96 research outputs found

    Redesigning pictographs for patients with low health literacy and establishing preliminary steps for delivery via smart phones.

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    BackgroundPictographs (or pictograms) have been widely utilized to convey medication related messages and to address nonadherence among patients with low health literacy. Yet, patients do not always interpret the intended messages on commonly used pictographs correctly and there are questions how they may be delivered on mobile devices.ObjectiveOur objectives are to refine a set of pictographs to use as medication reminders and to establish preliminary steps for delivery via smart phones.MethodsCard sorting was used to identify existing pictographs that focus group members found "not easy" to understand. Participants then explored improvements to these pictographs while iterations were sketched in real-time by a graphic artist. Feedback was also solicited on how selected pictographs might be delivered via smart phones in a sequential reminder message. The study was conducted at a community learning center that provides literacy services to underserved populations in Seattle, WA. Participants aged 18 years and older who met the criteria for low health literacy using S-TOFHLA were recruited.ResultsAmong the 45 participants screened for health literacy, 29 were eligible and consented to participate. Across four focus group sessions, participants examined 91 commonly used pictographs, 20 of these were ultimately refined to improve comprehensibility using participatory design approaches. All participants in the fifth focus group owned and used cell phones and provided feedback on preferred sequencing of pictographs to represent medication messages.ConclusionLow literacy adults found a substantial number of common medication label pictographs difficult to understand. Participative design processes helped generate new pictographs, as well as feedback on the sequencing of messages on cell phones, that may be evaluated in future research

    Macrophage migration inhibitory factor stimulated by Helicobacter pylori increases proliferation of gastric epithelial cells

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    AIM: Helicobacter pylori (H pylori) is associated with increased gastric inflammatory and epithelial expression of macrophage migration inhibitory factor (MIF) and gastric epithelial cell proliferation. This study aimed at determining whether H pylori directly stimulates release of MIF in monocytes, whether the cag pathogenicity island (PAI) is involved for this function, and whether MIF stimulated by H pylori increases gastric epithelial cell proliferation in vitro. METHODS: A cytotoxic wild-type H pylori strain (TN2)and its three isogenic mutants (TN2△cag, TN2△cagA and TN2△cagE) were co-cultured with cells of a human monocyte cell line, THP-1, for 24 h at different organism/cell ratios. MIF in the supernatants was measured by an ELISA. Cells of a human gastric cancer cell line, MKN45, were then co-cultured with the supernatants, with and without monoclonal anti-MIF antibody for 24 h. The cells were further incubated for 12 h after addition of (3)H-thymidine, and the levels of incorporation of (3)H-thymidine were measured with a liquid scintillation counter. RESULTS: The wild-type strain and the isogenic mutants, TN2△cagA and TN2△cagE, increased MIF release at organism/cell ratios of 200/1 and 400/1, but not at the ratios of 50/1 and 100/1. However, the mutant TN2△cag did not increase the release of MIF at any of the four ratios. (3)H-thymidine readings for MKN-45 cells were significantly increased with supernatants derived from the wild-type strain and the mutants TN2△cagA and TN2△cagE, but not from the mutant TN2△cag. Moreover, in the presence of monoclonal anti-MIF antibody, the stimulatory effects of the wild-type strain on cell proliferation disappeared. CONCLUSION: H pylori stimulates MIF release in monocytes, likely through its cag PAI, but not related to cagA or cagE. H pylori-stimulated monocyte culture supernatant increases gastric cell proliferation, which is blocked by anti-MIF antibody, suggesting that MIF plays an important role in H pylori-induced gastric epithelial cell proliferation

    Genome maps across 26 human populations reveal population-specific patterns of structural variation.

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    Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome

    Association analysis identifies ZNF750 regulatory variants in psoriasis

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    <p>Abstract</p> <p>Background</p> <p>Mutations in the <it>ZNF750 </it>promoter and coding regions have been previously associated with Mendelian forms of psoriasis and psoriasiform dermatitis. <it>ZNF750 </it>encodes a putative zinc finger transcription factor that is highly expressed in keratinocytes and represents a candidate psoriasis gene.</p> <p>Methods</p> <p>We examined whether <it>ZNF750 </it>variants were associated with psoriasis in a large case-control population. We sequenced the promoter and exon regions of <it>ZNF750 </it>in 716 Caucasian psoriasis cases and 397 Caucasian controls.</p> <p>Results</p> <p>We identified a total of 47 variants, including 38 rare variants of which 35 were novel. Association testing identified two <it>ZNF750 </it>haplotypes associated with psoriasis (p < 0.05). We also identified an excess of rare promoter and 5'untranslated region (UTR) variants in psoriasis cases compared to controls (p = 0.041), whereas there was no significant difference in the number of rare coding and rare 3' UTR variants. Using a promoter functional assay in stimulated human primary keratinocytes, we showed that four <it>ZNF750 </it>promoter and 5' UTR variants displayed a 35-55% reduction of <it>ZNF750 </it>promoter activity, consistent with the promoter activity reduction seen in a Mendelian psoriasis family with a <it>ZNF750 </it>promoter variant. However, the rare promoter and 5' UTR variants identified in this study did not strictly segregate with the psoriasis phenotype within families.</p> <p>Conclusions</p> <p>Two haplotypes of <it>ZNF750 </it>and rare 5' regulatory variants of <it>ZNF750 </it>were found to be associated with psoriasis. These rare 5' regulatory variants, though not causal, might serve as a genetic modifier of psoriasis.</p

    The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

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    The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

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    AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec

    Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015

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    Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe
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