446 research outputs found

    Regulation of signal transducers and activators of transcription (STATs) by effectors of adipogenesis: Coordinate regulation of STATs 1, 5A, and 5B with peroxisome proliferator-activated receptor-γ and C/AAAT enhancer binding protein-α

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    We have recently demonstrated that three signal transducers and activators of transcription (STAT) family members are induced during adipocyte differentiation (Stephens et al., J. Biol. Chem. 271 (1996) 10441- 10444). Since STATs 1, 5A, and 5B are induced during adipocyte differentiation, we have examined the ability of these proteins to be regulated by components of the differentiation cocktail. In addition, we have examined the effects of potent effectors of differentiation on STAT protein expression during adipogenesis. A negative effector, tumor necrosis factor-α (TNFα), and a positive effector, a thiazolidinedione, were used in these experiments. Our results demonstrate that the expression of STATs 1, 5A, and 5B is not dramatically influenced by individual components of the differentiation cocktail. However, the expression of these three STAT family members tightly correlates with lipid accumulation. Moreover, the expression of STATs 1, 5A, and 5B, but not STATs 3 and 6, are regulated in an identical fashion to both C/AAAT enhancer binding proteins α and peroxisome proliferator-activated receptor-γ by TNFα and a thiazolidinedione. Furthermore, the expression of adipocyte-expressed JAK kinases are unaffected by effectors of differentiation. These findings suggest that three STAT family members may play a role in the regulation of adipocyte gene expression

    A complex speciation-richness relationship in a simple neutral model

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    Speciation is the "elephant in the room" of community ecology. As the ultimate source of biodiversity, its integration in ecology's theoretical corpus is necessary to understand community assembly. Yet, speciation is often completely ignored or stripped of its spatial dimension. Recent approaches based on network theory have allowed ecologists to effectively model complex landscapes. In this study, we use this framework to model allopatric and parapatric speciation in networks of communities and focus on the relationship between speciation, richness, and the spatial structure of communities. We find a strong opposition between speciation and local richness, with speciation being more common in isolated communities and local richness being higher in more connected communities. Unlike previous models, we also find a transition to a positive relationship between speciation and local richness when dispersal is low and the number of communities is small. Also, we use several measures of centrality to characterize the effect of network structure on diversity. The degree, the simplest measure of centrality, is found to be the best predictor of local richness and speciation, although it loses some of its predictive power as connectivity grows. Our framework shows how a simple neutral model can be combined with network theory to reveal complex relationships between speciation, richness, and the spatial organization of populations.Comment: 9 pages, 5 figures, 1 table, 50 reference

    Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA

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    Whole transcriptome sequencing by mRNA-Seq is now used extensively to perform global gene expression, mutation, allele-specific expression and other genome-wide analyses. mRNA-Seq even opens the gate for gene expression analysis of non-sequenced genomes. mRNA-Seq offers high sensitivity, a large dynamic range and allows measurement of transcript copy numbers in a sample. Illumina’s genome analyzer performs sequencing of a large number (> 107) of relatively short sequence reads (< 150 bp).The "paired end" approach, wherein a single long read is sequenced at both its ends, allows for tracking alternate splice junctions, insertions and deletions, and is useful for de novo transcriptome assembly

    Evaluation of Gene Association Methods for Coexpression Network Construction and Biological Knowledge Discovery

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    Background Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. Methods and Results In this study, we compared eight gene association methods – Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding\u27s D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson – and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. Conclusions We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction

    Ultrasonic/Sonic Mechanisms for Drilling and Coring

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    Two apparatuses now under development are intended to perform a variety of deep-drilling, coring, and sensing functions for subsurface exploration of rock and soil. These are modified versions of the apparatuses described in Ultrasonic/Sonic Drill/Corers With Integrated Sensors (NPO-20856), NASA Tech Briefs, Vol. 25, No. 1 (January 2001), page 38. In comparison with the drilling equipment traditionally used in such exploration, these apparatuses weigh less and consume less power. Moreover, unlike traditional drills and corers, these apparatuses function without need for large externally applied axial forces

    Athletes’ Relationships with Training Scale (ART)

