1,470 research outputs found

    stm: An R Package for Structural Topic Models

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    This paper demonstrates how to use the R package stm for structural topic modeling. The structural topic model allows researchers to flexibly estimate a topic model that includes document-level metadata. Estimation is accomplished through a fast variational approximation. The stm package provides many useful features, including rich ways to explore topics, estimate uncertainty, and visualize quantities of interest

    Genome-wide identification of FoxO-dependent gene networks in skeletal muscle during C26 cancer cachexia

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    BACKGROUND: Evidence from cachectic cancer patients and animal models of cancer cachexia supports the involvement of Forkhead box O (FoxO) transcription factors in driving cancer-induced skeletal muscle wasting. However, the genome-wide gene networks and associated biological processes regulated by FoxO during cancer cachexia are unknown. We hypothesize that FoxO is a central upstream regulator of diverse gene networks in skeletal muscle during cancer that may act coordinately to promote the wasting phenotype. METHODS: To inhibit endogenous FoxO DNA-binding, we transduced limb and diaphragm muscles of mice with AAV9 containing the cDNA for a dominant negative (d.n.) FoxO protein (or GFP control). The d.n.FoxO construct consists of only the FoxO3a DNA-binding domain that is highly homologous to that of FoxO1 and FoxO4, and which outcompetes and blocks endogenous FoxO DNA binding. Mice were subsequently inoculated with Colon-26 (C26) cells and muscles harvested 26 days later. RESULTS: Blocking FoxO prevented C26-induced muscle fiber atrophy of both locomotor muscles and the diaphragm and significantly spared force deficits. This sparing of muscle size and function was associated with the differential regulation of 543 transcripts (out of 2,093) which changed in response to C26. Bioinformatics analysis of upregulated gene transcripts that required FoxO revealed enrichment of the proteasome, AP-1 and IL-6 pathways, and included several atrophy-related transcription factors, including Stat3, Fos, and Cebpb. FoxO was also necessary for the cancer-induced downregulation of several gene transcripts that were enriched for extracellular matrix and sarcomere protein-encoding genes. We validated these findings in limb muscles and the diaphragm through qRT-PCR, and further demonstrate that FoxO1 and/or FoxO3a are sufficient to increase Stat3, Fos, Cebpb, and the C/EBPβ target gene, Ubr2. Analysis of the Cebpb proximal promoter revealed two bona fide FoxO binding elements, which we further establish are necessary for Cebpb promoter activation in response to IL-6, a predominant cytokine in the C26 cancer model. CONCLUSIONS: These findings provide new evidence that FoxO-dependent transcription is a central node controlling diverse gene networks in skeletal muscle during cancer cachexia, and identifies novel candidate genes and networks for further investigation as causative factors in cancer-induced wasting.R01 AR060217 - NIAMS NIH HHS; R01 AR060209 - NIAMS NIH HHS; T32 HD043730 - NICHD NIH HHS; R00 HL098453 - NHLBI NIH HHS; R00HL098453 - NHLBI NIH HHS; R01AR060209 - NIAMS NIH HHS; R01AR060217 - NIAMS NIH HH

    Barriers to and Strategies for Engaging Extension Educators in Family Caregiver Education

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    Oklahoma Extension educators encountered barriers related to trainings and program delivery for a caregiver education program produced by Oklahoma State University Extension. Oklahoma family and consumer sciences educators were interviewed about perceived barriers to attending trainings and delivering the program. Findings indicated that staff shortages, program prioritization, challenges in developing an audience, and communication issues with the program team made it difficult for educators to engage with the program. Strategies for improvement based on the findings were devised

    Structural Topic Models for Open-Ended Survey Responses

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    Collection and especially analysis of open-ended survey responses are relatively rare in the discipline and when conducted are almost exclusively done through human coding. We present an alternative, semiautomated approach, the structural topic model (STM) (Roberts, Stewart, and Airoldi 2013; Roberts et al. 2013), that draws on recent developments in machine learning based analysis of textual data. A crucial contribution of the method is that it incorporates information about the document, such as the author's gender, political affiliation, and treatment assignment (if an experimental study). This article focuses on how the STM is helpful for survey researchers and experimentalists. The STM makes analyzing open-ended responses easier, more revealing, and capable of being used to estimate treatment effects. We illustrate these innovations with analysis of text from surveys and experiments

