Mating system and avpr1a promoter variation in primates.

It has been suggested that primate mating and social behaviours may be influenced by variation in promoter region repetitive DNA of the vasopressin receptor 1a gene (avpr1a). We show that male mating behaviour does not covary in a simple way with promoter repetitive DNA in 12 Old World primates. We found that one microsatellite (-553 bp upstream) was present in all species, irrespective of their behaviour. By contrast, two microsatellites (-3956 and -3625 bp upstream) were present only in some species, yet this variation did not correlate with behaviour. These findings agree with a recent comparative analysis of voles and show that the variation in repetitive DNA in the avpr1a promoter region does not generally explain variation in male mating behaviour. Phylogenetic analysis revealed a GAGTA motif that has been independently deleted three times and involved in another larger deletion. Importantly, the presence/absence of this GAGTA motif leads to changes in predicted transcription factor-binding sites. Given the repeated loss of this motif, we speculate that it might be of functional relevance. We suggest that such non-repetitive variation, either in indels or in sequence variation, are likely to be important in explaining interspecific variation in avpr1a expression.

Computed tomography angiography vs 3 T black-blood cardiovascular magnetic resonance for identification of symptomatic carotid plaques.

BACKGROUND: The purpose of this prospective study was to perform a head-to-head comparison of the two methods most frequently used for evaluation of carotid plaque characteristics: Multi-detector Computed Tomography Angiography (MDCTA) and black-blood 3 T-cardiovascular magnetic resonance (bb-CMR) with respect to their ability to identify symptomatic carotid plaques. METHODS: 22 stroke unit patients with unilateral symptomatic carotid disease and >50% stenosis by duplex ultrasound underwent MDCTA and bb-CMR (TOF, pre- and post-contrast fsT1w-, and fsT2w- sequences) within 15 days of symptom onset. Both symptomatic and contralateral asymptomatic sides were evaluated. By bb-CMR, plaque morphology, composition and prevalence of complicated AHA type VI lesions (AHA-LT6) were evaluated. By MDCTA, plaque type (non-calcified, mixed, calcified), plaque density in HU and presence of ulceration and/or thrombus were evaluated. Sensitivity (SE), specificity (SP), positive and negative predictive value (PPV, NPV) were calculated using a 2-by-2-table. RESULTS: To distinguish between symptomatic and asymptomatic plaques AHA-LT6 was the best CMR variable and presence / absence of plaque ulceration was the best CT variable, resulting in a SE, SP, PPV and NPV of 80%, 80%, 80% and 80% for AHA-LT6 as assessed by bb-CMR and 40%, 95%, 89% and 61% for plaque ulceration as assessed by MDCTA. The combined SE, SP, PPV and NPV of bb-CMR and MDCTA was 85%, 75%, 77% and 83%, respectively. CONCLUSIONS: Bb-CMR is superior to MDCTA at identifying symptomatic carotid plaques, while MDCTA offers high specificity at the cost of low sensitivity. Results were only slightly improved over bb-CMR alone when combining both techniques.

Stomach content analyses of Simulium perflavum Roubaud 1906 (Diptera: Simuliidae) larvae from streams in Central Amazônia, Brazil

Stomach contents of Simulium perflavum Roubaud larvae were analyzed and compared with plankton and periphyton collected in five streams, in Central Amazonia (Manaus and Presidente Figueiredo counties), in Sep./Oct.1996 (dry season) and Feb./Mar. 1997 (rainy season). A total of 1,400 last-instar larvae were dissected; the stomach contents were analyzed using different methods: fresh and after oxidation. A total of 87 taxa (algae, diatoms and rotifers) were found in the stomach contents. In each stream, qualitative samples of plankton and periphyton were collected; these were mounted between slides and cover slips. A total of 94 taxa of plankton and 54 taxa of periphyton were collected. One species of Rotifera was present in the stomach contents, plankton and periphyton. Cluster analysis based on species composition of the organisms present in the stomach contents grouped the streams into two major groups, each belonging to a different drainage area. Correlations based on presence/absence of species of microalgae in the stomach contents, plankton and periphyton indicated significant associations (p<0.05) between stomach contents and plankton and between plankton and periphyton (z test); the Sorensen coefficient and cluster analysis corroborate the same associations.

