1,591 research outputs found

    Adaptation and application of the large LAERTES-EU regional climate model ensemble for modeling hydrological extremes: a pilot study for the Rhine basin

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    Enduring and extensive heavy precipitation events associated with widespread river floods are among the main natural hazards affecting central Europe. Since such events are characterized by long return periods, it is difficult to adequately quantify their frequency and intensity solely based on the available observations of precipitation. Furthermore, long-term observations are rare, not homogeneous in space and time, and thus not suitable to running hydrological models (HMs) with respect to extremes. To overcome this issue, we make use of the recently introduced LAERTES-EU (LArge Ensemble of Regional climaTe modEl Simulations for EUrope) data set, which is an ensemble of regional climate model simulations providing over 12 000 simulated years. LAERTES-EU is adapted for use in an HM to calculate discharges for large river basins by applying quantile mapping with a parameterized gamma distribution to correct the mainly positive bias in model precipitation. The Rhine basin serves as a pilot area for calibration and validation. The results show clear improvements in the representation of both precipitation (e.g., annual cycle and intensity distributions) and simulated discharges by the HM after the bias correction. Furthermore, the large size of LAERTES-EU also improves the statistical representativeness for high return values above 100 years of discharges. We conclude that the bias-corrected LAERTES-EU data set is generally suitable for hydrological applications and posterior risk analyses. The results of this pilot study will soon be applied to several large river basins in central Europe

    Allelic Ratios and the Mutational Landscape Reveal Biologically Significant Heterozygous SNVs

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    The issue of heterozygosity continues to be a challenge in the analysis of genome sequences. In this article, we describe the use of allele ratios to distinguish biologically significant single-nucleotide variants from background noise. An application of this approach is the identification of lethal mutations in Caenorhabditis elegans essential genes, which must be maintained by the presence of a wild-type allele on a balancer. The h448 allele of let-504 is rescued by the duplication balancer sDp2. We readily identified the extent of the duplication when the percentage of read support for the lesion was between 70 and 80%. Examination of the EMS-induced changes throughout the genome revealed that these mutations exist in contiguous blocks. During early embryonic division in self-fertilizing C. elegans, alkylated guanines pair with thymines. As a result, EMS-induced changes become fixed as either G→A or C→T changes along the length of the chromosome. Thus, examination of the distribution of EMS-induced changes revealed the mutational and recombinational history of the chromosome, even generations later. We identified the mutational change responsible for the h448 mutation and sequenced PCR products for an additional four alleles, correlating let-504 with the DNA-coding region for an ortholog of a NFκB-activating protein, NKAP. Our results confirm that whole-genome sequencing is an efficient and inexpensive way of identifying nucleotide alterations responsible for lethal phenotypes and can be applied on a large scale to identify the molecular basis of essential genes

    Quantum entanglement and disentanglement of multi-atom systems

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    We present a review of recent research on quantum entanglement, with special emphasis on entanglement between single atoms, processing of an encoded entanglement and its temporary evolution. Analysis based on the density matrix formalism are described. We give a simple description of the entangling procedure and explore the role of the environment in creation of entanglement and in disentanglement of atomic systems. A particular process we will focus on is spontaneous emission, usually recognized as an irreversible loss of information and entanglement encoded in the internal states of the system. We illustrate some certain circumstances where this irreversible process can in fact induce entanglement between separated systems. We also show how spontaneous emission reveals a competition between the Bell states of a two qubit system that leads to the recently discovered "sudden" features in the temporal evolution of entanglement. An another problem illustrated in details is a deterministic preparation of atoms and atomic ensembles in long-lived stationary squeezed states and entangled cluster states. We then determine how to trigger the evolution of the stable entanglement and also address the issue of a steered evolution of entanglement between desired pairs of qubits that can be achieved simply by varying the parameters of a given system.Comment: Review articl

    Intracellular Proton Conductance of the Hepatitis C Virus p7 Protein and Its Contribution to Infectious Virus Production

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    The hepatitis C virus (HCV) p7 protein is critical for virus production and an attractive antiviral target. p7 is an ion channel when reconstituted in artificial lipid bilayers, but channel function has not been demonstrated in vivo and it is unknown whether p7 channel activity plays a critical role in virus production. To evaluate the contribution of p7 to organelle pH regulation and virus production, we incorporated a fluorescent pH sensor within native, intracellular vesicles in the presence or absence of p7 expression. p7 increased proton (H+) conductance in vesicles and was able to rapidly equilibrate H+ gradients. This conductance was blocked by the viroporin inhibitors amantadine, rimantadine and hexamethylene amiloride. Fluorescence microscopy using pH indicators in live cells showed that both HCV infection and expression of p7 from replicon RNAs reduced the number of highly acidic (pH<5) vesicles and increased lysosomal pH from 4.5 to 6.0. These effects were not present in uninfected cells, sub-genomic replicon cells not expressing p7, or cells electroporated with viral RNA containing a channel-inactive p7 point mutation. The acidification inhibitor, bafilomycin A1, partially restored virus production to cells electroporated with viral RNA containing the channel inactive mutation, yet did not in cells containing p7-deleted RNA. Expression of influenza M2 protein also complemented the p7 mutant, confirming a requirement for H+ channel activity in virus production. Accordingly, exposure to acid pH rendered intracellular HCV particles non-infectious, whereas the infectivity of extracellular virions was acid stable and unaffected by incubation at low pH, further demonstrating a key requirement for p7-induced loss of acidification. We conclude that p7 functions as a H+ permeation pathway, acting to prevent acidification in otherwise acidic intracellular compartments. This loss of acidification is required for productive HCV infection, possibly through protecting nascent virus particles during an as yet uncharacterized maturation process

