Wnt4 Enhances Murine Hematopoietic Progenitor Cell Expansion Through a Planar Cell Polarity-Like Pathway

Background: While the role of canonical (b-catenin-mediated) Wnt signaling in hematolymphopoiesis has been studied extensively, little is known of the potential importance of non-canonical Wnt signals in hematopoietic cells. Wnt4 is one of the Wnt proteins that can elicit non-canonical pathways. We have previously shown that retroviral overexpression of Wnt4 by hematopoietic cells increased thymic cellularity as well as the frequency of early thymic progenitors and bone marrow hematopoietic progenitor cells (HPCs). However, the molecular pathways responsible for its effect in HPCs are not known. Methodology/Principal Findings: Here we report that Wnt4 stimulation resulted in the activation of the small GTPase Rac1 as well as Jnk kinases in an HPC cell line. Jnk activity was necessary, while b-catenin was dispensable, for the Wnt4-mediated expansion of primary fetal liver HPCs in culture. Furthermore, Jnk2-deficient and Wnt4 hemizygous mice presented lower numbers of HPCs in their bone marrow, and Jnk2-deficient HPCs showed increased rates of apoptosis. Wnt4 also improved HPC activity in a competitive reconstitution model in a cell-autonomous, Jnk2-dependent manner. Lastly, we identified Fz6 as a receptor for Wnt4 in immature HPCs and showed that the absence of Wnt4 led to a decreased expression of four polarity complex genes. Conclusions/Significance: Our results establish a functional role for non-canonical Wnt signaling in hematopoiesis throug

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Propagation of void fraction uncertainty measures in the RETRAN-3D simulation of the Peach Bottom turbine trip

The paper describes the propagation of void fraction uncertainty, as quantified by employing a novel methodology developed at Paul Scherrer Institut, in the RETRAN-3D simulation of the Peach Bottom turbine trip test. Since the transient considered is characterized by a strong coupling between thermal-hydraulics and neutronics. the accuracy in the void fraction model has a very important influence on the prediction of the power history and, in particular, of the maximum power reached. It has been shown that the objective measures used for the void fraction uncertainty, based on the direct comparison between experimental and predicted values extracted from a database of appropriate separate-effect tests, provides power uncertainty bands that are narrower and more realistic than those based, for example, on expert opinion. The applicability of such an approach to best estimate, nuclear power plant transient analysis has thus been demonstrated

Improvement of the one-dimensional dissolved-solute convection equation using the QUICKEST-ULTIMATE algorithm

The U.S.-NRC best-estimate system code TRACE adopts a finite volumes, first-order upwind discretization scheme to solve the dissolved-solute convection equation. Such a scheme is known to strongly suffer from numerical diffusion, which can be a significant drawback in analyzing certain safety relevant scenarios in nuclear power plants, e.g. with plugs of solute (or plugs of diluting water) traveling from the loops to the core and thus affecting the reactivity of the system. In such cases, high-order upwind convecting schemes are better suited to discretize and solve the solute convection equation. In particular, the explicit QUICKEST (Quadratic Upwind Interpolation for Convective Kinematics with Estimated Streaming Terms) scheme, together with the ULTIMATE (Universal Limiter for Transient Interpolation Modeling of the Advective Transport Equation) limiter, offers an attractive solution, thanks to the overall third-order accuracy, the intrinsic stability of the upwind scheme and the limited increase in computational costs. In order to demonstrate the feasibility and the advantages of the implementation of such a solution strategy in TRACE, the scheme has been implemented in the code and verified for simple geometries (e.g. straight pipes) and for a double T-junction loop, the latter in the context of using a CFD (Computational Fluid dynamics) code coupled with TRACE. (C) 2010 Elsevier B.V. All rights reserved

Calculation of gamma-ray exposure buildup factor based on backpropagation neural network

In this paper, a method based on a backpropagation neural network (BPNN) is proposed to calculate the exposure buildup factor (BD) of a point isotropic source in an infinite homogeneous medium under arbitrary energy and mean free path (mfp). The results obtained for aluminum, iron, lead, and concrete based on BPNN are compared to ANSI/ANS-6.4.3 standard data, the results calculated by MCNP 5 Monte Carlo code, and a geometric progression (G-P) fitting formula, and show that the BD calculated by the BPNN model is more consistent with the ANS standard data. This method improves the calculation and fitting effect of BD compared to other methods. This paper proposes a systematic process combining a Monte Carlo method and BPNN to calculate and predict the BD of new materials under different energy and mfp, thus replacing the G-P fitting formula and improving calculation accuracy