Artifact-free coronary magnetic resonance angiography and coronary vessel wall imaging in the presence of a new, metallic, coronary magnetic resonance imaging stent.

BACKGROUND: Coronary in-stent restenosis cannot be directly assessed by magnetic resonance angiography (MRA) because of the local signal void of currently used stainless steel stents. The aim of this study was to investigate the potential of a new, dedicated, coronary MR imaging (MRI) stent for artifact-free, coronary MRA and in-stent lumen and vessel wall visualization. METHODS AND RESULTS: Fifteen prototype stents were deployed in coronary arteries of 15 healthy swine and investigated with a double-oblique, navigator-gated, free-breathing, T2-prepared, 3D cartesian gradient-echo sequence; a T2-prepared, 3D spiral gradient-echo sequence; and a T2-prepared, 3D steady-state, free-precession coronary MRA sequence. Furthermore, black-blood vessel wall imaging by a dual-inversion-recovery, turbo spin-echo sequence was performed. Artifacts of the stented vessel segment and signal intensities of the coronary vessel lumen inside and outside the stent were assessed. With all investigated sequences, the vessel lumen and wall could be visualized without artifacts, including the stented vessel segment. No signal intensity alterations inside the stent when compared with the vessel lumen outside the stent were found. CONCLUSIONS: The new, coronary MRI stent allows for completely artifact-free coronary MRA and vessel wall imaging.

Natural classification of knots

The principal objective of the knot theory is to provide a simple way of classifying and ordering all the knot types. Here, we propose a natural classification of knots based on their intrinsic position in the knot space that is defined by the set of knots to which a given knot can be converted by individual intersegmental passages. In addition, we characterize various knots using a set of simple quantum numbers that can be determined upon inspection of minimal crossing diagram of a knot. These numbers include: crossing number; average three-dimensional writhe; number of topological domains; and the average relaxation value

AWSum-Combining Classification with Knowledge Aquisition

Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the^way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whilst providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.

The extended GLUT-family of sugar/polyol transport facilitators: nomenclature, sequence characteristics, and potential function of its novel members (review).

During the last 2 years, several novel genes that encode glucose transporter-like proteins have been identified and characterized. Because of their sequence similarity with GLUT1, these genes appear to belong to the family of solute carriers 2A (SLC2A, protein symbol GLUT). Sequence comparisons of all 13 family members allow the definition of characteristic sugar/polyol transporter signatures: (1) the presence of 12 membrane-spanning helices, (2) seven conserved glycine residues in the helices, (3) several basic and acidic residues at the intracellular surface of the proteins, (4) two conserved tryptophan residues, and (5) two conserved tyrosine residues. On the basis of sequence similarities and characteristic elements, the extended GLUT family can be divided into three subfamilies, namely class I (the previously known glucose transporters GLUT1-4), class II (the previously known fructose transporter GLUT5, the GLUT7, GLUT9 and GLUT11), and class III (GLUT6, 8, 10, 12, and the myo-inositol transporter HMIT1). Functional characteristics have been reported for some of the novel GLUTs. Like GLUT1-4, they exhibit a tissue/cell-specific expression (GLUT6, leukocytes, brain; GLUT8, testis, blastocysts, brain, muscle, adipocytes; GLUT9, liver, kidney; GLUT10, liver, pancreas; GLUT11, heart, skeletal muscle). GLUT6 and GLUT8 appear to be regulated by sub-cellular redistribution, because they are targeted to intra-cellular compartments by dileucine motifs in a dynamin dependent manner. Sugar transport has been reported for GLUT6, 8, and 11; HMIT1 has been shown to be a H+/myo-inositol co-transporter. Thus, the members of the extended GLUT family exhibit a surprisingly diverse substrate specificity, and the definition of sequence elements determining this substrate specificity will require a full functional characterization of all members.

International Union of Pharmacology. XXXV. The glucagon receptor family.

Peptide hormones within the secretin-glucagon family are expressed in endocrine cells of the pancreas and gastrointestinal epithelium and in specialized neurons in the brain, and subserve multiple biological functions, including regulation of growth, nutrient intake, and transit within the gut, and digestion, energy absorption, and energy assimilation. Glucagon, glucagon-like peptide-1, glucagon-like peptide-2, glucose-dependent insulinotropic peptide, growth hormone-releasing hormone and secretin are structurally related peptides that exert their actions through unique members of a structurally related G protein-coupled receptor class 2 family. This review discusses advances in our understanding of how these peptides exert their biological activities, with a focus on the biological actions and structural features of the cognate receptors. The receptors have been named after their parent and only physiologically relevant ligand, in line with the recommendations of the International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC-IUPHAR).

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Minimal data requirements for a continuous monitoring of the quality of care using the DRG classification.

The DRG classification provides a useful tool for the evaluation of hospital care. Indicators such as readmissions and mortality rates adjusted for the hospital Casemix could be adopted in Switzerland at the price of minor additions to the hospital discharge record. The additional information required to build patients histories and to identify the deaths occurring after hospital discharge is detailed.

Intrinsically photosensitive retinal ganglion cells: classification, function and clinical implications.

PURPOSE OF REVIEW: The discovery of a new class of intrinsically photosensitive retinal ganglion cells (ipRGCs) revealed their superior role for various nonvisual biological functions, including the pupil light reflex, and circadian photoentrainment. RECENT FINDINGS: Recent works have identified and characterized several anatomically and functionally distinct ipRGC subtypes and have added strong new evidence for the accessory role of ipRGCs in the visual system in humans. SUMMARY: This review summarizes current concepts related to ipRGC morphology, central connections and behavioural functions and highlights recent studies having clinical relevance to ipRGCs. Clinical implications of the melanopsin system are widespread, particularly as related to chronobiology.

Une nouvelle Classification des néoptasies intraépithélates vulvaires [A new classification of vulvar intraepithelial neoplasia (VIN)]

Vulvar cancer is a rare disease and its screening is depending on the quality and the relevance of our clinical examination. Incidence of vulvar cancer and especially precancerous lesions, vulvar intraepithelial neoplasias (VIN), increased during these last years. The new terminology of vulvar intraepithelial neoplasia will help us to identify high risk groups which could develop a cancer: usual and differentiated VIN. An early diagnosis is essential to propose an adequate treatment. Management is a major point according to the rising incidence of these lesions in younger women. Until we can observe a benefit from the vaccination against human papillomavirus, we must increase the quality of screening by a careful examination of the vulva.

What animals can teach clinicians about the hippocampus

Abnormalities in hippocampal structure and function have been reported in a number of human neuropathological and neurodevelopmental disorders, including Alzheimer's disease, autism spectrum disorders, Down syndrome, epilepsy, and schizophrenia. Given the complexity of these disorders, animal studies are invaluable and remain to date irreplaceable, providing fundamental knowledge regarding the basic mechanisms underlying normal and pathological human brain structure and function. However, there is a prominent ill-conceived view in current research that scientists should be restricted to using animal models of human diseases that can lead to results applicable to humans within a few years. Although there is no doubt that translational studies of this kind are important and necessary, limiting animal studies to applicable questions is counterproductive and will ultimately lead to a lack of knowledge and an inability to address human health problems. Here, we discuss findings regarding the normal postnatal development of the monkey hippocampal formation, which provide an essential framework to consider the etiologies of different neuropathological disorders affecting human hippocampal structure and function. We focus on studies of gene expression in distinct hippocampal regions that shed light on some basic mechanisms that might contribute to the etiology of schizophrenia. We argue that researchers, as well as clinicians, should not consider the use of animals in research only as 'animal models' of human diseases, as they will continue to need and benefit from a better understanding of the normal structure and functions of the hippocampus in 'model animals'.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.