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Azimuthally sensitive Hanbury Brown-Twiss interferometry in Au+Au collisions at sqrt[sNN]=200 GeV
(2004)
We present the results of a systematic study of the shape of the pion distribution in coordinate space at freeze-out in Au+Au collisions at BNL RHIC using two-pion Hanbury Brown-Twiss (HBT) interferometry. Oscillations of the extracted HBT radii versus emission angle indicate sources elongated perpendicular to the reaction plane. The results indicate that the pressure and expansion time of the collision system are not sufficient to completely quench its initial shape.
Background: To identify variables predicting outcome in neuroblastoma patients assigned to the high-risk group solely by the presence of MYCN oncogene amplification (MNA). Methods: Clinical characteristics, genomic information, and outcome of 190 patients solely assigned to high-risk neuroblastoma by MNA were analyzed and compared to 205 patients with stage 4 neuroblastoma aged ≥18 months with MNA (control group). Results: Event-free survival (EFS) and overall survival (OS) at 10 years were 47% (95%-CI 39–54%) and 56% (95%-CI 49–63%), respectively, which was significantly better than EFS and OS of the control group (EFS 25%, 95%-CI 18–31%, p < 0.001; OS 32% 95%-CI 25–39%, p < 0.001). The presence of RAS-/p53-pathway gene alterations was associated with impaired 10-year EFS and OS (19% vs. 55%, and 19% vs. 67%, respectively; both p < 0.001). In time-dependent multivariable analyses, alterations of RAS-/p53-pathway genes and the extent of the best primary tumor resection were the only independent prognostic variables for OS (p < 0.001 and p = 0.011, respectively). Conclusions: Neuroblastoma patients attributed to high risk solely by MYCN amplification have generally a more favorable outcome. Mutations of genes of the RAS and/or p53 pathways and incomplete resection are the main risk factors predicting poor outcome.
Association of autoimmune Addison's disease with alleles of STAT4 and GATA3 in European cohorts
(2014)
Background: Gene variants known to contribute to Autoimmune Addison's disease (AAD) susceptibility include those at the MHC, MICA, CIITA, CTLA4, PTPN22, CYP27B1, NLRP-1 and CD274 loci. The majority of the genetic component to disease susceptibility has yet to be accounted for.
Aim: To investigate the role of 19 candidate genes in AAD susceptibility in six European case-control cohorts.
Methods: A sequential association study design was employed with genotyping using Sequenom iPlex technology. In phase one, 85 SNPs in 19 genes were genotyped in UK and Norwegian AAD cohorts (691 AAD, 715 controls). In phase two, 21 SNPs in 11 genes were genotyped in German, Swedish, Italian and Polish cohorts (1264 AAD, 1221 controls). In phase three, to explore association of GATA3 polymorphisms with AAD and to determine if this association extended to other autoimmune conditions, 15 SNPs in GATA3 were studied in UK and Norwegian AAD cohorts, 1195 type 1 diabetes patients from Norway, 650 rheumatoid arthritis patients from New Zealand and in 283 UK Graves' disease patients. Meta-analysis was used to compare genotype frequencies between the participating centres, allowing for heterogeneity.
Results: We report significant association with alleles of two STAT4 markers in AAD cohorts (rs4274624: P = 0.00016; rs10931481: P = 0.0007). In addition, nominal association of AAD with alleles at GATA3 was found in 3 patient cohorts and supported by meta-analysis. Association of AAD with CYP27B1 alleles was also confirmed, which replicates previous published data. Finally, nominal association was found at SNPs in both the NF-κB1 and IL23A genes in the UK and Italian cohorts respectively.
Conclusions: Variants in the STAT4 gene, previously associated with other autoimmune conditions, confer susceptibility to AAD. Additionally, we report association of GATA3 variants with AAD: this adds to the recent report of association of GATA3 variants with rheumatoid arthritis.
Based on both stranding and sighting records, recent data on the status and distribution of whales and dolphins in the Cape Verde Islands are presented, including records of four taxa new to the archipelago, viz. Common minke whale Balaenoptera acutorostrata, Dwarf sperm whale Kogia sima, beaked whale Mesoplodon cf. europaeus and False killer whale Pseudorca crassidens. Distribution elsewhere in the tropical eastern Atlantic and some taxonomic issues are discussed.
"Flechtenreiche Kiefernwälder" (FKW) waren früher in Bayern besonders im Nürnberger Reichswald und im Oberpfälzer/Bayerischen Wald großflächig vorhanden. Mittlerweile sind sie selten. Der Waldtyp gilt als akut gefährdet, ebenso seine Flechten. Wir haben folgende Fragen zu klären versucht: Wie bzw. wie stark hat sich die floristische Zusammensetzung dieser Wälder in den zurückliegenden Jahrzehnten verändert? In welchem Maße ist die Fläche dieser Wälder zurückgegangen? Welche Aussichten zum Erhalt dieses Waldtyps bestehen, und was muss dazu ggf. getan werden?
2.363 historische Kiefernwald-Aufnahmen aus Bayern wurden recherchiert, in eine Datenbank eingegeben und multivariat statistisch analysiert mit dem Ziel, einen Referenzdatensatz für FKW in Bayern zu erzeugen. Dabei ergaben sich 216 Aufnahmen, die den floristischen Zustand der FKW von Mitte bis Ende des zwanzigsten Jahrhunderts repräsentieren. Darin finden sich 30 terricole Flechtenarten, überwiegend der Gattung Cladonia. Die Gesamtdeckung der terricolen Flechten in den einzelnen Aufnahmen variiert zwischen 0,1 % und 81 %. In 50 % der Aufnahmen überschreiten die Flechten 18 % Gesamtdeckung, in 25 % der Fälle sogar 38 % Gesamtdeckung. Die Bezeichnung "flechtenreiche Kiefernwälder" war seinerzeit also qualitativ wie quantitativ gerechtfertigt.
