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Neutral pion and η meson invariant differential yields were measured in non-single diffractive p–Pb collisions at sNN−−−√ = 5.02 TeV with the ALICE experiment at the CERN LHC. The analysis combines results from three complementary photon measurements, utilizing the PHOS and EMCal calorimeters and the Photon Conversion Method. The invariant differential yields of π0 and η meson inclusive production are measured near mid-rapidity in a broad transverse momentum range of 0.3<pT<20 GeV/c and 0.7<pT<20 GeV/c, respectively. The measured η/π0 ratio increases with pT and saturates for pT > 4 GeV/c at 0.483±0.015stat±0.015sys. A deviation from mT scaling is observed for pT< 2 GeV/c. The measured η/π0 ratio is consistent with previous measurements from proton-nucleus and pp collisions over the full pT range. The measured η/π0 ratio at high pT also agrees within uncertainties with measurements from nucleus–nucleus collisions. The π0 and η yields in p–Pb relative to the scaled pp interpolated reference, RpPb, are presented for 0.3<pT< 20 GeV/c and 0.7<pT< 20 GeV/c, respectively. The results are compared with theoretical model calculations. The values of RpPb are consistent with unity for transverse momenta above 2 GeV/c. These results support the interpretation that the suppressed yield of neutral mesons measured in Pb–Pb collisions at LHC energies is due to parton energy loss in the hot QCD medium.
Flower flies (Diptera, Syrphidae) of French Polynesia, with the description of two new species
(2018)
The flower flies (Diptera, Syrphidae) of French Polynesia are revised. A total of nine syrphid species were recorded from the five archipelagos of French Polynesia. Among them are two species new to science, Allograpta jacqi Mengual & Ramage sp. nov. and Melanostoma polynesiotes Mengual & Ramage sp. nov., and a new record for this country, Syritta aenigmatopatria Hardy, 1964. We provide DNA barcodes for all flower fly species of French Polynesia, making the syrphid fauna of this country the first one in the world to be entirely barcoded. New data on biology, flowers visited and some taxonomic notes are provided. An identification key for the species of Syrphidae in French Polynesia is given, as well as an identification key for the species of Melanostoma Schiner, 1860 in the Australasian and Oceanian Regions.
Background and aims: Spontaneous bacterial peritonitis (SBP) is a severe complication of decompensated cirrhosis. The prevalence of multidrug-resistant organisms (MDROs) in patients with cirrhosis is increasing. Identification of patients at risk for SBP due to MDROs (ie, SBP with the evidence of MDROs or Stenotrophomonas maltophilia in ascitic culture, MDRO-SBP) is crucial to the early adaptation of antibiotic treatment in such patients. We therefore investigated whether MDROs found in ascitic cultures can also be found in specimens determined by noninvasive screening procedures.
Patients and methods: This retrospective study was conducted at the liver center of the University Hospital Frankfurt, Germany. Between 2011 and 2016, patients with cirrhosis were included upon diagnosis of SBP and sample collection of aerobic/anaerobic ascitic cultures. Furthermore, the performance of at least one complete MDRO screening was mandatory for study inclusion.
Results: Of 133 patients diagnosed with SBP, 75 (56.4%) had culture-positive SBP and 22 (16.5%) had MDRO-SBP. Multidrug-resistant Escherichia coli (10/22; 45.5%) and vancomycin-resistant enterococci (7/22; 36.4%) resembled the major causatives of MDRO-SBP. Rectal swabs identified MDROs in 17 of 22 patients (77.3%) who developed MDRO-SBP with a time-dependent sensitivity of 77% and 87% after 30 and 90 days upon testing, while negative predictive value was 83% and 76%, respectively. The majority of patients were included from intensive care unit or intermediate care unit.
Conclusion: MDRO screening may serve as a noninvasive diagnostic tool to identify patients at risk for MDRO-SBP. Patients with decompensated cirrhosis should be screened for MDROs from the first day of inpatient treatment onward.
The overarching goal of the thesis was to create a holistic predictive framework, a vegetation model, by improving the representations of and interactions between the biosphere, hydrosphere, atmosphere and pedosphere. Vegetation models rep- resent a crucial component of Earth system model since the properties of the land surface, via interactions with the atmosphere, can have extremely large climatic effect. Yet, there remains great uncertainty associated with the dynamics of the vegetated land surface. Various vegetation models have been critiqued for numerous reasons including overly simplistic representations of vegetation, prescribed vegetation, poor representations of diversity, inaccurate representations of competition, non-transparent model calibration, and poor responses to drought. The purpose of the creation of this "next generation" model was to address deficiencies common to current vegetation modelling paradigms.
