936 resultados para Perineural invasion


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Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of affected sectors and the relative rarity of high-impact species.

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The author describes his escape from Nazi Germany to France together with his mother. He volunteered for the French army (Defense Nationale), but his application was rejected. After the outbreak of the war Schoenfeldt was interned in Antibes and Les Milles. Recollections of life in the internment camps. Lack of basic hygienic conditions. German invasion of France. Escape from the invading German army. Reunion with his mother. Fervent endeavors to leave France for Spain in order to escape another internment. Escape with his 76 year old mother via the Pyrenees. Arrival in Lisbon. Exit visa for America. In 1941 Herbert Schoenfeldt left with his mother for the United States.

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The memoirs were written in New York in 1999. Description of the childhood of Rosemarie Schink, the author's mother, in the rural area of Meuszelwitz, Thuringia, where her grandfather, Franz Harnish, was the station manager. Rosemarie Schink eloped to Amsterdam with the Dutch Jew Judah Easel in 1931. The marriage fall apart soon thereafter, and Rosemarie was taken under the wings of her father-in-law Joseph Easel. The couple stayed officially married until their divorce in 1940, and Rosemarie worked in the pension of her in-laws. She had a long affair with the German Jew Guy Weinberg from Hamburg, a married man who was living in Amsterdam and became the father of her daughter Julia. Description of the Weinberg family history. In 1941 Rosemarie Schink married the Austrian Jewish lawyer Herbert Mauthner, the eldest of three sons of Robert Mauthner, director of the Bodenbacher-Dux Railroad and Melanie Leitner, daughter of a wealthy family from Veszprem, Hungary. Mauthner family history and nobility of the Leitner family, who were admitted to the court of the Austrian Kaiser Franz Joseph.

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The memoirs were written in 2000 in California and contains some of the author's diary entries during the years of the family's emigration and reminiscences of the author's father. Detailed description of family history going back to the early 19th century. The author's grandfather Moses Stern had a rawproduct business in Gelsenkirchen, Westphalia. His father Max Stern took his graduate exam (Abitur) at the Jacobsohn boarding school in 1904 and was sent to a business school in Brussles, Belgium. Work in the family business M. Stern AG. World War One and rise of the family business with branches throughout Germany and offices in New York, London, Milan and Stockholm. Due to political unrest at the end of the war the business administration moved to Essen. Description of the family background of Beate Herzberg, the author's mother. Courtship of his parents and marriage in 1922. Birth of his sister Annelore in 1923. Martin Stern was born in 1924. Description of the family household and domestic life in a well-to-do family the 1920s. Friday visits to the synagogue and celebration of Jewish holidays. Vacations at the North sea and skiinig in the Alps. Martin attended a Jewish elementary school. Rising National Socialism. After Hitler came to power in 1933 the author's father immediately started preparations for the family's emigration, but was persuaded to stay by his family. Life under National Socialism. Martin attended Gymnasium and was one of only two Jewish students in his class. Antisemitic incidents. Private lessons in piano and Hebrew. Bar Mitzvah in 1937. Recollections of performances of the Kulturbund.

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Deaths of mother and father; memories of early childhood in Vienna; Anschluss in 1938; arrest of mother, father and grandmother; flight with family to Belgium; internment of father; flight of father to England; attempted flight through France after German invasion of Belgium; return to Belgium; arrest of author with sister; escape to Ardennes; work with resistance; end of war; reunion with mother and grandmother in Brussels; life in Belgium after the war; illegal voyage to Israel; marriage; pregnancy; work in clinic; work in kibbutz; birth of child; commencement of psychoanalysis.

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A recent study by Korolev et al. [Nat. Rev. Cancer, 14:371–379, 2014] evidences that the Allee effect—in its strong form, the requirement of a minimum density for cell growth—is important in the spreading of cancerous tumours. We present one of the first mathematical models of tumour invasion that incorporates the Allee effect. Based on analysis of the existence of travelling wave solutions to this model, we argue that it is an improvement on previous models of its kind. We show that, with the strong Allee effect, the model admits biologically relevant travelling wave solutions, with well-defined edges. Furthermore, we uncover an experimentally observed biphasic relationship between the invasion speed of the tumour and the background extracellular matrix density.

