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Virotherapy using oncolytic vaccinia virus (VACV) strains is one promising new strategy for canine cancer therapy. In this study we describe the establishment of an in vivo model of canine soft tissue sarcoma (CSTS) using the new isolated cell line STSA-1 and the analysis of the virus-mediated oncolytic and immunological effects of two different Lister VACV LIVP1.1.1 and GLV-1h68 strains against CSTS. Cell culture data demonstrated that both tested VACV strains efficiently infected and destroyed cells of the canine soft tissue sarcoma line STSA-1. In addition, in our new canine sarcoma tumor xenograft mouse model, systemic administration of LIVP1.1.1 or GLV-1h68 viruses led to significant inhibition of tumor growth compared to control mice. Furthermore, LIVP1.1.1 mediated therapy resulted in almost complete tumor regression and resulted in long-term survival of sarcoma-bearing mice. The replication of the tested VACV strains in tumor tissues led to strong oncolytic effects accompanied by an intense intratumoral infiltration of host immune cells, mainly neutrophils. These findings suggest that the direct viral oncolysis of tumor cells and the virus-dependent activation of tumor-associated host immune cells could be crucial parts of anti-tumor mechanism in STSA-1 xenografts. In summary, the data showed that both tested vaccinia virus strains and especially LIVP1.1.1 have great potential for effective treatment of CSTS.
Computer systems have replaced human work-force in many parts of everyday life, but there still exists a large number of tasks that cannot be automated, yet. This also includes tasks, which we consider to be rather simple like the categorization of image content or subjective ratings. Traditionally, these tasks have been completed by designated employees or outsourced to specialized companies. However, recently the crowdsourcing paradigm is more and more applied to complete such human-labor intensive tasks. Crowdsourcing aims at leveraging the huge number of Internet users all around the globe, which form a potentially highly available, low-cost, and easy accessible work-force.
To enable the distribution of work on a global scale, new web-based services emerged, so called crowdsourcing platforms, that act as mediator between employers posting tasks and workers completing tasks. However, the crowdsourcing approach, especially the large anonymous worker crowd, results in two types of challenges. On the one hand, there are technical challenges like the dimensioning of crowdsourcing platform infrastructure or the interconnection of crowdsourcing platforms and machine clouds to build hybrid services. On the other hand, there are conceptual challenges like identifying reliable workers or migrating traditional off-line work to the crowdsourcing environment. To tackle these challenges, this monograph analyzes and models current crowdsourcing systems to optimize crowdsourcing workflows and the underlying infrastructure. First, a categorization of crowdsourcing tasks and platforms is developed to derive generalizable properties. Based on this categorization and an exemplary analysis of a commercial crowdsourcing platform, models for different aspects of crowdsourcing platforms and crowdsourcing mechanisms are developed. A special focus is put on quality assurance mechanisms for crowdsourcing tasks, where the models are used to assess the suitability and costs of existing approaches for different types of tasks. Further, a novel quality assurance mechanism solely based on user-interactions is proposed and its feasibility is shown. The findings from the analysis of existing platforms, the derived models, and the developed quality assurance mechanisms are finally used to derive best practices for two crowdsourcing use-cases, crowdsourcing-based network measurements and crowdsourcing-based subjective user studies. These two exemplary use-cases cover aspects typical for a large range of crowdsourcing tasks and illustrated the potential benefits, but also resulting challenges when using crowdsourcing.
With the ongoing digitalization and globalization of the labor markets, the crowdsourcing paradigm is expected to gain even more importance in the next years. This is already evident in the currently new emerging fields of crowdsourcing, like enterprise crowdsourcing or mobile crowdsourcing. The models developed in the monograph enable platform providers to optimize their current systems and employers to optimize their workflows to increase their commercial success. Moreover, the results help to improve the general understanding of crowdsourcing systems, a key for identifying necessary adaptions and future improvements.
Rationale
The endocannabinoid (eCB) system is implicated in several psychiatric disorders. Investigating emotional–motivational dysfunctions as underlying mechanisms, a study in humans revealed that in the C385A polymorphism of the fatty acid amide hydrolase (FAAH), the degrading enzyme of the eCB anandamide (AEA), A carriers, who are characterized by increased signaling of AEA as compared to C/C carriers, exhibited reduced brain reactivity towards unpleasant faces and enhanced reactivity towards reward. However, the association of eCB system with emotional–motivational reactivity is complex and bidirectional due to upcoming compensatory processes.
Objectives
Therefore, we further investigated the relationship of the FAAH polymorphism and emotional–motivational reactivity in humans.
Methods
We assessed the affect-modulated startle, and ratings of valence and arousal in response to higher arousing pleasant, neutral, and unpleasant pictures in 67 FAAH C385A C/C carriers and 45 A carriers.
Results
Contrarily to the previous functional MRI study, A carriers compared to C/C carriers exhibited an increased startle potentiation and therefore emotional responsiveness towards unpleasant picture stimuli and reduced startle inhibition indicating reduced emotional reactivity in response to pleasant pictures, while both groups did not differ in ratings of arousal and valence.