The representation of the biosphere within this framework was improved via two separate development axes. First, ecological realism was improved by integrating concepts from community assembly theory, co-existence theory, and evolutionary theory. Explicitly, rather than defining teleonomic rules to define plant behaviour the process of natural selection is modelled. By modelling the pro- cess of natural selection and its affect on relative fitness, myriad "rules" which continually adapt to biotic and abiotic conditions "come out" as a consequence of the modelled dynamics rather than being "put in". In aDGVM2 (adaptive Dynamic Global Vegetation model 2) communities of plants and their trait values evolve through time, this evolution is constrained by trade-offs between traits. Poorly performing individuals are more likely to die and produce fewer copies of themselves, this results in a filtering of trait values. Further, the community and species’ trait values can evolve through successive generations via reproduction, mutation and crossover which we approximate by using a genetic optimisation algorithm. Thus, a plant community consisting of individuals and species with potentially novel and diverse trait values is assembled iteratively through time.
We tested the assertion that improved integration of concepts from community assembly, evolutionary, and co-existence theory could address limitations of DGVMs in Chapter 2. We demonstrated that such an approach does indeed allow diverse communities of plants to emerge from the modelling framework. We showed that the position of the emergent communities in trait space differed along abiotic gradients and that, in simulations where reproductive isolation was simulated, communities emerged which were composed of multiple co-existing clusters in trait-space. Simulated trait values of co-existing strategies emerging from aDGVM2 were often multimodal, indicative of the emergence of multiple life- history strategies.
Second, to successfully model how natural selection forms a community requires accurate representation of how resource availability affects fitness. In the majority of dynamic global vegetation models (DGVMs) there is no real representation of plant hydraulics with plant water availability being calculated as a simple function of relative soil moisture content and root fractions across a number of soil layers. Worryingly, a number vegetation models appear to under represent the magnitude of these observed responses to drought. This was deficiency was ad- dressed in Chapter 3 by designing a simplified version of the cohesion tension theory of sapwood ascent where elements determining plant conductances are considered in series and implementing a set of trait trade-offs which influence a plant’s hydraulic strategy whereby hydraulic safety trades-off against xylem and leaf conductivity.
Interactions between the biosphere, pedosphere, and hydrosphere can also potentially mediate water resource availability and thus fitness. In the majority of DGVMs the volume of soil explored and explorable by plant roots in fixed glob- ally and usually constrained to a depth not greater than 3m. However, we know that soils can have a strong effect on vegetation distributions, that soil depth is not constant globally, and that plants root to variable depths.
In Chapter 4 I explored interactions between soil depth, plant rooting and the emergent properties of communities and highlighted the importance of considering interactions between the biosphere, hydrosphere, pedosphere, and fire. Here I demonstrated that, in addition to fire and precipitation, edaphic constraints on the volume of soil explorable by plant roots (e.g. by shallow soils, lateritic layers, anoxic conditions due to water logging, toxicity resulting from heavy metal concentrations) can affect the process of plant community assembly, alter the mean values of multiple traits in communities, and the trait diversity of communities.
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Kidney injury is a common complication of severe disease. Here, we report that injuries of the zebrafish embryonal kidney are rapidly repaired by a migratory response in 2-, but not in 1-day-old embryos. Gene expression profiles between these two developmental stages identify cxcl12a and myca as candidates involved in the repair process. Zebrafish embryos with cxcl12a, cxcr4b, or myca deficiency display repair abnormalities, confirming their role in response to injury. In mice with a kidney-specific knockout, Cxcl12 and Myc gene deletions suppress mitochondrial metabolism and glycolysis, and delay the recovery after ischemia/reperfusion injury. Probing these observations in zebrafish reveal that inhibition of glycolysis slows fast migrating cells and delays the repair after injury, but does not affect the slow cell movements during kidney development. Our findings demonstrate that Cxcl12 and Myc facilitate glycolysis to promote fast migratory responses during development and repair, and potentially also during tumor invasion and metastasis.
In energy modelling, open data and open source code can help enhance traceability and reproducibility of model exercises which contribute to facilitate controversial debates and improve policy advice. While the availability of open power plant databases increased in recent years, they often differ considerably from each other and their data quality has not been systematically compared to proprietary sources yet. Here, we introduce the python-based ‘powerplantmatching’ (PPM), an open source toolset for cleaning, standardizing and combining multiple power plant databases. We apply it once only with open databases and once with an additional proprietary database in order to discuss and elaborate the issue of data quality, by analysing capacities, countries, fuel types, geographic coordinates and commissioning years for conventional power plants. We find that a derived dataset purely based on open data is not yet on a par with one in which a proprietary database has been added to the matching, even though the statistical values for capacity matched to a large degree with both datasets. When commissioning years are needed for modelling purposes in the final dataset, the proprietary database helps crucially to increase the quality of the derived dataset.
