The Use of Climatic Niches in Screening Procedures for Introduced Species to Evaluate Risk of Spread: A Case with the American Eastern Grey Squirrel

Species introduction represents one of the most serious threats for biodiversity. The realized climatic niche of an invasive species can be used to predict its potential distribution in new areas, providing a basis for screening procedures in the compilation of black and white lists to prevent new introductions. We tested this assertion by modeling the realized climatic niche of the Eastern grey squirrel Sciurus carolinensis. Maxent was used to develop three models: one considering only records from the native range (NRM), a second including records from native and invasive range (NIRM), a third calibrated with invasive occurrences and projected in the native range (RCM). Niche conservatism was tested considering both a niche equivalency and a niche similarity test. NRM failed to predict suitable parts of the currently invaded range in Europe, while RCM underestimated the suitability in the native range. NIRM accurately predicted both the native and invasive range. The niche equivalency hypothesis was rejected due to a significant difference between the grey squirrel’s niche in native and invasive ranges. The niche similarity test yielded no significant results. Our analyses support the hypothesis of a shift in the species’ climatic niche in the area of introductions. Species Distribution Models (SDMs) appear to be a useful tool in the compilation of black lists, allowing identifying areas vulnerable to invasions. We advise caution in the use of SDMs based only on the native range of a species for the compilation of white lists for other geographic areas, due to the significant risk of underestimating its potential invasive range.     

Sustained Reduction of the Dengue Vector Population Resulting from an Integrated Control Strategy Applied in Two Brazilian Cities

Aedes aegypti has developed evolution-driven adaptations for surviving in the domestic human habitat. Several trap models have been designed considering these strategies and tested for monitoring this efficient vector of Dengue. Here, we report a real-scale evaluation of a system for monitoring and controlling mosquito populations based on egg sampling coupled with geographic information systems technology. The SMCP-Aedes, a system based on open technology and open data standards, was set up from March/2008 to October/2011 as a pilot trial in two sites of Pernambuco -Brazil: Ipojuca (10,000 residents) and Santa Cruz (83,000), in a joint effort of health authorities and staff, and a network of scientists providing scientific support. A widespread infestation by Aedes was found in both sites in 2008–2009, with 96.8%–100% trap positivity. Egg densities were markedly higher in SCC than in Ipojuca. A 90% decrease in egg density was recorded in SCC after two years of sustained control pressure imposed by suppression of >7,500,000 eggs and >3,200 adults, plus larval control by adding fishes to cisterns. In Ipojuca, 1.1 million mosquito eggs were suppressed and a 77% reduction in egg density was achieved. This study aimed at assessing the applicability of a system using GIS and spatial statistic analysis tools for quantitative assessment of mosquito populations. It also provided useful information on the requirements for reducing well-established mosquito populations. Results from two cities led us to conclude that the success in markedly reducing an Aedes population required the appropriate choice of control measures for sustained mass elimination guided by a user-friendly mosquito surveillance system. The system was able to support interventional decisions and to assess the program’s success. Additionally, it created a stimulating environment for health staff and residents, which had a positive impact on their commitment to the dengue control program.     

Isolation of Arsenic Resistant and Arsenopyrite Oxidizing Acidithiobacillus Species from pH Neutral Colombian Mine Effluents

Abstract

Inactive mines provide a great source of bacterial diversity for studying acidophilic communities and their biotechnological applications, but prospecting of these anthropogenic environments in Colombia has been limited. Conventional microbiological methods were used to isolate acidophilic bacterial strains from effluents emanating from the Colombian gold mine ‘El Zancudo’ (Titiribí, Antioquia). Despite the drainage waters having circumneutral pH, all of the isolated strains were phylogenetically related to the extreme acidophile Acidithiobacillus genus. However, based upon 16S rRNA gene sequences the mesophilic sulfur-oxidizing indigenous strains could not be assigned to a species. Pure cultures were selected by screening in medium with soluble inorganic arsenic (III) and their mineral-oxidative activity was evaluated at 30?°C in Erlenmeyer flasks with arsenopyrite ore under rotary shaking conditions. The indigenous strains were able to catalyze arsenopyrite oxidation in a mixed culture with a pulp density of 10%, maintaining their growth in the presence of >80?mM leached arsenic. This research provides information regarding the isolation of arsenic resistant bacterial communities from neutral effluents from El Zancudo mine and the possibility of the isolated strains to be useful in the biooxidation pretreatment of refractory gold-bearing arsenopyrite ores and concentrates.     

Psychiatric disorders and SLC6A4 gene variants: possible effects on alcohol dependence and alzheimer’s disease

Molecular Biology Reports - Serotoninergic system is one of the most important neurotransmission systems investigated in the field of psychiatry. Extensive evidence reveals how alterations of this...     

Comparison of complex modeling strategies for prediction of a binary outcome based on a few,highly correlated predictors

Motivated by a clinical prediction problem, a simulation study was performed to compare different approaches for building risk prediction models. Robust prediction models for hospital survival in patients with acute heart failure were to be derived from three highly correlated blood parameters measured up to four times, with predictive ability having explicit priority over interpretability. Methods that relied only on the original predictors were compared with methods using an expanded predictor space including transformations and interactions. Predictors were simulated as transformations and combinations of multivariate normal variables which were fitted to the partly skewed and bimodally distributed original data in such a way that the simulated data mimicked the original covariate structure. Different penalized versions of logistic regression as well as random forests and generalized additive models were investigated using classical logistic regression as a benchmark. Their performance was assessed based on measures of predictive accuracy, model discrimination, and model calibration. Three different scenarios using different subsets of the original data with different numbers of observations and events per variable were investigated. In the investigated setting, where a risk prediction model should be based on a small set of highly correlated and interconnected predictors, Elastic Net and also Ridge logistic regression showed good performance compared to their competitors, while other methods did not lead to substantial improvements or even performed worse than standard logistic regression. Our work demonstrates how simulation studies that mimic relevant features of a specific data set can support the choice of a good modeling strategy.     

Distance-based analysis of variance for brain connectivity

The field of neuroimaging dedicated to mapping connections in the brain is increasingly being recognized as key for understanding neurodevelopment and pathology. Networks of these connections are quantitatively represented using complex structures, including matrices, functions, and graphs, which require specialized statistical techniques for estimation and inference about developmental and disorder-related changes. Unfortunately, classical statistical testing procedures are not well suited to high-dimensional testing problems. In the context of global or regional tests for differences in neuroimaging data, traditional analysis of variance (ANOVA) is not directly applicable without first summarizing the data into univariate or low-dimensional features, a process that might mask the salient features of high-dimensional distributions. In this work, we consider a general framework for two-sample testing of complex structures by studying generalized within-group and between-group variances based on distances between complex and potentially high-dimensional observations. We derive an asymptotic approximation to the null distribution of the ANOVA test statistic, and conduct simulation studies with scalar and graph outcomes to study finite sample properties of the test. Finally, we apply our test to our motivating study of structural connectivity in autism spectrum disorder.     

Seed dispersal networks in tropical forest fragments: Area effects,remnant species,and interaction diversity

Seed dispersal interactions involve key ecological processes in tropical forests that help to maintain ecosystem functioning. Yet this functionality may be threatened by increasing habitat loss, defaunation, and fragmentation. However, generalist species, and their interactions, can benefit from the habitat change caused by human disturbance while more specialized interactions mostly disappear. Therefore, changes in the structure of the local, within fragment, networks can be expected. Here we investigated how the structure of seed dispersal networks changes along a gradient of increasing habitat fragmentation. We analyzed 16 bird seed dispersal assemblages from forest fragments of a biodiversity-rich ecosystem. We found significant species–, interaction–, and network–area relationships, yet the later was determined by the number of species remaining in each community. The number of frugivorous bird and plant species, their interactions, and the number of links per species decreases as area is lost in the fragmented landscape. In contrast, network nestedness has a negative relationship with fragment area, suggesting an increasing generalization of the network structure in the gradient of fragmentation. Network specialization was not significantly affected by area, indicating that some network properties may be invariant to disturbance. Still, the local extinction of partner species, paralleled by a loss of interactions and specialist–specialist bird–plant seed dispersal associations, suggests the functional homogenization of the system as area is lost. Our study provides empirical evidence for network–area relationships driven by the presence/absence of remnant species and the interactions they perform.     

The novel NhaE-type Na+/H+ antiporter of the pathogenic bacterium Neisseria meningitidis

Neisseria meningitidis is a pathogenic bacterium responsible for meningitis. The mechanisms underlying the control of Na⁺ transmembrane movement, presumably important to pathogenicity, have been barely addressed. To elucidate the function of the components of the Na⁺ transport system in N. meningitidis, an open reading frame from the genome of this bacterium displaying similarity with the NhaE type of Na⁺/H⁺ antiporters was expressed in Escherichia coli and characterized for sodium transport ability. The N. meningitidis antiporter (NmNhaE) was able to complement an E. coli strain devoid of Na⁺/H⁺ antiporters (KNabc) respecting the ability to grow in the presence of NaCl and LiCl. Ion transport assays in everted vesicles prepared from KNabc expressing NmNhaE from a plasmid confirmed its ability to translocate Na⁺ and Li⁺. Here is presented the characterization of the first NhaE from a pathogen, an important contribution to the comprehension of sodium ion metabolism in this kind of microorganisms.     

Oxidized albumin. The long way of a protein of uncertain function

Background

Proteins are extremely reactive to oxidants and should represent a potential target of instable reactive oxygen. This may represent a problem for plasma proteins since they may be directly modified in vivo in a compartment where antioxidant enzymatic systems are scarcely represented. On the other hand, it is possible that some plasma components have evolved over time to guarantee protection, in which case they can be considered as anti-oxidants.

Scope of review

To present and discuss main studies which addressed the role of albumin in plasma antioxidant activity mainly utilizing in vitro models of oxidation. To present some advances on structural features of oxidized albumin deriving from studies carried out on in vitro models as well as albumin purified in vivo from patients affected by clinical conditions characterized by oxidative stress.

Major conclusions

There are different interaction with HOCl and chloramines. In the former case, HOCl produces an extensive alteration of ²³⁸Trp and ¹⁶²Tyr, ⁴²⁵Tyr, ⁴⁷Tyr, while thiol groups are only partially involved. Chloramines are extremely reactive with the unique free SH group of albumin (³⁴Cys) with the formation of sulfenic and sulfinic acid as intermediates and sulfonic acid as end-product. Oxidized albumin has a modified electrical charge for the addition of an acidic residue and presents α-helix and random coil reorganization with subtle changes in domain orientation.

General significance

Albumin, is the major antioxidants in plasma with a concentration (0.8 mM) higher than other antioxidants by an exponential factor. Functional and protective roles in the presence of oxidative stress must be defined. This article is part of a Special Issue entitled Serum Albumin.