67 research outputs found

    Black Literary Suite: Kansas Authors Edition

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    This collection consists of a single PDF containing all the posters from the Black Literary Suite: Kansas Authors Edition exhibit, as well as the audio commentary for each.Although not as popularly associated with African American literature as some other areas of the United States, there is a rich tradition of black writing in the Midwest, including in the state of Kansas. A number of important African American authors were born or lived in the Sunflower State, and their work often reflects their time in Kansas. This Black Literary Suite exhibit highlights four important black writers—Langston Hughes, Gwendolyn Brooks, Frank Marshall Davis, and Kevin Young—with Kansas connections

    Apixaban overdose in children:case report and proposed management. A brief communication from the Pediatric and Neonatal Thrombosis and Hemostasis SSC of ISTH

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    Background: Direct oral anticoagulants are commonly prescribed for adults and increasingly also for children requiring anticoagulation therapy. While household medications should not be accessible to children, accidental, and intentional overdoses occur. Key Clinical Question: How should apixaban overdose in children be managed?. Clinical Approach: We present a case of an accidental overdose with the factor Xa antagonist apixaban in a young child and propose an approach to the management of cases of apixaban overdose in children. Conclusion: Given the increasing use of direct oral anticoagulants, it is important to have an approach to the management of overdose of these medications.</p

    Plasticity in bilateral superior temporal cortex: effects of deafness and cochlear implantation on auditory and visual speech processing

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    While many individuals can benefit substantially from cochlear implantation, the ability to perceive and understand auditory speech with a cochlear implant (CI) remains highly variable amongst adult recipients. Importantly, auditory performance with a CI cannot be reliably predicted based solely on routinely obtained information regarding clinical characteristics of the CI candidate. This review argues that central factors, notably cortical function and plasticity, should also be considered as important contributors to the observed individual variability in CI outcome. Superior temporal cortex (STC), including auditory association areas, plays a crucial role in the processing of auditory and visual speech information. The current review considers evidence of cortical plasticity within bilateral STC, and how these effects may explain variability in CI outcome. Furthermore, evidence of audio-visual interactions in temporal and occipital cortices is examined, and relation to CI outcome is discussed. To date, longitudinal examination of changes in cortical function and plasticity over the period of rehabilitation with a CI has been restricted by methodological challenges. The application of functional near-infrared spectroscopy (fNIRS) in studying cortical function in CI users is becoming increasingly recognised as a potential solution to these problems. Here we suggest that fNIRS offers a powerful neuroimaging tool to elucidate the relationship between audio-visual interactions, cortical plasticity during deafness and following cochlear implantation, and individual variability in auditory performance with a CI

    Latent Markov and growth mixture models for ordinal individual responses with covariates: a comparison

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    We propose a short review between two alternative ways of modeling stability and change of longitudinal data when time-fixed and time-varying covariates referred to the observed individuals are available. They both build on the foundation of the finite mixture models and are commonly applied in many fields. They look at the data by a different perspective and in the literature they have not been compared when the ordinal nature of the response variable is of interest. The latent Markov model is based on time-varying latent variables to explain the observable behavior of the individuals. The model is proposed in a semi-parametric formulation as the latent Markov process has a discrete distribution and it is characterized by a Markov structure. The growth mixture model is based on a latent categorical variable that accounts for the unobserved heterogeneity in the observed trajectories and on a mixture of normally distributed random variable to account for the variability of growth rates. To illustrate the main differences among them we refer to a real data example on the self reported health status

    New genetic loci link adipose and insulin biology to body fat distribution.

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    Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

    Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

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    Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways

    Comparing pitch spelling algorithms

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    Algorithms for discovering repeated patterns in multidimensional representations of polyphonic music

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    In previous approaches to repetition discovery in music, the music to be analysed has been represented using strings. However, there are certain types of interesting musical repetitions that cannot be discovered using string algorithms. We propose a geometric approach to repetition discovery in which the music is represented as a multidimensional dataset. Certain types of interesting musical repetition that cannot be found using string algorithms can efficiently be found using algorithms that process multidimensional datasets. Our approach allows polyphonic music to be analysed as efficiently as monophonic music and it can be used to discover polyphonic repeated patterns `with gaps&apos; in the timbre, dynamic and rhythmic structure of a passage as well as its pitch structure. We present two new algorithms: SIA and SIATEC. SIA computes all the maximal repeated patterns in a multidimensional dataset and SIATEC computes all the occurrences of all the maximal repeated patterns in a dataset. For a k-dimensional dataset of size n, the worst-case running time of SIA is O(kn^2 log_2n) and the worst-case running time of SIATEC is O(kn^3)
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