bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring of intra‐operative nociception: skin conductance and surgical stress index versus stress hormone plasma levels
Authors: Ledowski T. , Pascoe E. , Ang B. , Schmarbeck T. , Clarke M.W. , Fuller C. , Kapoor V. 
Published: August 2010

Summary‘Surgical Stress Index’ and the ‘Number of Fluctuations in Skin Conductance.s−1, use different methods to analyse sympathetic tone and so provide an estimate of peri‐operative analgesia. The aim of our study was to investigate the relationship between these methods and stress hormone plasma levels. In 20 patients scheduled for elective surgery, values of the two methods, mean arterial blood pressure, heart rate and blood samples (to measure plasma levels of adrenaline, noradrenaline, adrenocorticotrophic hormone and cortisol) were obtained at five time points. Changes in Surgical Stress Index and the Number of Fluctuations in Skin Conductance.s−1 only partially reflected changes in plasma noradrenaline levels. Surgical Stress Index, heart rate and blood pressure, but not the ‘Number of Fluctuations in Skin Conductance.s−1 changed in response to changes in depth of analgesia by showing significant differences between before and after a bolus of fentanyl. However, the overall predictive ability of both methods was poor.
Landscape influences on genetic differentiation among bull trout populations in a stream‐lake network
Authors: MEEUWIG MICHAEL H. , GUY CHRISTOPHER S. , KALINOWSKI STEVEN T. , FREDENBERG WADE A. 
Published: August 2010

AbstractThis study examined the influence of landscape heterogeneity on genetic differentiation between migratory bull trout (Salvelinus confluentus) populations in Glacier National Park, Montana. An information‐theoretic approach was used to compare different conceptual models of dispersal associated with barriers, different models of isolation by distance, and the combined effects of barriers, waterway distance, patch size, and intra‐ and inter‐drainage distribution of populations on genetic differentiation between bull trout populations. The effect of distance between populations on genetic differentiation was best explained by partitioning the effects of mainstem and tributary stream sections. Models that categorized barriers as having a one‐way effect (i.e. allowed downstream dispersal) or a two‐way effect were best supported. Additionally, patch size and the distribution of populations among drainages influenced genetic differentiation. Genetic differentiation between bull trout populations in Glacier National Park is linked to landscape features that restrict dispersal. However, this analysis illustrates that modelling variability within landscape features, such as dispersal corridors, will benefit landscape genetic analyses. Additionally, the framework used for evaluating the effects of barriers must consider not just barrier presence, but also potential asymmetries in barrier effects with respect to the organism under investigation.
Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis
Authors: SPEAR STEPHEN F. , BALKENHOL NIKO , FORTIN MARIE‐JOSÉE , MCRAE BRAD H. , SCRIBNER KIM 
Published: August 2010

AbstractMeasures of genetic structure among individuals or populations collected at different spatial locations across a landscape are commonly used as surrogate measures of functional (i.e. demographic or genetic) connectivity. In order to understand how landscape characteristics influence functional connectivity, resistance surfaces are typically created in a raster GIS environment. These resistance surfaces represent hypothesized relationships between landscape features and gene flow, and are based on underlying biological functions such as relative abundance or movement probabilities in different land cover types. The biggest challenge for calculating resistance surfaces is assignment of resistance values to different landscape features. Here, we first identify study objectives that are consistent with the use of resistance surfaces and critically review the various approaches that have been used to parameterize resistance surfaces and select optimal models in landscape genetics. We then discuss the biological assumptions and considerations that influence analyses using resistance surfaces, such as the relationship between gene flow and dispersal, how habitat suitability may influence animal movement, and how resistance surfaces can be translated into estimates of functional landscape connectivity. Finally, we outline novel approaches for creating optimal resistance surfaces using either simulation or computational methods, as well as alternatives to resistance surfaces (e.g. network and buffered paths). These approaches have the potential to improve landscape genetic analyses, but they also create new challenges. We conclude that no single way of using resistance surfaces is appropriate for every situation. We suggest that researchers carefully consider objectives, important biological assumptions and available parameterization and validation techniques when planning landscape genetic studies.
Landscape genetics: where are we now?
Authors: STORFER ANDREW , MURPHY MELANIE A. , SPEAR STEPHEN F. , HOLDEREGGER ROLF , WAITS LISETTE P. 
Published: August 2010

