Species distribution models for conservation-oriented studies in Switzerland : filling data and tools gaps

SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.

A critical role for the T cell receptor alpha-chain connecting peptide domain in positive selection of CD1-independent NKT cells.

Natural killer T (NKT) cells are a subset of mature alpha beta TCR(+) cells that co-express NK lineage markers. Whereas most NKT cells express a canonical Valpha14/Vbeta8.2 TCR and are selected by CD1d, a minority of NKT cells express a diverse TCR repertoire and develop independently of CD1d. Little is known about the selection requirements of CD1d-independent NKT cells. We show here that NKT cells develop in RAG-deficient mice expressing an MHC class II-restricted transgenic TCR (Valpha2/Vbeta8.1) but only under conditions that lead to negative selection of conventional T cells. Moreover development of NKT cells in these mice is absolutely dependent upon an intact TCR alpha-chain connecting peptide domain, which is required for positive selection of conventional T cells via recruitment of the ERK signaling pathway. Collectively our data demonstrate that NKT cells can develop as a result of high avidity TCR/MHC class II interactions and suggest that common signaling pathways are involved in the positive selection of CD1d-independent NKT cells and conventional T cells.

Selection, Recombination and History in a Parasitic Flatworm (Echinococcus) Inferred from Nucleotide Sequences

Three species of flatworms from the genus Echinococcus (E. granulosus, E. multilocularis and E. vogeli) and four strains of E. granulosus (cattle, horse, pig and sheep strains) were analysed by the PCR-SSCP method followed by sequencing, using as targets two non-coding and two coding (one nuclear and one mitochondrial) genomic regions. The sequencing data was used to evaluate hypothesis about the parasite breeding system and the causes of genetic diversification. The calculated recombination parameters suggested that cross-fertilisation was rare in the history of the group. However, the relative rates of substitution in the coding sequences showed that positive selection (instead of purifying selection) drove the evolution of an elastase and neutrophil chemotaxis inhibitor gene (AgB/1). The phylogenetic analyses revealed several ambiguities, indicating that the taxonomic status of the E. granulosus horse strain should be revised

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (R (adj) (2) > 0.5). 2) Models including PCNM variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation of non-model species under global change.

Cutting edge: influence of the TCR Vbeta domain on the selection of semi-invariant NKT cells by endogenous ligands.

Invariant Valpha14 (Valpha14i) NKT cells are a murine CD1d-dependent regulatory T cell subset characterized by a Valpha14-Jalpha18 rearrangement and expression of mostly Vbeta8.2 and Vbeta7. Whereas the TCR Vbeta domain influences the binding avidity of the Valpha14i TCR for CD1d-alpha-galactosylceramide complexes, with Vbeta8.2 conferring higher avidity binding than Vbeta7, a possible impact of the TCR Vbeta domain on Valpha14i NKT cell selection by endogenous ligands has not been studied. In this study, we show that thymic selection of Vbeta7(+), but not Vbeta8.2(+), Valpha14i NKT cells is favored in situations where endogenous ligand concentration or TCRalpha-chain avidity are suboptimal. Furthermore, thymic Vbeta7(+) Valpha14i NKT cells were preferentially selected in vitro in response to CD1d-dependent presentation of endogenous ligands or exogenously added self ligand isoglobotrihexosylceramide. Collectively, our data demonstrate that the TCR Vbeta domain influences the selection of Valpha14i NKT cells by endogenous ligands, presumably because Vbeta7 confers higher avidity binding.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Mechanisms governing lentivirus integration site selection.

An essential step of the life cycle of retroviruses is the stable insertion of a copy of their DNA genome into the host cell genome, and lentiviruses are no exception. This integration step, catalyzed by the viral-encoded integrase, ensures long-term expression of the viral genes, thus allowing a productive viral replication and rendering retroviral vectors also attractive for the field of gene therapy. At the same time, this ability to integrate into the host genome raises safety concerns regarding the use of retroviral-based gene therapy vectors, due to the genomic locations of integration sites. The availability of the human genome sequence made possible the analysis of the integration site preferences, which revealed to be nonrandom and retrovirus-specific, i.e. all lentiviruses studied so far favor integration in active transcription units, while other retroviruses have a different integration site distribution. Several mechanisms have been proposed that may influence integration targeting, which include (i) chromatin accessibility, (ii) cell cycle effects, and (iii) tethering proteins. Recent data provide evidence that integration site selection can occur via a tethering mechanism, through the recruitment of the lentiviral integrase by the cellular LEDGF/p75 protein, both proteins being the two major players in lentiviral integration targeting.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Analysis and estimative of schistosomiasis prevalence for the state of Minas Gerais, Brazil, using multiple regression with social and environmental spatial data

The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.

