Einfluss des Treg-Aktivierungsmarkers GARP auf die Differenzierung und Funktion von T-Zellen

CD4+CD25+FoxP3+ regulatorische T-Zellen (Treg) spielen eine essentielle Rolle bei der Unterdrückung von schädlichen Immunreaktionen. Da aktivierte CD4+ T-Helferzellen auch CD25 und FoxP3 exprimieren, können diese nicht als spezifische Marker zur Identifikation von Treg verwendet werden. Die Analyse der Membranproteinexpression beider Populationen führte zur Identifikation von GARP (glycoprotein A repetitions predominant) als spezifischer Marker auf aktivierten Treg. GARP bindet LAP und TGF-beta, welches für die Unterdrückung von entzündlichen T-Zellantworten von Bedeutung ist. Um die Funktion von GARP unabhängig von Treg zu untersuchen, wurde ein lösliches GARP Protein (sGARP) synthetisiert und sein Effekt auf die Aktivierung und Differenzierung von humanen T-Zellen untersucht. Die Ergebnisse zeigen, dass sGARP die Proliferation von naiven CD4+ T-Zellen supprimiert und zu einer Phosphorylierung von SMAD2/3 sowie zu der Induktion von FoxP3 führt. Zusätzlich inhibiert sGARP die Produktion von Effektorzytokinen wie IL-2 und IFN-gamma. Die Stimulation von naiven CD4+ T-Zellen mit sGARP induziert die Differenzierung zu Treg, welche in Kokultur die Aktivierung von T-Effektorzellen supprimieren. Die Wirkung war vergleichbar in naiven CD4+ und ruhenden CD4+CD45RA+ T-Zellen, konnte aber in differenzierten CD4+CD45RO+ T-Zellen nicht nachgewiesen werden. Die Induktion von FoxP3 und die Phosphorylierung von SMAD2/3 konnte durch eine Blockade des TGF-beta-Signalweges inhibiert werden. Dies lässt vermuten, dass die Funktion von sGARP zumindest teilweise von TGF-beta abhängig ist. Zusätzlich zu seiner passiven Rolle als TGF-beta-Transporter, induzierte sGARP die TGF-beta-Produktion in naiven T-Zellen und trägt so zum Mechanismus der infektiösen Toleranz bei. Des Weiteren fördert die Stimulation von sGARP in Anwesenheit von IL-6 und IL-23 die Differenzierung zu Th17 Zellen. rnNeben dem Einfluss von sGARP auf die Differenzierung von CD4+ T-Zellen, supprimiert sGARP die Proliferation und Granzyme B-Expression in CD8+ T-Zellen. rnFür die Analyse der immunmodulatorischen Funktion von sGARP in vivo wurde ein Modell einer xenogenen GvHD (graft-versus-host disease) verwendet. Der Transfer von humanen PBMC in neugeborene, immundefiziente Rag2-/-gamma-chain-/--Mäuse führt zu einer letalen GvHD, welche durch die Applikation von humanen Treg dosisabhängig unterdrückt werden kann. In diesem Modell konnte die repetitive Gabe von sGARP, ohne zusätzliche Zugabe von Treg, ebenfalls die GvHD unterdrücken. Dies lässt auf einen synergistischen Effekt von sGARP und Treg bei der Suppression inflammatorischer T-Zellantworten schließen. rnZusammengefasst lassen die Ergebnisse auf eine entscheidende Rolle von GARP in der Modulation der peripheren Toleranz folgern und zeigen sGARP als potentes Biological für die Behandlung von unerwünschten inflammatorischen Immunantworten.

Radiation balance of the tropical ocean surface measured during Atlantic Expedition GARP 1974 (Table 1)

The net flux of all irreversible fluxes of radiation and heat crossing the ocean surface is determined for phase III of GATE at position no. 27 (WFS "Planet", FRG). The radiation fluxes have been measured directly, while the heat fluxes have been parameterized with the bulk formula however with bulk coefficients depending on stability. The heat loss of the ocean due to warming of the cooler precipitation is included for the determination of the net flux at the ocean surface. Some examples of hourly mean values of different fluxes during different weather conditions are additionally shown.