Conclusions
Our findings emphasize the bidirectionality and thorough examination of the eCB system’s impact on emotional reactivity as a central endophenotype underlying various psychiatric disorders.
Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000–2010, were used to derive areas with an apparent negative vegetation trend; this was interpreted as an indicator of land degradation. About one third (161,000 ha) of the region’s area experienced negative trends of different magnitude. The vegetation decline was particularly evident on the low-fertility lands bordering on the natural sandy desert, suggesting that these areas should be prioritized in mitigation planning. The results of logistic modeling indicate that the spatial pattern of the observed trend is mainly associated with the level of the groundwater table (odds = 330 %), land-use intensity (odds = 103 %), low soil quality (odds = 49 %), slope (odds = 29 %), and salinity of the groundwater (odds = 26 %). Areas, threatened by land degradation, were mapped by fitting the estimated model parameters to available data. The elaborated approach, combining remote-sensing and GIS, can form the basis for developing a common tool for monitoring land degradation trends in irrigated croplands of Central Asia.
We present the complete threshold enhanced predictions in QCD for the total cross section of gluino pair production at hadron colliders at next-to-next-to-leading order. Thanks to the computation of the required one-loop hard matching coefficients our results are accurate to the next-to-next-to-leading logarithm. In a brief phenomenological study we provide predictions for the total hadronic cross sections at the LHC and we discuss the uncertainties arising from scale variations and the parton distribution functions.
Results are presented of a search for new particles decaying to large numbers of jets in association with missing transverse momentum, using 4.7 fb\(^{−1}\) of pp collision data at √s=7TeV collected by the ATLAS experiment at the Large Hadron Collider in 2011. The event selection requires missing transverse momentum, no isolated electrons or muons, and from ≥6 to ≥9 jets. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of a MSUGRA/CMSSM supersymmetric model, where, for large universal scalar mass m 0, gluino masses smaller than 840 GeV are excluded at the 95% confidence level, extending previously published limits. Within a simplified model containing only a gluino octet and a neutralino, gluino masses smaller than 870 GeV are similarly excluded for neutralino masses below 100 GeV.
For many practical purposes, it is convenient to formulate unbroken non-abelian gauge theories like QCD in a color-flow basis. We present a new derivation of SU(N) interactions in the color-flow basis by extending the gauge group to U(N) × U(1)′ in such a way that the two U(1) factors cancel each other. We use the quantum action principles to show the equivalence to the usual basis to all orders in perturbation theory. We extend the known Feynman rules to exotic color representations (e.g. sextets) and discuss practical applications as they occur in automatic computation programs.
We perform global fits to the parameters of the Constrained Minimal Super-symmetric Standard Model (CMSSM) and to a variant with non-universal Higgs masses (NUHM1). In addition to constraints from low-energy precision observables and the cosmological dark matter density, we take into account the LHC exclusions from searches in jets plus missing transverse energy signatures with about 5 fb\(^{−1}\) of integrated luminosity. We also include the most recent upper bound on the branching ratio B\(_s\) → μμ from LHCb. Furthermore, constraints from and implications for direct and indirect dark matter searches are discussed. The best fit of the CMSSM prefers a light Higgs boson just above the experimentally excluded mass. We find that the description of the low-energy observables, (g − 2)\(_μ\) in particular, and the non-observation of SUSY at the LHC become more and more incompatible within the CMSSM. A potential SM-like Higgs boson with mass around 126 GeV can barely be accommodated. Values for B(B\(_s\)→μμ) just around the Standard Model prediction are naturally expected in the best fit region. The most-preferred region is not yet affected by limits on direct WIMP searches, but the next generation of experiments will probe this region. Finally, we discuss implications from fine-tuning for the best fit regions.
A search is presented for the pair production of light scalar top quarks in √s=7 TeV proton–proton collisions recorded with the ATLAS detector at the Large Hadron Collider. This analysis uses the full data sample collected during 2011 running that corresponds to a total integrated luminosity of 4.7 fb\(^{−1}\). Light scalar top quarks are searched for in events with two opposite-sign leptons (e, μ), large missing transverse momentum and at least one jet in the final state. No excess over Standard Model expectations is found, and the results are interpreted under the assumption that the light scalar top decays to a b-quark in addition to an on-shell chargino whose decay occurs through a virtual W boson. If the chargino mass is 106 GeV, light scalar top-quark masses up to 130 GeV are excluded for neutralino masses below 70 GeV.
A search for resonant production of high-mass top-quark pairs is performed on 2.05 fb\(^{−1}\) of proton-proton collisions at √s=7 TeV collected in 2011 with the ATLAS experiment at the Large Hadron Collider. This analysis of the lepton+jets final state is specifically designed for the particular topology that arises from the decay of highly boosted top quarks. The observed \(t\overline t\) invariant mass spectrum is found to be compatible with the Standard Model prediction and 95% credibility level upper limits are derived on the \(t\overline t\) production rate through new massive states. An upper limit of 0.7 pb is set on the production cross section times branching fraction of a narrow 1 TeV resonance. A Kaluza-Klein gluon with a mass smaller than 1.5 TeV is excluded.