Targeted expression of human CD1d in transgenic mice reveals independent roles for thymocytes and thymic APCs in positive and negative selection of Valpha14i NKT cells.

CD1d-dependent invariant Valpha14 (Valpha14i) NKT cells are innate T lymphocytes expressing a conserved semi-invariant TCR, consisting, in mice, of the invariant Valpha14-Jalpha18 TCR alpha-chain paired mostly with Vbeta8.2 and Vbeta7. The cellular requirements for thymic positive and negative selection of Valpha14i NKT cells are only partially understood. Therefore, we generated transgenic mice expressing human CD1d (hCD1d) either on thymocytes, mainly CD4+ CD8+ double positive, or on APCs, the cells implicated in the selection of Valpha14i NKT cells. In the absence of the endogenous mouse CD1d (mCD1d), the expression of hCD1d on thymocytes, but not on APCs, was sufficient to select Valpha14i NKT cells that proved functional when activated ex vivo with the Ag alpha-galactosyl ceramide. Valpha14i NKT cells selected by hCD1d on thymocytes, however, attained lower numbers than in control mice and expressed essentially Vbeta8.2. The low number of Vbeta8.2+ Valpha14i NKT cells selected by hCD1d on thymocytes was not reversed by the concomitant expression of mCD1d, which, instead, restored the development of Vbeta7+ Valpha14i NKT cells. Vbeta8.2+, but not Vbeta7+, NKT cell development was impaired in mice expressing both hCD1d on APCs and mCD1d. Taken together, our data reveal that selective CD1d expression by thymocytes is sufficient for positive selection of functional Valpha14i NKT cells and that both thymocytes and APCs may independently mediate negative selection.

Selection of peptides and synthesis of pentameric peptabody molecules reacting specifically with ErbB-2 receptor.

The HER-2/ErbB-2 oncoprotein is overexpressed in human breast and ovarian adenocarcinomas and is clearly associated with the malignant phenotype. Although no specific ligand for this receptor has been positively identified, ErbB-2 was shown to play a central role in a network of interactions with the related ErbB-1, ErbB-3 and ErbB-4 receptors. We have selected new peptides binding to ErbB-2 extracellular domain protein (ECD) by screening 2 newly developed constrained and unconstrained random hexapeptide phage libraries. Out of 37 phage clones, which bound specifically to ErbB-2 ECD, we found 6 constrained and 10 linear different hexapeptide sequences. Among the latter, 5 consensus motifs, all with a common methionine and a positively charged residue at positions 1 and 3, respectively, were identified. Furthermore, 3 representative hexapeptides were fused to a coiled-coil pentameric recombinant protein to form the so-called peptabodies recently developed in our laboratory. The 3 peptabodies bound specifically to the ErbB-2 ECD, as determined by enzyme-linked immunosorbent assay and BIAcore analysis and to tumor cells overexpressing ErbB-2, as shown by flow cytometry. Interestingly, one of the free selected linear peptides and all 3 peptabodies inhibited the proliferation of tumor cells overexpressing ErbB-2. In conclusion, a novel type of ErbB-2-specific ligand is described that might complement presently available monoclonal antibodies.

In Vivo Selection of Fluoroquinolone-Resistant Escherichia coli Isolates Expressing Plasmid-Mediated Quinolone Resistance and Expanded-Spectrum β-Lactamase

A ciprofloxacin-resistant Escherichia coli isolate, isolate 1B, was obtained from a urinary specimen of a Canadian patient treated with norfloxacin for infection due to a ciprofloxacin-susceptible isolate, isolate 1A. Both isolates harbored a plasmid-encoded sul1-type integron with qnrA1 and blaVEB-1 genes. Isolate 1B had amino acid substitutions in gyrase and topoisomerase.