The flow of reality’s development: from postmodernism to post-postmodernism in John Irving’s The World According to Garp and Last Night in Twisted River

In this master’s thesis, I examine the development of writer-characters and metafiction from John Irving’s The World According to Garp to Last Night in Twisted River and how this development relates to the development of late twentieth century postmodern literary theory to twenty-first century post-postmodern literary theory. The purpose of my study is to determine how the prominently postmodern feature metafiction, created through the writer-character’s stories-within-stories, has changed in form and function in the two novels published thirty years apart from one another, and what possible features this indicates for future post-postmodern theory. I establish my theoretical framework on the development of metafiction largely on late twentieth-century models of author and authorship as discussed by Roland Barthes, Wayne Booth and Michel Foucault. I base my close analysis of metafiction mostly on Linda Hutcheon’s model of overt and covert metafiction. At the end of my study, I examine Irving’s later novel through Suzanne Rohr’s models of reality constitution and fictional reality. The analysis of the two novels focuses on excerpts that feature the writer-characters, their stories-within-stories and the novels’ other characters and the narrators’ evaluations of these two. I draw examples from both novels, but I illustrate my choice of focus on the novels at the beginning of each section. Through this, I establish a method of analysis that best illustrates the development as a continuum from pre-existing postmodern models and theories to the formation of new post-postmodern theory. Based on my findings, the thesis argues that twenty-first century literary theory has moved away from postmodern overt deconstruction of the narrative and its meaning. New post-postmodern literary theory reacquires the previously deconstructed boundaries that define reality and truth and re-establishes them as having intrinsic value that cannot be disputed. In establishing fictional reality as self-governing and non-intrudable, post-postmodern theory takes a stance against postmodern nihilism, which indicates the re-founded, non-questionable value of the text’s reality. To continue mapping other possible features of future post-postmodern theory, I recommend further analysis solely on John Irving’s novels’ published in the twenty-first century.

DISTRIBUTION OF CAPYBARAS IN AN AGROECOSYSTEM, SOUTHEASTERN BRAZIL, BASED ON ECOLOGICAL NICHE MODELING

Southeastern Brazil has seen dramatic landscape modifications in recent decades, due to expansion of agriculture and urban areas; these changes have influenced the distribution and abundance of vertebrates. We developed predictive models of ecological and spatial distributions of capybaras (Hydrochoerus hydrochaeris) using ecological niche modeling. Most Occurrences of capybaras were in flat areas with water bodies Surrounded by sugarcane and pasture. More than 75% of the Piracicaba River basin was estimated as potentially habitable by capybara. The models had low omission error (2.3-3.4%), but higher commission error (91.0-98.5%); these ""model failures"" seem to be more related to local habitat characteristics than to spatial ones. The potential distribution of capybaras in the basin is associated with anthropogenic habitats, particularly with intensive land use for agriculture.

Modelling the distribution of cetaceans using opportunistic presence-only data in S. Miguel Island (Azores)

25th Annual Conference of the European Cetacean Society, Cadiz, Spain 21-23 March 2011.

Distribuição geográfica potencial de espécies americanas do caranguejo "violinista" (Uca spp.) (Crustacea, Decapoda) com base em modelagem de nicho ecológico

