Hasil Plagiasi artikel dengan judul :Efektivitas Akupressure Hegu LI 4 Terhadap Intensitas Nyeri Persalinan Kala I Fase Aktif

Childbirth is a moment full of stress that causes pain, fear, and anxiety. Acupressure Hegu LI 4 is one of the techniques to reduce pain during labor. Objective of the study was to identify the difference in pain on first stage active phase of labor in acupressure Hegu LI 4 group and control group. Samples were obtained through consecutive sampling technique from parturient which fulfill inclusion criteria. The study was a quasy experiment design. Data analysis used mean and deviation standard for univariate analysis, Independent Sample T Test for bivariable analysis, and linier regretion for multivariable analysis. Mean of decrease of pain labor in aromatheraphy group was higher than control group. The mean decrease in pain score in the intervention group was 3.03 ± 0.669 while the mean reduction in pain in the control group was 2.07 ± 0.740. The average difference from the Independent Sample T Test obtained significant results with P values <0.001 and 95% C.I. -1,331 - (-0,602). Analysis of external variables that affect the decrease in labor pain scores is anxiety with P value = 0.020. The results of this study are expected to be the basis of studies in the field of midwifery, especially labor on effective methods to reduce labor pain in a non-pharmacological manne

Enhanced Statistical Tests for GWAS in Admixed Populations: Assessment using African Americans from CARe and a Breast Cancer Consortium

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations

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Leveraging population admixture to characterize the heritability of complex traits

Despite recent progress on estimating the heritability explained by genotyped SNPs (h(2)g), a large gap between h(2)g and estimates of total narrow-sense heritability (h(2)) remains. Explanations for this gap include rare variants or upward bias in family-based estimates of h(2) due to shared environment or epistasis. We estimate h(2) from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (h(2)γ). We show that h(2)γ = 2FSTCθ(1 - θ)h(2), where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We applied this approach to the analysis of 13 phenotypes in 21,497 African-American individuals from 3 cohorts. For height and body mass index (BMI), we obtained h(2) estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of h(2)g in these and other data but smaller than family-based estimates of h(2)