Enhancing the discovery of rare disease variants through hierarchical modeling

Advances in next-generation sequencing technology are enabling researchers to capture a comprehensive picture of genomic variation across large numbers of individuals with unprecedented levels of efficiency. The main analytic challenge in disease mapping is how to mine the data for rare causal variants among a sea of neutral variation. To achieve this goal, investigators have proposed a number of methods that exploit biological knowledge. In this paper, I propose applying a Bayesian stochastic search variable selection algorithm in this context. My multivariate method is inspired by the combined multivariate and collapsing method. In this proposed method, however, I allow an arbitrary number of different sources of biological knowledge to inform the model as prior distributions in a two-level hierarchical model. This allows rare variants with similar prior distributions to share evidence of association. Using the 1000 Genomes Project single-nucleotide polymorphism data provided by Genetic Analysis Workshop 17, I show that through biologically informative prior distributions, some power can be gained over noninformative prior distributions

Ultrathin compound semiconductor on insulator layers for high performance nanoscale transistors

Over the past several years, the inherent scaling limitations of electron devices have fueled the exploration of high carrier mobility semiconductors as a Si replacement to further enhance the device performance. In particular, compound semiconductors heterogeneously integrated on Si substrates have been actively studied, combining the high mobility of III-V semiconductors and the well-established, low cost processing of Si technology. This integration, however, presents significant challenges. Conventionally, heteroepitaxial growth of complex multilayers on Si has been explored. Besides complexity, high defect densities and junction leakage currents present limitations in the approach. Motivated by this challenge, here we utilize an epitaxial transfer method for the integration of ultrathin layers of single-crystalline InAs on Si/SiO2 substrates. As a parallel to silicon-on-insulator (SOI) technology14,we use the abbreviation "XOI" to represent our compound semiconductor-on-insulator platform. Through experiments and simulation, the electrical properties of InAs XOI transistors are explored, elucidating the critical role of quantum confinement in the transport properties of ultrathin XOI layers. Importantly, a high quality InAs/dielectric interface is obtained by the use of a novel thermally grown interfacial InAsOx layer (~1 nm thick). The fabricated FETs exhibit an impressive peak transconductance of ~1.6 mS/{\mu}m at VDS=0.5V with ON/OFF current ratio of greater than 10,000 and a subthreshold swing of 107-150 mV/decade for a channel length of ~0.5 {\mu}m

Applying refinement to the use of mice and rats in rheumatoid arthritis research

Rheumatoid arthritis (RA) is a painful, chronic disorder and there is currently an unmet need for effective therapies that will benefit a wide range of patients. The research and development process for therapies and treatments currently involves in vivo studies, which have the potential to cause discomfort, pain or distress. This Working Group report focuses on identifying causes of suffering within commonly used mouse and rat ‘models’ of RA, describing practical refinements to help reduce suffering and improve welfare without compromising the scientific objectives. The report also discusses other, relevant topics including identifying and minimising sources of variation within in vivo RA studies, the potential to provide pain relief including analgesia, welfare assessment, humane endpoints, reporting standards and the potential to replace animals in RA research

Genetic and other factors determining mannose-binding lectin levels in American Indians: the Strong Heart Study

<p>Abstract</p> <p>Background</p> <p>Mannose-binding lectin (MBL) forms an integral part of the innate immune system. Persistent, subclinical infections and chronic inflammatory states are hypothesized to contribute to the pathogenesis of atherosclerosis. MBL gene (<it>MBL2</it>) variants with between 12 to 25% allele frequency in Caucasian and other populations, result in markedly reduced expression of functional protein. Prospective epidemiologic studies, including a nested, case-control study from the present population, have demonstrated the ability of <it>MBL2 </it>genotypes to predict complications of atherosclerosis,. The genetic control of <it>MBL2 </it>expression is complex and genetic background effects in specific populations are largely unknown.</p> <p>Methods</p> <p>The Strong Heart Study is a longitudinal, cohort study of cardiovascular disease among American Indians. A subset of individuals genotyped for the above mentioned case-control study were selected for analysis of circulating MBL levels by double sandwich ELISA method. Mean MBL levels were compared between genotypic groups and multivariate regression was used to determine other independent factors influencing <it>MBL2 </it>expression.</p> <p>Results</p> <p>Our results confirm the effects of variant structural (B, C, and D) and promoter (H and Y) alleles that have been seen in other populations. In addition, MBL levels were found to be positively associated with male gender and hemoglobin A1c levels, but inversely related to triglyceride levels. Correlation was not found between MBL and other markers of inflammation.</p> <p>Conclusion</p> <p>New data is presented concerning the effects of known genetic variants on MBL levels in an American Indian population, as well as the relationship of <it>MBL2 </it>expression to clinical and environmental factors, including inflammatory markers.</p

Tetradecylthioacetic Acid Increases Hepatic Mitochondrial β-Oxidation and Alters Fatty Acid Composition in a Mouse Model of Chronic Inflammation

