176 research outputs found

    Cavitation induced by explosion in a model of ideal fluid

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    We discuss the problem of an explosion in the cubic-quintic superfluid model, in relation to some experimental observations. We show numerically that an explosion in such a model might induce a cavitation bubble for large enough energy. This gives a consistent view for rebound bubbles in superfluid and we indentify the loss of energy between the successive rebounds as radiated waves. We compute self-similar solution of the explosion for the early stage, when no bubbles have been nucleated. The solution also gives the wave number of the excitations emitted through the shock wave.Comment: 21 pages,13 figures, other comment

    Linking Metabolic QTLs with Network and cis-eQTLs Controlling Biosynthetic Pathways

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    Phenotypic variation between individuals of a species is often under quantitative genetic control. Genomic analysis of gene expression polymorphisms between individuals is rapidly gaining popularity as a way to query the underlying mechanistic causes of variation between individuals. However, there is little direct evidence of a linkage between global gene expression polymorphisms and phenotypic consequences. In this report, we have mapped quantitative trait loci (QTLs)–controlling glucosinolate content in a population of 403 Arabidopsis Bay × Sha recombinant inbred lines, 211 of which were previously used to identify expression QTLs controlling the transcript levels of biosynthetic genes. In a comparative study, we have directly tested two plant biosynthetic pathways for association between polymorphisms controlling biosynthetic gene transcripts and the resulting metabolites within the Arabidopsis Bay × Sha recombinant inbred line population. In this analysis, all loci controlling expression variation also affected the accumulation of the resulting metabolites. In addition, epistasis was detected more frequently for metabolic traits compared to transcript traits, even when both traits showed similar distributions. An analysis of candidate genes for QTL-controlling networks of transcripts and metabolites suggested that the controlling factors are a mix of enzymes and regulatory factors. This analysis showed that regulatory connections can feedback from metabolism to transcripts. Surprisingly, the most likely major regulator of both transcript level for nearly the entire pathway and aliphatic glucosinolate accumulation is variation in the last enzyme in the biosynthetic pathway, AOP2. This suggests that natural variation in transcripts may significantly impact phenotypic variation, but that natural variation in metabolites or their enzymatic loci can feed back to affect the transcripts

    Direct observation of nuclear reorganization driven by ultrafast spin transitions

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    One of the most basic molecular photophysical processes is that of spin transitions and intersystem crossing between excited states surfaces. The change in spin states affects the spatial distribution of electron density through the spin orbit coupling interaction. The subsequent nuclear reorganization reports on the full extent of the spin induced change in electron distribution, which can be treated similarly to intramolecular charge transfer with effective reaction coordinates depicting the spin transition. Here, single-crystal [FeII(bpy)3] (PF6)2, a prototypical system for spin crossover (SCO) dynamics, is studied using ultrafast electron diffraction in the single-photon excitation regime. The photoinduced SCO dynamics are resolved, revealing two distinct processes with a (450 ± 20)-fs fast component and a (2.4 ± 0.4)-ps slow component. Using principal component analysis, we uncover the key structural modes, ultrafast Fe–N bond elongations coupled with ligand motions, that define the effective reaction coordinate to fully capture the relevant molecular reorganization

    A Mouse Model of Heritable Cerebrovascular Disease

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    The study of animal models of heritable cerebrovascular diseases can improve our understanding of disease mechanisms, identify candidate genes for related human disorders, and provide experimental models for preclinical trials. Here we describe a spontaneous mouse mutation that results in reproducible, adult-onset, progressive, focal ischemia in the brain. The pathology is not the result of hemorrhage, embolism, or an anatomical abnormality in the cerebral vasculature. The mutation maps as a single site recessive locus to mouse Chromosome 9 at 105 Mb, a region of shared synteny with human chromosome 3q22. The genetic interval, defined by recombination mapping, contains seven protein-coding genes and one processed transcript, none of which are changed in their expression level, splicing, or sequence in affected mice. Targeted resequencing of the entire interval did not reveal any provocative changes; thus, the causative molecular lesion has not been identified

    Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development

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    Most phenotypic variation present in natural populations is under polygenic control, largely determined by genetic variation at quantitative trait loci (QTLs). These genetic loci frequently interact with the environment, development, and each other, yet the importance of these interactions on the underlying genetic architecture of quantitative traits is not well characterized. To better study how epistasis and development may influence quantitative traits, we studied genetic variation in Arabidopsis glucosinolate activation using the moderately sized Bayreuth×Shahdara recombinant inbred population, in terms of number of lines. We identified QTLs for glucosinolate activation at three different developmental stages. Numerous QTLs showed developmental dependency, as well as a large epistatic network, centered on the previously cloned large-effect glucosinolate activation QTL, ESP. Analysis of Heterogeneous Inbred Families validated seven loci and all of the QTL×DPG (days post-germination) interactions tested, but was complicated by the extensive epistasis. A comparison of transcript accumulation data within 211 of these RILs showed an extensive overlap of gene expression QTLs for structural specifiers and their homologs with the identified glucosinolate activation loci. Finally, we were able to show that two of the QTLs are the result of whole-genome duplications of a glucosinolate activation gene cluster. These data reveal complex age-dependent regulation of structural outcomes and suggest that transcriptional regulation is associated with a significant portion of the underlying ontogenic variation and epistatic interactions in glucosinolate activation

    Elucidating real-world vehicle emission factors from mobile measurements over a large metropolitan region: a focus on isocyanic acid, hydrogen cyanide, and black carbon

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    A mobile laboratory equipped with state-of-the-art gaseous and particulate instrumentation was deployed across the Greater Toronto Area (GTA) during two seasons. A high-resolution time-of-flight chemical ionization mass spectrometer (HR-TOF-CIMS) measured isocyanic acid (HNCO) and hydrogen cyanide (HCN), and a high-sensitivity laser-induced incandescence (HS-LII) instrument measured black carbon (BC). Results indicate that on-road vehicles are a clear source of HNCO and HCN and that their impact is more pronounced in the winter, when influences from biomass burning (BB) and secondary photochemistry are weakest. Plume-based and time-based algorithms were developed to calculate fleet-average vehicle emission factors (EFs); the algorithms were found to yield comparable results, depending on the pollutant identity. With respect to literature EFs for benzene, toluene, C2 benzene (sum of m-, p-, and o-xylenes and ethylbenzene), nitrogen oxides, particle number concentration (PN), and black carbon, the calculated EFs were characteristic of a relatively clean vehicle fleet dominated by light-duty vehicles (LDV). Our fleet-average EF for BC (median: 25&thinsp;mg&thinsp;kgfuel-1; interquartile range, IQR: 10–76&thinsp;mg&thinsp;kgfuel-1) suggests that overall vehicular emissions of BC have decreased over time. However, the distribution of EFs indicates that a small proportion of high-emitters continue to contribute disproportionately to total BC emissions. We report the first fleet-average EF for HNCO (median: 2.3&thinsp;mg&thinsp;kgfuel-1, IQR: 1.4–4.2&thinsp;mg&thinsp;kgfuel-1) and HCN (median: 0.52&thinsp;mg&thinsp;kgfuel-1, IQR: 0.32–0.88&thinsp;mg&thinsp;kgfuel-1). The distribution of the estimated EFs provides insight into the real-world variability of HNCO and HCN emissions and constrains the wide range of literature EFs obtained from prior dynamometer studies. The impact of vehicle emissions on urban HNCO levels can be expected to be further enhanced if secondary HNCO formation from vehicle exhaust is considered.</p

    Use of divalent metal ions in the DNA cleavage reaction of topoisomerase IV

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    It has long been known that type II topoisomerases require divalent metal ions in order to cleave DNA. Kinetic, mutagenesis and structural studies indicate that the eukaryotic enzymes utilize a novel variant of the canonical two-metal-ion mechanism to promote DNA scission. However, the role of metal ions in the cleavage reaction mediated by bacterial type II enzymes has been controversial. Therefore, to resolve this critical issue, this study characterized the DNA cleavage reaction of Escherichia coli topoisomerase IV. We utilized a series of divalent metal ions with varying thiophilicities in conjunction with oligonucleotides that replaced bridging and non-bridging oxygen atoms at (and near) the scissile bond with sulfur atoms. DNA scission was enhanced when thiophilic metal ions were used with substrates that contained bridging sulfur atoms. In addition, the metal-ion dependence of DNA cleavage was sigmoidal in nature, and rates and levels of DNA cleavage increased when metal ion mixtures were used in reactions. Based on these findings, we propose that topoisomerase IV cleaves DNA using a two-metal-ion mechanism in which one of the metal ions makes a critical interaction with the 3′-bridging atom of the scissile phosphate and facilitates DNA scission by the bacterial type II enzyme

    Nucleation and condensational growth to CCN sizes during a sustained pristine biogenic SOA event in a forested mountain valley

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    The Whistler Aerosol and Cloud Study (WACS 2010), included intensive measurements of trace gases and particles at two sites on Whistler Mountain. Between 6–11 July 2010 there was a sustained high-pressure system over the region with cloud-free conditions and the highest temperatures of the study. During this period, the organic aerosol concentrations rose from &lt;1 μg m&lt;sup&gt;−3&lt;/sup&gt; to &amp;sim;6 μg m&lt;sup&gt;−3&lt;/sup&gt;. Precursor gas and aerosol composition measurements show that these organics were almost entirely of secondary biogenic nature. Throughout 6–11 July, the anthropogenic influence was minimal with sulfate concentrations &lt;0.2 μg m&lt;sup&gt;−3&lt;/sup&gt; and SO&lt;sub&gt;2&lt;/sub&gt; mixing ratios &amp;approx; 0.05–0.1 ppbv. Thus, this case provides excellent conditions to probe the role of biogenic secondary organic aerosol in aerosol microphysics. Although SO&lt;sub&gt;2&lt;/sub&gt; mixing ratios were relatively low, box-model simulations show that nucleation and growth may be modeled accurately if &lt;i&gt;J&lt;/i&gt;&lt;sub&gt;nuc&lt;/sub&gt; = 3 × 10&lt;sup&gt;&amp;minus;7&lt;/sup&gt;[H&lt;sub&gt;2&lt;/sub&gt;SO&lt;sub&gt;4&lt;/sub&gt;] and the organics are treated as effectively non-volatile. Due to the low condensation sink and the fast condensation rate of organics, the nucleated particles grew rapidly (2–5 nm h&lt;sup&gt;&amp;minus;1&lt;/sup&gt;) with a 10–25% probability of growing to CCN sizes (100 nm) in the first two days as opposed to being scavenged by coagulation with larger particles. The nucleated particles were observed to grow to &amp;sim;200 nm after three days. Comparisons of size-distribution with CCN data show that particle hygroscopicity (&amp;kappa;) was &amp;sim;0.1 for particles larger 150 nm, but for smaller particles near 100 nm the κ value decreased near midway through the period from 0.17 to less than 0.06. In this environment of little anthropogenic influence and low SO&lt;sub&gt;2&lt;/sub&gt;, the rapid growth rates of the regionally nucleated particles – due to condensation of biogenic SOA – results in an unusually high efficiency of conversion of the nucleated particles to CCN. Consequently, despite the low SO&lt;sub&gt;2&lt;/sub&gt;, nucleation/growth appear to be the dominant source of particle number

    The Complex Genetic Architecture of the Metabolome

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    Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype–metabolite associations distributed non-randomly within the genome. These clusters of genotype–metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype–metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable

    The structure of SgrAI bound to DNA; recognition of an 8 base pair target

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    The three-dimensional X-ray crystal structure of the ‘rare cutting’ type II restriction endonuclease SgrAI bound to cognate DNA is presented. SgrAI forms a dimer bound to one duplex of DNA. Two Ca2+ bind in the enzyme active site, with one ion at the interface between the protein and DNA, and the second bound distal from the DNA. These sites are differentially occupied by Mn2+, with strong binding at the protein–DNA interface, but only partial occupancy of the distal site. The DNA remains uncleaved in the structures from crystals grown in the presence of either divalent cation. The structure of the dimer of SgrAI is similar to those of Cfr10I, Bse634I and NgoMIV, however no tetrameric structure of SgrAI is observed. DNA contacts to the central CCGG base pairs of the SgrAI canonical target sequence (CR|CCGGYG, | marks the site of cleavage) are found to be very similar to those in the NgoMIV/DNA structure (target sequence G|CCGGC). Specificity at the degenerate YR base pairs of the SgrAI sequence may occur via indirect readout using DNA distortion. Recognition of the outer GC base pairs occurs through a single contact to the G from an arginine side chain located in a region unique to SgrAI
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