Discovery and characterization of two types of liver-expressed antimicrobial peptide 2 (LEAP-2) genes in rainbow trout

The sequences and gene organisation of two LEAP-2 molecules (LEAP-2A and LEAP-2B) from rainbow trout, Oncorhynchus mykiss are presented. Both genes consist of a 3 exon/2 intron structure, with exon sizes comparable to known mammalian genes. LEAP-2A notably differs from LEAP-2B in having larger introns and a larger 3'UTR. The predicted proteins contain a signal peptide and prodomain, followed by a mature peptide of 41 aa containing four conserved cysteines. The RXXR cleavage site to release the mature peptide was also conserved. Both genes were found to be constitutively expressed in the liver, with expression in the intestine, and to a lesser extent the skin, evident after bacterial challenge. (C) 2004 Elsevier B.V. All rights reserved.

Respiratory syncytial virus (RSV) vaccines - Two steps back for one leap forward

Respiratory viruses are among the most important causes of morbidity and mortality worldwide. From a vaccine viewpoint, such viruses may be divided into two principle groups-those where infection results in long-term immunity and whose continued survival requires constant mutation, and those where infection induces incomplete immunity and repeated infections are common, even with little or no mutation. Influenza virus and respiratory syncytial virus (RSV) typify the former and latter groups, respectively. Importantly, successful vaccines have been developed against influenza virus. However, this is not the case for RSV, despite many decades of research and several vaccine approaches. Similar to natural infection, the principle limitation of candidate RSV vaccines in humans is limited immunogenicity, characterised in part by short-term RSV-specific adaptive immunity. The specific reasons why natural RSV infection is insufficiently immunogenic in humans are unknown but circumvention of innate and adaptive immune responses are likely causes. Fundamental questions concerning RSV/host interactions remain to be addressed at both the innate and adaptive immune levels in humans in order to elucidate mechanisms of immune response circumvention. Taking the necessary steps back to generate such knowledge will provide the means to leap forward in our quest for a successful RSV vaccine. Recent developments relating to some of these questions are discussed. (C) 2007 Elsevier B.V. All rights reserved.

Dolphins leap lampposts.

Antología de poemas. Cuenta con la mejor obra de tres poetas: Ian Souter, Eric Finney y Dave Calder.

All maximal-pairs in step-leap representation of melodic sequence

This paper proposes an efficient pattern extraction algorithm that can be applied on melodic sequences that are represented as strings of abstract intervallic symbols; the melodic representation introduces special “binary don’t care” symbols for intervals that may belong to two partially overlapping intervallic categories. As a special case the well established “step–leap” representation is examined. In the step–leap representation, each melodic diatonic interval is classified as a step (±s), a leap (±l) or a unison (u). Binary don’t care symbols are used to represent the possible overlapping between the various abstract categories e.g. *=s, *=l and #=-s, #=-l. We propose an O(n+d(n-d)+z)-time algorithm for computing all maximal-pairs in a given sequence x=x[1..n], where x contains d occurrences of binary don’t cares and z is the number of reported maximal-pairs.

All maximal-pairs in step-leap representation of melodic sequence

This paper proposes an efficient pattern extraction algorithm that can be applied on melodic sequences that are represented as strings of abstract intervallic symbols; the melodic representation introduces special “binary don’t care” symbols for intervals that may belong to two partially overlapping intervallic categories. As a special case the well established “step–leap” representation is examined. In the step–leap representation, each melodic diatonic interval is classified as a step (±s), a leap (±l) or a unison (u). Binary don’t care symbols are used to represent the possible overlapping between the various abstract categories e.g. *=s, *=l and #=-s, #=-l. We propose an O(n+d(n-d)+z)-time algorithm for computing all maximal-pairs in a given sequence x=x[1..n], where x contains d occurrences of binary don’t cares and z is the number of reported maximal-pairs.

One small scan for radiology, one giant leap for forensic medicine - Post-mortem imaging replaces forensic autopsy in a case of traumatic aortic laceration

The questions of cause and manner of death are the most pressing ones in any forensic investigation. Traditionally, autopsy is the means to provide answers to these questions and despite the increasing use of CT and MR in the post-mortem setting, imaging has usually been an adjunct to forensic autopsy. Here we describe a case where post-mortem CT and MR were performed instead of autopsy, at the request of the responsible public prosecutor. The forensic conclusions derived from imaging, including cause and manner of death were accepted by the legal authorities, thereby setting precedence for future cases. This case represents a landmark in forensic medicine and is another step toward the full realization of minimally invasive forensic autopsy.

Desarrollo de un prototipo usando como dispositivo de interacción Leap Motion

Leap Motion [1] es un pequeño dispositivo que se coloca frente al monitor, conectado mediante un cable USB al ordenador, capaz de capturar los movimientos de nuestras manos y dedos con alta precisión, además de algunos objetos como pinceles o bolígrafos. El objetivo principal de este trabajo es evaluar las capacidades de este dispositivo y crear un prototipo que sea capaz de grabar y reconocer gestos para que pueda ser fácilmente integrado a cualquier aplicación. Para ello, el prototipo consta de 2 funciones principales: Grabar un movimiento: en el que recojo los datos que nos ofrece el Leap Motion, los proceso y los guardo en un formato específico. Reconocer un gesto: en el que comparo en cada momento el gesto que se está realizando con los gestos grabados mediante un algoritmo que detectara si son similares o no. Este es un resumen básico del prototipo, sin embargo debemos tener en cuenta una serie de requisitos y parámetros para hacerlo más eficiente y personalizable dependiendo de las necesidades del usuario. ---ABSTRACT---Leap Motion [1] is a small device we place in front of the display unit, connected to a USB cable to the computer. It is able to capture the motion of our hands and fingers with high accuracy, as well as some objects such as pens and brushes. This project's main goal is to evaluate the proficiency of the device, and create a prototype that is able to record and recognize gestures in order for it to be easily integrated into any application. For that, the prototype has 2 main functions: Recording a motion: in which I collect the data offered by the Leap Motion, process it and keep it in a specific format. Recognizing a gesture: in which I compare each time the gesture being made with the gestures recorded using an algorithm to detect whether they are similar or not. This is a basic summary of the prototype, but we need to take into consideration a number of requirements and parameters to make it more efficient and customizable depending on the user's needs.

Vista del salto de Chulilla [Material gráfico] = Vue du saut de Chulilla = View of the leap of Chulilla

Datos de publicación tomados de la obra a la que pertenece

Study and analysis of the Leap Motion sensor and the Software Development Kit (SDK) for the implementation of visual Human Computer Interfaces

En este proyecto, se presenta un informe técnico sobre la cámara Leap Motion y el Software Development Kit correspondiente, el cual es un dispositivo con una cámara de profundidad orientada a interfaces hombre-máquina. Esto es realizado con el propósito de desarrollar una interfaz hombre-máquina basada en un sistema de reconocimiento de gestos de manos. Después de un exhaustivo estudio de la cámara Leap Motion, se han realizado diversos programas de ejemplo con la intención de verificar las capacidades descritas en el informe técnico, poniendo a prueba la Application Programming Interface y evaluando la precisión de las diferentes medidas obtenidas sobre los datos de la cámara. Finalmente, se desarrolla un prototipo de un sistema de reconocimiento de gestos. Los datos sobre la posición y orientación de la punta de los dedos obtenidos de la Leap Motion son usados para describir un gesto mediante un vector descriptor, el cual es enviado a una Máquina Vectores Soporte, utilizada como clasificador multi-clase.