212 research outputs found
Fortuitous structure determination of ‘as-isolated’ Escherichia coli bacterioferritin in a novel crystal form
E. coli bacterioferritin was crystallized in a novel crystal form from different conditions and the structure was solved. The crystals belonged to space group P213 and diffracted to a resolution of 2.5 Å
Development and validation of the General Procrastination Scale (GPS-9): A short and reliable measure of trait procrastination
Trait procrastination is increasingly recognised as having relevance for a number of consequential outcomes, including health. However, research with clinical populations may be hindered by longer scales. The present research addresses this issue by developing and validating a short version of Lay's General Procrastination Scale (GPS), a widely used self-report measure of trait procrastination. Study 1 used factor analysis to reduce the 20-item GPS to 9 items across two large samples (N = 620, N = 920). In Study 2 the GPS-9 demonstrated very good internal consistency across 15 student, adult and chronic illness samples, with a meta-analysis of coefficient alpha finding an average reliability coefficient of 0.89 (Total N = 4492). The GPS-9 also demonstrated good test-retest reliability (r = 0.89), and the expected associations with variables known to be part of the nomological network of trait procrastination. Findings from the current research provide evidence that the GPS-9 is a brief, valid, and reliable measure of trait procrastination
Robert Roe's (944-2016) temporalism: A commentary
Dit artikel is geschreven ter nagedachtenis aan Robert Roe (1944-2016) en bevat een commentaar op zijn laatste contributie aan Gedrag & Organisatie, 'Op weg naar temporeel onderzoek: issues, tips en de tijdscoop als nieuw instrument', die eveneens in deze aflevering gepubliceerd is. We gaan in op de uitdagingen waarvoor temporeel onderzoek momenteel staat en geven een aantal suggesties hiervoor. Daarnaast gaan wij in op wat naar onze mening houdbare en onhoudbare vormen van temporalisme zijn. Houdbaar temporalisme uit zich in het consequent doorvoeren van temporele assumpties in alle aspecten van de methodologie. Temporalisme is houdbaar als het verbinding weet te leggen met het differentiële paradigma en nabijgelegen onderzoekstradities en als het erin slaagt de intersubjectieve gemeenschappelijkheid van verandering bloot te leggen. Wij staan stil bij Robert Roe's tijdscoop en zijn methodologische begrippen waarachtigheid en betekenisvolheid en laten zien welke centrale rol theorie in dit alles speelt. Ten slotte komen wij met suggesties aangaande hoe temporele theorievorming meer armslag kan krijge
Robert Roe's (944-2016) temporalism: A commentary
Dit artikel is geschreven ter nagedachtenis aan Robert Roe (1944-2016) en bevat een commentaar op zijn laatste contributie aan Gedrag & Organisatie, 'Op weg naar temporeel onderzoek: issues, tips en de tijdscoop als nieuw instrument', die eveneens in deze aflevering gepubliceerd is. We gaan in op de uitdagingen waarvoor temporeel onderzoek momenteel staat en geven een aantal suggesties hiervoor. Daarnaast gaan wij in op wat naar onze mening houdbare en onhoudbare vormen van temporalisme zijn. Houdbaar temporalisme uit zich in het consequent doorvoeren van temporele assumpties in alle aspecten van de methodologie. Temporalisme is houdbaar als het verbinding weet te leggen met het differentiële paradigma en nabijgelegen onderzoekstradities en als het erin slaagt de intersubjectieve gemeenschappelijkheid van verandering bloot te leggen. Wij staan stil bij Robert Roe's tijdscoop en zijn methodologische begrippen waarachtigheid en betekenisvolheid en laten zien welke centrale rol theorie in dit alles speelt. Ten slotte komen wij met suggesties aangaande hoe temporele theorievorming meer armslag kan krijge
Pregnancy in Advanced Kidney Disease:Clinical Practice Considerations on a Challenging Combination
Background:Thanks to the advances in care, pregnancy is now attainable for the majority of young female CKD patients, although it is still a high-risk endeavor. Clinical decision-making in these cases is impacted by a myriad of factors, making (pre)pregnancy counseling a complex process. The complexities, further impacted by limited data and unknown risks regarding outcome, can cause discussions when deciding on the best care for a specific patient. Objectives:In this article, we provide an overview of the considerations and dilemmas we encounter in preconception counseling and offer our perspective on how to deal with them in daily clinical practice. Methods:The main topics we discuss in our counseling are (1) the high risk of pregnancy complications, (2) the risk of permanent CKD deterioration due to pregnancy and subsequent decreased life expectancy, (3) appropriate changes in renal medication, and (4) assisted reproduction, genetic testing, and prenatal or preimplantation genetic diagnostics. Results and Conclusions:In our clinic, we openly address moral dilemmas arising in clinical practice in pregnancy and CKD, both within the physician team and with the patient. We do this by ensuring an interpretive physician-patient interaction and shared decision-making, deliberating in a multidisciplinary setting and, if needed, with input from an expert committee
KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease
Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p
KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease
Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p
KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease
Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p
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