Utrecht University

About: Utrecht University is a education organization based out in Utrecht, Utrecht, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 58176 authors who have published 139351 publications receiving 6214282 citations. The organization is also known as: UU & Universiteit Utrecht.

Mutations in the APC tumour suppressor gene cause chromosomal instability

Abstract: Two forms of genetic instability have been described in colorectal cancer: microsatellite instability and chromosomal instability. Microsatellite instability results from mutations in mismatch repair genes; chromosomal instability is the hallmark of many colorectal cancers, although it is not completely understood at the molecular level. As truncations of the Adenomatous Polyposis Coli (APC) gene are found in most colorectal tumours, we thought that mutations in APC might be responsible for chromosomal instability. To test this hypothesis, we examined mouse embryonic stem (ES) cells homozygous for Min (multiple intestinal neoplasia) or Apc1638T alleles. Here we show that Apc mutant ES cells display extensive chromosome and spindle aberrations, providing genetic evidence for a role of APC in chromosome segregation. Consistent with this, APC accumulates at the kinetochore during mitosis. Apc mutant cells form mitotic spindles with an abundance of microtubules that inefficiently connect with kinetochores. This phenotype is recapitulated by the induced expression of a 253-amino-acid carboxy-terminal fragment of APC in microsatellite unstable colorectal cancer cells. We conclude that loss of APC sequences that lie C-terminal to the beta-catenin regulatory domain contributes to chromosomal instability in colorectal cancer.

Reduced airway surface pH impairs bacterial killing in the porcine cystic fibrosis lung

Abstract: Cystic fibrosis (CF) is a life-shortening disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene Although bacterial lung infection and the resulting inflammation cause most of the morbidity and mortality, how the loss of CFTR function first disrupts airway host defence has remained uncertain To investigate the abnormalities that impair elimination when a bacterium lands on the pristine surface of a newborn CF airway, we interrogated the viability of individual bacteria immobilized on solid grids and placed onto the airway surface As a model, we studied CF pigs, which spontaneously develop hallmark features of CF lung disease At birth, their lungs lack infection and inflammation, but have a reduced ability to eradicate bacteria Here we show that in newborn wild-type pigs, the thin layer of airway surface liquid (ASL) rapidly kills bacteria in vivo, when removed from the lung and in primary epithelial cultures Lack of CFTR reduces bacterial killing We found that the ASL pH was more acidic in CF pigs, and reducing pH inhibited the antimicrobial activity of ASL Reducing ASL pH diminished bacterial killing in wild-type pigs, and, conversely, increasing ASL pH rescued killing in CF pigs These results directly link the initial host defence defect to the loss of CFTR, an anion channel that facilitates HCO(3)(-) transport Without CFTR, airway epithelial HCO(3)(-) secretion is defective, the ASL pH falls and inhibits antimicrobial function, and thereby impairs the killing of bacteria that enter the newborn lung These findings suggest that increasing ASL pH might prevent the initial infection in patients with CF, and that assaying bacterial killing could report on the benefit of therapeutic interventions

Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker

Abstract: Prediction models are increasingly used to complement clinical reasoning and decision making in modern medicine in general, and in the cardiovascular domain in particular. Developed models first and foremost need to provide accurate and (internally and externally) validated estimates of probabilities of specific health conditions or outcomes in targeted patients. The adoption of such models must guide physician's decision making and an individual's behaviour, and consequently improve individual outcomes and the cost-effectiveness of care. In a series of two articles we review the consecutive steps generally advocated for risk prediction model research. This first article focuses on the different aspects of model development studies, from design to reporting, how to estimate a model's predictive performance and the potential optimism in these estimates using internal validation techniques, and how to quantify the added or incremental value of new predictors or biomarkers (of whatever type) to existing predictors. Each step is illustrated with empirical examples from the cardiovascular field.