Evaluating the ability of habitat suitability models to predict species presences.

Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.

Sensitivity of predictive species distribution models to change in grain size

Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.

Preliminary results of random amplification of polymorphic DNA among Triatominae of the phyllosoma complex (Hemiptera, Reduviidae)

In Mexico, Triatoma longipennis (Usinger), Triatoma picturata (Usinger), and Triatoma pallidipennis (Stal), primary Chagas disease vector species of the phyllosoma complex, were analyzed by randomly amplified polymorphic DNA (RAPD). Sixteen decametric primers resolved individual profiles not identical, but partially discriminative between species. Analysis based on pairwise presence/absence comparisons between the three species was performed using three primers and two outgroup species Triatoma infestans (Klug) and Triatoma barberi (Usinger). Fifty-three bands in total were scored, although only two bands were constant among the three phyllosoma complex species. Two other bands were constant only for T. longipennis and T. picturata together, and not present in T. pallidipennis. Neighbor Joining tree and the multiple correspondence analysis discriminated T. pallidipennis clearly from the other two species, although there was overlap between T. longipennis and T. picturata. The results indicate a close relationship between the studied species and support the hypothesis of their recent evolution. The suitability of RAPD to discern populations within the species is discussed.

Detection of enteric viruses in recreational waters of an urban lagoon in the city of Rio de Janeiro, Brazil

The aim of this study was to determine the occurrences of the group A rotavirus (RVA), norovirus (NoV) and human adenovirus (HAdV) in the surface waters of an urban lagoon (Rodrigo de Freitas Lagoon) in the city of Rio de Janeiro, Brazil. During one year of surveillance, water samples were obtained from the lagoon and other interconnected ecosystems (river and beach). The samples were concentrated using an adsorption-elution method with a negatively charged membrane and tested by qualitative and quantitative polymerase chain reaction assays. RVA was the most prevalent virus detected (24.3%) with a viral load ranging from 3.0 x 10¹-5.6 x 10(4) genome copies/L, followed by NoV (18.8%) and HAdV (16.7%). Considering water samples suitable for bathing, according to Escherichia coli criterion (< 2,000 most probable number/100 mL), viruses were detected in 50% (57/114) of them. Physicochemical parameters were also measured and showed possible correlations between turbidity and RVA presence and between pH and NoV presence. These data demonstrate the importance of considering viral parameters to ensure water quality and the utilisation of these parameters as additional tools for the characterisation of environmental contamination.

Two functional variants of IRF5 influence the development of macular edema in patients with non-anterior uveitis.

OBJECTIVE Interferon (IFN) signaling plays a crucial role in autoimmunity. Genetic variation in interferon regulatory factor 5 (IRF5), a major regulator of the type I interferon induction, has been associated with risk of developing several autoimmune diseases. In the current study we aimed to evaluate whether three sets of correlated IRF5 genetic variants, independently associated with SLE and with different functional roles, are involved in uveitis susceptibility and its clinical subphenotypes. METHODS Three IRF5 polymorphisms, rs2004640, rs2070197 and rs10954213, representative of each group, were genotyped using TaqMan® allelic discrimination assays in a total of 263 non-anterior uveitis patients and 724 healthy controls of Spanish origin. RESULTS A clear association between two of the three analyzed genetic variants, rs2004640 and rs10954213, and the absence of macular edema was observed in the case/control analysis (P FDR =5.07E-03, OR=1.48, CI 95%=1.14-1.92 and P FDR =3.37E-03, OR=1.54, CI 95%=1.19-2.01, respectively). Consistently, the subphenotype analysis accordingly with the presence/absence of this clinical condition also reached statistical significance (rs2004640: P=0.037, OR=0.69, CI 95%=0.48-0.98; rs10954213: P=0.030, OR=0.67, CI 95%=0.47-0.96), thus suggesting that both IRF5 genetic variants are specifically associated with the lack of macular edema in uveitis patients. CONCLUSION Our results clearly showed for the first time that two functional genetic variants of IRF5 may play a role in the development of macular edema in non-anterior uveitis patients. Identifying genetic markers for macular edema could lead to the possibility of developing novel treatments or preventive therapies.