The administration of tetradecylthioacetic acid (TTA), a hypolipidemic and anti-inflammatory modified bioactive fatty acid, has in several experiments based on high fat diets been shown to improve lipid transport and utilization. It was suggested that increased mitochondrial and peroxisomal fatty acid oxidation in the liver of Wistar rats results in reduced plasma triacylglycerol (TAG) levels. Here we assessed the potential of TTA to prevent tumor necrosis factor (TNF) α-induced lipid modifications in human TNFα (hTNFα) transgenic mice. These mice are characterized by reduced β-oxidation and changed fatty acid composition in the liver. The effect of dietary treatment with TTA on persistent, low-grade hTNFα overexpression in mice showed a beneficial effect through decreasing TAG plasma concentrations and positively affecting saturated and monounsaturated fatty acid proportions in the liver, leading to an increased anti-inflammatory fatty acid index in this group. We also observed an increase of mitochondrial β-oxidation in the livers of TTA treated mice. Concomitantly, there were enhanced plasma levels of carnitine, acetyl carnitine, propionyl carnitine, and octanoyl carnitine, no changed levels in trimethyllysine and palmitoyl carnitine, and a decreased level of the precursor for carnitine, called γ-butyrobetaine. Nevertheless, TTA administration led to increased hepatic TAG levels that warrant further investigations to ascertain that TTA may be a promising candidate for use in the amelioration of inflammatory disorders characterized by changed lipid metabolism due to raised TNFα levels

GH mediates exercise-dependent activation of SVZ neural precursor cells in aged mice

Here we demonstrate, both in vivo and in vitro, that growth hormone (GH) mediates precursor cell activation in the subventricular zone (SVZ) of the aged (12-month-old) brain following exercise, and that GH signaling stimulates precursor activation to a similar extent to exercise. Our results reveal that both addition of GH in culture and direct intracerebroventricular infusion of GH stimulate neural precursor cells in the aged brain. In contrast, no increase in neurosphere numbers was observed in GH receptor null animals following exercise. Continuous infusion of a GH antagonist into the lateral ventricle of wild-type animals completely abolished the exercise-induced increase in neural precursor cell number. Given that the aged brain does not recover well after injury, we investigated the direct effect of exercise and GH on neural precursor cell activation following irradiation. This revealed that physical exercise as well as infusion of GH promoted repopulation of neural precursor cells in irradiated aged animals. Conversely, infusion of a GH antagonist during exercise prevented recovery of precursor cells in the SVZ following irradiation

Use of Cis-[18F]Fluoro-Proline for Assessment of Exercise-Related Collagen Synthesis in Musculoskeletal Connective Tissue

Protein turnover in collagen rich tissue is influenced by exercise, but can only with difficulty be studied in vivo due to use of invasive procedure. The present study was done to investigate the possibility of applying the PET-tracer, cis-[18F]fluoro-proline (cis-Fpro), for non-invasive assessment of collagen synthesis in rat musculoskeletal tissues at rest and following short-term (3 days) treadmill running. Musculoskeletal collagen synthesis was studied in rats at rest and 24 h post-exercise. At each session, rats were PET scanned at two time points following injection of cis-FPro: (60 and 240 min p.i). SUV were calculated for Achilles tendon, calf muscle and tibial bone. The PET-derived results were compared to mRNA expression of collagen type I and III. Tibial bone had the highest SUV that increased significantly (p<0.001) from the early (60 min) to the late (240 min) PET scan, while SUV in tendon and muscle decreased (p<0.001). Exercise had no influence on SUV, which was contradicted by an increased gene expression of collagen type I and III in muscle and tendon. The clearly, visible uptake of cis-Fpro in the collagen-rich musculoskeletal tissues is promising for multi-tissue studies in vivo. The tissue-specific differences with the highest basal uptake in bone are in accordance with earlier studies relying on tissue incorporation of isotopic-labelled proline. A possible explanation of the failure to demonstrate enhanced collagen synthesis following exercise, despite augmented collagen type I and III transcription, is that SUV calculations are not sensitive enough to detect minor changes in collagen synthesis. Further studies including kinetic compartment modeling must be performed to establish whether cis-Fpro can be used for non-invasive in-vivo assessment of exercise-induced changes in musculoskeletal collagen synthesis

Identification and design principles of low hole effective mass p-type transparent conducting oxides

The development of high-performance transparent conducting oxides is critical to many technologies from transparent electronics to solar cells. Whereas n-type transparent conducting oxides are present in many devices, their p-type counterparts are not largely commercialized, as they exhibit much lower carrier mobilities due to the large hole effective masses of most oxides. Here we conduct a high-throughput computational search on thousands of binary and ternary oxides and identify several highly promising compounds displaying exceptionally low hole effective masses (up to an order of magnitude lower than state-of-the-art p-type transparent conducting oxides), as well as wide band gaps. In addition to the discovery of specific compounds, the chemical rationalization of our findings opens new directions, beyond current Cu-based chemistries, for the design and development of future p-type transparent conducting oxides.United States. Office of Naval Research (Award N00014-11-1-0212

Modeling Statistical Properties of Written Text

Written text is one of the fundamental manifestations of human language, and the study of its universal regularities can give clues about how our brains process information and how we, as a society, organize and share it. Among these regularities, only Zipf's law has been explored in depth. Other basic properties, such as the existence of bursts of rare words in specific documents, have only been studied independently of each other and mainly by descriptive models. As a consequence, there is a lack of understanding of linguistic processes as complex emergent phenomena. Beyond Zipf's law for word frequencies, here we focus on burstiness, Heaps' law describing the sublinear growth of vocabulary size with the length of a document, and the topicality of document collections, which encode correlations within and across documents absent in random null models. We introduce and validate a generative model that explains the simultaneous emergence of all these patterns from simple rules. As a result, we find a connection between the bursty nature of rare words and the topical organization of texts and identify dynamic word ranking and memory across documents as key mechanisms explaining the non trivial organization of written text. Our research can have broad implications and practical applications in computer science, cognitive science and linguistics