Im Jahre 2014 wurden auf 85 historischen Aufnahmeflächen aus dem Zeitraum 1980 bis 1996 Neuerhebungen durchgeführt. Die gemeinsame multivariate Analyse von Erst- und Wiederholungsaufnahmen zeigt, dass in den vergangenen gut drei Jahrzehnten in den FKW in Bayern ein grundlegender floristischer Umbau stattgefunden hat. Während die Bodenvegetation dieser Bestände früher von zahlreichen Flechten sowie langsamwüchsigen, oft acrokarpen Moosen geprägt wurden, breitet sich heutzutage eine üppige Decke meist pleurokarper Moose aus, überstockt von einer dichten Zwergstrauchschicht und einer heranwachsenden Kiefern-Verjüngungsschicht. Diese Entwicklung findet sowohl in forstlich genutzten FKW als auch in Naturwaldreservaten (Totalreservat) statt. Als Ursachen sind vor allem der Wegfall des Nährstoffentzugs (Streurechen) sowie der Stickstoffeintrag durch die Luft anzunehmen. Der Vergleich einer Kartierung von FKW in Teilen des Nürnberger Reichswaldes von Anfang der 1980er Jahre mit einer Kartierung von 2012 weist einen Flächenverlust der FKW von 90 % aus.
Die FKW befinden sich auf einem dramatischen Rückzug. Ohne gezieltes Management werden die verbliebenen Bestände weitgehend und rasch verschwinden. Dies gilt auch in Schutzgebieten, die dem Schutz und Erhalt der flechtenreichen Kiefernwälder gewidmet sind. Selbst das Wiedereinführen des Streurechens wird heute kaum mehr ausreichen; vielmehr muss den wenigen verbliebenen Flechten mittels "Aussaat" von Thallus-Bruchstücken überhaupt die Möglichkeit gegeben werden, die neu angebotenen Flächen zu erreichen.
Primary cilia are microtubule-based organelles that detect mechanical and chemical stimuli. Although cilia house a number of oncogenic molecules (including Smoothened, KRAS, EGFR, and PDGFR), their precise role in cancer remains unclear. We have interrogated the role of cilia in acquired and de novo resistance to a variety of kinase inhibitors, and found that, in several examples, resistant cells are distinctly characterized by an increase in the number and/or length of cilia with altered structural features. Changes in ciliation seem to be linked to differences in the molecular composition of cilia and result in enhanced Hedgehog pathway activation. Notably, manipulating cilia length via Kif7 knockdown is sufficient to confer drug resistance in drug-sensitive cells. Conversely, targeting of cilia length or integrity through genetic and pharmacological approaches overcomes kinase inhibitor resistance. Our work establishes a role for ciliogenesis and cilia length in promoting cancer drug resistance and has significant translational implications.
Despite an increasing demand for Burgundy truffles (Tuber aestivum), gaps remain in our understanding of the fungus’ overall lifecycle and ecology. Here, we compile evidence from three independent surveys in Hungary and Switzerland. First, we measured the weight and maturity of 2,656 T. aestivum fruit bodies from a three-day harvest in August 2014 in a highly productive orchard in Hungary. All specimens ranging between 2 and 755 g were almost evenly distributed through five maturation classes. Then, we measured the weight and maturity of another 4,795 T. aestivum fruit bodies harvested on four occasions between June and October 2015 in the same truffière. Again, different maturation stages occurred at varying fruit body size and during the entire fruiting season. Finally, the predominantly unrelated weight and maturity of 81 T. aestivum fruit bodies from four fruiting seasons between 2010 and 2013 in Switzerland confirmed the Hungarian results. The spatiotemporal coexistence of 7,532 small-ripe and large-unripe T. aestivum, which accumulate to ~182 kg, differs from species-specific associations between the size and ripeness that have been reported for other mushrooms. Although size-independent truffle maturation stages may possibly relate to the perpetual belowground environment, the role of mycelial connectivity, soil property, microclimatology, as well as other abiotic factors and a combination thereof, is still unclear. Despite its massive sample size and proof of concept, this study, together with existing literature, suggests consideration of a wider ecological and biogeographical range, as well as the complex symbiotic fungus-host interaction, to further illuminate the hidden development of belowground truffle fruit bodies.
The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future due to global climate change. Dynamic global vegetation models (DGVMs) are very useful for understanding vegetation dynamics under the present climate, and for predicting its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna, and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modeling. The outcomes of the models, which include different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. By drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need improved representation in the examined DGVMs. The first mechanism includes water limitation to tree growth, and tree–grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass–fire feedback, which maintains both forest and savanna presence in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant forest trees, and fire-resistant and shade-intolerant savanna trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.
The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future, due to global climate change. Dynamic Global Vegetation Models (DGVMs) are very useful to understand vegetation dynamics under present climate, and to predict its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modelling. Model outcomes, obtained including different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. Through these comparisons, and by drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need an improved representation in the DGVMs. The first mechanism includes water limitation to tree growth, and tree-grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass-fire feedback, which maintains both forest and savanna occurrences in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant savanna trees, and fire-resistant and shade-intolerant forest trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.
Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of ∼150–350 MeV. We use Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma’s final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities.