm conclusions are possible, but findings indicative of damage suggest much more selective use of Ezetimibe±simvastatin.     

Reconstruction of the Evolutionary Dynamics of A(H3N2) Influenza Viruses Circulating in Italy from 2004 to 2012

Background

Influenza A viruses are characterised by their rapid evolution, and the appearance of point mutations in the viral hemagglutinin (HA) domain causes seasonal epidemics. The A(H3N2) virus has higher mutation rate than the A(H1N1) virus. The aim of this study was to reconstruct the evolutionary dynamics of the A(H3N2) viruses circulating in Italy between 2004 and 2012 in the light of the forces driving viral evolution.

Methods

Phylodinamic analyses were made using a Bayesian method, and codon-specific positive selection acting on the HA coding sequence was evaluated.

Results

Global and local phylogenetic analyses showed that the Italian strains collected between 2004 and 2012 grouped into five significant Italian clades that included viral sequences circulating in different epidemic seasons. The time of the most recent common ancestor (tMRCA) of the tree root was between May and December 2003. The tMRCA estimates of the major clades suggest that the origin of a new viral strain precedes the effective circulation of the strain in the Italian population by 6–31 months, thus supporting a central role of global migration in seeding the epidemics in Italy. The study of selection pressure showed that four codons were under positive selection, three of which were located in antigenic sites. Analysis of population dynamics showed the alternation of periods of exponential growth followed by a decrease in the effective number of infections corresponding to epidemic and inter-epidemic seasons.

Conclusions

Our analyses suggest that a complex interaction between the immune status of the population, migrations, and a few selective sweeps drive the influenza A(H3N2) virus evolution. Our findings suggest the possibility of the year-round survival of local strains even in temperate zones, a hypothesis that warrants further investigation.     

Weather-Related Flood and Landslide Damage: A Risk Index for Italian Regions

The frequency of natural hazards has been increasing in the last decades in Europe and specifically in Mediterranean regions due to climate change. For example heavy precipitation events can lead to disasters through the interaction with exposed and vulnerable people and natural systems. It is therefore necessary a prevention planning to preserve human health and to reduce economic losses. Prevention should mainly be carried out with more adequate land management, also supported by the development of an appropriate risk prediction tool based on weather forecasts. The main aim of this study is to investigate the relationship between weather types (WTs) and the frequency of floods and landslides that have caused damage to properties, personal injuries, or deaths in the Italian regions over recent decades. In particular, a specific risk index (WT-FLARI) for each WT was developed at national and regional scale. This study has identified a specific risk index associated with each weather type, calibrated for each Italian region and applicable to both annual and seasonal levels. The risk index represents the seasonal and annual vulnerability of each Italian region and indicates that additional preventive actions are necessary for some regions. The results of this study represent a good starting point towards the development of a tool to support policy-makers, local authorities and health agencies in planning actions, mainly in the medium to long term, aimed at the weather damage reduction that represents an important issue of the World Meteorological Organization mission.     

Impact of food processing and detoxification treatments on mycotoxin contamination

Mycotoxins are fungal metabolites commonly occurring in food, which pose a health risk to the consumer. Maximum levels for major mycotoxins allowed in food have been established worldwide. Good agricultural practices, plant disease management, and adequate storage conditions limit mycotoxin levels in the food chain yet do not eliminate mycotoxins completely. Food processing can further reduce mycotoxin levels by physical removal and decontamination by chemical or enzymatic transformation of mycotoxins into less toxic products. Physical removal of mycotoxins is very efficient: manual sorting of grains, nuts, and fruits by farmers as well as automatic sorting by the industry significantly lowers the mean mycotoxin content. Further processing such as milling, steeping, and extrusion can also reduce mycotoxin content. Mycotoxins can be detoxified chemically by reacting with food components and technical aids; these reactions are facilitated by high temperature and alkaline or acidic conditions. Detoxification of mycotoxins can also be achieved enzymatically. Some enzymes able to transform mycotoxins naturally occur in food commodities or are produced during fermentation but more efficient detoxification can be achieved by deliberate introduction of purified enzymes. We recommend integrating evaluation of processing technologies for their impact on mycotoxins into risk management. Processing steps proven to mitigate mycotoxin contamination should be used whenever necessary. Development of detoxification technologies for high-risk commodities should be a priority for research. While physical techniques currently offer the most efficient post-harvest reduction of mycotoxin content in food, biotechnology possesses the largest potential for future developments.