1,553 research outputs found

    Large N and Bosonization in Three Dimensions

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    Bosonization is normally thought of as a purely two-dimensional phenomenon, and generic field theories with fermions in D>2 are not expected be describable by local bosonic actions, except in some special cases. We point out that 3D SU(N) gauge theories on R^{1,1} x S^{1}_{L} with adjoint fermions can be bosonized in the large N limit. The key feature of such theories is that they enjoy large N volume independence for arbitrary circle size L. A consequence of this is a large N equivalence between these 3D gauge theories and certain 2D gauge theories, which matches a set of correlation functions in the 3D theories to corresponding observables in the 2D theories. As an example, we focus on a 3D SU(N) gauge theory with one flavor of adjoint Majorana fermions and derive the large-N equivalent 2D gauge theory. The extra dimension is encoded in the color degrees of freedom of the 2D theory. We then apply the technique of non-Abelian bosonization to the 2D theory to obtain an equivalent local theory written purely in terms of bosonic variables. Hence the bosonized version of the large N three-dimensional theory turns out to live in two dimensions.Comment: 30 pages, 2 tables. v2 minor revisions, references adde

    A p53-independent role for the MDM2 antagonist Nutlin-3 in DNA damage response initiation.

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    BACKGROUND: The mammalian DNA-damage response (DDR) has evolved to protect genome stability and maximize cell survival following DNA-damage. One of the key regulators of the DDR is p53, itself tightly regulated by MDM2. Following double-strand DNA breaks (DSBs), mediators including ATM are recruited to the site of DNA-damage. Subsequent phosphorylation of p53 by ATM and ATM-induced CHK2 results in p53 stabilization, ultimately intensifying transcription of p53-responsive genes involved in DNA repair, cell-cycle checkpoint control and apoptosis. METHODS: In the current study, we investigated the stabilization and activation of p53 and associated DDR proteins in response to treatment of human colorectal cancer cells (HCT116p53+/+) with the MDM2 antagonist, Nutlin-3. RESULTS: Using immunoblotting, Nutlin-3 was observed to stabilize p53, and activate p53 target proteins. Unexpectedly, Nutlin-3 also mediated phosphorylation of p53 at key DNA-damage-specific serine residues (Ser15, 20 and 37). Furthermore, Nutlin-3 induced activation of CHK2 and ATM - proteins required for DNA-damage-dependent phosphorylation and activation of p53, and the phosphorylation of BRCA1 and H2AX - proteins known to be activated specifically in response to DNA damage. Indeed, using immunofluorescent labeling, Nutlin-3 was seen to induce formation of γH2AX foci, an early hallmark of the DDR. Moreover, Nutlin-3 induced phosphorylation of key DDR proteins, initiated cell cycle arrest and led to formation of γH2AX foci in cells lacking p53, whilst γH2AX foci were also noted in MDM2-deficient cells. CONCLUSION: To our knowledge, this is the first solid evidence showing a secondary role for Nutlin-3 as a DDR triggering agent, independent of p53 status, and unrelated to its role as an MDM2 antagonist

    A Model-Based Analysis of GC-Biased Gene Conversion in the Human and Chimpanzee Genomes

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    GC-biased gene conversion (gBGC) is a recombination-associated process that favors the fixation of G/C alleles over A/T alleles. In mammals, gBGC is hypothesized to contribute to variation in GC content, rapidly evolving sequences, and the fixation of deleterious mutations, but its prevalence and general functional consequences remain poorly understood. gBGC is difficult to incorporate into models of molecular evolution and so far has primarily been studied using summary statistics from genomic comparisons. Here, we introduce a new probabilistic model that captures the joint effects of natural selection and gBGC on nucleotide substitution patterns, while allowing for correlations along the genome in these effects. We implemented our model in a computer program, called phastBias, that can accurately detect gBGC tracts about 1 kilobase or longer in simulated sequence alignments. When applied to real primate genome sequences, phastBias predicts gBGC tracts that cover roughly 0.3% of the human and chimpanzee genomes and account for 1.2% of human-chimpanzee nucleotide differences. These tracts fall in clusters, particularly in subtelomeric regions; they are enriched for recombination hotspots and fast-evolving sequences; and they display an ongoing fixation preference for G and C alleles. They are also significantly enriched for disease-associated polymorphisms, suggesting that they contribute to the fixation of deleterious alleles. The gBGC tracts provide a unique window into historical recombination processes along the human and chimpanzee lineages. They supply additional evidence of long-term conservation of megabase-scale recombination rates accompanied by rapid turnover of hotspots. Together, these findings shed new light on the evolutionary, functional, and disease implications of gBGC. The phastBias program and our predicted tracts are freely available. © 2013 Capra et al

    Logarithmic correction to BH entropy as Noether charge

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    We consider the role of the type-A trace anomaly in static black hole solutions to semiclassical Einstein equation in four dimensions. Via Wald's Noether charge formalism, we compute the contribution to the entropy coming from the anomaly induced effective action and unveil a logarithmic correction to the Bekenstein-Hawking area law. The corrected entropy is given by a seemingly universal formula involving the coefficient of the type-A trace anomaly, the Euler characteristic of the horizon and the value at the horizon of the solution to the uniformization problem for Q-curvature. Two instances are examined in detail: Schwarzschild and a four-dimensional massless topological black hole. We also find agreement with the logarithmic correction due to one-loop contribution of conformal fields in the Schwarzschild background.Comment: 14 pages, JHEP styl

    Outcome measurement in functional neurological disorder: a systematic review and recommendations.