Natural killer (NK) cells are innate lymphocytes with a strong antitumor ability. In tumor patients, such as multiple myeloma (MM) patients, an elevated number of NK cells after stem cell transplantation (SCT) has been reported to be correlated with a higher overall survival rate. With the aim of improving NK cell use for adoptive cell therapy, we also addressed the cytotoxicity of patient-derived, cytokine-stimulated NK cells against MM cells at specific time points: at diagnosis and before and after autologous stem cell transplantation. Remarkably, after cytokine stimulation, the patients' NK cells did not significantly differ from those of healthy donors. In a small cohort of MM patients, we were able to isolate autologous tumor cells, and we could demonstrate that IL-2/15 stimulated autologous NK cells were able to significantly improve their killing capacity of autologous tumor cells. With the aim to further improve the NK cell killing capacity against MM cells, we investigated the potential use of NK specific check point inhibitors with focus on NKG2A because this inhibitory NK cell receptor was upregulated following ex vivo cytokine stimulation and MM cells showed HLA-E expression that could even be increased by exposure to IFN-γ. Importantly, blocking of NKG2A resulted in a significant increase in the NK cell-mediated lysis of different MM target cells. Finally, these results let suggest that combining cytokine induced NK cell activation and the specific check point inhibition of the NKG2A-mediated pathways can be an effective strategy to optimize NK cell therapeutic approaches for treatment of multiple myeloma.
Chemotherapy and diffuse low-grade gliomas : a survey within the European Low-Grade Glioma Network
(2018)
Background: Diffuse low-grade gliomas (DLGGs) are rare and incurable tumors. Whereas maximal safe, functional-based surgical resection is the first-line treatment, the timing and choice of further treatments (chemotherapy, radiation therapy, or combined treatments) remain controversial.
Methods: An online survey on the management of DLGG patients was sent to 28 expert centers from the European Low-Grade Glioma Network (ELGGN) in May 2015. It contained 40 specific questions addressing the modalities of use of chemotherapy in these patients.
Results: The survey demonstrated a significant heterogeneity in practice regarding the initial management of DLGG patients and the use of chemotherapy. Interestingly, radiation therapy combined with the procarbazine, CCNU (lomustine), and vincristine regimen has not imposed itself as the gold-standard treatment after surgery, despite the results of the Radiation Therapy Oncology Group 9802 study. Temozolomide is largely used as first-line treatment after surgical resection for high-risk DLGG patients, or at progression.
Conclusions: The heterogeneity in the management of patients with DLGG demonstrates that many questions regarding the postoperative strategy and the use of chemotherapy remain unanswered. Our survey reveals a high recruitment potential within the ELGGN for retrospective or prospective studies to generate new data regarding these issues.
Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Pediatric patients with disease refractory to last chemotherapy, relapse after allogeneic hematopoietic stem-cell transplantation (alloHSCT), or second or further relapse have a particularly poor prognosis. Intensive chemotherapy followed by alloHSCT after achieving remission can result in cure for some patients. However, survival is still low with this approach. Thus, additional treatment modalities with acceptable toxicity are needed to improve long-term survival. ...
Defossiliation of the energy system is crucial in the face of the impending risks of climate change. Electricity generation by burning fossil fuels is being displaced by renewable energy sources like hydro, wind and solar, driven by support schemes and falling costs from technological advances as well as manufacturing scale effects. The unavoidable shift from flexibly dispatchable generation to weather-dependent spatio-temporally varying generators transforms the generation and distribution of electricity into highly interdependent complex systems in multiple dimensions and disciplines:
In time, different scales, stretching from intra-day, diurnal, synoptic to seasonal oscillations of the weather interact with years and decades of planning and construction of capacity. In space, long-range correlations and local variations of weather systems as well as local bottlenecks in transmission networks affect solutions. The investment decisions about technological mix and spatial distribution of capacity follow economic principles, within restrictions which adapt in social feedback loops to public opinion and lobbyist influences.
In this work, a family of self-consistent models is developed which map physical steady-state operation, capacity investments and exogeneous restrictions of a European electricity system, in higher simultaneous spatial and temporal detail as well as scope than has previously been computationally tractable. Increasing the spatial detail of the renewable resources and co-optimizing the expansion of only a few transmission lines, reveals solutions to serve the European electricity demand at about today’s electricity cost with only 5% of its carbon-dioxide emissions; and importantly their electricity mix differs from the findings at low spatial resolution.
As important intermediate steps,
• new algorithms for the convex optimization of electricity system infrastructure are derived from graph-theoretic decompositions of network flows. Only these enable the investigation of model detail beyond previous computational limitations.
• a comprehensive European electricity network model down to individual substations at the transmission voltage levels is built by combining and completing data from freely available sources.
• a network reduction technique is developed to approximate the detailed model at a sequence of spatial resolutions to investigate the role of spatial scale, and identify a level of spatial resolution which captures all relevant detail, but is still computationally tractable.
• a method to trace the flow of power through the network, which is related to a vector diffusion process on a directed flow graph embedded in a network, is used to analyse the resulting technology mix and its interactions with the power network
The open-source nature of the model and restriction to freely available data encourages an accessible and transparent discussion about the future European electricity system, primarily based on renewable wind and solar resources.