"Why me, why now?" Using clinical immunology and epidemiology to explain who gets nontuberculous mycobacterial infection

BACKGROUND: The prevalence of nontuberculous mycobacterial (NTM) disease is rising. An understanding of known risk factors for disease sheds light on the immunological and physical barriers to infection, and how and why they may be overcome. This review focuses on human NTM infection, supported by experimental and in vitro data of relevance to the practising clinician who seeks to understand why their patient has NTM infection and how to further investigate. DISCUSSION: First, the underlying immune response to NTM disease is examined. Important insights regarding NTM disease susceptibility come from nature's own knockouts, the primary immune deficiency disorders. We summarise the current knowledge surrounding interferon-gamma (IFNγ)-interleukin-12 (IL-12) axis abnormalities, followed by a review of phagocytic defects, T cell lymphopenia and rarer genetic conditions known to predispose to NTM disease. We discuss how these define key immune pathways involved in the host response to NTM. Iatrogenic immunosuppression is also important, and we evaluate the impact of novel biological therapies, as well as bone marrow transplant and chemotherapy for solid organ malignancy, on the epidemiology and presentation of NTM disease, and discuss the host defence dynamics thus revealed. NTM infection and disease in the context of other chronic illnesses including HIV and malnutrition is reviewed. The role of physical barriers to infection is explored. We describe how their compromise through different mechanisms including cystic fibrosis, bronchiectasis and smoking-related lung disease can result in pulmonary NTM colonisation or infection. We also summarise further associations with host factors including body habitus and age. We use the presented data to develop an over-arching model that describes human host defences against NTM infection, where they may fail, and how this framework can be applied to investigation in routine clinical practice

Negative frequency-dependent selection is intensified at higher population densities in protist populations

This is the final version of the article. Available from the Royal Society via the DOI in this record.Natural populations of free-living protists often exhibit high-levels of intraspecific diversity, yet this is puzzling as classic evolutionary theory predicts dominance by genotypes with high fitness, particularly in large populations where selection is efficient. Here, we test whether negative frequency-dependent selection (NFDS) plays a role in the maintenance of diversity in the marine flagellate Oxyrrhis marina using competition experiments between multiple pairs of strains. We observed strain-specific responses to frequency and density, but an overall signature of NFDS that was intensified at higher population densities. Because our strains were not selected a priori on the basis of particular traits expected to exhibit NFDS, these data represent a relatively unbiased estimate of the role for NFDS in maintaining diversity in protist populations. These findings could help to explain how bloom-forming plankton, which periodically achieve exceptionally high population densities, maintain substantial intraspecific diversity.E.J.A.M. was supported by a NERC research studentship (NE/H025472/2) as part of the UK Ocean Acidification Research Programme

Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization

Image-based camera relocalization is an important problem in computer vision and robotics. Recent works utilize convolutional neural networks (CNNs) to regress for pixels in a query image their corresponding 3D world coordinates in the scene. The final pose is then solved via a RANSAC-based optimization scheme using the predicted coordinates. Usually, the CNN is trained with ground truth scene coordinates, but it has also been shown that the network can discover 3D scene geometry automatically by minimizing single-view reprojection loss. However, due to the deficiencies of the reprojection loss, the network needs to be carefully initialized. In this paper, we present a new angle-based reprojection loss, which resolves the issues of the original reprojection loss. With this new loss function, the network can be trained without careful initialization, and the system achieves more accurate results. The new loss also enables us to utilize available multi-view constraints, which further improve performance.Comment: ECCV 2018 Workshop (Geometry Meets Deep Learning

A Review of Object Detection Models based on Convolutional Neural Network

Convolutional Neural Network (CNN) has become the state-of-the-art for object detection in image task. In this chapter, we have explained different state-of-the-art CNN based object detection models. We have made this review with categorization those detection models according to two different approaches: two-stage approach and one-stage approach. Through this chapter, it has shown advancements in object detection models from R-CNN to latest RefineDet. It has also discussed the model description and training details of each model. Here, we have also drawn a comparison among those models.Comment: 17 pages, 11 figures, 1 tabl

Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data

This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data. SDF starts from superpixel segmentation, which effectively captures prior information of feature appearances. The feature appearances are beneficial to reduce the computational complexity for deterministic fitting methods. SDF also includes two original elements, i.e., a deterministic sampling algorithm and a novel model selection algorithm. The two algorithms are tightly coupled to boost the performance of SDF in both speed and accuracy. Specifically, the proposed sampling algorithm leverages the grouping cues of superpixels to generate reliable and consistent hypotheses. The proposed model selection algorithm further makes use of desirable properties of the generated hypotheses, to improve the conventional fit-and-remove framework for more efficient and effective performance. The key characteristic of SDF is that it can efficiently and deterministically estimate the parameters of model instances in multi-structure data. Experimental results demonstrate that the proposed SDF shows superiority over several state-of-the-art fitting methods for real images with single-structure and multiple-structure data.Comment: Accepted by European Conference on Computer Vision (ECCV