AbstractLandscape genetics has seen rapid growth in number of publications since the term was coined in 2003. An extensive literature search from 1998 to 2008 using keywords associated with landscape genetics yielded 655 articles encompassing a vast array of study organisms, study designs and methodology. These publications were screened to identify 174 studies that explicitly incorporated at least one landscape variable with genetic data. We systematically reviewed this set of papers to assess taxonomic and temporal trends in: (i) geographic regions studied; (ii) types of questions addressed; (iii) molecular markers used; (iv) statistical analyses used; and (v) types and nature of spatial data used. Overall, studies have occurred in geographic regions proximal to developed countries and more commonly in terrestrial vs. aquatic habitats. Questions most often focused on effects of barriers and/or landscape variables on gene flow. The most commonly used molecular markers were microsatellites and amplified fragment length polymorphism (AFLPs), with AFLPs used more frequently in plants than animals. Analysis methods were dominated by Mantel and assignment tests. We also assessed differences among journals to evaluate the uniformity of reporting and publication standards. Few studies presented an explicit study design or explicit descriptions of spatial extent. While some landscape variables such as topographic relief affected most species studied, effects were not universal, and some species appeared unaffected by the landscape. Effects of habitat fragmentation were mixed, with some species altering movement paths and others unaffected. Taken together, although some generalities emerged regarding effects of specific landscape variables, results varied, thereby reinforcing the need for species‐specific work. We conclude by: highlighting gaps in knowledge and methodology, providing guidelines to authors and reviewers of landscape genetics studies, and suggesting promising future directions of inquiry.
Modelling functional landscape connectivity from genetic population structure: a new spatially explicit approach
Authors: BRAUNISCH VERONIKA , SEGELBACHER GERNOT , HIRZEL ALEXANDRE H. 
Published: August 2010

AbstractFunctional connectivity between spatially disjoint habitat patches is a key factor for the persistence of species in fragmented landscapes. Modelling landscape connectivity to identify potential dispersal corridors requires information about those landscape features affecting dispersal. Here we present a new approach using spatial and genetic data of a highly fragmented population of capercaillie (Tetrao urogallus) in the Black Forest, Germany, to investigate effects of landscape structure on gene flow and to parameterize a spatially explicit corridor model for conservation purposes. Mantel tests and multiple regressions on distance matrices were employed to detect and quantify the effect of different landscape features on relatedness among individuals, while controlling for the effect of geographic distance. We extrapolated the results to an area‐wide landscape permeability map and developed a new corridor model that incorporates stochasticity in simulating animal movement. The model was evaluated using both a partition of the data previously set apart and independent observation data of dispersing birds. Most land cover variables (such as coniferous forest, forest edges, agricultural land, roads, settlements) and one topographic variable (topographic exposure) were significantly correlated with gene flow. Although inter‐individual relatedness inherently varies greatly and the variance explained by geographic distance and landscape structure was low, the permeability map and the corridor model significantly explained relatedness in the validation data and the spatial distribution of dispersing birds. Thus, landscape structure measurably affected within‐population gene flow in the study area. By converting these effects into spatially explicit information our model enables localizing priority areas for the preservation or restoration of metapopulation connectivity.
Perspectives on the use of landscape genetics to detect genetic adaptive variation in the field
Authors: MANEL STÉPHANIE , JOOST STÉPHANE , EPPERSON BRYAN K. , HOLDEREGGER ROLF , STORFER ANDREW , ROSENBERG MICHAEL S. , SCRIBNER KIM T. , BONIN AURÉLIE , FORTIN MARIE‐JOSÉE 
Published: August 2010

AbstractUnderstanding the genetic basis of species adaptation in the context of global change poses one of the greatest challenges of this century. Although we have begun to understand the molecular basis of adaptation in those species for which whole genome sequences are available, the molecular basis of adaptation is still poorly understood for most non‐model species. In this paper, we outline major challenges and future research directions for correlating environmental factors with molecular markers to identify adaptive genetic variation, and point to research gaps in the application of landscape genetics to real‐world problems arising from global change, such as the ability of organisms to adapt over rapid time scales. High throughput sequencing generates vast quantities of molecular data to address the challenge of studying adaptive genetic variation in non‐model species. Here, we suggest that improvements in the sampling design should consider spatial dependence among sampled individuals. Then, we describe available statistical approaches for integrating spatial dependence into landscape analyses of adaptive genetic variation.
Gene movement and genetic association with regional climate gradients in California valley oak (Quercus lobataNée) in the face of climate change
Authors: SORK VICTORIA L. , DAVIS FRANK W. , WESTFALL ROBERT , FLINT ALAN , IKEGAMI MAKIHIKO , WANG HONGFANG , GRIVET DELPHINE 
Published: August 2010

