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Giant X-ray outbursts, with luminosities of about 10(37) erg s(-1), are observed roughly every five years from the nearby Be/pulsar binary 1A 0535+262. In this article, we present observations of the source with VERITAS at very high energies (VHEs; E > 100 GeV) triggered by the X-ray outburst in 2009 December. The observations started shortly after the onset of the outburst and provided comprehensive coverage of the episode, as well as the 111 day binary orbit. No VHE emission is evident at any time. We also examined data from the contemporaneous observations of 1A 0535+262 with the Fermi/Large Area Telescope at high-energy photons (E > 0.1 GeV) and failed to detect the source at GeV energies. The X-ray continua measured with the Swift/X-Ray Telescope and the RXTE/PCA can be well described by the combination of blackbody and Comptonized emission from thermal electrons. Therefore, the gamma-ray and X-ray observations suggest the absence of a significant population of non-thermal particles in the system. This distinguishes 1A 0535+262 from those Be X-ray binaries (such as PSR B1259-63 and LS I +61 degrees 303) that have been detected at GeV-TeV energies. We discuss the implications of the results on theoretical models.
We present the results of 16 Swift-triggered Gamma-ray burst (GRB) follow-up observations taken with the Very Energetic Radiation Imaging Telescope Array System (VERITAS) telescope array from 2007 January to 2009 June. The median energy threshold and response time of these observations were 260 GeV and 320 s, respectively. Observations had an average duration of 90 minutes. Each burst is analyzed independently in two modes: over the whole duration of the observations and again over a shorter timescale determined by the maximum VERITAS sensitivity to a burst with a t(-1.5) time profile. This temporal model is characteristic of GRB afterglows with high-energy, long-lived emission that have been detected by the Large Area Telescope on board the Fermi satellite. No significant very high energy (VHE) gamma-ray emission was detected and upper limits above the VERITAS threshold energy are calculated. The VERITAS upper limits are corrected for gamma-ray extinction by the extragalactic background light and interpreted in the context of the keV emission detected by Swift. For some bursts the VHE emission must have less power than the keV emission, placing constraints on inverse Compton models of VHE emission.
We report the discovery of TeV gamma-ray emission from the Type Ia supernova remnant (SNR) G120.1+1.4, known as Tycho's SNR. Observations performed in the period 2008-2010 with the VERITAS ground-based gamma-ray observatory reveal weak emission coming from the direction of the remnant, compatible with a point source located at 00(h)25(m)27(s).0, +64 degrees 10'50 '' (J2000). The TeV photon spectrum measured by VERITAS can be described with a power law dN/dE = C(E/3.42 TeV)(-Gamma) with Gamma = 1.95 +/- 0.51(stat) +/- 0.30(sys) and C = (1.55 +/- 0.43(stat) +/- 0.47(sys)) x 10(-14) cm(-2) s(-1) TeV-1. The integral flux above 1 TeV corresponds to similar to 0.9% of the steady Crab Nebula emission above the same energy, making it one of the weakest sources yet detected in TeV gamma rays. We present both leptonic and hadronic models that can describe the data. The lowest magnetic field allowed in these models is similar to 80 mu G, which may be interpreted as evidence for magnetic field amplification.
Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P< 5 x 10(-8). In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.
Ammonium is a primary source of N for plants, so knowing how it is transported, stored, and assimilated in plant cells is important for rational approaches to optimise N-use in agriculture. Electrophysiological studies of Arabidopsis AtAMT1;1 expressed in oocytes revealed passive, Delta psi-driven transport of NH4+ through this protein. Expression of AtAMT1;1 in a novel yeast mutant defective in endogenous ammonium transport and vacuolar acidification supported the above mechanism for AtAMT1;1 and revealed a central role for acid vacuoles in storage and retention of ammonia in cells. These results highlight the mechanistic differences between plant AMT proteins and related transporters in bacteria and animal cells, and suggest novel strategies to enhance nitrogen use efficiency in agriculture. (c) 2006 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved
Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 Â 10 À8 . In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.
Food system innovations will be instrumental to achieving multiple Sustainable Development Goals (SDGs). However, major innovation breakthroughs can trigger profound and disruptive changes, leading to simultaneous and interlinked reconfigurations of multiple parts of the global food system. The emergence of new technologies or social solutions, therefore, have very different impact profiles, with favourable consequences for some SDGs and unintended adverse side-effects for others. Stand-alone innovations seldom achieve positive outcomes over multiple sustainability dimensions. Instead, they should be embedded as part of systemic changes that facilitate the implementation of the SDGs. Emerging trade-offs need to be intentionally addressed to achieve true sustainability, particularly those involving social aspects like inequality in its many forms, social justice, and strong institutions, which remain challenging. Trade-offs with undesirable consequences are manageable through the development of well planned transition pathways, careful monitoring of key indicators, and through the implementation of transparent science targets at the local level.
Venomous snakes often display extensive variation in venom composition both between and within species. However, the mechanisms underlying the distribution of different toxins and venom types among populations and taxa remain insufficiently known. Rattlesnakes (Crotalus, Sistrurus) display extreme inter-and intraspecific variation in venom composition, centered particularly on the presence or absence of presynaptically neurotoxic phospholipases A2 such as Mojave toxin (MTX). Interspecific hybridization has been invoked as a mechanism to explain the distribution of these toxins across rattlesnakes, with the implicit assumption that they are adaptively advantageous. Here, we test the potential of adaptive hybridization as a mechanism for venom evolution by assessing the distribution of genes encoding the acidic and basic subunits of Mojave toxin across a hybrid zone between MTX-positive Crotalus scutulatus and MTX-negative C. viridis in southwestern New Mexico, USA. Analyses of morphology, mitochondrial and single copy-nuclear genes document extensive admixture within a narrow hybrid zone. The genes encoding the two MTX subunits are strictly linked, and found in most hybrids and backcrossed individuals, but not in C. viridis away from the hybrid zone. Presence of the genes is invariably associated with presence of the corresponding toxin in the venom. We conclude that introgression of highly lethal neurotoxins through hybridization is not necessarily favored by natural selection in rattlesnakes, and that even extensive hybridization may not lead to introgression of these genes into another species.
Venomous snakes often display extensive variation in venom composition both between and within species. However, the mechanisms underlying the distribution of different toxins and venom types among populations and taxa remain insufficiently known. Rattlesnakes (Crotalus, Sistrurus) display extreme inter-and intraspecific variation in venom composition, centered particularly on the presence or absence of presynaptically neurotoxic phospholipases A2 such as Mojave toxin (MTX). Interspecific hybridization has been invoked as a mechanism to explain the distribution of these toxins across rattlesnakes, with the implicit assumption that they are adaptively advantageous. Here, we test the potential of adaptive hybridization as a mechanism for venom evolution by assessing the distribution of genes encoding the acidic and basic subunits of Mojave toxin across a hybrid zone between MTX-positive Crotalus scutulatus and MTX-negative C. viridis in southwestern New Mexico, USA. Analyses of morphology, mitochondrial and single copy-nuclear genes document extensive admixture within a narrow hybrid zone. The genes encoding the two MTX subunits are strictly linked, and found in most hybrids and backcrossed individuals, but not in C. viridis away from the hybrid zone. Presence of the genes is invariably associated with presence of the corresponding toxin in the venom. We conclude that introgression of highly lethal neurotoxins through hybridization is not necessarily favored by natural selection in rattlesnakes, and that even extensive hybridization may not lead to introgression of these genes into another species.
Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.