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    The Athletes’ Relationships with Training Scale (ART)* is a self-report measure of unhealthy training behaviors and beliefs in athletes. The ART was designed for use by clinicians and athletic trainers to help identify athletes who are engaging in unhealthy training practices which could be associated with an eating disorder. The ART may also be helpful for tracking clinical outcomes in athletes with eating disorders who are receiving treatment. This record contains the 15-item ART as well as scoring instructions and guidelines for interpreting total scores

    RNA-Seq gene expression estimation with read mapping uncertainty

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    Motivation: RNA-Seq is a promising new technology for accurately measuring gene expression levels. Expression estimation with RNA-Seq requires the mapping of relatively short sequencing reads to a reference genome or transcript set. Because reads are generally shorter than transcripts from which they are derived, a single read may map to multiple genes and isoforms, complicating expression analyses. Previous computational methods either discard reads that map to multiple locations or allocate them to genes heuristically

    The interRAI suite of mental health assessment instruments: an integrated system for the continuum of care

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    The lives of persons living with mental illness are affected by psychological, biological, social, economic, and environmental factors over the life course. It is therefore unlikely that simple preventive strategies, clinical treatments, therapeutic interventions, or policy options will succeed as singular solutions for the challenges of mental illness. Persons living with mental illness receive services and supports in multiple settings across the health care continuum that are often fragmented, uncoordinated, and inadequately responsive. Appropriate assessment is an important tool that health systems must deploy to respond to the strengths, preferences, and needs of persons with mental illness. However, standard approaches are often focused on measurement of psychiatric symptoms without taking a broader perspective to address issues like growth, development, and aging; physical health and disability; social relationships; economic resources; housing; substance use; involvement with criminal justice; stigma; and recovery. Using conglomerations of instruments to cover more domains is impractical, inconsistent, and incomplete while posing considerable assessment burden. interRAI mental health instruments were developed by a network of over 100 researchers, clinicians, and policy experts from over 35 nations. This includes assessment systems for adults in inpatient psychiatry, community mental health, emergency departments, mobile crisis teams, and long-term care settings, as well as a screening system for police officers. A similar set of instruments is available for child/youth mental health. The instruments form an integrated mental health information system because they share a common assessment language, conceptual basis, clinical emphasis, data collection approach, data elements, and care planning protocols. The key applications of these instruments include care planning, outcome measurement, quality improvement, and resource allocation. The composition of these instruments and psychometric properties are reviewed, and examples related to homeless are used to illustrate the various applications of these assessment systems

    Development and preliminary evaluation of a quality of life measure targeted at dementia caregivers

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    <p>Abstract</p> <p>Background</p> <p>Providing care for individuals with a progressive, debilitating condition such as dementia can adversely impact the quality of life (QOL) of informal caregivers. To date, there is no existing caregiver quality of life measure for dementia caregivers with breadth of coverage or that is applicable to caregivers of diverse ethnic backgrounds. The purpose of this study was to develop and evaluate a caregiver-targeted quality-of-life measure (CGQOL) for informal caregivers of persons with dementia that can be used with caregivers from a variety of ethnicities.</p> <p>Methods</p> <p>91 items were field tested by telephone interviews with 179 English-speaking and 21 monolingual Spanish-speaking caregivers of persons with dementia. Repeat interviews were conducted with 71 caregivers. Administration time, scale score distributions, item-scale correlations, reliability, and associations of scales with patient and caregiver demographic and caregiving characteristics were estimated. Structure of associations among scales was examined using exploratory factor analysis.</p> <p>Results</p> <p>Item analysis yielded 80 items distributed across 10 scales, with median administration time of 17 minutes [IQR 13.5–22 minutes] and minimal missing data. There were few floor or ceiling effects in scale score distributions. Internal consistency reliability was ≥ 0.78 for all scales; test-retest reliability (intraclass correlation) estimates exceeded 0.70 for 6 scales. More hours weekly spent in caregiving was uniquely associated with worse quality of life on 8 scales (p's ≤ 0.05). Three higher-order dimensions of caregiving assistance, emotional and social concerns, and spirituality and benefits were identified.</p> <p>Conclusion</p> <p>These preliminary results support subsequent evaluation of test-retest reliability, construct validity, and responsiveness to change of this quality-of-life measure for caregivers from diverse ethnicities.</p
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