132,533 research outputs found
Identification of the gene for Nance-Horan syndrome (NHS)
No full textObjective: To identify the gene or genes responsible for these diseases.
Methods: Families with NHS were ascertained. The refined locus for CXN was used to focus the search for candidate genes, which were screened by polymerase chain reaction and direct sequencing of potential exons and intron-exon splice sites. Genomic structures and homologies were determined using bioinformatics. Expression studies were undertaken using specific exonic primers to amplify human fetal cDNA and mouse RNA.
Results: A novel gene NHS, with no known function, was identified as causative for NHS. Protein truncating mutations were detected in all three NHS pedigrees, but no mutation was identified in a CXN family, raising the possibility that NHS and CXN may not be allelic. The NHS gene forms a new gene family with a closely related novel gene NHS-Like1 (NHSL1). NHS and NHSL1 lie in paralogous duplicated chromosomal intervals on Xp22 and 6q24, and NHSL1 is more broadly expressed than NHS in human fetal tissues.
Conclusions: This study reports the independent identification of the gene causative for Nance-Horan syndrome and extends the number of mutations identified
[Photograph of Claude D. Horan]
No full textPhotograph of Claude D. Horan, Jr. standing with his uniform. There is a mural in the background. In the mural, there is a water tower with Camp Barkeley Texas on it
Patrick Horan, circa 1965
No full textPatrick D. Horan, instructor in Journalism at Marquette University, circa 1965
Turpin, Horan, Johnson DDD
No full textA photograph of Glen Turpin, Roy Horan, and Pine Johnson with several quarter horses at Three D Stock Farm.https://mavmatrix.uta.edu/specialcollections_jwdunlopphotograph/1421/thumbnail.jp
[Photograph of Claude Horan]
No full textPhotograph of Claude D. Horan, Jr. standing with another serviceman. There is a mural in the background. In the mural, there is a water tower with Camp Barkeley Texas on it
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[Letter from D. Jack Davis and R. William McCarter to Aileen Horan, May 23, 1988]
No full textPhotocopy of a letter from D. Jack Davis and Bill McCarter to Aileen Horan thanking her for making room in her schedule to visit with Joe N. Prince while he was on his site visit for the Getty proposal. They also thank Horan for having both lunch and dinner with them recently
Relationship between dairy cow genetic merit and profit on commercial spring calving dairy farms
No full textpeer-reviewedBecause not all animal factors influencing profitability can be included in total merit breeding indices for profitability, the
association between animal total merit index and true profitability, taking cognisance of all factors associated with costs and
revenues, is generally not known. One method to estimate such associations is at the herd level, associating herd average genetic
merit with herd profitability. The objective of this study was to primarily relate herd average genetic merit for a range of traits,
including the Irish total merit index, with indicators of performance, including profitability, using correlation and multiple
regression analyses. Physical, genetic and financial performance data from 1131 Irish seasonal calving pasture-based dairy farms
were available following edits; data on some herds were available for more than 1 year of the 3-year study period (2007 to 2009).
Herd average economic breeding index (EBI) was associated with reduced herd average phenotypic milk yield but with greater
milk composition, resulting in higher milk prices. Moderate positive correlations (0.26 to 0.61) existed between genetic merit for
an individual trait and average herd performance for that trait (e.g. genetic merit for milk yield and average per cow milk yield).
Following adjustment for year, stocking rate, herd size and quantity of purchased feed in the multiple regression analysis, average
herd EBI was positively and linearly associated with net margin per cow and per litre as well as gross revenue output per cow
and per litre. The change in net margin per cow per unit change in the total merit index was h1.94 (s.e.50.42), which was not
different from the expectation of h2. This study, based on a large data set of commercial herds with accurate information
on profitability and genetic merit, confirms that, after accounting for confounding factors, the change in herd profitability per
unit change in herd genetic merit for the total merit index is within expectations
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Examining Assessment and Instructional Practices to Empower Teachers and Students: An Appreciative Inquiry Approach
No full textThe purpose of this qualitative study was to use an Appreciative Inquiry (AI) approach to discover generative instructional and assessment practices of teachers in the language arts classroom at a 5th and 6th grade low socioeconomic public school campus in Texas that earned five distinctions for three consecutive years. The study sought to design a framework for promoting generative teaching and instructional practices which enhance student learning and engagement utilizing the first three phases of the AI 4D Model: Discovery, Dream, and Design. Through a systematic process of discovering the best of what is, dreaming about what could be, designing a plan for what should be, and creating collective commitments about what will be, data was collected through an iterative process of (a) journaling and observations, (b) semi-structured participant interviews, and (c) participant-created documents. Five salient themes emerged from which five pillars of collective commitment were co-created by the study participants as an alternative to highstakes testing and prescriptive learning. A proposed solution was espoused through the following generative learning processes of (a) generative relationships, (b) generative meaning, (c) generative thinking, (d) generative conversation, and (e) generative empowerment. These five new generative learning processes form the basis for future development of a framework that produces generative learning outcomes that empower teachers and students as independent learners who construct meaning through discovery, discourse, and dialogue.ProQuest Traditional Publishing Optio
Replication Data for: The Song Remains Not the Same: Correlated Intercept and Slope Uncertainties Matter to Prices vs Quantities
No full textMathematica programs to derive results for the numerical example
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