Multibacillary leprosy patients with high and persistent serum antibodies to leprosy IDRI diagnostic-1/LID-1: higher susceptibility to develop type 2 reactions

Leprosy inflammatory episodes [type 1 (T1R) and type 2 (T2R) reactions] represent the major cause of irreversible nerve damage. Leprosy serology is known to be influenced by the patient’s bacterial index (BI) with higher positivity in multibacillary patients (MB) and specific multidrug therapy (MDT) reduces antibody production. This study evaluated by ELISA antibody responses to leprosy Infectious Disease Research Institute diagnostic-1 (LID-1) fusion protein and phenolic glycolipid I (PGL-I) in 100 paired serum samples of 50 MB patients collected in the presence/absence of reactions and in nonreactional patients before/after MDT. Patients who presented T2R had a median BI of 3+, while MB patients with T1R and nonreactional patients had median BI of 2.5+ (p > 0.05). Anti-LID-1 and anti-PGL-I antibodies declined in patients diagnosed during T1R (p < 0.05). Anti-LID-1 levels waned in MB with T2R at diagnosis and nonreactional MB patients (p < 0.05). Higher anti-LID-1 levels were seen in patients with T2R at diagnosis (vs. patients with T1R at diagnosis, p = 0.008; vs. nonreactional patients, p = 0.020) and in patients with T2R during MDT (vs. nonreactional MB, p = 0.020). In MB patients, high and persistent anti-LID-1 antibody levels might be a useful tool for clinicians to predict which patients are more susceptible to develop leprosy T2R.

The DART classification of unannotated transcription within the ENCODE regions: associating transcription with known and novel loci

For the ∼1% of the human genome in the ENCODE regions, only about half of the transcriptionally active regions (TARs) identified with tiling microarrays correspond to annotated exons. Here we categorize this large amount of “unannotated transcription.” We use a number of disparate features to classify the 6988 novel TARs—array expression profiles across cell lines and conditions, sequence composition, phylogenetic profiles (presence/absence of syntenic conservation across 17 species), and locations relative to genes. In the classification, we first filter out TARs with unusual sequence composition and those likely resulting from cross-hybridization. We then associate some of those remaining with proximal exons having correlated expression profiles. Finally, we cluster unclassified TARs into putative novel loci, based on similar expression and phylogenetic profiles. To encapsulate our classification, we construct a Database of Active Regions and Tools (DART.gersteinlab.org). DART has special facilities for rapidly handling and comparing many sets of TARs and their heterogeneous features, synchronizing across builds, and interfacing with other resources. Overall, we find that ∼14% of the novel TARs can be associated with known genes, while ∼21% can be clustered into ∼200 novel loci. We observe that TARs associated with genes are enriched in the potential to form structural RNAs and many novel TAR clusters are associated with nearby promoters. To benchmark our classification, we design a set of experiments for testing the connectivity of novel TARs. Overall, we find that 18 of the 46 connections tested validate by RT-PCR and four of five sequenced PCR products confirm connectivity unambiguously.

Avaliação da infestação de insetos-praga associados à batata (Solanum tuberosum L.) sob efeito de nutrientes nitrogenados e potássicos e teores acumulados de aminoácidos livres nas cultivares Achat e Monalisa

Evaluation of insect-pest infestation associated to potato (Solanum tuberosum L.) under effect of nitrogen and potassium fertilizers and the accumulated amount of free aminoacids in Achat and Monalisa cultivars. The objective of this work was to evaluate the occurence of insect-pests on potato plants influenced by dosages of nitrogen and potassium accumulated in plant organs. A total of 169 plants of the Achat and Monalisa cultivars were evaluated to determine the presence-absence of Diabrotica speciosa Germar, 1824 and Agrotis ipsilon Hüfnagel, 1767. The experiment was carried out and executed at the Universidade Federal Fluminense, and the delineation was complete randomized block design, with four replication and nine treatments, using three fertilization level (0; 75 and 150 Kg/ha) with N-urea + KCl. The aminoacid levels were adjusted by the Leucine standard-curve (µg/l), using the Ninhydrin method, at 570 nm. The results showed that the tubercles of Monalisa accumulated high free aminoacid levels with 7,95% in the treatment N1K2 and 7,75% in the N2K1.These treatments, induced the infestation by D. speciosa larvae in 27,03%, when the aminoacid level was 2,01 ± 0,58% (X ± EP), with probability of 0,0196

Unfolding nature "in silico" : overcoming practical and metodological limitations of species distribution models

Abstract : The existence of a causal relationship between the spatial distribution of living organisms and their environment, in particular climate, has been long recognized and is the central principle of biogeography. In turn, this recognition has led scientists to the idea of using the climatic, topographic, edaphic and biotic characteristics of the environment to predict its potential suitability for a given species or biological community. In this thesis, my objective is to contribute to the development of methodological improvements in the field of species distribution modeling. More precisely, the objectives are to propose solutions to overcome limitations of species distribution models when applied to conservation biology issues, or when .used as an assessment tool of the potential impacts of global change. The first objective of my thesis is to contribute to evidence the potential of species distribution models for conservation-related applications. I present a methodology to generate pseudo-absences in order to overcome the frequent lack of reliable absence data. I also demonstrate, both theoretically (simulation-based) and practically (field-based), how species distribution models can be successfully used to model and sample rare species. Overall, the results of this first part of the thesis demonstrate the strong potential of species distribution models as a tool for practical applications in conservation biology. The second objective this thesis is to contribute to improve .projections of potential climate change impacts on species distributions, and in particular for mountain flora. I develop and a dynamic model, MIGCLIM, that allows the implementation of dispersal limitations into classic species distribution models and present an application of this model to two virtual species. Given that accounting for dispersal limitations requires information on seed dispersal, distances, a general methodology to classify species into broad dispersal types is also developed. Finally, the M~GCLIM model is applied to a large number of species in a study area of the western Swiss Alps. Overall, the results indicate that while dispersal limitations can have an important impact on the outcome of future projections of species distributions under climate change scenarios, estimating species threat levels (e.g. species extinction rates) for a mountainous areas of limited size (i.e. regional scale) can also be successfully achieved when considering dispersal as unlimited (i.e. ignoring dispersal limitations, which is easier from a practical point of view). Finally, I present the largest fine scale assessment of potential climate change impacts on mountain vegetation that has been carried-out to date. This assessment involves vegetation from 12 study areas distributed across all major western and central European mountain ranges. The results highlight that some mountain ranges (the Pyrenees and the Austrian Alps) are expected to be more affected by climate change than others (Norway and the Scottish Highlands). The results I obtain in this study also indicate that the threat levels projected by fine scale models are less severe than those derived from coarse scale models. This result suggests that some species could persist in small refugias that are not detected by coarse scale models. Résumé : L'existence d'une relation causale entre la répartition des espèces animales et végétales et leur environnement, en particulier le climat, a été mis en évidence depuis longtemps et est un des principes centraux en biogéographie. Ce lien a naturellement conduit à l'idée d'utiliser les caractéristiques climatiques, topographiques, édaphiques et biotiques de l'environnement afin d'en prédire la qualité pour une espèce ou une communauté. Dans ce travail de thèse, mon objectif est de contribuer au développement d'améliorations méthodologiques dans le domaine de la modélisation de la distribution d'espèces dans le paysage. Plus précisément, les objectifs sont de proposer des solutions afin de surmonter certaines limitations des modèles de distribution d'espèces dans des applications pratiques de biologie de la conservation ou dans leur utilisation pour évaluer l'impact potentiel des changements climatiques sur l'environnement. Le premier objectif majeur de mon travail est de contribuer à démontrer le potentiel des modèles de distribution d'espèces pour des applications pratiques en biologie de la conservation. Je propose une méthode pour générer des pseudo-absences qui permet de surmonter le problème récurent du manque de données d'absences fiables. Je démontre aussi, de manière théorique (par simulation) et pratique (par échantillonnage de terrain), comment les modèles de distribution d'espèces peuvent être utilisés pour modéliser et améliorer l'échantillonnage des espèces rares. Ces résultats démontrent le potentiel des modèles de distribution d'espèces comme outils pour des applications de biologie de la conservation. Le deuxième objectif majeur de ce travail est de contribuer à améliorer les projections d'impacts potentiels des changements climatiques sur la flore, en particulier dans les zones de montagnes. Je développe un modèle dynamique de distribution appelé MigClim qui permet de tenir compte des limitations de dispersion dans les projections futures de distribution potentielle d'espèces, et teste son application sur deux espèces virtuelles. Vu que le fait de prendre en compte les limitations dues à la dispersion demande des données supplémentaires importantes (p.ex. la distance de dispersion des graines), ce travail propose aussi une méthode de classification simplifiée des espèces végétales dans de grands "types de disperseurs", ce qui permet ainsi de d'obtenir de bonnes approximations de distances de dispersions pour un grand nombre d'espèces. Finalement, j'applique aussi le modèle MIGCLIM à un grand nombre d'espèces de plantes dans une zone d'études des pré-Alpes vaudoises. Les résultats montrent que les limitations de dispersion peuvent avoir un impact considérable sur la distribution potentielle d'espèces prédites sous des scénarios de changements climatiques. Cependant, quand les modèles sont utilisés pour évaluer les taux d'extinction d'espèces dans des zones de montages de taille limitée (évaluation régionale), il est aussi possible d'obtenir de bonnes approximations en considérant la dispersion des espèces comme illimitée, ce qui est nettement plus simple d'un point dé vue pratique. Pour terminer je présente la plus grande évaluation à fine échelle d'impact potentiel des changements climatiques sur la flore des montagnes conduite à ce jour. Cette évaluation englobe 12 zones d'études réparties sur toutes les chaines de montages principales d'Europe occidentale et centrale. Les résultats montrent que certaines chaines de montagnes (les Pyrénées et les Alpes Autrichiennes) sont projetées comme plus sensibles aux changements climatiques que d'autres (les Alpes Scandinaves et les Highlands d'Ecosse). Les résultats obtenus montrent aussi que les modèles à échelle fine projettent des impacts de changement climatiques (p. ex. taux d'extinction d'espèces) moins sévères que les modèles à échelle large. Cela laisse supposer que les modèles a échelle fine sont capables de modéliser des micro-niches climatiques non-détectées par les modèles à échelle large.

