2,117 research outputs found
A Combination Theorem for Metric Bundles
We define metric bundles/metric graph bundles which provide a purely
topological/coarse-geometric generalization of the notion of trees of metric
spaces a la Bestvina-Feighn in the special case that the inclusions of the edge
spaces into the vertex spaces are uniform coarsely surjective quasi-isometries.
We prove the existence of quasi-isometric sections in this generality. Then we
prove a combination theorem for metric (graph) bundles (including exact
sequences of groups) that establishes sufficient conditions, particularly
flaring, under which the metric bundles are hyperbolic. We use this to give
examples of surface bundles over hyperbolic disks, whose universal cover is
Gromov-hyperbolic. We also show that in typical situations, flaring is also a
necessary condition.Comment: v3: Major revision: 56 pages 5 figures. Many details added.
Characterization of convex cocompact subgroups of mapping class groups of
surfaces with punctures in terms of relative hyperbolicity given v4: Final
version incorporating referee comments: 63 pages 5 figures. To appear in
Geom. Funct. Ana
Optimal strategies for a game on amenable semigroups
The semigroup game is a two-person zero-sum game defined on a semigroup S as
follows: Players 1 and 2 choose elements x and y in S, respectively, and player
1 receives a payoff f(xy) defined by a function f from S to [-1,1]. If the
semigroup is amenable in the sense of Day and von Neumann, one can extend the
set of classical strategies, namely countably additive probability measures on
S, to include some finitely additive measures in a natural way. This extended
game has a value and the players have optimal strategies. This theorem extends
previous results for the multiplication game on a compact group or on the
positive integers with a specific payoff. We also prove that the procedure of
extending the set of allowed strategies preserves classical solutions: if a
semigroup game has a classical solution, this solution solves also the extended
game.Comment: 17 pages. To appear in International Journal of Game Theor
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Genome-wide screening of mouse knockouts reveals novel genes required for normal integumentary and oculocutaneous structure and function.
Oculocutaneous syndromes are often due to mutations in single genes. In some cases, mouse models for these diseases exist in spontaneously occurring mutations, or in mice resulting from forward mutatagenesis screens. Here we present novel genes that may be causative for oculocutaneous disease in humans, discovered as part of a genome-wide screen of knockout-mice in a targeted single-gene deletion project. The International Mouse Phenotyping Consortium (IMPC) database (data release 10.0) was interrogated for all mouse strains with integument abnormalities, which were then cross-referenced individually to identify knockouts with concomitant ocular abnormalities attributed to the same targeted gene deletion. The search yielded 307 knockout strains from unique genes with integument abnormalities, 226 of which have not been previously associated with oculocutaneous conditions. Of the 307 knockout strains with integument abnormalities, 52 were determined to have ocular changes attributed to the targeted deletion, 35 of which represent novel oculocutaneous genes. Some examples of various integument abnormalities are shown, as well as two examples of knockout strains with oculocutaneous phenotypes. Each of the novel genes provided here are potentially relevant to the pathophysiology of human integumentary, or oculocutaneous conditions, such as albinism, phakomatoses, or other multi-system syndromes. The novel genes reported here may implicate molecular pathways relevant to these human diseases and may contribute to the discovery of novel therapeutic targets
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The translational potential of sleep and circadian rhythm disturbances as a biomarker of Alzheimer's disease
GIVE: portable genome browsers for personal websites.
