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Fluctuations of conserved quantities such as baryon number, charge, and strangeness are sensitive to the correlation length of the hot and dense matter created in relativistic heavy-ion collisions and can be used to search for the QCD critical point. We report the first measurements of the moments of net-kaon multiplicity distributions in Au+Au collisions at √sNN = 7.7, 11.5, 14.5, 19.6, 27, 39, 62.4, and 200 GeV. The collision centrality and energy dependence of the mean (M), variance (σ 2), skewness (S), and kurtosis (κ) for net-kaon multiplicity distributions as well as the ratio σ 2/M and the products Sσ and κσ 2 are presented. Comparisons are made with Poisson and negative binomial baseline calculations as well as with UrQMD, a transport model (UrQMD) that does not include effects from the QCD critical point. Within current uncertainties, the net-kaon cumulant ratios appear to be monotonic as a function of collision energy.
We report the direct virtual photon invariant yields in the transverse momentum ranges 1 < pT < 3 GeV/c and 5 < pT < 10 GeV/c at mid-rapidity derived from the dielectron invariant mass continuum region 0.10 < Mee < 0.28 GeV/c2 for 0–80% minimum-bias Au+Au collisions at √sN N = 200 GeV. A clear excess in the invariant yield compared to the nuclear overlap function T A A scaled p + p reference is observed in the pT range 1 < pT < 3 GeV/c. For pT > 6 GeV/c the production follows T A A scaling. Model calculations with contributions from thermal radiation and initial hard parton scattering are consistent ithin uncertainties with the direct virtual photon invariant yield.
The inclusive J/ψ transverse momentum spectra and nuclear modification factors are reported at midrapidity (|y| < 1.0) in Au+Au collisions at √sN N = 39, 62.4 and 200 GeV taken by the STAR experiment. A suppression of J/ψ production, with respect to the production in p + p scaled by the number of binary nucleon–nucleon collisions, is observed in central Au+Au collisions at these three energies. No significant energy dependence of nuclear modification factors is found within uncertainties. The measured nuclear modification factors can be described by model calculations that take into account both suppression of direct J/ψ production due to the color screening effect and J/ψ regeneration from recombination of uncorrelated charm–anticharm quark pairs.
We report new STAR measurements of the single-spin asymmetries 𝐴𝐿 for 𝑊+ and 𝑊− bosons produced in polarized proton-proton collisions at √𝑠=510 GeV as a function of the decay-positron and decay-electron pseudorapidity. The data were obtained in 2013 and correspond to an integrated luminosity of 250 pb−1. The results are combined with previous results obtained with 86 pb−1. A comparison with theoretical expectations based on polarized lepton-nucleon deep-inelastic scattering and prior polarized proton-proton data suggests a difference between the ¯𝑢 and ¯𝑑 quark helicity distributions for 0.05<𝑥<0.25. In addition, we report new results for the double-spin asymmetries 𝐴𝐿𝐿 for 𝑊±, as well as 𝐴𝐿 for 𝑍/𝛾* production and subsequent decay into electron-positron pairs.
Background: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls.
Principal findings: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci.
Significance: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
A floristic survey of 40 x 0.1 ha plots within the Demon Nature Reserve, 30 km east-south-east (lat. 29°05'S, long 152°15'E) of Tenterfield, was conducted in March, 1997. The Reserve (887 hectares in area) is on a western facing escarpment ranging from 500–1000 m above sea level. The survey data were analysed and seven vegetation communities defined. This paper describes the seven communities and discusses their significance and distribution within the reserve. A vegetation map and plant species list are provided.
Yellow fever virus (YFV) represents a re-emerging zoonotic pathogen, transmitted by mosquito vectors to humans from primate reservoirs. Sporadic outbreaks of YFV occur in endemic tropical regions, causing a viral hemorrhagic fever (VHF) associated with high mortality rates. Despite a highly effective vaccine, no antiviral treatments currently exist. Therefore, YFV represents a neglected tropical disease and is chronically understudied, with many aspects of YFV biology incompletely defined including host range, host–virus interactions and correlates of host immunity and pathogenicity. In this article, we review the current state of YFV research, focusing on the viral lifecycle, host responses to infection, species tropism and the success and associated limitations of the YFV-17D vaccine. In addition, we highlight the current lack of available treatments and use publicly available sequence and structural data to assess global patterns of YFV sequence diversity and identify potential drug targets. Finally, we discuss how technological advances, including real-time epidemiological monitoring of outbreaks using next-generation sequencing and CRISPR/Cas9 modification of vector species, could be utilized in future battles against this re-emerging pathogen which continues to cause devastating disease.
The success of invasive species has been explained by two contrasting but non-exclusive views: (i) intrinsic factors make some species inherently good invaders; (ii) species become invasive as a result of extrinsic ecological and genetic influences such as release from natural enemies, hybridization or other novel ecological and evolutionary interactions. These viewpoints are rarely distinguished but hinge on distinct mechanisms leading to different management scenarios. To improve tests of these hypotheses of invasion success we introduce a simple mathematical framework to quantify the invasiveness of species along two axes: (i) interspecific differences in performance among native and introduced species within a region, and (ii) intraspecific differences between populations of a species in its native and introduced ranges. Applying these equations to a sample dataset of occurrences of 1,416 plant species across Europe, Argentina, and South Africa, we found that many species are common in their native range but become rare following introduction; only a few introduced species become more common. Biogeographical factors limiting spread (e.g. biotic resistance, time of invasion) therefore appear more common than those promoting invasion (e.g. enemy release). Invasiveness, as measured by occurrence data, is better explained by inter-specific variation in invasion potential than biogeographical changes in performance. We discuss how applying these comparisons to more detailed performance data would improve hypothesis testing in invasion biology and potentially lead to more efficient management strategies.
National greenhouse gas inventories (GHGIs) are submitted annually to the United Nations Framework Convention on Climate Change (UNFCCC). They are estimated in compliance with Intergovernmental Panel on Climate Change (IPCC) methodological guidance using activity data, emission factors and facility-level measurements. For some sources, the outputs from these calculations are very uncertain. Inverse modelling techniques that use high-quality, long-term measurements of atmospheric gases have been developed to provide independent verification of national GHGIs. This is considered good practice by the IPCC as it helps national inventory compilers to verify reported emissions and to reduce emission uncertainty. Emission estimates from the InTEM (Inversion Technique for Emission Modelling) model are presented for the UK for the hydrofluorocarbons (HFCs) reported to the UNFCCC (HFC-125, HFC-134a, HFC-143a, HFC-152a, HFC-23, HFC-32, HFC-227ea, HFC-245fa, HFC-43-10mee and HFC-365mfc). These HFCs have high global warming potentials (GWPs), and the global background mole fractions of all but two are increasing, thus highlighting their relevance to the climate and a need for increasing the accuracy of emission estimation for regulatory purposes. This study presents evidence that the long-term annual increase in growth of HFC-134a has stopped and is now decreasing. For HFC-32 there is an early indication, its rapid global growth period has ended, and there is evidence that the annual increase in global growth for HFC-125 has slowed from 2018. The inverse modelling results indicate that the UK implementation of European Union regulation of HFC emissions has been successful in initiating a decline in UK emissions from 2018. Comparison of the total InTEM UK HFC emissions in 2020 with the average from 2009–2012 shows a drop of 35 %, indicating progress toward the target of a 79 % decrease in sales by 2030. The total InTEM HFC emission estimates (2008–2018) are on average 73 (62–83) % of, or 4.3 (2.7–5.9) Tg CO2-eq yr−1 lower than, the total HFC emission estimates from the UK GHGI. There are also significant discrepancies between the two estimates for the individual HFCs.
National Greenhouse Gas Inventories (GHGI) are submitted annually to the United Nations Framework Convention on Climate Change (UNFCCC). They are estimated in compliance with Intergovernmental Panel on Climate Change (IPCC) methodological guidance using activity data, emission factors and facility-level measurements. For some sources, the outputs from these calculations are very uncertain. Inverse modelling techniques that use high-quality, long-term measurements of atmospheric gases have been developed to provide independent verification of national GHGI. This is considered good practice by the IPCC as it helps national inventory compilers to verify reported emissions and to reduce emission uncertainty. Emission estimates from the InTEM (Inversion Technique for Emissions Modelling) model are presented for the UK for the hydrofluorocarbons (HFCs) reported to the UNFCCC (HFC-125, HFC-134a, HFC-143a, HFC-152a, HFC-23, HFC-32, HFC-227ea, HFC-245fa, HFC-43-10mee and HFC-365mfc). These HFCs have high Global Warming Potentials (GWPs) and the global background mole fractions of all but two are increasing, thus highlighting their relevance to the climate and a need for increasing the accuracy of emission estimation for regulatory purposes. This study presents evidence that the long-term annual increase in growth of HFC-134a has stopped and is now decreasing. For HFC-32 there is an early indication its rapid global growth period has ended, and there is evidence that the annual increase in global growth for HFC-125 has slowed from 2018. The inverse modelling results indicate that the UK implementation of European Union regulation of HFC emissions has been successful in initiating a decline in UK emissions in the since 2018. Comparison of the total InTEM UK HFC emissions in 2020 with the average from 2009–2012 shows a drop of 35%, indicating progress toward the target of a 79% decrease in sales by 2030. The total InTEM HFC emission estimates (2008–2018) are on average 73 (62–83)% of, or 4.3 (2.7–5.9) Tg CO2-eq yr−1 lower than, the total HFC emission estimates from the UK GHGI inventory. There are also significant discrepancies between the two estimates for the individual HFCs.
Introduced perennial grasses are capable of altering the habitat of native species, causing reductions in population size and vigour, and potentially affecting life-history processes such as survival, pollination and seedling recruitment. We examined the utility of herbicide treatment on two exotic grasses, Pennisetum clandestinum (Kikuyu) and Stenotaphrum secundatum (Buffalo grass) to restore the habitat of Calystegia affinis, a critically endangered species endemic to Lord Howe and Norfolk Islands. Using two herbicides, Asset (designed to affect only grasses) and Glyphosate (a general herbicide), we compared effectiveness in reducing grass cover on a population of Calystegia affinis. We protected Calystegia plants from the herbicides by ensuring their leaves were covered by plastic bags during herbicide application. Both herbicides were similarly effective in reducing grass cover after four weeks and had no noticeable adverse affect on Calystegia (suggesting the plastic bag protection was effective). After 26 weeks, Glyphosate was more effective in maintaining a reduced grass cover. Plots treated with either herbicide had a greater relative increase in abundance of Calystegia stems compared to untreated controls. The Glyphosate treatment resulted in the greatest relative increase in stem abundance, but this was not significantly greater than in the Asset treatment. We consider that spraying with Glyphosate treatment, with follow-up monitoring and spot-spraying, will assist the recovery of the Calystegia affinis population. Ultimately, the maintenance of a weed-free zone at the forest edge will provide suitable habitat for additional recruitment of this and other native species.
Knowledge about the biogeographic affinities of the world’s tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world’s tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests.
Background: Histone lysine demethylases (KDMs) are of interest as drug targets due to their regulatory roles in chromatin organization and their tight associations with diseases including cancer and mental disorders. The first KDM inhibitors for KDM1 have entered clinical trials, and efforts are ongoing to develop potent, selective and cell-active ‘probe’ molecules for this target class. Robust cellular assays to assess the specific engagement of KDM inhibitors in cells as well as their cellular selectivity are a prerequisite for the development of high-quality inhibitors. Here we describe the use of a high-content cellular immunofluorescence assay as a method for demonstrating target engagement in cells.
Results: A panel of assays for the Jumonji C subfamily of KDMs was developed to encompass all major branches of the JmjC phylogenetic tree. These assays compare compound activity against wild-type KDM proteins to a catalytically inactive version of the KDM, in which residues involved in the active-site iron coordination are mutated to inactivate the enzyme activity. These mutants are critical for assessing the specific effect of KDM inhibitors and for revealing indirect effects on histone methylation status. The reported assays make use of ectopically expressed demethylases, and we demonstrate their use to profile several recently identified classes of KDM inhibitors and their structurally matched inactive controls. The generated data correlate well with assay results assessing endogenous KDM inhibition and confirm the selectivity observed in biochemical assays with isolated enzymes. We find that both cellular permeability and competition with 2-oxoglutarate affect the translation of biochemical activity to cellular inhibition.
Conclusions: High-content-based immunofluorescence assays have been established for eight KDM members of the 2-oxoglutarate-dependent oxygenases covering all major branches of the JmjC-KDM phylogenetic tree. The usage of both full-length, wild-type and catalytically inactive mutant ectopically expressed protein, as well as structure-matched inactive control compounds, allowed for detection of nonspecific effects causing changes in histone methylation as a result of compound toxicity. The developed assays offer a histone lysine demethylase family-wide tool for assessing KDM inhibitors for cell activity and on-target efficacy. In addition, the presented data may inform further studies to assess the cell-based activity of histone lysine methylation inhibitors.