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Measurements of anisotropic flow coefficients (vn) and their cross-correlations using two- and multi-particle cumulant methods are reported in collisions of pp at s√=13 TeV, p-Pb at sNN−−−√=5.02 TeV, Xe-Xe at sNN−−−√=5.44 TeV, and Pb-Pb at sNN−−−√=5.02 TeV recorded with the ALICE detector. These measurements are performed as a function of multiplicity in the mid-rapidity region |η|<0.8 for the transverse momentum range 0.2<pT<3.0 GeV/c. An ordering of the coefficients v2>v3>v4 is found in pp and p-Pb collisions, similar to that seen in large collision systems, while a weak v2 multiplicity dependence is observed relative to nucleus--nucleus collisions in the same multiplicity range. Using the novel subevent method, v2 measured in pp and p-Pb collisions with four-particle cumulants is found to be compatible with that from six-particle cumulants. The symmetric cumulants SC(m,n) calculated with the subevent method which evaluate the correlation strength between v2n and v2m are also presented. The presented data, which add further support to the existence of long-range multi-particle azimuthal correlations in high multiplicity pp and p-Pb collisions, can neither be described by PYTHIA8 nor by IP-Glasma+MUSIC+UrQMD model calculations, and hence provide new insights into the understanding of collective effects in small collision systems.
The highly infectious disease COVID-19 caused by the Betacoronavirus SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international COVID19-NMR consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in COVID19-NMR and the resources provided through the consortium are fully disclosed to accelerate access and exploitation. NMR investigations of the viral molecular components are designated to provide the essential basis for further work, including macromolecular interaction studies and high-throughput drug screening. Here, we present the extensive catalog of a holistic SARS-CoV-2 protein preparation approach based on the consortium’s collective efforts. We provide protocols for the large-scale production of more than 80% of all SARS-CoV-2 proteins or essential parts of them. Several of the proteins were produced in more than one laboratory, demonstrating the high interoperability between NMR groups worldwide. For the majority of proteins, we can produce isotope-labeled samples of HSQC-grade. Together with several NMR chemical shift assignments made publicly available on covid19-nmr.com, we here provide highly valuable resources for the production of SARS-CoV-2 proteins in isotope-labeled form.
Background: Leukocyte progenitors derived from clonal hematopoiesis of undetermined potential (CHIP) are associated with increased cardiovascular events. However, the prevalence and functional relevance of CHIP in coronary artery disease (CAD) are unclear, and cells affected by CHIP have not been detected in human atherosclerotic plaques.
Methods: CHIP mutations in blood and tissues were identified by targeted deep-DNA-sequencing (DNAseq: coverage >3,000) and whole-genome-sequencing (WGS: coverage >35). CHIP-mutated leukocytes were visualized in human atherosclerotic plaques by mutaFISHTM. Functional relevance of CHIP mutations was studied by RNAseq.
Results: DNAseq of whole blood from 540 deceased CAD patients of the Munich cardIovaScular StudIes biObaNk (MISSION) identified 253 (46.9%) CHIP mutation carriers (mean age 78.3 years). DNAseq on myocardium, atherosclerotic coronary and carotid arteries detected identical CHIP mutations in 18 out of 25 mutation carriers in tissue DNA. MutaFISHTM visualized individual macrophages carrying DNMT3A CHIP mutations in human atherosclerotic plaques. Studying monocyte-derived macrophages from Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET; n=941) by WGS revealed CHIP mutations in 14.2% (mean age 67.1 years). RNAseq of these macrophages revealed that expression patterns in CHIP mutation carriers differed substantially from those of non-carriers. Moreover, patterns were different depending on the underlying mutations, e.g. those carrying TET2 mutations predominantly displayed upregulated inflammatory signaling whereas ASXL1 mutations showed stronger effects on metabolic pathways.
Conclusions: Deep-DNA-sequencing reveals a high prevalence of CHIP mutations in whole blood of CAD patients. CHIP-affected leukocytes invade plaques in human coronary arteries. RNAseq data obtained from macrophages of CHIP-affected patients suggest that pro-atherosclerotic signaling differs depending on the underlying mutations. Further studies are necessary to understand whether specific pathways affected by CHIP mutations may be targeted for personalized treatment.
