Adenomatous Polyposis Coli is Present Near the Minimal Level Required for Accurate Graded Responses to the Wingless Morphogen

The mechanisms by which the Wingless (Wg) morphogen modulates the activity of the transcriptional activator Armadillo (Arm) to elicit precise, concentration-dependent cellular responses remain uncertain. Arm is targeted for proteolysis by the Axin/Adenomatous polyposis coli (Apc1 and Apc2)/Zeste-white 3 destruction complex, and Wg-dependent inactivation of destruction complex activity is crucial to trigger Arm signaling. In the prevailing model for Wg transduction, only Axin levels limit destruction complex activity, whereas Apc is present in vast excess. To test this model, we reduced Apc activity to different degrees, and analyzed the effects on three concentration-dependent responses to Arm signaling that specify distinct retinal photoreceptor fates. We find that both Apc1 and Apc2 negatively regulate Arm activity in photoreceptors, but that the relative contribution of Apc1 is much greater than that of Apc2. Unexpectedly, a less than twofold reduction in total Apc activity, achieved by loss of Apc2, decreases the effective threshold at which Wg elicits a cellular response, thereby resulting in ectopic responses that are spatially restricted to regions with low Wg concentration. We conclude that Apc activity is not present in vast excess, but instead is near the minimal level required for accurate graded responses to the Wg morphogen

The Hanabi Challenge: A New Frontier for AI Research

From the early days of computing, games have been important testbeds for studying how well machines can do sophisticated decision making. In recent years, machine learning has made dramatic advances with artificial agents reaching superhuman performance in challenge domains like Go, Atari, and some variants of poker. As with their predecessors of chess, checkers, and backgammon, these game domains have driven research by providing sophisticated yet well-defined challenges for artificial intelligence practitioners. We continue this tradition by proposing the game of Hanabi as a new challenge domain with novel problems that arise from its combination of purely cooperative gameplay with two to five players and imperfect information. In particular, we argue that Hanabi elevates reasoning about the beliefs and intentions of other agents to the foreground. We believe developing novel techniques for such theory of mind reasoning will not only be crucial for success in Hanabi, but also in broader collaborative efforts, especially those with human partners. To facilitate future research, we introduce the open-source Hanabi Learning Environment, propose an experimental framework for the research community to evaluate algorithmic advances, and assess the performance of current state-of-the-art techniques.Comment: 32 pages, 5 figures, In Press (Artificial Intelligence

Mapping and simplifying construction project delivery

The nature of project complexity within construction engineering projects has been the subject of study with growing interest, especially since the Engineering and Physical Sciences Research Council (EPSRC) Networks- Engineering and Physical Sciences Research Council was set-up in 2003. Yet, it could be argued in research terms, that project complexity has been neglected both in terms of conceptualising it and in terms of empirical study. Given the supposed severity of project complexity and the obvious failings of the industry’s approach towards project delivery, it is reasonable to assume that such an issue would provide a focus for research to improve practice. The main issues appraised are structural complexity, uncertainty, organisational complexity and technological complexity. As established from the reviewed literature, one of the hindrances to project performance within the construction industry is project complexity, which mainly emerges during the construction and design process

Effect of body composition methodology on heritability estimation of body fatness

Heritability estimates of human body fatness vary widely and the contribution of body composition methodology to this variability is unknown. The effect of body composition methodology on estimations of genetic and environmental contributions to body fatness variation was examined in 78 adult male and female monozygotic twin pairs reared apart or together. Body composition was assessed by six methods - body mass index (BMI), dual energy x-ray absorptiometry (DXA), underwater weighing (UWW), total body water (TBW), bioelectric impedance (BIA), and skinfold thickness. Body fatness was expressed as percent body fat, fat mass, and fat mass/height2 to assess the effect of body fatness expression on heritability estimates. Model-fitting multivariate analyses were used to assess the genetic and environmental components of variance. Mean BMI was 24.5 kg/m2 (range of 17.8-43.4 kg/m2). There was a significant effect of body composition methodology (p<0.001) on heritability estimates, with UWW giving the highest estimate (69%) and BIA giving the lowest estimate (47%) for fat mass/height2. Expression of body fatness as percent body fat resulted in significantly higher heritability estimates (on average 10.3% higher) compared to expression as fat mass/height2 (p=0.015). DXA and TBW methods expressing body fatness as fat mass/height2 gave the least biased heritability assessments, based on the small contribution of specific genetic factors to their genetic variance. A model combining DXA and TBW methods resulted in a relatively low FM/ht2 heritability estimate of 60%, and significant contributions of common and unique environmental factors (22% and 18%, respectively). The body fatness heritability estimate of 60% indicates a smaller contribution of genetic variance to total variance than many previous studies using less powerful research designs have indicated. The results also highlight the importance of environmental factors and possibly genotype by environmental interactions in the etiology of weight gain and the obesity epidemic.R01 AR046124 - NIAMS NIH HHS; R01 MH065322 - NIMH NIH HHS; T32 HL069772 - NHLBI NIH HHS; R21 DK078867 - NIDDK NIH HHS; R37 DA018673 - NIDA NIH HHS; R01 DK076092 - NIDDK NIH HHS; R01 DK079003 - NIDDK NIH HHS; F32 DK009747 - NIDDK NIH HHS; R01 DA018673 - NIDA NIH HH

Touching the heart of HIV-1 drug resistance: the fingers close down on the dNTP at the polymerase active site

AbstractComparison of the recently solved structure of HIV-1reverse transcriptase (RT)-DNA-dNTP ternary complex with the previously solved structure of RT-DNA binary complex suggests mechanisms by which the HIV-1 RT becomes resistant to nucleoside-analog inhibitors, drugs currently used in the treatment of AIDS

Complementary role of cardiac CT in the assessment of aortic valve replacement dysfunction

Aortic valve replacement is the second most common cardiothoracic procedure in the UK. With an ageing population, there are an increasing number of patients with prosthetic valves that require follow-up. Imaging of prosthetic valves is challenging with conventional echocardiographic techniques making early detection of valve dysfunction or complications difficult. CT has recently emerged as a complementary approach offering excellent spatial resolution and the ability to identify a range of aortic valve replacement complications including structural valve dysfunction, thrombus development, pannus formation and prosthetic valve infective endocarditis. This review discusses each and how CT might be incorporated into a multimodal cardiovascular imaging pathway for the assessment of aortic valve replacements and in guiding clinical management

py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full 2D image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields and other sample-dependent properties. However, extracting this information requires complex analysis pipelines, from data wrangling to calibration to analysis to visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail, and present results from several experimental datasets. We have also implemented a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open source HDF5 standard. We hope this tool will benefit the research community, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project

Finding Apparent Horizons in Dynamic 3D Numerical Spacetimes

We have developed a general method for finding apparent horizons in 3D numerical relativity. Instead of solving for the partial differential equation describing the location of the apparent horizons, we expand the closed 2D surfaces in terms of symmetric trace--free tensors and solve for the expansion coefficients using a minimization procedure. Our method is applied to a number of different spacetimes, including numerically constructed spacetimes containing highly distorted axisymmetric black holes in spherical coordinates, and 3D rotating, and colliding black holes in Cartesian coordinates.Comment: 19 pages, 13 figures, LaTex, to appear in Phys. Rev. D. Minor changes mad