scholarly journals Genetic underpinnings of affective temperaments: a pilot GWAS investigation identifies a new genome-wide significant SNP for anxious temperament in ADGRB3 gene

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xenia Gonda ◽  
Nora Eszlari ◽  
Dora Torok ◽  
Zsofia Gal ◽  
Janos Bokor ◽  
...  
Keyword(s):  
Affective Disorders ◽  
Regression Models ◽  
Population Sample ◽  
Significant Snps ◽  
The Other ◽  
Additive Genetic Effect ◽  
Linear Regression Models ◽  
Affective Temperaments ◽  
Significance Threshold ◽  
The Brain

AbstractAlthough recently a large-sample GWASs identified significant loci in the background of depression, the heterogeneity of the depressive phenotype and the lack of accurate phenotyping hinders applicability of findings. We carried out a pilot GWAS with in-depth phenotyping of affective temperaments, considered as subclinical manifestations and high-risk states for affective disorders, in a general population sample of European origin. Affective temperaments were measured by TEMPS-A. SNP-level association was assessed by linear regression models, assuming an additive genetic effect, using PLINK1.9. Gender, age, the first ten principal components (PCs) and the other four temperaments were included in the regression models as covariates. SNP-level relevances (p-values) were aggregated to gene level using the PEGASUS method1. In SNP-based tests, a Bonferroni-corrected significance threshold of p ≤ 5.0 × 10−8 and a suggestive significance threshold of p ≤ 1.0 × 10−5, whereas in gene-based tests a Bonferroni-corrected significance of 2.0 × 10−6 and a suggestive significance of p ≤ 4.0 × 10−4 was established. To explore known functional effects of the most significant SNPs, FUMA v1.3.5 was used. We identified 1 significant and 21 suggestively significant SNPs in ADGRB3, expressed in the brain, for anxious temperament. Several other brain-relevant SNPs and genes emerged at suggestive significance for the other temperaments. Functional analyses reflecting effect on gene expression and participation in chromatin interactions also pointed to several genes expressed in the brain with potentially relevant phenotypes regulated by our top SNPs. Our findings need to be tested in larger GWA studies and candidate gene analyses in well-phenotyped samples in relation to affective disorders and related phenotypes.

scholarly journals INFLUENCE OF THE VEGETATION PERIOD ON THE SPREAD OF ECONOMICALLY IMPORTANT VIRAL DISEASES IN BURLEY TOBACCO

2019 ◽  
Vol 17 (1) ◽  
pp. 28-33
Author(s):  
Y. Yonchev ◽  
N. Keranova
Keyword(s):  
Correlation Analysis ◽  
Regression Models ◽  
Positive Impact ◽  
Vegetation Period ◽  
The Other ◽  
Viral Diseases ◽  
Strong Positive Correlation ◽  
Linear Regression Models ◽  
Burley Tobacco ◽  
Positive Effect

The present study explores the influence of the vegetation period of Burley tobacco on the spread of viruses such as TMW, PVY-Complex, CMV / PVY-Complex, TSWV and CMV. To establish this relation, a correlation analysis is applied and the proven effects are represented by linear regression models. In 2014, the number of days from replanting has a strong positive impact on the percentage of plants infected by PVY-Complex (0.985**) as well as by TMV (0.781*). For 2015, the very strong effect was only seen on CMV / PVY-Complex (0.976**). In 2016, the duration of the period had a positive effect on the spread of CMV / PVY-Complex (0.868*), CMV (0.904 **) and TSWV (0.966**). In 2017 there is a very strong positive correlation between PVY-Complex (0.885*), CMV (0.948**) and TSWV (0.955**) on one hand and the planting period on the other. As a result of the conducted study over the entire four-year period, it has been proven that during the first two years the increase in the vegetation period leads to an increase in the incidence of PVY complex. During the second half of the analyzed period, CMV and TSWV are proved to be affected by the length of the time from the replanting.

scholarly journals Homoscedasticity: an overlooked critical assumption for linear regression

2019 ◽  
Vol 32 (5) ◽  
pp. e100148
Author(s):  
Kun Yang ◽  
Justin Tu ◽  
Tian Chen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Linear Regression ◽  
Regression Models ◽  
Data Distribution ◽  
The Other ◽  
Simulation Studies ◽  
Linear Regression Models ◽  
Popular Belief

Linear regression is widely used in biomedical and psychosocial research. A critical assumption that is often overlooked is homoscedasticity. Unlike normality, the other assumption on data distribution, homoscedasticity is often taken for granted when fitting linear regression models. However, contrary to popular belief, this assumption actually has a bigger impact on validity of linear regression results than normality. In this report, we use Monte Carlo simulation studies to investigate and compare their effects on validity of inference.

scholarly journals Bayesian model evidence as a practical alternative to deviance information criterion