Caranguejos do gênero Uca Leach, 1814 (caranguejo "violinista") são um grupo bem conhecido e caracterizado por um acentuado dimorfismo sexual e assimetria da quela do macho. Atualmente, estão descritas 97 espécies no mundo. Objetivou-se estimar a distribuição geográfica potencial de 4 espécies do gênero Uca que ocorrem na costa do continente Americano: Uca maracoani Latreille, 1802-1803, U. uruguayensis Nobili, 1901, U. panacea Novak & Salmon, 1974 e U. monilifera Rathbun, 1914. Para modelar a distribuição dessas espécies nas Américas foram utilizados pontos de ocorrência compilados da literatura. Para a modelagem foram utilizados os programas Maxent e GARP a partir de 10 variáveis climáticas e três variáveis topográficas. Todas as variáveis foram convertidas para uma malha com resolução de 0,0417 graus. Nos dois modelos (Maxent e GARP) as espécies apresentaram distribuição geográfica maior do que sugerido por outros trabalhos de registro de ocorrência, com exceção de U. monilifera. Segundo o critério de área sob a curva (AUC), os modelos gerados pelo GARP apresentaram melhores resultados do que os modelos do Maxent. Entretanto, avaliando em conjunto os resultados dos dois modelos é possível melhor estabelecer planos de conservação para espécies com habitat restrito (U. panaceae e U. monilifera), além de recomendar um aumento na amostragem de U. maracoani no nordeste brasileiro e U. uruguyaensis no sudeste brasileiro, a fim de detectar possíveis aumentos na sua distribuição geográfica com base nas predições dos modelos de nicho.

An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology

Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima, Brazil, in the northern Amazon Basin, focused on the natural history of malaria and transmission. We used unsupervised maximum likelihood classification, principal components analysis, and weighted overlay with equal contribution analyses to fine-scale thematic maps that resulted in clustered regions. We used ecological niche modeling techniques to develop a fine-scale picture of malaria vector distributions in the state. Eight ecoregions were identified and malaria-related aspects are discussed based on this classification, including 5 types of dense tropical rain forest and 3 types of savannah. Ecoregions formed by dense tropical rain forest were named as montane (ecoregion I), submontane (II), plateau (III), lowland (IV), and alluvial (V). Ecoregions formed by savannah were divided into steppe (VI, campos de Roraima), savannah (VII, cerrado), and wetland (VIII, campinarana). Such ecoregional mappings are important tools in integrated malaria control programs that aim to identify specific characteristics of malaria transmission, classify transmission risk, and define priority areas and appropriate interventions. For some areas, extension of these approaches to still-finer resolutions will provide an improved picture of malaria transmission patterns.

Ecological niche modelling and differentiation between Rhodnius neglectus Lent, 1954 and Rhodnius nasutus Stål, 1859 (Hemiptera: Reduviidae: Triatominae) in Brazil

Ecological niche modelling was used to predict the potential geographical distribution of Rhodnius nasutus Stål and Rhodnius neglectus Lent, in Brazil and to investigate the niche divergence between these morphologically similar triatomine species. The distribution of R. neglectus covered mainly the cerrado of Central Brazil, but the prediction maps also revealed its occurrence in transitional areas within the caatinga, Pantanal and Amazon biomes. The potential distribution of R. nasutus covered the Northeastern Region of Brazil in the semi-arid caatinga and the Maranhão babaçu forests. Clear ecological niche differences between these species were observed. R. nasutus occurred more in warmer and drier areas than R. neglectus. In the principal component analysis PC1 was correlated with altitude and temperature (mainly temperature in the coldest and driest months) and PC2 with vegetation index and precipitation. The prediction maps support potential areas of co-occurrence for these species in the Maranhão babaçu forests and in caatinga/cerrado transitional areas, mainly in state of Piaui. Entomologists engaged in Chagas disease vector surveillance should be aware that R. neglectus and R. nasutus can occur in the same localities of Northeastern Brazil. Thus, the identification of bugs in these areas should be improved by applying morphometrical and/or molecular methods.

Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

A microRNA profile of human CD8.

