122 research outputs found

    Obesity and the Rate of Time Preference: Is there a Connection?

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    We hypothesize that recent trends in U.S. and worldwide obesity are, in part, related to an increase in the marginal rate of time preference, where time preference refers to the rate at which people are willing to trade current benefit for future benefit. The higher the rate of time preference, the larger is the factor by which individuals discount the future health risks associated with current consumption. Data from the United States, as well as international evidence, suggests that a relationship between these two variables is plausible. We encourage researchers to explore the possible link between obesity and time preference, as important insights are likely to result

    In Vivo Expression of MHC Class I Genes Depends on the Presence of a Downstream Barrier Element

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    Regulation of MHC class I gene expression is critical to achieve proper immune surveillance. In this work, we identify elements downstream of the MHC class I promoter that are necessary for appropriate in vivo regulation: a novel barrier element that protects the MHC class I gene from silencing and elements within the first two introns that contribute to tissue specific transcription. The barrier element is located in intergenic sequences 3′ to the polyA addition site. It is necessary for stable expression in vivo, but has no effect in transient transfection assays. Accordingly, in both transgenic mice and stably transfected cell lines, truncation of the barrier resulted in transcriptional gene silencing, increased nucleosomal density and decreased histone H3K9/K14 acetylation and H3K4 di-methylation across the gene. Significantly, distinct sequences within the barrier element govern anti-silencing and chromatin modifications. Thus, this novel barrier element functions to maintain transcriptionally permissive chromatin organization and prevent transcriptional silencing of the MHC class I gene, ensuring it is poised to respond to immune signaling

    MMN and Differential Waveform

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    A mismatch negativity response (MMN) and a new differential waveform were derived in an effort to evaluate a neural refractory or recovery effect in adult listeners. The MMN was elicited using oddball test runs in which the standard and deviant stimuli differed in frequency. To derive the differential waveform, the same standard and deviant stimuli were presented alone. MMN responses were obtained by subtracting the averaged responses to standards from the deviants. The differential waveforms were obtained by subtracting the averaged responses to standards presented alone from deviants presented alone. Scalp topography for the MMN and differential waveforms were similar. A significant (p < .05) positive and negative correlation was found between the earlier and later components of the bimodal MMN and the N1 and P2 component of the differential waveform, respectively. Further, N1 and P2 of the differential waveform were significant (p < .05) predictor variables of early and late peak amplitudes of the MMN. These results suggest that refractory effects may overlay/modify the morphology of the MMN waveform

    Genome Wide Analysis of Acute Myeloid Leukemia Reveal Leukemia Specific Methylome and Subtype Specific Hypomethylation of Repeats

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    Methylated DNA immunoprecipitation followed by high-throughput sequencing (MeDIP-seq) has the potential to identify changes in DNA methylation important in cancer development. In order to understand the role of epigenetic modulation in the development of acute myeloid leukemia (AML) we have applied MeDIP-seq to the DNA of 12 AML patients and 4 normal bone marrows. This analysis revealed leukemia-associated differentially methylated regions that included gene promoters, gene bodies, CpG islands and CpG island shores. Two genes (SPHKAP and DPP6) with significantly methylated promoters were of interest and further analysis of their expression showed them to be repressed in AML. We also demonstrated considerable cytogenetic subtype specificity in the methylomes affecting different genomic features. Significantly distinct patterns of hypomethylation of certain interspersed repeat elements were associated with cytogenetic subtypes. The methylation patterns of members of the SINE family tightly clustered all leukemic patients with an enrichment of Alu repeats with a high CpG density (P<0.0001). We were able to demonstrate significant inverse correlation between intragenic interspersed repeat sequence methylation and gene expression with SINEs showing the strongest inverse correlation (R2 = 0.7). We conclude that the alterations in DNA methylation that accompany the development of AML affect not only the promoters, but also the non-promoter genomic features, with significant demethylation of certain interspersed repeat DNA elements being associated with AML cytogenetic subtypes. MeDIP-seq data were validated using bisulfite pyrosequencing and the Infinium array

    Meta-Analysis of the Alzheimer\u27s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models.

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    We present a consensus atlas of the human brain transcriptome in Alzheimer\u27s disease (AD), based on meta-analysis of differential gene expression in 2,114 postmortem samples. We discover 30 brain coexpression modules from seven regions as the major source of AD transcriptional perturbations. We next examine overlap with 251 brain differentially expressed gene sets from mouse models of AD and other neurodegenerative disorders. Human-mouse overlaps highlight responses to amyloid versus tau pathology and reveal age- and sex-dependent expression signatures for disease progression. Human coexpression modules enriched for neuronal and/or microglial genes broadly overlap with mouse models of AD, Huntington\u27s disease, amyotrophic lateral sclerosis, and aging. Other human coexpression modules, including those implicated in proteostasis, are not activated in AD models but rather following other, unexpected genetic manipulations. Our results comprise a cross-species resource, highlighting transcriptional networks altered by human brain pathophysiology and identifying correspondences with mouse models for AD preclinical studies
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