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Postglacial climate changes and vegetation responses were studied using a combination of biological and physical indicators preserved in lake sediments. Low-frequency trends, high-frequency events and rapid shifts in temperature and moisture balance were probed using pollen-based quantitative temperature reconstructions and oxygen-isotopes from authigenic carbonate and aquatic cellulose, respectively. Pollen and plant macrofossils were employed to shed light on the presence and response rates of plant populations in response to climate changes, particularly focusing on common boreal and temperate tree species. Additional geochemical and isotopic tracers facilitated the interpretation of pollen- and oxygen-isotope data. The results show that the common boreal trees were present in the Baltic region (~55°N) during the Lateglacial, which contrasts with the traditional view of species refuge locations in the south-European peninsulas during the glacial/interglacial cycles. The findings of this work are in agreement with recent paleoecological and genetic evidence suggesting that scattered populations of tree species persisted at higher latitudes, and that these taxa were likely limited to boreal trees. Moreover, the results demonstrate that stepwise changes in plant communities took place in concert with major climate fluctuations of the glacial/interglacial transition. Postglacial climate trends in northern Europe were characterized by rise, maxima and fall in temperatures and related changes in moisture balance. Following the deglaciation of the Northern Hemisphere and the early Holocene reorganization of the ice-ocean-atmosphere system, the long-term temperature trends followed gradually decreasing summer insolation. The early Holocene (~11,700-8000 cal yr BP) was overall cool, moist and oceanic, although the earliest Holocene effective humidity may have been low particularly in the eastern part of northern Europe. The gradual warming trend was interrupted by a cold event ~8200 cal yr BP. The maximum temperatures, ~1.5-3.0°C above modern values, were attained ~8000-4000 cal yr BP. This mid-Holocene peak warmth was coupled with low lake levels, low effective humidity and summertime drought. The late Holocene (~4000 cal yr BP-present) was characterized by gradually decreasing temperatures, higher lake levels and higher effective humidity. Moreover, the gradual trends of the late Holocene were probably superimposed by higher-frequency variability. The spatial variability of the Holocene temperature and moisture balance patterns were tentatively attributed to the differing heat capacities of continents and oceans, changes in atmospheric circulation modes and position of sites and subregions with respect to large water bodies and topographic barriers. The combination of physical and biological proxy archives is a pivotal aspect of this work, because non-climatic factors, such as postglacial migration, disturbances and competitive interactions, can influence reshuffling of vegetation and hence, pollen-based climate reconstructions. The oxygen-isotope records and other physical proxies presented in this work manifest that postglacial climate changes were the main driver of the establishment and expansion of temperate and boreal tree populations, and hence, large-scale and long-term vegetation patterns were in dynamic equilibrium with climate. A notable exception to this pattern may be the postglacial invasion of Norway spruce and the related suppression of mid-Holocene temperate forest. This salient step in north-European vegetation history, the development of the modern boreal ecosystem, cannot be unambiguously explained by current evidence of postglacial climate changes. The results of this work highlight that plant populations, including long-lived trees, may be able to respond strikingly rapidly to changes in climate. Moreover, interannual and seasonal variation and extreme events can exert an important influence on vegetation reshuffling. Importantly, the studies imply that the presence of diffuse refuge populations or local stands among the prevailing vegetation may have provided the means for extraordinarily rapid vegetation responses. Hence, if scattered populations are not provided and tree populations are to migrate long distances, their capacity to keep up with predicted rates of future climate change may be lower than previously thought.