BackgroundRecently, regulatory T (Treg) cells have gained interest in the fields of immunopathology, transplantation and oncoimmunology. Here, we investigated the microRNA expression profile of human natural CD8+CD25+ Treg cells and the impact of microRNAs on molecules associated with immune regulation.MethodsWe purified human natural CD8+ Treg cells and assessed the expression of FOXP3 and CTLA-4 by flow cytometry. We have also tested the ex vivo suppressive capacity of these cells in mixed leukocyte reactions. Using TaqMan low-density arrays and microRNA qPCR for validation, we could identify a microRNA `signature¿ for CD8+CD25+FOXP3+CTLA-4+ natural Treg cells. We used the `TargetScan¿ and `miRBase¿ bioinformatics programs to identify potential target sites for these microRNAs in the 3¿-UTR of important Treg cell-associated genes.ResultsThe human CD8+CD25+ natural Treg cell microRNA signature includes 10 differentially expressed microRNAs. We demonstrated an impact of this signature on Treg cell biology by showing specific regulation of FOXP3, CTLA-4 and GARP gene expression by microRNA using site-directed mutagenesis and a dual-luciferase reporter assay. Furthermore, we used microRNA transduction experiments to demonstrate that these microRNAs impacted their target genes in human primary Treg cells ex vivo.ConclusionsWe are examining the biological relevance of this `signature¿ by studying its impact on other important Treg cell-associated genes. These efforts could result in a better understanding of the regulation of Treg cell function and might reveal new targets for immunotherapy in immune disorders and cancer.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

Performance Comparison of Behavioral Finance -based Investment Strategies in the Finnish Stock Market 1996-2010

In this thesis traditional investment strategies (value and growth) are compared to modern investment strategies (momentum, contrarian and GARP) in terms of risk, performance and cumulative returns. Strategies are compared during time period reaching from 1996 to 2010 in the Finnish stock market. Used data includes all listed main list stocks, dividends and is adjusted in case of splits, and mergers and acquisitions. Strategies are tested using different holding periods (6, 12 and 36 months) and data is divided into tercile portfolios based on different ranking criteria. Contrarian and growth strategies are the only strategies with improved cumulative returns when longer holding periods are used. Momentum (52-week high price1) and GARP strategies based on short holding period have the best performance and contrarian and growth strategies the worst. Momentum strategies (52-week high price) along with short holding period contrarian strategies (52-week low price2) have the lowest risk. Strategies with the highest risk are both growth strategies and two momentum strategies (52-week low price). The empirical results support the efficiency of momentum, GARP and value strategies. The least efficient strategies are contrarian and growth strategies in terms of risk, performance and cumulative returns. Most strategies outperform the market portfolio in all three measures. 1 Stock ranking criterion (current price/52-week highest price) 2 Stock ranking criterion (current price/52-week lowest price)

Modelagem da distribuição geográfica de espécies lenhosas de cerrado no Estado de São Paulo

Atualmente vêm sendo desenvolvidas e utilizadas várias técnicas de modelagem de distribuição geográfica de espécies com os mais variados objetivos. Algumas dessas técnicas envolvem modelagem baseada em análise ambiental, nas quais os algoritmos procuram por condições ambientais semelhantes àquelas onde as espécies foram encontradas, resultando em áreas potenciais onde as condições ambientais seriam propícias ao desenvolvimento dessas espécies. O presente estudo trata do uso da modelagem preditiva de distribuição geográfica de espécies nativas, através da utilização de algoritmo genético, como ferramenta para auxiliar o entendimento dos padrões de distribuição do bioma cerrado no Estado de São Paulo. A metodologia empregada e os resultados obtidos foram considerados satisfatórios para a geração de modelos de distribuição geográfica de espécies vegetais, baseados em dados abióticos, para as regiões de estudo. A eficácia do modelo em predizer a ocorrência de espécies do cerrado é maior se forem utilizados apenas pontos de amostragem com fisionomias de cerrado, excluindo-se áreas de transição. Para minimizar problemas decorrentes da falta de convergência do algoritmo utilizado GARP ("Genetic Algorithm for Rule Set Production"), foram gerados 100 modelos para cada espécie modelada. O uso de modelagem pode auxiliar no entendimento dos padrões de distribuição de um bioma ou ecossistema em uma análise regional.