Background: Misconceptions about ADHD stigmatize affected people, reduce credibility of providers, and prevent/delay treatment. To challenge misconceptions, we curated findings with strong evidence base. Methods: We reviewed studies with more than 2000 participants or meta-analyses from five or more studies or 2000 or more participants. We excluded meta-analyses that did not assess publication bias, except for meta-analyses of prevalence. For network meta-analyses we required comparison adjusted funnel plots. We excluded treatment studies with waiting-list or treatment as usual controls. From this literature, we extracted evidence-based assertions about the disorder. Results: We generated 208 empirically supported statements about ADHD. The status of the included statements as empirically supported is approved by 80 authors from 27 countries and 6 continents. The contents of the manuscript are endorsed by 366 people who have read this document and agree with its contents. Conclusions: Many findings in ADHD are supported by meta-analysis. These allow for firm statements about the nature, course, outcome causes, and treatments for disorders that are useful for reducing misconceptions and stigma.
This paper compares measurements of gaseous and particulate emissions from a wide range of biomass-burning plumes intercepted by the NASA DC-8 research aircraft during the three phases of the ARCTAS-2008 experiment: ARCTAS-A, based out of Fairbanks, Alaska USA (3 April to 19 April 2008); ARCTAS-B based out of Cold Lake, Alberta, Canada (29 June to 13 July 2008); and ARCTAS-CARB, based out of Palmdale, California, USA (18 June to 24 June 2008). Extensive investigations of boreal fire plume evolution were undertaken during ARCTAS-B, where four distinct fire plumes that were intercepted by the aircraft over a range of down-wind distances (0.1 to 16 hr transport times) were studied in detail. Based on these analyses, there was no evidence for ozone production and a box model simulation of the data confirmed that net ozone production was slow (on average 1 ppbv h−1 in the first 3 h and much lower afterwards) due to limited NOx. Peroxyacetyl nitrate concentrations (PAN) increased with plume age and the box model estimated an average production rate of ~80 pptv h−1 in the first 3 h. Like ozone, there was also no evidence for net secondary inorganic or organic aerosol formation. There was no apparent increase in aerosol mass concentrations in the boreal fire plumes due to secondary organic aerosol (SOA) formation; however, there were indications of chemical processing of the organic aerosols. In addition to the detailed studies of boreal fire plume evolution, about 500 smoke plumes intercepted by the NASA DC-8 aircraft were segregated by fire source region. The normalized excess mixing ratios (i.e. ΔX/ΔCO) of gaseous (carbon dioxide, acetonitrile, hydrogen cyanide, toluene, benzene, methane, oxides of nitrogen (NOx), ozone, PAN) and fine aerosol particulate components (nitrate, sulfate, ammonium, chloride, organic aerosols and water soluble organic carbon) of these plumes were compared.
This paper compares measurements of gaseous and particulate emissions from a wide range of biomass-burning plumes intercepted by the NASA DC-8 research aircraft during the three phases of the ARCTAS-2008 experiment: ARCTAS-A, based out of Fairbanks, Alaska, USA (3 April to 19 April 2008); ARCTAS-B based out of Cold Lake, Alberta, Canada (29 June to 13 July 2008); and ARCTAS-CARB, based out of Palmdale, California, USA (18 June to 24 June 2008). Approximately 500 smoke plumes from biomass burning emissions that varied in age from minutes to days were segregated by fire source region and urban emission influences. The normalized excess mixing ratios (NEMR) of gaseous (carbon dioxide, acetonitrile, hydrogen cyanide, toluene, benzene, methane, oxides of nitrogen and ozone) and fine aerosol particulate components (nitrate, sulfate, ammonium, chloride, organic aerosols and water soluble organic carbon) of these plumes were compared. A detailed statistical analysis of the different plume categories for different gaseous and aerosol species is presented in this paper.
The comparison of NEMR values showed that CH4 concentrations were higher in air-masses that were influenced by urban emissions. Fresh biomass burning plumes mixed with urban emissions showed a higher degree of oxidative processing in comparison with fresh biomass burning only plumes. This was evident in higher concentrations of inorganic aerosol components such as sulfate, nitrate and ammonium, but not reflected in the organic components. Lower NOx NEMRs combined with high sulfate, nitrate and ammonium NEMRs in aerosols of plumes subject to long-range transport, when comparing all plume categories, provided evidence of advanced processing of these plumes.
Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a full seasonal cycle (Mar 2014–Feb 2015). In a companion part 1 paper, we presented an in-depth CCN characterization based on annually as well as seasonally averaged time intervals and discuss different parametrization strategies to represent the Amazonian CCN cycling in modelling studies (M. Pöhlker et al., 2016b). The present part 2 study analyzes the aerosol and CCN variability in original time resolution and, thus, resolves aerosol advection and transformation for the following case studies, which represent the most characteristic states of the Amazonian atmosphere:
1. Near-pristine (NP) conditions, defined as the absence of detectable black carbon (< 0.01 µg m−3), showed their highest occurrence (up to 30 %) in the wet season (i.e., Mar–May). On average, the NP episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode: DAit = 70 nm, NAit = ~ 200 cm−3 vs. weaker accumulation mode: Dacc = 170 nm, Nacc = ~ 60 cm−3), a mostly organic particle composition, and relatively low hygroscopicity levels (κAit = 0.12 vs. κacc = 0.18). The NP CCN efficiency spectrum shows that the CCN population is sensitive to changes in supersaturation (S) over a wide S range.
2. Long-range transport (LRT) conditions frequently mix Saharan dust, African combustion smoke, and sea spray aerosols into the Amazonian wet season atmosphere. The LRT episodes (i.e., Feb–Apr) are characterized by an accumulation mode dominated size distribution (DAit = 80 nm, NAit = 120 cm−3 vs. Dacc = 180 nm, Nacc = 300 cm−3), a clearly increased abundance of dust and salt compounds, and relatively high hygroscopicity levels (κAit = 0.18, κacc = 0.34). The LRT CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime.
3. Biomass burning (BB) conditions dominate the Amazonian dry season. A selected characteristic BB episode shows a very strong accumulation mode (DAit = 70 nm, NAit = ~ 140 cm−3 vs. Dacc = 170 nm, Nacc = ~ 3400 cm−3), particles with very high organic fractions (> 90 %), and correspondingly low hygroscopicity levels (κAit = 0.14, κacc = 0.17). The BB CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime.
4. Mixed pollution conditions show the superposition of African (i.e., volcanic) and Amazonian (i.e., biomass burning) aerosol emissions during the dry season. The African aerosols showed a broad monomodal distribution (D = 130 nm, N = ~ 1300 cm−3), with very high sulfate fractions (20 %), and correspondingly high hygroscopicity (κAit = 0.14, κacc = 0.22). This was superimposed by fresh smoke from nearby fires with one strong mode (D = 113 nm, Nacc = ~ 2800 cm−3), an organic-dominated aerosol, and sharply decreased hygroscopicity (κAit = 0.10, κacc = 0.20). These conditions underline the rapidly changing pollution regimes with clear impacts on the aerosol and CCN properties.
Overall, this study provides detailed insights into the CCN cycling in relation to aerosol-cloud interaction in the vulnerable and climate-relevant Amazon region. The detailed analysis of aerosol and CCN key properties and particularly the extracted CCN efficiency spectra with the associated fit parameters provide a basis for an in-depth analysis of aerosol-cloud interaction in the Amazon and beyond.
Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). The measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.
The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), higher values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.
The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.
For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.
Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations as well as hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a one-year period and full seasonal cycle (March 2014 - February 2015). The presented measurements provide a climatology of CCN properties for a characteristic central Amazonian rain forest site.
The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The observed mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), elevated values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.
The hygroscopicity parameter κ exhibits remarkably little temporal variability: no pronounced diurnal cycles, weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.
For modelling purposes, we compare different approaches of predicting CCN number concentration and present a novel parameterization, which allows accurate CCN predictions based on a small set of input data.
Streamer chamber data for collisions of Ar + KCl and Ar + BaI2 at 1.2 GeV/nucleon are compared with microscopic model predictions based on the Vlasov-Uehling-Uhlenbeck equation, for various density-dependent nuclear equations of state. Multiplicity distributions and inclusive rapidity and transverse momentum spectra are in good agreement. Rapidity spectra show evidence of being useful in determining whether the model uses the correct cross sections for binary collisions in the nuclear medium, and whether momentum-dependent interactions are correctly incorporated. Sideward flow results do not favor the same nuclear stiffness parameter at all multiplicities.