AbstractRapid climate change jeopardizes tree populations by shifting current climate zones. To avoid extinction, tree populations must tolerate, adapt, or migrate. Here we investigate geographic patterns of genetic variation in valley oak,Quercus lobataNée, to assess how underlying genetic structure of populations might influence this species’ ability to survive climate change. First, to understand how genetic lineages shape spatial genetic patterns, we examine historical patterns of colonization. Second, we examine the correlation between multivariate nuclear genetic variation and climatic variation. Third, to illustrate how geographic genetic variation could interact with regional patterns of 21st Century climate change, we produce region‐specific bioclimatic distributions of valley oak using Maximum Entropy (MAXENT) models based on downscaled historical (1971–2000) and future (2070–2100) climate grids. Future climatologies are based on a moderate‐high (A2) carbon emission scenario and two different global climate models. Chloroplast markers indicate historical range‐wide connectivity via colonization, especially in the north. Multivariate nuclear genotypes show a strong association with climate variation that provides opportunity for local adaptation to the conditions within their climatic envelope. Comparison of regional current and projected patterns of climate suitability indicates that valley oaks grow in distinctly different climate conditions in different parts of their range. Our models predict widely different regional outcomes from local displacement of a few kilometres to hundreds of kilometres. We conclude that the relative importance of migration, adaptation, and tolerance are likely to vary widely for populations among regions, and that late 21st Century conditions could lead to regional extinctions.
Spatial modelling and landscape‐level approaches for visualizing intra‐specific variation
Authors: THOMASSEN HENRI A. , CHEVIRON ZACHARY A. , FREEDMAN ADAM H. , HARRIGAN RYAN J. , WAYNE ROBERT K. , SMITH THOMAS B. 
Published: August 2010

AbstractSpatial analytical methods have been used by biologists for decades, but with new modelling approaches and data availability their application is accelerating. While early approaches were purely spatial in nature, it is now possible to explore the underlying causes of spatial heterogeneity of biological variation using a wealth of environmental data, especially from satellite remote sensing. Recent methods can not only make inferences regarding spatial relationships and the causes of spatial heterogeneity, but also create predictive maps of patterns of biological variation under changing environmental conditions. Here, we review the methods involved in making continuous spatial predictions from biological variation using spatial and environmental predictor variables, provide examples of their use and critically evaluate the advantages and limitations. In the final section, we discuss some of the key challenges and opportunities for future work.
Considering spatial and temporal scale in landscape‐genetic studies of gene flow
Authors: ANDERSON COREY DEVIN , EPPERSON BRYAN K. , FORTIN MARIE‐JOSÉE , HOLDEREGGER ROLF , JAMES PATRICK M. A. , ROSENBERG MICHAEL S. , SCRIBNER KIM T. , SPEAR STEPHEN 
Published: August 2010

AbstractLandscape features exist at multiple spatial and temporal scales, and these naturally affect spatial genetic structure and our ability to make inferences about gene flow. This article discusses how decisions about sampling of genotypes (including choices about analytical methods and genetic markers) should be driven by the scale of spatial genetic structure, the time frame that landscape features have existed in their current state, and all aspects of a species’ life history. Researchers should use caution when making inferences about gene flow, especially when the spatial extent of the study area is limited. The scale of sampling of the landscape introduces different features that may affect gene flow. Sampling grain should be smaller than the average home‐range size or dispersal distance of the study organism and, for raster data, existing research suggests that simplifying the thematic resolution into discrete classes may result in low power to detect effects on gene flow. Therefore, the methods used to characterize the landscape between sampling sites may be a primary determinant for the spatial scale at which analytical results are applicable, and the use of only one sampling scale for a particular statistical method may lead researchers to overlook important factors affecting gene flow. The particular analytical technique used to correlate landscape data and genetic data may also influence results; common landscape‐genetic methods may not be suitable for all study systems, particularly when the rate of landscape change is faster than can be resolved by common molecular markers.
Genetic discontinuities and disequilibria in recently established populations of the plant pathogenic fungus Mycosphaerella fijiensis
Authors: HALKETT F. , COSTE D. , RIVAS PLATERO G. G. , ZAPATER M. F. , ABADIE C. , CARLIER J. 
Published: August 2010

AbstractDispersal processes of fungal plant pathogens can be inferred from analysis of spatial genetic structures resulting from recent range expansion. The relative importance of long‐distance dispersal (LDD) events vs. gradual dispersal in shaping population structures depends on the geographical scale considered. The fungus Mycosphaerella fijiensis, pathogenic on banana, is an example of a recent worldwide epidemic. Founder effects in this species were detected at both global and continental scale, suggesting stochastic spread of the disease through LDD events. In this study, we analysed the structure of M. fijiensis populations in two recently (∼1979–1980) colonized areas in Costa Rica and Cameroon. Isolates collected in 10–15 sites distributed along a ∼250‐ to 300‐ km‐long transect in each country were analysed using 19 microsatellite markers. We detected low‐to‐moderate genetic differentiation among populations in both countries and isolation by distance in Cameroon. Combined with historical data, these observations suggest continuous range expansion at the scale of banana‐production area through gradual dispersal of spores. However, both countries displayed specific additional signatures of colonization: a sharp discontinuity in gene frequencies was observed along the Cameroon transect, while the Costa Rican populations seemed not yet to have reached genetic equilibrium. These differences in the genetic characteristics of M. fijiensis populations in two recently colonized areas are discussed in the light of historical data on disease spread and ecological data on landscape features.
The BCCT family of carriers: from physiology to crystal structure
Authors: Ziegler Christine , Bremer Erhard , Krämer Reinhard 
Published: August 2010