Assessing alpine plant vulnerability to climate change: A modeling perspective

The potential ecological impact of ongoing climate change has been much discussed. High mountain ecosystems were identified early on as potentially very sensitive areas. Scenarios of upward species movement and vegetation shift are commonly discussed in the literature. Mountains being characteristically conic in shape, impact scenarios usually assume that a smaller surface area will be available as species move up. However, as the frequency distribution of additional physiographic factors (e.g., slope angle) changes with increasing elevation (e.g., with few gentle slopes available at higher elevation), species migrating upslope may encounter increasingly unsuitable conditions. As a result, many species could suffer severe reduction of their habitat surface, which could in turn affect patterns of biodiversity. In this paper, results from static plant distribution modeling are used to derive climate change impact scenarios in a high mountain environment. Models are adjusted with presence/absence of species. Environmental predictors used are: annual mean air temperature, slope, indices of topographic position, geology, rock cover, modeled permafrost and several indices of solar radiation and snow cover duration. Potential Habitat Distribution maps were drawn for 62 higher plant species, from which three separate climate change impact scenarios were derived. These scenarios show a great range of response, depending on the species and the degree of warming. Alpine species would be at greatest risk of local extinction, whereas species with a large elevation range would run the lowest risk. Limitations of the models and scenarios are further discussed.

A comparison of three methods of Mendelian randomization when the genetic instrument, the risk factor and the outcome are all binary.

The method of instrumental variable (referred to as Mendelian randomization when the instrument is a genetic variant) has been initially developed to infer on a causal effect of a risk factor on some outcome of interest in a linear model. Adapting this method to nonlinear models, however, is known to be problematic. In this paper, we consider the simple case when the genetic instrument, the risk factor, and the outcome are all binary. We compare via simulations the usual two-stages estimate of a causal odds-ratio and its adjusted version with a recently proposed estimate in the context of a clinical trial with noncompliance. In contrast to the former two, we confirm that the latter is (under some conditions) a valid estimate of a causal odds-ratio defined in the subpopulation of compliers, and we propose its use in the context of Mendelian randomization. By analogy with a clinical trial with noncompliance, compliers are those individuals for whom the presence/absence of the risk factor X is determined by the presence/absence of the genetic variant Z (i.e., for whom we would observe X = Z whatever the alleles randomly received at conception). We also recall and illustrate the huge variability of instrumental variable estimates when the instrument is weak (i.e., with a low percentage of compliers, as is typically the case with genetic instruments for which this proportion is frequently smaller than 10%) where the inter-quartile range of our simulated estimates was up to 18 times higher compared to a conventional (e.g., intention-to-treat) approach. We thus conclude that the need to find stronger instruments is probably as important as the need to develop a methodology allowing to consistently estimate a causal odds-ratio.

Rapid Biodiversity Assessment and Monitoring Method for Highly Diverse Benthic Communities: A Case Study of Mediterranean Coralligenous Outcrops

Increasing anthropogenic pressures urge enhanced knowledge and understanding of the current state of marine biodiversity. This baseline information is pivotal to explore present trends, detect future modifications and propose adequate management actions for marine ecosystems. Coralligenous outcrops are a highly diverse and structurally complex deep-water habitat faced with major threats in the Mediterranean Sea. Despite its ecological, aesthetic and economic value, coralligenous biodiversity patterns are still poorly understood. There is currently no single sampling method that has been demonstrated to be sufficiently representative to ensure adequate community assessment and monitoring in this habitat. Therefore, we propose a rapid non-destructive protocol for biodiversity assessment and monitoring of coralligenous outcrops providing good estimates of its structure and species composition, based on photographic sampling and the determination of presence/absence of macrobenthic species. We used an extensive photographic survey, covering several spatial scales (100s of m to 100s of km) within the NW Mediterranean and including 2 different coralligenous assemblages: Paramuricea clavata (PCA) and Corallium rubrum assemblage (CRA). This approach allowed us to determine the minimal sampling area for each assemblage (5000 cm² for PCA and 2500 cm²for CRA). In addition, we conclude that 3 replicates provide an optimal sampling effort in order to maximize the species number and to assess the main biodiversity patterns of studied assemblages in variability studies requiring replicates. We contend that the proposed sampling approach provides a valuable tool for management and conservation planning, monitoring and research programs focused on coralligenous outcrops, potentially also applicable in other benthic ecosystems