Crystallographic Studies of Iodide-Containing Quasi-One-Dimensional Conductors

The crystal structures of three iodide-containing quasi-one-dimensional conductors, (tetrathiotetracene)2(iodide)3 (high disorder), tetrathiotetracene-iodide, and (hexamethylenetetraselenofulvalene)-(iodide)x were solved by single crystal X-ray diffraction methods. These three iodides are single charge-carrier conductors and allow a comparison of such competing effects as disorder, interchain coupling, and overlap. The crystal structure of metallic (tetrathiotetracene)2(iodide)3 (high disorder), TTT2I3 (h.d.), was solved at room temperature (~294° K), 164° K, 74° K, and at 19° K. At all four temperatures the lattice symmetry remained orthorhombic and the structures were successfully refined in the space group Cmca. During slow cooling the diffuse layer lines were also carefully monitored. In contrast to TTFC10.67, even with slow cooling the iodide chains do not three-dimensionally order, and there are no distortions in the TTT lattice to 19° K. A model of the iodide chains is presented which explains the positions and intensities of the diffuse layer lines and also explains why three-dimensional ordering at low temperatures is not observed. The structure of semiconducting tetrathiotetracene-iodide (TTTI) was studied at room temperature. The structure consists of two ordered lattices which are incommensurate along →c, the stacking axis. The unit cell dimensions for Lattice 1 (triclinic, C-l) are a = 13.028(2), b = 16.445(2), c = 3.643(1) Å and α = 90.81(1)°, β = 96.11(1)°, and γ = 91 .11(1)°. For Lattice 2, c ≃ 4.78 Å. The positions of all of the layer lines, including the two “sixth” layer lines, which are observed on X-ray oscillation photographs of crystals of TTTI rotated about →c, can be explained by the presence of two lattices. The measured density dm ≃ 2.09 g/cm3 and refinement of the [001] projection (hk0 reflections) confirmed that the overall stoichiometry is TTTI (1:1). For a complete data set collected with copper Kα radiation, the refinement of Lattice 1 converged to R = 0.102. For the 1132 reflections with Fo2 > 3σ(Fo2), R = 0.081. The overlap between adjacent TTT cations in the same stack in TTTI is significantly different from that observed in TTT2I3 (h.d.). There is also very little interchain coupling in TTTI. Hexamethylenetetraselenofulvalene-iodide, HMTSF-Ix, is triclinic, P-l, with the unit cell parameters a = 8.056(4), b = 12.740(4), c = 8.016(3) Å and α = 81.72(4)°, β = 67.73(5)°, and γ = 102.64(4)°. For a complete data set of 4213 reflections collected with monochromatized molybdenum Kα radiation to 2θ = 60° the structure refined to R = 0.097. For 2042 reflections with Fo2 > 3σ(Fo2), R = 0.051. The hydrogen atoms were not located. There is disordered iodide and solvent at 1/2,1/2,1/2. The HMTSF cations stack along →a. A new type of alternating overlap between adjacent HMTSF molecules was observed. The magnitude of the d.c. electrical conductivity at room temperature suggests that this phase of HMTSF-Ix is semiconducting. These iodide-containing structures show three different types of iodide behavior in quasi-one-dimensional conductors. In TTT2I3 (h.d.) the slip-stacking and large interchain coupling favor formation of a metallic state at high temperatures. At low temperatures the disordered iodide chains have a major effect on the transport properties by allowing states to exist in the semiconductor band gap. In TTTI the iodides are no longer disordered but still dominate the physical properties by causing a modulation of the TTT lattice. There is very little interchain coupling in TTTI. In HMTSF-Ix the iodide is probably of minor importance.</p

Rectification from Radially-Distorted Scales

This paper introduces the first minimal solvers that jointly estimate lens distortion and affine rectification from repetitions of rigidly transformed coplanar local features. The proposed solvers incorporate lens distortion into the camera model and extend accurate rectification to wide-angle images that contain nearly any type of coplanar repeated content. We demonstrate a principled approach to generating stable minimal solvers by the Grobner basis method, which is accomplished by sampling feasible monomial bases to maximize numerical stability. Synthetic and real-image experiments confirm that the solvers give accurate rectifications from noisy measurements when used in a RANSAC-based estimator. The proposed solvers demonstrate superior robustness to noise compared to the state-of-the-art. The solvers work on scenes without straight lines and, in general, relax the strong assumptions on scene content made by the state-of-the-art. Accurate rectifications on imagery that was taken with narrow focal length to near fish-eye lenses demonstrate the wide applicability of the proposed method. The method is fully automated, and the code is publicly available at https://github.com/prittjam/repeats.Comment: pre-prin

Entanglement in holographic dark energy models

We study a process of equilibration of holographic dark energy (HDE) with the cosmic horizon around the dark-energy dominated epoch. This process is characterized by a huge amount of information conveyed across the horizon, filling thereby a large gap in entropy between the system on the brink of experiencing a sudden collapse to a black hole and the black hole itself. At the same time, even in the absence of interaction between dark matter and dark energy, such a process marks a strong jump in the entanglement entropy, measuring the quantum-mechanical correlations between the horizon and its interior. Although the effective quantum field theory (QFT) with a peculiar relationship between the UV and IR cutoffs, a framework underlying all HDE models, may formally account for such a huge shift in the number of distinct quantum states, we show that the scope of such a framework becomes tremendously restricted, devoiding it virtually any application in other cosmological epochs or particle-physics phenomena. The problem of negative entropies for the non-phantom stuff is also discussed.Comment: 10 pages, version to appear in PL

The expression of CD23 in cutaneous non-lymphoid neoplasms

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73682/1/j.1600-0560.2006.00685.x.pd

Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes

In this paper we address the problem of multiple camera calibration in the presence of a homogeneous scene, and without the possibility of employing calibration object based methods. The proposed solution exploits salient features present in a larger field of view, but instead of employing active vision we replace the cameras with stereo rigs featuring a long focal analysis camera, as well as a short focal registration camera. Thus, we are able to propose an accurate solution which does not require intrinsic variation models as in the case of zooming cameras. Moreover, the availability of the two views simultaneously in each rig allows for pose re-estimation between rigs as often as necessary. The algorithm has been successfully validated in an indoor setting, as well as on a difficult scene featuring a highly dense pilgrim crowd in Makkah.Comment: 13 pages, 6 figures, submitted to Machine Vision and Application