87 research outputs found

    Passive phloem loading and long-distance transport in a synthetic tree-on-a-chip

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    Vascular plants rely on differences of osmotic pressure to export sugars from regions of synthesis (mature leaves) to sugar sinks (roots, fruits). In this process, known as M\"unch pressure flow, the loading of sugars from photosynthetic cells to the export conduit (the phloem) is crucial, as it sets the pressure head necessary to power long-distance transport. Whereas most herbaceous plants use active mechanisms to increase phloem concentration above that of the photosynthetic cells, in most tree species, for which transport distances are largest, loading seems to occur via passive symplastic diffusion from the mesophyll to the phloem. Here, we use a synthetic microfluidic model of a passive loader to explore the nonlinear dynamics that arise during export and determine the ability of passive loading to drive long-distance transport. We first demonstrate that in our device, phloem concentration is set by the balance between the resistances to diffusive loading from the source and convective export through the phloem. Convection-limited export corresponds to classical models of M\"unch transport, where phloem concentration is close to that of the source; in contrast, diffusion-limited export leads to small phloem concentrations and weak scaling of flow rates with the hydraulic resistance. We then show that the effective regime of convection-limited export is predominant in plants with large transport resistances and low xylem pressures. Moreover, hydrostatic pressures developed in our synthetic passive loader can reach botanically relevant values as high as 10 bars. We conclude that passive loading is sufficient to drive long-distance transport in large plants, and that trees are well suited to take full advantage of passive phloem loading strategies

    2013 Review and Update of the Genetic Counseling Practice Based Competencies by a Task Force of the Accreditation Council for Genetic Counseling

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    The first practice based competencies (PBCs) for the field of genetic counseling were adopted by the American Board of Genetic Counseling (ABGC), 1996. Since that time, there has been significant growth in established and new work settings (clinical and non‐clinical) and changes in service delivery models and the roles of genetic counselors. These changes prompted the ABGC to appoint a PBC Task Force in 2011 to review the PBCs with respect to their current relevance and to revise and update them as necessary. There are four domains in the revised PBCs: (I) Genetics Expertise and Analysis (II) Interpersonal, Psychosocial and Counseling Skills (III) Education and (IV) Professional Development and Practice. There are 22 competencies, each clarified with learning objectives or samples of activities and skills; a glossary is included. New competencies were added that address genomics, genetic testing and genetic counselors’ roles in risk assessment, education, supervision, conducting research and presenting research options to patients. With PBCs serving as the pre‐defined abilities or outcomes of training, graduating genetic counselors will be well prepared to enter the field with a minimum level of skills and abilities. A description of the Task Force’s work, key changes and the 2013 PBCs are presented herein.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147172/1/jgc40868.pd

    Gastroesophageal reflux GWAS identifies risk loci that also associate with subsequent severe esophageal diseases

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    Funder: The Swedish Esophageal Cancer Study was funded by grants (R01 CA57947-03) from the National Cancer Institute he California Tobacco Related Research Program (3RT-0122; and; 10RT-0251) Marit Peterson Fund for Melanoma Research. CIDR is supported by contract HHSN268200782096CAbstract: Gastroesophageal reflux disease (GERD) is caused by gastric acid entering the esophagus. GERD has high prevalence and is the major risk factor for Barrett’s esophagus (BE) and esophageal adenocarcinoma (EA). We conduct a large GERD GWAS meta-analysis (80,265 cases, 305,011 controls), identifying 25 independent genome-wide significant loci for GERD. Several of the implicated genes are existing or putative drug targets. Loci discovery is greatest with a broad GERD definition (including cases defined by self-report or medication data). Further, 91% of the GERD risk-increasing alleles also increase BE and/or EA risk, greatly expanding gene discovery for these traits. Our results map genes for GERD and related traits and uncover potential new drug targets for these conditions

    Genome-wide association study of REM sleep behavior disorder identifies polygenic risk and brain expression effects

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    Rapid-eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies and defines a more severe subtype. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we perform a genome-wide association study of RBD, identifying five RBD risk loci near SNCA, GBA, TMEM175, INPP5F, and SCARB2. Expression analyses highlight SNCA-AS1 and potentially SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Polygenic risk score, pathway analysis, and genetic correlations provide further insights into RBD genetics, highlighting RBD as a unique alpha-synucleinopathy subpopulation that will allow future early intervention

    Identification of common genetic risk variants for autism spectrum disorder

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    Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe
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