160 research outputs found

    Pengaruh Komunikasi Terapeutik Perawat Terhadap Kepuasan Pasien Di Rawat Jalan RSUD Jogja

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    The Objective of this study is to know influence of nurse therapeutic communication to satisfaction of patients satisfaction in RSUD Yogyakarta. The study was a quantitative research methods such as surveys of descriptive inferential research with cross sectional approach. Number of samples in this research is 285 sample in inpatient and 140 in emergency room. The instrument used a questionnaire. Analysis of data using multiple linear regression. This study show that there is the influence of therapeutic communication nurse to satisfaction of outpatients and Emergency room in RSUD Yogyakarta, and orientation phase is a phase that most influence on patient satisfaction. The most influential to therapeutic communication is termination stage

    Summary results of the GWAS and the replication study of TP, ALB, and NAP.

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    a<p>A1/A2: major/minor alleles.</p>b<p>The effect of the minor allele on the normalized values based on an additive genetic model.</p>c<p>For the GWAS and replication analysis, <i>P</i>-values were obtained by linear regression test model, for the Meta analysis by inverse-variance method.</p>*<p>SNPs obtained by whole-genome imputation analysis.</p><p>Abbreviations: GWAS: genome-wide association study, MAF: minor allele frequency, TP: total protein, ALB: albumin, NAP: non-albumin protein, s.e: standard error.</p

    Characteristics of the examined proteins.

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    a<p>M±S.D: mean value±standard deviation of each protein is indicated in g/dl except for IgE, which is indicated as IU/ml.</p>b<p>Age and body mass index (BMI) are indicated as mean values±standard deviation.</p>*<p>Log-transformed values were applied in the analysis.</p><p>Abbreviations: GWAS: genome-wide association study, TP: total protein, ALB: albumin, NAP: non-albumin protein.</p

    Regional plots for the associations of the SNPs in the GWAS stage of TP, ALB and NAP.

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    <p>SNPs plotted with their –log<sub>10</sub> (<i>P</i>-values) in the GWAS based on their physical chromosomal positions. Genotyped SNPs are indicated as circles, while imputed SNPs are indicated as triangles. The color scheme indicated the linkage disequilibrium displayed as <i>r</i><sup>2</sup> values between all SNPs and the top-ranked SNP in each plot. The tested trait, chromosomal locus, and the top-ranked SNPs (in purple color) in the GWAS and combined analyses together with their <i>P</i>-values are shown in each plot. The blue lines represent the recombination rates estimated based on HapMap Phase ΙΙ database. The plots were drawn using Locus Zoom software.</p

    Association of the SNPs in the GWAS of the NAP with immunoglobulin isotypes.

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    a<p>The effect of the minor alleles on the standardized values.</p>b<p><i>P</i>-values for the associations of SNPs with each normalized immunoglobulin isotype obtained by using a linear regression model.</p><p>Abbreviations: s.e: standard error, %EV: percentage of the explanatory variance.</p

    Manhattan plots for the GWAS of (A) TP, (B) NAP, and (C) ALB.

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    <p>SNPs were plotted based on their physical chromosomal positions (horizontal axis) together with their –log<sub>10</sub> (<i>P-</i>values) in the GWAS (vertical axis). The black horizontal line shows the genome-wide significance threshold of <i>P</i> = 5.0×10<sup>−8</sup>. The SNPs for which <i>P</i>-values were smaller than 1.0×10<sup>−15</sup> are indicated at the upper limit of the plots.</p

    Quantitative Structural Characterization of Local N‑Glycan Microheterogeneity in Therapeutic Antibodies by Energy-Resolved Oxonium Ion Monitoring

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    Site-specific characterization of glycoform heterogeneity currently requires glycan structure assignment and glycopeptide quantification in two independent experiments. We present here a new method combining multiple reaction monitoring mass spectrometry with energy-resolved structural analysis, which we termed “energy-resolved oxonium ion monitoring”. We demonstrated that monitoring the yields of oligosaccharide-derived fragment ions (oxonium ions) over a wide range of collision induced dissociation (CID) energy applied to a glycopeptide precursor exhibits a glycan structure-unique fragmentation pattern. In the analysis of purified immunoglobulin glycopeptides, the energy-resolved oxonium ion profile was shown to clearly distinguish between isomeric glycopeptides. Moreover, limit of detection (LOD) of glycopeptide detection was 30 attomole injection, and quantitative dynamic range spanned 4 orders magnitude. Therefore, both quantification of glycopeptides and assignment of their glycan structures were achieved by a simple analysis procedure. We assessed the utility of this method for characterizing site-specific N-glycan microheterogeneity on therapeutic antibodies, including validation of lot-to-lot glycoform variability. A significant change in the degree of terminal galactosylation was observed in different production lots of trastuzumab and bevacizumab. Cetuximab Fab glycosylation, previously known to cause anaphylaxis, was also analyzed, and several causative antigens including Lewis X motifs were quantitatively detected. The data suggests that energy-resolved oxonium ion monitoring could fulfill the regulatory requirement on the routine quality control analysis of forthcoming biosimilar therapeutics

    Association results in Japanese woman of previously identified SNPs with age at menarche in Caucasian woman.

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    <p>Genotyping result of 15,495 Japanese subjects were anlayzed in this study. Imputed SNPs with R2 of less than 0.7 were excluded from this analysis. A1 frequency of JPT were those from release 24 Hapmap JPT. N.D.; no data. References: 1 Elks et al Nat Genet 2010, 2 He et al Nature Genet 2009, 3 Liu et al Plos Genet 2009. P-value of 0.0015 (0.05/33) was set at the significant threshold for this candidate analysis.</p>*<p>:Effect size and S.E. of allele1 on age at menarche (year per allele) and P-values were obtained by inverse-variance method.</p>**<p>Concordance of association direction between this study and the previous report.</p

    Genome-Wide Association Study of Breast Cancer in the Japanese Population

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    <div><p>Breast cancer is the most common malignancy among women in worldwide including Japan. Several studies have identified common genetic variants to be associated with the risk of breast cancer. Due to the complex linkage disequilibrium structure and various environmental exposures in different populations, it is essential to identify variants associated with breast cancer in each population, which subsequently facilitate the better understanding of mammary carcinogenesis. In this study, we conducted a genome-wide association study (GWAS) as well as whole-genome imputation with 2,642 cases and 2,099 unaffected female controls. We further examined 13 suggestive loci (<i>P</i><1.0×10<sup>−5</sup>) using an independent sample set of 2,885 cases and 3,395 controls and successfully validated two previously-reported loci, rs2981578 (combined <i>P</i>-value of 1.31×10<sup>−12</sup>, OR = 1.23; 95% CI = 1.16–.30) on chromosome 10q26 (<i>FGFR2</i>), rs3803662 (combined <i>P</i>-value of 2.79×10<sup>−11</sup>, OR = 1.21; 95% CI = 1.15–.28) and rs12922061 (combined <i>P</i>-value of 3.97×10<sup>−10</sup>, OR = 1.23; 95% CI = 1.15–.31) on chromosome 16q12 (<i>TOX3-LOC643714</i>). Weighted genetic risk score on the basis of three significantly associated variants and two previously reported breast cancer associated loci in East Asian population revealed that individuals who carry the most risk alleles in category 5 have 2.2 times higher risk of developing breast cancer in the Japanese population than those who carry the least risk alleles in reference category 1. Although we could not identify additional loci associated with breast cancer, our study utilized one of the largest sample sizes reported to date, and provided genetic status that represent the Japanese population. Further local and international collaborative study is essential to identify additional genetic variants that could lead to a better, accurate prediction for breast cancer.</p></div
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