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The future use of genetically modified (GM) plants in food, feed and biomass production requires a careful consideration of possible risks related to the unintended spread of trangenes into new habitats. This may occur via introgression of the transgene to conventional genotypes, due to cross-pollination, and via the invasion of GM plants to new habitats. Assessment of possible environmental impacts of GM plants requires estimation of the level of gene flow from a GM population. Furthermore, management measures for reducing gene flow from GM populations are needed in order to prevent possible unwanted effects of transgenes on ecosystems. This work develops modeling tools for estimating gene flow from GM plant populations in boreal environments and for investigating the mechanisms of the gene flow process. To describe spatial dimensions of the gene flow, dispersal models are developed for the local and regional scale spread of pollen grains and seeds, with special emphasis on wind dispersal. This study provides tools for describing cross-pollination between GM and conventional populations and for estimating the levels of transgenic contamination of the conventional crops. For perennial populations, a modeling framework describing the dynamics of plants and genotypes is developed, in order to estimate the gene flow process over a sequence of years. The dispersal of airborne pollen and seeds cannot be easily controlled, and small amounts of these particles are likely to disperse over long distances. Wind dispersal processes are highly stochastic due to variation in atmospheric conditions, so that there may be considerable variation between individual dispersal patterns. This, in turn, is reflected to the large amount of variation in annual levels of cross-pollination between GM and conventional populations. Even though land-use practices have effects on the average levels of cross-pollination between GM and conventional fields, the level of transgenic contamination of a conventional crop remains highly stochastic. The demographic effects of a transgene have impacts on the establishment of trangenic plants amongst conventional genotypes of the same species. If the transgene gives a plant a considerable fitness advantage in comparison to conventional genotypes, the spread of transgenes to conventional population can be strongly increased. In such cases, dominance of the transgene considerably increases gene flow from GM to conventional populations, due to the enhanced fitness of heterozygous hybrids. The fitness of GM plants in conventional populations can be reduced by linking the selectively favoured primary transgene to a disfavoured mitigation transgene. Recombination between these transgenes is a major risk related to this technique, especially because it tends to take place amongst the conventional genotypes and thus promotes the establishment of invasive transgenic plants in conventional populations.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Bactrocera frauenfeldi (Schiner), the ‘mango fruit fly’, is a horticultural pest originating from the Papua New Guinea region. It was first detected in Australia on Cape York Peninsula in north Queensland in 1974 and had spread to Cairns by 1994 and Townsville by 1997. Bactrocera frauenfeldi has not been recorded further south since then despite its invasive potential, an absence of any controls and an abundance of hosts in southern areas. Analysis of cue-lure trapping data from 1997 to 2012 in relation to environmental variables shows that the distribution of B. frauenfeldi in Queensland correlates to locations with a minimum temperature for the coldest month >13.2°C, annual temperature range <19.3°C, mean temperature of the driest quarter >20.2°C, precipitation of the wettest month >268 mm, precipitation of the wettest quarter >697 mm, temperature seasonality <30.9°C (i.e. lower temperature variability) and areas with higher human population per square kilometre. Annual temperature range was the most important variable in predicting this species' distribution. Predictive distribution maps based on an uncorrelated subset of these variables reasonably reflected the current distribution of this species in northern Australia and predicted other areas in the world potentially at risk from invasion by this species. This analysis shows that the distribution of B. frauenfeldi in Australia is correlated to certain environmental variables that have most likely limited this species' spread southward in Queensland. This is of importance to Australian horticulture in demonstrating that B. frauenfeldi is unlikely to establish in horticultural production areas further south than Townsville.

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Much of our understanding and management of ecological processes requires knowledge of the distribution and abundance of species. Reliable abundance or density estimates are essential for managing both threatened and invasive populations, yet are often challenging to obtain. Recent and emerging technological advances, particularly in unmanned aerial vehicles (UAVs), provide exciting opportunities to overcome these challenges in ecological surveillance. UAVs can provide automated, cost-effective surveillance and offer repeat surveys for pest incursions at an invasion front. They can capitalise on manoeuvrability and advanced imagery options to detect species that are cryptic due to behaviour, life-history or inaccessible habitat. UAVs may also cause less disturbance, in magnitude and duration, for sensitive fauna than other survey methods such as transect counting by humans or sniffer dogs. The surveillance approach depends upon the particular ecological context and the objective. For example, animal, plant and microbial target species differ in their movement, spread and observability. Lag-times may exist between a pest species presence at a site and its detectability, prompting a need for repeat surveys. Operationally, however, the frequency and coverage of UAV surveys may be limited by financial and other constraints, leading to errors in estimating species occurrence or density. We use simulation modelling to investigate how movement ecology should influence fine-scale decisions regarding ecological surveillance using UAVs. Movement and dispersal parameter choices allow contrasts between locally mobile but slow-dispersing populations, and species that are locally more static but invasive at the landscape scale. We find that low and slow UAV flights may offer the best monitoring strategy to predict local population densities in transects, but that the consequent reduction in overall area sampled may sacrifice the ability to reliably predict regional population density. Alternative flight plans may perform better, but this is also dependent on movement ecology and the magnitude of relative detection errors for different flight choices. Simulated investigations such as this will become increasingly useful to reveal how spatio-temporal extent and resolution of UAV monitoring should be adjusted to reduce observation errors and thus provide better population estimates, maximising the efficacy and efficiency of unmanned aerial surveys.