    A Critical Evaluation of the Biological Construct Skeletal Muscle Hypertrophy: Size Matters but So Does the Measurement

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    Skeletal muscle is highly adaptable and has consistently been shown to morphologically respond to exercise training. Skeletal muscle growth during periods of resistance training has traditionally been referred to as skeletal muscle hypertrophy, and this manifests as increases in muscle mass, muscle thickness, muscle area, muscle volume, and muscle fiber cross-sectional area (fCSA). Delicate electron microscopy and biochemical techniques have also been used to demonstrate that resistance exercise promotes ultrastructural adaptations within muscle fibers. Decades of research in this area of exercise physiology have promulgated a widespread hypothetical model of training-induced skeletal muscle hypertrophy; specifically, fCSA increases are accompanied by proportional increases in myofibrillar protein, leading to an expansion in the number of sarcomeres in parallel and/or an increase in myofibril number. However, there is ample evidence to suggest that myofibrillar protein concentration may be diluted through sarcoplasmic expansion as fCSA increases occur. Furthermore, and perhaps more problematic, are numerous investigations reporting that pre-to-post training change scores in macroscopic, microscopic, and molecular variables supporting this model are often poorly associated with one another. The current review first provides a brief description of skeletal muscle composition and structure. We then provide a historical overview of muscle hypertrophy assessment. Next, current-day methods commonly used to assess skeletal muscle hypertrophy at the biochemical, ultramicroscopic, microscopic, macroscopic, and whole-body levels in response to training are examined. Data from our laboratory, and others, demonstrating correlations (or the lack thereof) between these variables are also presented, and reasons for comparative discrepancies are discussed with particular attention directed to studies reporting ultrastructural and muscle protein concentration alterations. Finally, we critically evaluate the biological construct of skeletal muscle hypertrophy, propose potential operational definitions, and provide suggestions for consideration in hopes of guiding future research in this area

    A Critical Evaluation of the Biological Construct Skeletal Muscle Hypertrophy: Size Matters but So Does the Measurement

    Get PDF
    Skeletal muscle is highly adaptable and has consistently been shown to morphologically respond to exercise training. Skeletal muscle growth during periods of resistance training has traditionally been referred to as skeletal muscle hypertrophy, and this manifests as increases in muscle mass, muscle thickness, muscle area, muscle volume, and muscle fiber cross-sectional area (fCSA). Delicate electron microscopy and biochemical techniques have also been used to demonstrate that resistance exercise promotes ultrastructural adaptations within muscle fibers. Decades of research in this area of exercise physiology have promulgated a widespread hypothetical model of training-induced skeletal muscle hypertrophy; specifically, fCSA increases are accompanied by proportional increases in myofibrillar protein, leading to an expansion in the number of sarcomeres in parallel and/or an increase in myofibril number. However, there is ample evidence to suggest that myofibrillar protein concentration may be diluted through sarcoplasmic expansion as fCSA increases occur. Furthermore, and perhaps more problematic, are numerous investigations reporting that pre-to-post training change scores in macroscopic, microscopic, and molecular variables supporting this model are often poorly associated with one another. The current review first provides a brief description of skeletal muscle composition and structure. We then provide a historical overview of muscle hypertrophy assessment. Next, current-day methods commonly used to assess skeletal muscle hypertrophy at the biochemical, ultramicroscopic, microscopic, macroscopic, and whole-body levels in response to training are examined. Data from our laboratory, and others, demonstrating correlations (or the lack thereof) between these variables are also presented, and reasons for comparative discrepancies are discussed with particular attention directed to studies reporting ultrastructural and muscle protein concentration alterations. Finally, we critically evaluate the biological construct of skeletal muscle hypertrophy, propose potential operational definitions, and provide suggestions for consideration in hopes of guiding future research in this area
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