Growing popularity and diversity of genomic data demand portable and versatile genome browsers. Here, we present an open source programming library called GIVE that facilitates the creation of personalized genome browsers without requiring a system administrator. By inserting HTML tags, one can add to a personal webpage interactive visualization of multiple types of genomics data, including genome annotation, "linear" quantitative data, and genome interaction data. GIVE includes a graphical interface called HUG (HTML Universal Generator) that automatically generates HTML code for displaying user chosen data, which can be copy-pasted into user's personal website or saved and shared with collaborators. GIVE is available at: https://www.givengine.org/
Research methods for subgrouping low back pain
<p>Abstract</p> <p>Background</p> <p>There is considerable clinician and researcher interest in whether the outcomes for patients with low back pain, and the efficiency of the health systems that treat them, can be improved by 'subgrouping research'. Subgrouping research seeks to identify subgroups of people who have clinically important distinctions in their treatment needs or prognoses. Due to a proliferation of research methods and variability in how subgrouping results are interpreted, it is timely to open discussion regarding a conceptual framework for the research designs and statistical methods available for subgrouping studies (a method framework). The aims of this debate article are: (1) to present a method framework to inform the design and evaluation of subgrouping research in low back pain, (2) to describe method options when investigating prognostic effects or subgroup treatment effects, and (3) to discuss the strengths and limitations of research methods suitable for the hypothesis-setting phase of subgroup studies.</p> <p>Discussion</p> <p>The proposed method framework proposes six phases for studies of subgroups: studies of assessment methods, hypothesis-setting studies, hypothesis-testing studies, narrow validation studies, broad validation studies, and impact analysis studies. This framework extends and relabels a classification system previously proposed by McGinn et al (2000) as suitable for studies of clinical prediction rules. This extended classification, and its descriptive terms, explicitly anchor research findings to the type of evidence each provides. The inclusive nature of the framework invites appropriate consideration of the results of diverse research designs. Method pathways are described for studies designed to test and quantify prognostic effects or subgroup treatment effects, and examples are discussed. The proposed method framework is presented as a roadmap for conversation amongst researchers and clinicians who plan, stage and perform subgrouping research.</p> <p>Summary</p> <p>This article proposes a research method framework for studies of subgroups in low back pain. Research designs and statistical methods appropriate for sequential phases in this research are discussed, with an emphasis on those suitable for hypothesis-setting studies of subgroups of people seeking care.</p
QSRA – a quality-value guided de novo short read assembler
<p>Abstract</p> <p>Background</p> <p>New rapid high-throughput sequencing technologies have sparked the creation of a new class of assembler. Since all high-throughput sequencing platforms incorporate errors in their output, short-read assemblers must be designed to account for this error while utilizing all available data.</p> <p>Results</p> <p>We have designed and implemented an assembler, Quality-value guided Short Read Assembler, created to take advantage of quality-value scores as a further method of dealing with error. Compared to previous published algorithms, our assembler shows significant improvements not only in speed but also in output quality.</p> <p>Conclusion</p> <p>QSRA generally produced the highest genomic coverage, while being faster than VCAKE. QSRA is extremely competitive in its longest contig and N50/N80 contig lengths, producing results of similar quality to those of EDENA and VELVET. QSRA provides a step closer to the goal of de novo assembly of complex genomes, improving upon the original VCAKE algorithm by not only drastically reducing runtimes but also increasing the viability of the assembly algorithm through further error handling capabilities.</p
High loading of polygenic risk for ADHD in children with comorbid aggression
Objective: Although attention deficit hyperactivity disorder (ADHD) is highly heritable, genome-wide association studies (GWAS) have not yet identified any common genetic variants that contribute to risk. There is evidence that aggression or conduct disorder in children with ADHD indexes higher genetic loading and clinical severity. The authors examine whether common genetic variants considered en masse as polygenic scores for ADHD are especially enriched in children with comorbid conduct disorder.
Method: Polygenic scores derived from an ADHD GWAS meta-analysis were calculated in an independent ADHD sample (452 case subjects, 5,081 comparison subjects). Multivariate logistic regression analyses were employed to compare polygenic scores in the ADHD and comparison groups and test for higher scores in ADHD case subjects with comorbid conduct disorder relative to comparison subjects and relative to those without comorbid conduct disorder. Association with symptom scores was tested using linear regression.
Results: Polygenic risk for ADD, derived from the meta-analysis, was higher in the independent ADHD group than in the comparison group. Polygenic score was significantly higher in ADHD case subjects with conduct disorder relative to ADHD case subjects without conduct disorder. ADHD polygenic score showed significant association with comorbid conduct disorder symptoms. This relationship was explained by,the aggression items.
Conclusions: Common genetic variation is relevant to ADHD, especially in individuals with comorbid aggression. The findings suggest that the previously published ADHD GWAS meta-analysis contains weak but true associations with common variants, support for which falls below genome-wide significance levels. The findings also highlight the fact that aggression in ADHD indexes genetic as well as clinical severity
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