Altered Bone Development and an Increase in FGF-23 Expression in <em>Enpp1-</em>/- Mice

Nucleotide pyrophosphatase phosphodiesterase 1 (NPP1) is required for the conversion of extracellular ATP into inorganic pyrophosphate (PP(i)), a recognised inhibitor of hydroxyapatite (HA) crystal formation. A detailed phenotypic assessment of a mouse model lacking NPP1 (Enpp1(-/-)) was completed to determine the role of NPP1 in skeletal and soft tissue mineralization in juvenile and adult mice. Histopathological assessment of Enpp1(-/-) mice at 22 weeks of age revealed calcification in the aorta and kidney and ectopic cartilage formation in the joints and spine. Radiographic assessment of the hind-limb showed hyper-mineralization in the talocrural joint and hypo-mineralization in the femur and tibia. MicroCT analysis of the tibia and femur disclosed altered trabecular architecture and bone geometry at 6 and 22 weeks of age in Enpp1(-/-) mice. Trabecular number, trabecular bone volume, structure model index, trabecular and cortical thickness were all significantly reduced in tibiae and femurs from Enpp1(-/-) mice (P<0.05). Bone stiffness as determined by 3-point bending was significantly reduced in Enpp1(-/-) tibiae and femurs from 22-week-old mice (P<0.05). Circulating phosphate and calcium levels were reduced (P<0.05) in the Enpp1(-/-) null mice. Plasma levels of osteocalcin were significantly decreased at 6 weeks of age (P<0.05) in Enpp1(-/-) mice, with no differences noted at 22 weeks of age. Plasma levels of CTx (Ratlaps™) and the phosphaturic hormone FGF-23 were significantly increased in the Enpp1(-/-) mice at 22 weeks of age (P<0.05). Fgf-23 messenger RNA expression in cavarial osteoblasts was increased 12-fold in Enpp1(-/-) mice compared to controls. These results indicate that Enpp1(-/-) mice are characterized by severe disruption to the architecture and mineralization of long-bones, dysregulation of calcium/phosphate homeostasis and changes in Fgf-23 expression. We conclude that NPP1 is essential for normal bone development and control of physiological bone mineralization

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Sheep Updates 2007 - part 4

This session covers eight papers from different authors: GRAZING 1. The impact of high dietary salt and its implications for the management of livestock grazing saline land, Dean Thomas, Dominique Blache, Dean Revell, Hayley Norman, Phil Vercoe, Zoey Durmic, Serina Digby, Di Mayberry, Megan Chadwick, Martin Sillence and David Masters, CRC for Plant-based Management of Dryland Salinity, Faculty of Natural & Agricultural Sciences, The University of Western Australia, WA. 2. Sustainable Grazing on Saline Lands - outcomes from the WA1 research project, H.C. Norman1,2, D.G. Masters1,2, R. Silberstein1,2, F. Byrne2,3, P.G.H. Nichols2,4, J. Young3, L. Atkins1,2, M.G. Wilmot1,2, A.J. Rintoul1,2, T. Lambert1,2, D.R. McClements2,4, P. Raper4, P. Ward1,2, C. Walton5 and T. York6 1CSIRO Centre for Environment and Life Sciences, Wembley, WA 2CRC for Plant-based Management of Dryland Salinity. 3School of Agricultural and Resource Economics, University of Western Australia. 4Department of Agriculture and Food WA. 5Condering Hills, Yealering. 6Anameka Farms, Tammin. MEAT QUALITY 3. Development of intramuscular fat in prime lambs, young sheep and beef cattle, David Pethick1, David Hopkins2 and Malcolm McPhee3,1School of Veterinary and Biomedical Sciences, Murdoch University, Murdoch, WA, 2NSW Department of Primary Industries, Cowra, NSW,3NSW Dept. of Primary Industries, University of New England, Armidale, NSW, 4. Importance of drinking water temperature for managing heat stress in sheep, Savage DB, Nolan JV, Godwin IR, Aoetpah A, Nguyen T, Baillie N and Lawler C University of New England, Armidale, NSW, Australia EWE MANAGEMENT TOOLS 5. E - sheep Management of Pregnant Merino Ewes and their Finishing Lambs, Ken GeentyA, John SmithA, Darryl SmithB, Tim DyallA and Grant UphillA A Sheep CRC and CSIRO Livestock Industries, Chiswick, NSW B Turretfield Research Station, SARDI, Roseworthy, SA 6. Is it important to manage ewes to CS targets? John Young, Farming Systems Analysis Service, Kojonup, WA MULESING 7. Mulesing accreditation - Vital for Wool\u27s Future, Dr Michael Paton, Department of Agriculture and Food WA, 8. Mulesing Alternatives, Jules Dorrian, Affiliation Project Manager Blowfly Control Australian Wool Inovatio

A simple algebraic cancer equation: calculating how cancers may arise with normal mutation rates

<p>Abstract</p> <p>Background</p> <p>The purpose of this article is to present a relatively easy to understand cancer model where transformation occurs when the first cell, among many at risk within a colon, accumulates a set of driver mutations. The analysis of this model yields a simple algebraic equation, which takes as inputs the number of stem cells, mutation and division rates, and the number of driver mutations, and makes predictions about cancer epidemiology.</p> <p>Methods</p> <p>The equation [<it>p </it>= 1 - (1 - (1 - (1 - <it>u</it>)^<it>d</it>)^<it>k</it>)^{<it>Nm </it>}] calculates the probability of cancer (<it>p</it>) and contains five parameters: the number of divisions (<it>d</it>), the number of stem cells (<it>N </it>× <it>m</it>), the number of critical rate-limiting pathway driver mutations (<it>k</it>), and the mutation rate (<it>u</it>). In this model progression to cancer "starts" at conception and mutations accumulate with cell division. Transformation occurs when a critical number of rate-limiting pathway mutations first accumulates within a single stem cell.</p> <p>Results</p> <p>When applied to several colorectal cancer data sets, parameter values consistent with crypt stem cell biology and normal mutation rates were able to match the increase in cancer with aging, and the mutation frequencies found in cancer genomes. The equation can help explain how cancer risks may vary with age, height, germline mutations, and aspirin use. APC mutations may shorten pathways to cancer by effectively increasing the numbers of stem cells at risk.</p> <p>Conclusions</p> <p>The equation illustrates that age-related increases in cancer frequencies may result from relatively normal division and mutation rates. Although this equation does not encompass all of the known complexity of cancer, it may be useful, especially in a teaching setting, to help illustrate relationships between small and large cancer features.</p

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead