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.

Use of the cell wall precursor lipid II by a pore-forming peptide antibiotic

Abstract: Resistance to antibiotics is increasing in some groups of clinically important pathogens. For instance, high vancomycin resistance has emerged in enterococci. Promising alternative antibiotics are the peptide antibiotics, abundant in host defense systems, which kill their targets by permeabilizing the plasma membrane. These peptides generally do not act via specific receptors and are active in the micromolar range. Here it is shown that vancomycin and the antibacterial peptide nisin Z use the same target: the membrane-anchored cell wall precursor Lipid II. Nisin combines high affinity for Lipid II with its pore-forming ability, thus causing the peptide to be highly active (in the nanomolar range).

Interleukin-22 promotes intestinal-stem-cell-mediated epithelial regeneration

Abstract: Epithelial regeneration is critical for barrier maintenance and organ function after intestinal injury. The intestinal stem cell (ISC) niche provides Wnt, Notch and epidermal growth factor (EGF) signals supporting Lgr5(+) crypt base columnar ISCs for normal epithelial maintenance. However, little is known about the regulation of the ISC compartment after tissue damage. Using ex vivo organoid cultures, here we show that innate lymphoid cells (ILCs), potent producers of interleukin-22 (IL-22) after intestinal injury, increase the growth of mouse small intestine organoids in an IL-22-dependent fashion. Recombinant IL-22 directly targeted ISCs, augmenting the growth of both mouse and human intestinal organoids, increasing proliferation and promoting ISC expansion. IL-22 induced STAT3 phosphorylation in Lgr5(+) ISCs, and STAT3 was crucial for both organoid formation and IL-22-mediated regeneration. Treatment with IL-22 in vivo after mouse allogeneic bone marrow transplantation enhanced the recovery of ISCs, increased epithelial regeneration and reduced intestinal pathology and mortality from graft-versus-host disease. ATOH1-deficient organoid culture demonstrated that IL-22 induced epithelial regeneration independently of the Paneth cell niche. Our findings reveal a fundamental mechanism by which the immune system is able to support the intestinal epithelium, activating ISCs to promote regeneration.

The same sequence variant on 9p21 associates with myocardial infarction, abdominal aortic aneurysm and intracranial aneurysm

Abstract: Recently, two common sequence variants on 9p21, tagged by rs10757278-G and rs10811661-T, were reported to be associated with coronary artery disease (CAD)(1-4) and type 2 diabetes (T2D)(5-7), respectively. We proceeded to further investigate the contributions of these variants to arterial diseases and T2D. Here we report that rs10757278-G is associated with, in addition to CAD, abdominal aortic aneurysm (AAA; odds ratio (OR) 1.31, P = 1.2 x 10(-12)) and intracranial aneurysm (OR = 1.29, P = 2.5 x 10(-6)), but not with T2D. This variant is the first to be described that affects the risk of AAA and intracranial aneurysm in many populations. The association of rs10811661-T to T2D replicates in our samples, but the variant does not associate with any of the five arterial diseases examined. These findings extend our insight into the role of the sequence variant tagged by rs10757278-G and show that it is not confined to atherosclerotic diseases.

Robustness issues in multilevel regression analysis

Abstract: A multilevel problem concerns a population with a hierarchical structure. A sample from such a population can be described as a multistage sample. First, a sample of higher level units is drawn (e.g. schools or organizations), and next a sample of the sub-units from the available units (e.g. pupils in schools or employees in organizations). In such samples, the individual observations are in general not completely independent. Multilevel analysis software accounts for this dependence and in recent years these programs have been widely accepted. Two problems that occur in the practice of multilevel modeling will be discussed. The first problem is the choice of the sample sizes at the different levels. What are sufficient sample sizes for accurate estimation? The second problem is the normality assumption of the level-2 error distribution. When one wants to conduct tests of significance, the errors need to be normally distributed. What happens when this is not the case? In this paper, simulation studies are used to answer both questions. With respect to the first question, the results show that a small sample size at level two (meaning a sample of 50 or less) leads to biased estimates of the second-level standard errors. The answer to the second question is that only the standard errors for the random effects at the second level are highly inaccurate if the distributional assumptions concerning the level-2 errors are not fulfilled. Robust standard errors turn out to be more reliable than the asymptotic standard errors based on maximum likelihood.

Regular pattern formation in real ecosystems

Abstract: Localized ecological interactions can generate striking large-scale spatial patterns in ecosystems through spatial self-organization. Possible mechanisms include oscillating consumer–resource interactions, localized disturbance-recovery processes and scale-dependent feedback. Despite abundant theoretical literature, studies revealing spatial self-organization in real ecosystems are limited. Recently, however, many examples of regular pattern formation have been discovered, supporting the importance of scale-dependent feedback. Here, we review these studies, showing regular pattern formation to be a general phenomenon rather than a peculiarity. We provide a conceptual framework explaining how scale-dependent feedback determines regular pattern formation in ecosystems. More empirical studies are needed to better understand regular pattern formation in ecosystems, and how this affects the response of ecosystems to global environmental change.