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Depending on their developmental stage in the life cycle, malaria parasites develop within or outside host cells, and in extremely diverse contexts such as the vertebrate liver and blood circulation, or the insect midgut and hemocoel. Cellular and molecular mechanisms enabling the parasite to sense and respond to the intra- and the extra-cellular environments are therefore key elements for the proliferation and transmission of Plasmodium, and therefore are, from a public health perspective, strategic targets in the fight against this deadly disease. The MALSIG consortium, which was initiated in February 2009, was designed with the primary objective to integrate research ongoing in Europe and India on i) the properties of Plasmodium signalling molecules, and ii) developmental processes occurring at various points of the parasite life cycle. On one hand, functional studies of individual genes and their products in Plasmodium falciparum (and in the technically more manageable rodent model Plasmodium berghei) are providing information on parasite protein kinases and phosphatases, and of the molecules governing cyclic nucleotide metabolism and calcium signalling. On the other hand, cellular and molecular studies are elucidating key steps of parasite development such as merozoite invasion and egress in blood and liver parasite stages, control of DNA replication in asexual and sexual development, membrane dynamics and trafficking, production of gametocytes in the vertebrate host and further parasite development in the mosquito. This article, which synthetically reviews such signalling molecules and cellular processes, aims to provide a glimpse of the global frame in which the activities of the MALSIG consortium will develop over the next three years.

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Incursions of plant pests and diseases pose serious threats to food security, agricultural productivity and the natural environment. One of the challenges in confidently delimiting and eradicating incursions is how to choose from an arsenal of surveillance and quarantine approaches in order to best control multiple dispersal pathways. Anthropogenic spread (propagules carried on humans or transported on produce or equipment) can be controlled with quarantine measures, which in turn can vary in intensity. In contrast, environmental spread processes are more difficult to control, but often have a temporal signal (e.g. seasonality) which can introduce both challenges and opportunities for surveillance and control. This leads to complex decisions regarding when, where and how to search. Recent modelling investigations of surveillance performance have optimised the output of simulation models, and found that a risk-weighted randomised search can perform close to optimally. However, exactly how quarantine and surveillance strategies should change to reflect different dispersal modes remains largely unaddressed. Here we develop a spatial simulation model of a plant fungal-pathogen incursion into an agricultural region, and its subsequent surveillance and control. We include structural differences in dispersal via the interplay of biological, environmental and anthropogenic connectivity between host sites (farms). Our objective was to gain broad insights into the relative roles played by different spread modes in propagating an invasion, and how incorporating knowledge of these spread risks may improve approaches to quarantine restrictions and surveillance. We find that broad heuristic rules for quarantine restrictions fail to contain the pathogen due to residual connectivity between sites, but surveillance measures enable early detection and successfully lead to suppression of the pathogen in all farms. Alternative surveillance strategies attain similar levels of performance by incorporating environmental or anthropogenic dispersal risk in the prioritisation of sites. Our model provides the basis to develop essential insights into the effectiveness of different surveillance and quarantine decisions for fungal pathogen control. Parameterised for authentic settings it will aid our understanding of how the extent and resolution of interventions should suitably reflect the spatial structure of dispersal processes.

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Mammalian heparanase is an endo-β-glucuronidase associated with cell invasion in cancer metastasis, angiogenesis and inflammation. Heparanase cleaves heparan sulfate proteoglycans in the extracellular matrix and basement membrane, releasing heparin/heparan sulfate oligosaccharides of appreciable size. This in turn causes the release of growth factors, which accelerate tumor growth and metastasis. Heparanase has two glycosaminoglycan-binding domains; however, no three-dimensional structure information is available for human heparanase that can provide insights into how the two domains interact to degrade heparin fragments. We have constructed a new homology model of heparanase that takes into account the most recent structural and bioinformatics data available. Heparin analogs and glycosaminoglycan mimetics were computationally docked into the active site with energetically stable ring conformations and their interaction energies were compared. The resulting docked structures were used to propose a model for substrates and conformer selectivity based on the dimensions of the active site. The docking of substrates and inhibitors indicates the existence of a large binding site extending at least two saccharide units beyond the cleavage site (toward the nonreducing end) and at least three saccharides toward the reducing end (toward heparin-binding site 2). The docking of substrates suggests that heparanase recognizes the N-sulfated and O-sulfated glucosamines at subsite +1 and glucuronic acid at the cleavage site, whereas in the absence of 6-O-sulfation in glucosamine, glucuronic acid is docked at subsite +2. These findings will help us to focus on the rational design of heparanase-inhibiting molecules for anticancer drug development by targeting the two heparin/heparan sulfate recognition domains.