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    OBJECTIVES: We aimed to identify existing outcome measures for functional neurological disorder (FND), to inform the development of recommendations and to guide future research on FND outcomes. METHODS: A systematic review was conducted to identify existing FND-specific outcome measures and the most common measurement domains and measures in previous treatment studies. Searches of Embase, MEDLINE and PsycINFO were conducted between January 1965 and June 2019. The findings were discussed during two international meetings of the FND-Core Outcome Measures group. RESULTS: Five FND-specific measures were identified-three clinician-rated and two patient-rated-but their measurement properties have not been rigorously evaluated. No single measure was identified for use across the range of FND symptoms in adults. Across randomised controlled trials (k=40) and observational treatment studies (k=40), outcome measures most often assessed core FND symptom change. Other domains measured commonly were additional physical and psychological symptoms, life impact (ie, quality of life, disability and general functioning) and health economics/cost-utility (eg, healthcare resource use and quality-adjusted life years). CONCLUSIONS: There are few well-validated FND-specific outcome measures. Thus, at present, we recommend that existing outcome measures, known to be reliable, valid and responsive in FND or closely related populations, are used to capture key outcome domains. Increased consistency in outcome measurement will facilitate comparison of treatment effects across FND symptom types and treatment modalities. Future work needs to more rigorously validate outcome measures used in this population

    Directing Experimental Biology: A Case Study in Mitochondrial Biogenesis

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    Computational approaches have promised to organize collections of functional genomics data into testable predictions of gene and protein involvement in biological processes and pathways. However, few such predictions have been experimentally validated on a large scale, leaving many bioinformatic methods unproven and underutilized in the biology community. Further, it remains unclear what biological concerns should be taken into account when using computational methods to drive real-world experimental efforts. To investigate these concerns and to establish the utility of computational predictions of gene function, we experimentally tested hundreds of predictions generated from an ensemble of three complementary methods for the process of mitochondrial organization and biogenesis in Saccharomyces cerevisiae. The biological data with respect to the mitochondria are presented in a companion manuscript published in PLoS Genetics (doi:10.1371/journal.pgen.1000407). Here we analyze and explore the results of this study that are broadly applicable for computationalists applying gene function prediction techniques, including a new experimental comparison with 48 genes representing the genomic background. Our study leads to several conclusions that are important to consider when driving laboratory investigations using computational prediction approaches. While most genes in yeast are already known to participate in at least one biological process, we confirm that genes with known functions can still be strong candidates for annotation of additional gene functions. We find that different analysis techniques and different underlying data can both greatly affect the types of functional predictions produced by computational methods. This diversity allows an ensemble of techniques to substantially broaden the biological scope and breadth of predictions. We also find that performing prediction and validation steps iteratively allows us to more completely characterize a biological area of interest. While this study focused on a specific functional area in yeast, many of these observations may be useful in the contexts of other processes and organisms

    ?2-Microglobulin Amyloid Fibril-Induced Membrane Disruption Is Enhanced by Endosomal Lipids and Acidic pH

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    Although the molecular mechanisms underlying the pathology of amyloidoses are not well understood, the interaction between amyloid proteins and cell membranes is thought to play a role in several amyloid diseases. Amyloid fibrils of ?2-microglobulin (?2m), associated with dialysis-related amyloidosis (DRA), have been shown to cause disruption of anionic lipid bilayers in vitro. However, the effect of lipid composition and the chemical environment in which ?2m-lipid interactions occur have not been investigated previously. Here we examine membrane damage resulting from the interaction of ?2m monomers and fibrils with lipid bilayers. Using dye release, tryptophan fluorescence quenching and fluorescence confocal microscopy assays we investigate the effect of anionic lipid composition and pH on the susceptibility of liposomes to fibril-induced membrane damage. We show that ?2m fibril-induced membrane disruption is modulated by anionic lipid composition and is enhanced by acidic pH. Most strikingly, the greatest degree of membrane disruption is observed for liposomes containing bis(monoacylglycero)phosphate (BMP) at acidic pH, conditions likely to reflect those encountered in the endocytic pathway. The results suggest that the interaction between ?2m fibrils and membranes of endosomal origin may play a role in the molecular mechanism of ?2m amyloid-associated osteoarticular tissue destruction in DRA

    GABA-A receptor differences in schizophrenia: a positron emission tomography study using [C-11]Ro154513

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    A loss of GABA signaling is a prevailing hypothesis for the pathogenesis of schizophrenia. Preclinical studies indicate that blockade of the α5 subtype of the GABA receptor (α5-GABAARs) leads to behavioral phenotypes associated with schizophrenia, and postmortem evidence indicates lower hippocampal α5-GABAARs protein and mRNA levels in schizophrenia. However, it is unclear if α5-GABAARs are altered in vivo or related to symptoms. We investigated α5-GABAARs availability in antipsychotic-free schizophrenia patients and antipsychotic-medicated schizophrenia patients using [11C]Ro15-4513 PET imaging in a cross-sectional, case–control study design. Thirty-one schizophrenia patients (n = 10 antipsychotic free) and twenty-nine matched healthy controls underwent a [11C]Ro15-4513 PET scan and MRI. The α5 subtype GABA-A receptor availability was indexed using [11C]Ro15-4513 PET imaging. Dynamic PET data were analyzed using the two-tissue compartment model with an arterial plasma input function and total volume of distribution (VT) as the outcome measure. Symptom severity was assessed using the PANSS scale. There was significantly lower [11C]Ro15-4513 VT in the hippocampus of antipsychotic-free patients, but not in medicated patients (p = 0.64), relative to healthy controls (p < 0.05; effect size = 1.4). There was also a significant positive correlation between [11C]Ro15-4513 VT and total PANSS score in antipsychotic-free patients (r = 0.72; p = 0.044). The results suggest that antipsychotic-free patients with schizophrenia have lower α5-GABAARs levels in the hippocampus, consistent with the hypothesis that GABA hypofunction underlies the pathophysiology of the disorder
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