2018 ◽  
Vol 5 (3) ◽  
pp. 171519 ◽  
Author(s):  
C. M. Pooley ◽  
G. Marion
Keyword(s):  
Linear Regression ◽  
Bayesian Model ◽  
Regression Models ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
The Other ◽  
Model Choice ◽  
Linear Regression Models ◽  
True Model ◽  
Model Evidence

While model evidence is considered by Bayesian statisticians as a gold standard for model selection (the ratio in model evidence between two models giving the Bayes factor), its calculation is often viewed as too computationally demanding for many applications. By contrast, the widely used deviance information criterion (DIC), a different measure that balances model accuracy against complexity, is commonly considered a much faster alternative. However, recent advances in computational tools for efficient multi-temperature Markov chain Monte Carlo algorithms, such as steppingstone sampling (SS) and thermodynamic integration schemes, enable efficient calculation of the Bayesian model evidence. This paper compares both the capability (i.e. ability to select the true model) and speed (i.e. CPU time to achieve a given accuracy) of DIC with model evidence calculated using SS. Three important model classes are considered: linear regression models, mixed models and compartmental models widely used in epidemiology. While DIC was found to correctly identify the true model when applied to linear regression models, it led to incorrect model choice in the other two cases. On the other hand, model evidence led to correct model choice in all cases considered. Importantly, and perhaps surprisingly, DIC and model evidence were found to run at similar computational speeds, a result reinforced by analytically derived expressions.

scholarly journals A study on factors related to readership of scientific articles

2017 ◽  
Vol 3 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Tony Xu ◽  
Shayan Khalili ◽  
Cynthia Deng
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Scientific Research ◽  
The Other ◽  
Linear Regression Models ◽  
Research Papers ◽  
Scatter Plots ◽  
The Subject ◽  
Moderate Effect ◽  
The Relationship

This paper analyzes the relationship between the number of Twitter and Mendeley readers with the article’s subject, publisher, journal, and title length. It also looks at which country has the greatest number of readers to see if researchers can garner more visibility by publishing an article relevant to issues in those countries. The purpose of this report is to help researchers improve the visibility and impact value of their research. The data was gathered from 550,000 scientific research papers published between January 1st and July 1st of 2016. Python’s built-in JSON library was used to extract the number of Twitter and Mendeley readers, as well as the article count for each factor. The correlation between readers per article and each factor was then visualized using bubble graphs, linear regression models, and scatter plots. This paper concludes that the length of the title is the strongest factor affecting readership. In particular, titles with lengths between 51 and 90 characters have the greatest number of readers. Moreover, articles relevant to issues in countries with a higher GDP have the highest overall readership. On the other hand, the publisher and the journal did not have a significant effect on readership, while the subject of the article had a moderate effect on readership.

scholarly journals Economic Growth and Public Indebtedness in the Last Four Decades: Is Portugal different from the other PIIGS’ economies?

2015 ◽  
Vol 61 (6) ◽  
pp. 3-11 ◽  
Author(s):  
Ricardo Ferraz ◽  
António Portugal Duarte
Keyword(s):  
Economic Growth ◽  
Linear Regression ◽  
Public Debt ◽  
Regression Models ◽  
Time Horizon ◽  
Negative Relationship ◽  
The Other ◽  
Extended Time ◽  
Linear Regression Models ◽  
The Relationship

Abstract Portugal is a member of the group known by investors as ‘PIIGS’, countries characterised by having high public debt and weak economic growth. Using an extended time horizon, 1974–2014, this study seeks to empirically explore the relationship between economic growth and public debt in the PIIGS economies, particularly in the case of Portugal. Based on the estimation of linear regression models, it was concluded that in the last four decades there has been a negative relationship between economic growth and public debt in both cases, which is consistent with the literature. The negative relationship was even more pronounced in the case of the PIIGS than it was in the case of Portugal.

scholarly journals PENGARUH INFLASI, BI RATE, SUKU BUNGA KREDIT UMKM TERHADAP NON PERFORMING LOAN KREDIT UMKM PADA BANK UMUM

2020 ◽  
Vol 8 (2) ◽  
pp. 156
Author(s):  
Suharna Suharna
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Commercial Banks ◽  
Regression Models ◽  
Inflation Rate ◽  
Secondary Data ◽  
The Other ◽  
Linear Regression Models ◽  
Multiple Linear Regression Models

This study aims to obtain empirical evidence on the influence of inflation, rate of Bank Indonesia, and credit interest rate on non - performing SMEs credit loan at Commercial Banks. This study uses secondary data obtained from quarterly OJK reports and Bank Indonesia monthly reports for the period of 2014 - 2018. Multiple linear regression models are used to test the hypotheses of this study. It was found that the inflation rate and the rate of Bank Indonesia individually doesn't have a siignificant influence on non - performing SMEs credit loans. On the other hand, it was found that credit interest rate has a signifinicant influence on non - performing SMEs credit loans.