SummaryIncreases in the environmental osmolarity are key determinants for the growth of microorganisms. To ensure a physiologically acceptable level of cellular hydration and turgor at high osmolarity, many bacteria accumulate compatible solutes. Osmotically controlled uptake systems allow the scavenging of these compounds from scarce environmental sources as effective osmoprotectants. A number of these systems belong to the BCCT family (betaine‐choline‐carnitine‐transporter), sodium‐ or proton‐coupled transporters (e.g. BetP and BetT respectively) that are ubiquitous in microorganisms. The BCCT family also contains CaiT, an l‐carnitine/γ‐butyrobetaine antiporter that is not involved in osmotic stress responses. The glycine betaine transporter BetP from Corynebacterium glutamicum is a representative for osmoregulated symporters of the BCCT family and functions both as an osmosensor and osmoregulator. The crystal structure of BetP in an occluded conformation in complex with its substrate glycine betaine and two crystal structures of CaiT in an inward‐facing open conformation in complex with l‐carnitine and γ‐butyrobetaine were reported recently. These structures and the wealth of biochemical data on the activity control of BetP in response to osmotic stress enable a correlation between the sensing of osmotic stress by a transporter protein with the ensuing regulation of transport activity. Molecular determinants governing the high‐affinity binding of the compatible solutes by BetP and CaiT, the coupling in symporters and antiporters, and the osmoregulatory properties are discussed in detail for BetP and various BCCT carriers.
ABI domain‐containing proteins contribute to surface protein display and cell division in Staphylococcus aureus
Authors: Frankel Matthew B. , Wojcik Brandon M. , DeDent Andrea C. , Missiakas Dominique M. , Schneewind Olaf 
Published: August 2010

SummaryThe human pathogen Staphyloccocus aureus requires cell wall anchored surface proteins to cause disease. During cell division, surface proteins with YSIRK signal peptides are secreted into the cross‐wall, a layer of newly synthesized peptidoglycan between separating daughter cells. The molecular determinants for the trafficking of surface proteins are, however, still unknown. We screened mutants with non‐redundant transposon insertions by fluorescence‐activated cell sorting for reduced deposition of protein A (SpA) into the staphylococcal envelope. Three mutants, each of which harboured transposon insertions in genes for transmembrane proteins, displayed greatly reduced envelope abundance of SpA and surface proteins with YSIRK signal peptides. Characterization of the corresponding mutations identified three transmembrane proteins with abortive infectivity (ABI) domains, elements first described in lactococci for their role in phage exclusion. Mutations in genes for ABI domain proteins, designated spdA, spdB and spdC (surface protein display), diminish the expression of surface proteins with YSIRK signal peptides, but not of precursor proteins with conventional signal peptides. spdA, spdB and spdC mutants display an increase in the thickness of cross‐walls and in the relative abundance of staphylococci with cross‐walls, suggesting that spd mutations may represent a possible link between staphylococcal cell division and protein secretion.
Recognition of heptameric seed sequence underlies multi‐target regulation by RybB small RNA in Salmonella enterica
Authors: Balbontín Roberto , Fiorini Francesca , Figueroa‐Bossi Nara , Casadesús Josep , Bossi Lionello 
Published: August 2010

SummaryProkaryotic regulatory small RNAs act by a conserved mechanism and yet display a stunning structural variability. In the present study, we used mutational analysis to dissect the functional anatomy of RybB, a σE‐dependent sRNA that regulates the synthesis of major porins in Escherichia coli and Salmonella. Mutations in the chromosomal rybB locus that altered the expression of an ompC–lac fusion were identified. Some of the mutations cluster within a seven‐nucleotide segment at the 5′ end of the sRNA and affect its ability to pair with a sequence 40 nucleotides upstream from ompC translation start site. Other mutations map near the 3′ end of RybB, destabilizing the sRNA or altering its binding to Hfq. The 5′ end of RybB is also involved in ompD regulation. In this case, the sRNA can choose between two mutually exclusive pairing sites within the translated portion of the mRNA. Some of the RybB 5′ end mutations affect the choice between the two sites, resulting in regulatory responses that diverge from those observed in ompC. Further analysis of RybB target specificity identified chiP (ybfM), a gene encoding an inducible chitoporin, as an additional member of the RybB regulon. Altogether, our results indicate that an heptameric ‘seed’ sequence is sufficient to confer susceptibility to RybB regulation.