    The Complexity of Approximating complex-valued Ising and Tutte partition functions

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    We study the complexity of approximately evaluating the Ising and Tutte partition functions with complex parameters. Our results are partly motivated by the study of the quantum complexity classes BQP and IQP. Recent results show how to encode quantum computations as evaluations of classical partition functions. These results rely on interesting and deep results about quantum computation in order to obtain hardness results about the difficulty of (classically) evaluating the partition functions for certain fixed parameters. The motivation for this paper is to study more comprehensively the complexity of (classically) approximating the Ising and Tutte partition functions with complex parameters. Partition functions are combinatorial in nature and quantifying their approximation complexity does not require a detailed understanding of quantum computation. Using combinatorial arguments, we give the first full classification of the complexity of multiplicatively approximating the norm and additively approximating the argument of the Ising partition function for complex edge interactions (as well as of approximating the partition function according to a natural complex metric). We also study the norm approximation problem in the presence of external fields, for which we give a complete dichotomy when the parameters are roots of unity. Previous results were known just for a few such points, and we strengthen these results from BQP-hardness to #P-hardness. Moreover, we show that computing the sign of the Tutte polynomial is #P-hard at certain points related to the simulation of BQP. Using our classifications, we then revisit the connections to quantum computation, drawing conclusions that are a little different from (and incomparable to) ones in the quantum literature, but along similar lines

    Polygenicity of Comorbid Depression in Multiple Sclerosis

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    BACKGROUND AND OBJECTIVES: Depression is common in multiple sclerosis (MS) and is associated with faster disability progression. The etiology of comorbid depression in MS remains poorly understood. Identification of individuals with a high risk of depression, through polygenic scores (PGS), may facilitate earlier identification. Previous genetic studies of depression considered depression as a primary disorder, not a comorbidity, and thus, findings may not generalize to MS. Body mass index (BMI) is a risk factor of both MS and depression, and its association may highlight differences in depression in MS. To improve the understanding of comorbid depression in MS, we will investigate PGS in people with MS, with the hypothesis that a higher depression PGS is associated with increased odds for comorbid depression in MS. METHODS: Samples from 3 sources (Canada, UK Biobank, and the United States) were used. Individuals were grouped into cases (MS/comorbid depression) and compared with 3 control groups: MS/no depression, depression/no immune disease, and healthy persons. We used 3 depression definitions: lifetime clinical diagnoses, self-reported diagnoses, and depressive symptoms. The PGS were tested in association with depression using regression. RESULTS: A total of 106,682 individuals of European genetic ancestry were used: Canada (n = 370; 213 with MS), UK Biobank (n = 105,734; 1,390 with MS), and the United States (n = 578 with MS). Meta-analyses revealed individuals with MS and depression had a higher depression PGS compared with both individuals with MS without depression (odds ratio range per SD 1.29-1.38, DISCUSSION: A higher depression genetic burden was associated with approximately 30%-40% increased odds of depression in European genetic ancestry participants with MS compared with those without depression and was no different compared with those with depression and no comorbid immune disease. This study paves the way for further investigations into the possible use of PGS for assessing psychiatric disorder risk in MS and its application to non-European genetic ancestries

    Adaptation and application of the large LAERTES-EU RCM ensemble for modeling hydrological extremes: A pilot study for the Rhine basin

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    Enduring and extensive heavy precipitation associated with widespread river floods are among the main natural hazards affecting Central Europe. Since such events are characterized by long return periods, it is difficult to adequately quantify their frequency and intensity solely based on the available observations of precipitation. Furthermore, long-term observations are rare, not homogeneous in space and time, and thus not suitable to run hydrological models (HMs) with respect to extremes. To overcome this issue, we make use of the recently introduced LAERTES-EU (LArge Ensemble of Regional climaTe modEl Simulations for EUrope) data set, which is an ensemble of regional climate model simulations providing over 12.000 simulated years. LAERTES-EU is adapted for the use in an HM to calculate discharges for large river basins by applying a quantile mapping with a fixed density function to correct the mainly positive bias in model precipitation. The Rhine basin serves as a pilot area for calibration and validation. The results show clear improvements in the representation of both precipitation (e.g., annual cycle and intensity distributions) and simulated discharges by the HM after the bias correction. Furthermore, the large size of LAERTES-EU improves the statistical representativeness also for high return values above 100 years of discharges. We conclude that the bias-corrected LAERTES-EU data set is generally suitable for hydrological applications and posterior risk analyses. The results of this pilot study will soon be applied to several large river basins in Central Europe
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