scholarly journals Empathy and its associations with age and sociodemographic characteristics in a large UK population sample

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257557
Author(s):  
Andrew Sommerlad ◽  
Jonathan Huntley ◽  
Gill Livingston ◽  
Katherine P. Rankin ◽  
Daisy Fancourt
Keyword(s):  
Perspective Taking ◽  
Regression Models ◽  
Social Care ◽  
Population Sample ◽  
Female Gender ◽  
Empathic Concern ◽  
Reactivity Index ◽  
Linear Regression Models ◽  
White Ethnicity ◽  
Younger Age

Objectives Empathy is fundamental to social cognition, driving prosocial behaviour and mental health but associations with aging and other socio-demographic characteristics are unclear. We therefore aimed to characterise associations of these characteristics with two main self-reported components of empathy, namely empathic-concern (feeling compassion) and perspective-taking (understanding others’ perspective). Methods We asked participants in an internet-based survey of UK-dwelling adults aged ≥18 years to complete the Interpersonal Reactivity Index subscales measuring empathic concern and perspective taking, and sociodemographic and personality questionnaires. We weighted the sample to be UK population representative and employed multivariable weighted linear regression models. Results In 30,033 respondents, mean empathic concern score was 3.86 (95% confidence interval 3.85, 3.88) and perspective taking was 3.57 (3.56. 3.59); the correlation between these sub-scores was 0.45 (p < 0.001). Empathic concern and perspective taking followed an inverse-u shape trajectory in women with peak between 40 and 50 years whereas in men, perspective taking declines with age but empathic concern increases. In fully adjusted models, greater empathic concern was associated with female gender, non-white ethnicity, having more education, working in health, social-care, or childcare professions, and having higher neuroticism, extroversion, openness to experience and agreeableness traits. Perspective taking was associated with younger age, female gender, more education, employment in health or social-care, neuroticism, openness, and agreeableness. Conclusions Empathic compassion and understanding are distinct dimensions of empathy with differential demographic associations. Perspective taking may decline due to cognitive inflexibility with older age whereas empathic concern increases in older men suggesting it is socially-driven.

scholarly journals Power Comparisons of Five Most Commonly Used Autocorrelation Tests

2020 ◽  
pp. 119-130
Author(s):  
Stanislaus S. Uyanto
Keyword(s):  
Regression Models ◽  
Ordinary Least Squares ◽  
The Other ◽  
Standard Errors ◽  
Linear Regression Models ◽  
Power Comparison ◽  
Power Comparisons ◽  
Lagged Dependent Variable ◽  
Error Terms ◽  
Watson Test

In regression analysis, autocorrelation of the error terms violates the ordinary least squares assumption that the error terms are uncorrelated. The consequence is that the estimates of coefficients and their standard errors will be wrong if the autocorrelation is ignored. There are many tests for autocorrelation, we want to know which test is more powerful. We use Monte Carlo methods to compare the power of five most commonly used tests for autocorrlation, namely Durbin-Watson, Breusch-Godfrey, Box–Pierce, Ljung Box, and Runs tests in two different linear regression models. The results indicate the Durbin-Watson test performs better in the regression model without lagged dependent variable, although the advantage over the other tests reduce with increasing autocorrelation and sample sizes. For the model with lagged dependent variable, the Breusch-Godfrey test is generally superior to the other tests.R code for Power Comparison of the Five Autocorrelation Tests is provided.

MICROCHEMICAL ASSAYS OF GLUCOSE AND GLUCOSE-6-PHOSPHATE IN MAMMALIAN PANCREATIC β-CELLS

1968 ◽  
Vol 59 (3) ◽  
pp. 479-486 ◽  
Author(s):  
Lars-Ake Idahl ◽  
Bo Hellman
Keyword(s):  
Glucose Level ◽  
Exocrine Pancreas ◽  
The Other ◽  
Wide Concentration Range ◽  
Β Cells ◽  
Pancreatic Β Cells ◽  
Enzymatic Cycling ◽  
Glucose Diffusion ◽  
Significant Barrier ◽  
The Brain

ABSTRACT The combination of enzymatic cycling and fluorometry was used for measuring glucose and glucose-6-phosphate in pancreatic β-cells from obese-hyperglycaemic mice. The glucose level of the β-cells corresponded to that of serum over a wide concentration range. In the exocrine pancreas, on the other hand, a significant barrier to glucose diffusion across the cell membranes was demonstrated. During 5 min of ischaemia, the glucose level remained practically unchanged in the β-cells while it increased in the liver and decreased in the brain. The observation that the pancreatic β-cells are characterized by a relatively low ratio of glucose-6-phosphate to glucose may be attributed to the presence of a specific glucose-6-phosphatase.

Sign in / Sign up

Export Citation Format

Share Document