Prevalent role of TCR alpha-chain in the selection of the preimmune repertoire specific for a human tumor-associated self-antigen.

The specificity of recognition of pMHC complexes by T lymphocytes is determined by the V regions of the TCR alpha- and beta-chains. Recent experimental evidence has suggested that Ag-specific TCR repertoires may exhibit a more V alpha- than V beta-restricted usage. Whether V alpha usage is narrowed during immune responses to Ag or if, on the contrary, restricted V alpha usage is already defined at the early stages of TCR repertoire selection, however, has remained unexplored. Here, we analyzed V and CDR3 TCR regions of single circulating naive T cells specifically detected ex vivo and isolated with HLA-A2/melan-A peptide multimers. Similarly to what was previously observed for melan-A-specific Ag-experienced T cells, we found a relatively wide V beta usage, but a preferential V alpha 2.1 usage. Restricted V alpha 2.1 usage was also found among single CD8(+) A2/melan-A multimer(+) thymocytes, indicating that V alpha-restricted selection takes place in the thymus. V alpha 2.1 usage, however, was independent from functional avidity of Ag recognition. Thus, interaction of the pMHC complex with selected V alpha-chains contributes to set the broad Ag specificity, as underlined by preferential binding of A2/melan-A multimers to V alpha 2.1-bearing TCRs, whereas functional outcomes result from the sum of these with other interactions between pMHC complex and TCR.

Video-assisted thoracoscopic surgery lobectomy or open lobectomy for non-small-cell lung cancer? Minimizing selection bias in observational studies.

PURPOSE OF REVIEW: Adherence to preventive measures and prescribed medications is the cornerstone of the successful management of hypertension. The role of adherence is particularly important when treatments are not providing the expected clinical results, for example, in patients with resistant hypertension. The goal of this article is to review the recent observations regarding drug adherence in resistant hypertension. RECENT FINDINGS: Today, the role of drug adherence as a potential cause of resistant hypertension is largely underestimated. Most studies suggest that a low adherence to the prescribed medications can affect up to 50% of patients with resistant hypertension.A good adherence to therapy is generally associated with an improved prognosis. Nonetheless, adherence should probably not be a target for treatment per se because data on adherence should always be interpreted in the view of clinical results. In our opinion, the availability of reliable data on drug adherence would be a major help for physicians to manage patients apparently resistant to therapy. SUMMARY: The actual development of new drugs for hypertension is slow. Thus, focusing on drug adherence to the drugs available is an important way to improve blood pressure control in the population. More emphasis should be put on measuring drug adherence in patients with resistant hypertension to avoid costly investigations and treatments.

Extensive variation at MHC DRB in the New Zealand sea lion (Phocarctos hookeri) provides evidence for balancing selection.

Marine mammals are often reported to possess reduced variation of major histocompatibility complex (MHC) genes compared with their terrestrial counterparts. We evaluated diversity at two MHC class II B genes, DQB and DRB, in the New Zealand sea lion (Phocarctos hookeri, NZSL) a species that has suffered high mortality owing to bacterial epizootics, using Sanger sequencing and haplotype reconstruction, together with next-generation sequencing. Despite this species' prolonged history of small population size and highly restricted distribution, we demonstrate extensive diversity at MHC DRB with 26 alleles, whereas MHC DQB is dimorphic. We identify four DRB codons, predicted to be involved in antigen binding, that are evolving under adaptive evolution. Our data suggest diversity at DRB may be maintained by balancing selection, consistent with the role of this locus as an antigen-binding region and the species' recent history of mass mortality during a series of bacterial epizootics. Phylogenetic analyses of DQB and DRB sequences from pinnipeds and other carnivores revealed significant allelic diversity, but little phylogenetic depth or structure among pinniped alleles; thus, we could neither confirm nor refute the possibility of trans-species polymorphism in this group. The phylogenetic pattern observed however, suggests some significant evolutionary constraint on these loci in the recent past, with the pattern consistent with that expected following an epizootic event. These data may help further elucidate some of the genetic factors underlying the unusually high susceptibility to bacterial infection of the threatened NZSL, and help us to better understand the extent and pattern of MHC diversity in pinnipeds.