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The Allergenic Structure of the Thaumatinlike Protein Ole e 13 Is Degraded by Processing of Raw Olive Fruits

Background: The thaumatin-like protein (TLP) Ole e 13 in raw olive fruit is responsible for occupational allergy in olive oil mill workers. However,these workers do not experience allergic symptoms after ingestion of edible olive.Objectives: To analyze the presence of IgE-reactive TLP in raw and edible olive fruit and to assess the allergenic potency of both sources.Methods: The content of TLP in raw and edible olive fruit protein extracts was analyzed using immunoblotting with sera from allergic patients and with olive TLP–specific IgG. The structural and immunological stability of TLP were assayed using immunoblotting after treatment of both raw olive and purified TLP with 0.25 M NaOH solution for 24 hours. Olive pollen extract was investigated by immunoblotting for TLP content. Results: The TLP contained in raw olive fruit was not present in edible olives as a result of maceration before human consumption. No TLP was detected in olive pollen using specific IgG or sera from patients allergic to olive fruit. Sera from patients allergic to olive pollen did not react with purified TLP. Conclusions: IgE-reactive TLP is not present in edible olive, thus explaining the low number of patients allergic to this highly consumed fruit. Patients allergic to olive pollen are not sensitized to TLP and, therefore, not expected to be at risk of food allergy to olive fruit or TLP plant source

Segmentación automática de estudios PET cardíacos con ¹³NH_3 basada en correlación iterativa

Actas de: XXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica (CASEIB 2010). Madrid, 24-26 de noviembre de 2010.La obtención de la función de entrada en estudios dinámicos de corazón a partir de la imagen PET se realiza habitualmente mediante la selección previa de una región de interés (ROI) o utilizando procedimientos de análisis factorial para encontrar aquellas curvas actividad/tiempo que mejor se adaptan a la función de entrada. En este trabajo se presenta un método novedoso de segmentación automática y obtención de la función de entrada que utiliza mapas de correlación calculados sobre estudios dinámicos que emplean ¹³NH_3 como trazador. Partiendo de un modelo analítico inicial, se buscan las curvas temporales más parecidas en el estudio real empleando la correlación. Tomando como datos estas curvas se calculan nuevos modelos con los que realizar sucesivas iteraciones. El resultado final es tanto una segmentación automática como la curva de actividad/tiempo de cada región segmentada.Ministerio de Ciencia e Innovación, TEC2007-64731, TEC 2008-06715-C02-1, la RETIC-RECAVA del Ministerio de Sanidad y Consumo, y el programa ARTEMIS S2009/DPI-1802 de la Comunidad de Madrid.Publicad

Iterative Automatic Segmentation in cardiac PET based on TAC correlation: preliminary results

Proceeding of: 2010 IEEE Nuclear Science Symposium, Medical Imaging Conference and 17th Room Temperature Semiconductor Detector Workshop (IEEE), Knoxville, Tennessee, USA, October 30 - November 6, 2010Conventional kinetic parameter estimation based on compartmental models requires an accurate estimation of arterial blood input function. To avoid invasive blood sampling, an image-derived input function can be obtained by manually defining a Region of Interest. Here we propose a new and simple, iterative method for automatic segmentation and input function calculation of PET cardiac studies using correlation as a distance metric between a priori information regarding the approximate shape of the final time-activity curve (TAC) and the actual TAC extracted from the image temporal series.This work was supported in part by the CENIT-AMIT Ingenio 2010, Ministerio de Ciencia e Innovación, TEC2007-64731, TEC 2008-06715-C02-1, RETIC-RECAVA, Ministerio de Sanidad y Consumo, and the ARTEMIS de la Comunidad de Madrid (S2009/DPI-1802) programsPublicad

A note on optimal transient growth in turbulent channel flows

International audienceWe compute the optimal transient growth of perturbations sustained by a turbulent channel flow following the same approach recently used by del Álamo and Jiménez [J. Fluid Mech.559, 205 (2006)]. Contrary to this previous analysis, we use generalized Orr-Sommerfeld and Squire operators consistent with previous investigations of mean flows with variable viscosity. The optimal perturbations are streamwise vortices evolving into streamwise streaks. In accordance with del Álamo and Jiménez, it is found that for very elongated structures and for sufficiently large Reynolds numbers, the optimal energy growth presents a primary peak in the spanwise wavelength, scaling in outer units, and a secondary peak scaling in inner units and corresponding to λ+z≈100. Contrary to the previous results, however, it is found that the maximum energy growth associated with the primary peak increases with the Reynolds number. This growth, in a first approximation, scales linearly with an effective Reynolds number based on the centerline velocity, the channel half width and the maximum eddyviscosity associated. The optimal streaks associated with the primary peak have an optimal spacing of λz=4h and scale in outer units in the outer region and in wall units in the near wall region, where they still have up to 50% of their maximum amplitude near y+=10. © 2009 American Institute of Physics

jClustering, an open framework for the development of 4D clustering algorithms

We present jClustering, an open framework for the design of clustering algorithms in dynamic medical imaging. We developed this tool because of the difficulty involved in manually segmenting dynamic PET images and the lack of availability of source code for published segmentation algorithms. Providing an easily extensible open tool encourages publication of source code to facilitate the process of comparing algorithms and provide interested third parties with the opportunity to review code. The internal structure of the framework allows an external developer to implement new algorithms easily and quickly, focusing only on the particulars of the method being implemented and not on image data handling and preprocessing. This tool has been coded in Java and is presented as an ImageJ plugin in order to take advantage of all the functionalities offered by this imaging analysis platform. Both binary packages and source code have been published, the latter under a free software license (GNU General Public License) to allow modification if necessary.Funded by TEC2011-28972-C02-01, Ministerio de Ciencia e Innovación, CEN-20101014; Programa CENIT-CDTI, Ministerio de Ciencia e Innovación; S2009/DPI-1802 (ARTEMIS), Comunidad de Madrid. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Publicad

Agency theory: Forecasting agent remuneration at insurance companies

The principal–agent problem occurs when one entity (the ‘‘agent’’), is able to make decisions and/or take actions on behalf of another person or entity (the ‘‘principal’’). The agent earnings are regulated under a contract designed by the principal. Under the principal’s point of view, the main goal while designing said contract (and the payment rules incorporated on it) is to align the actions made by the agent to the principal’s own goals. So, in this paper we will define a method that will allow the principal to forecast the remuneration obtained by the agent under an established contract in the insurance sector

Source identification for mobile devices, based on wavelet transforms combined with sensor imperfections

One of the most relevant applications of digital image forensics is to accurately identify the device used for taking a given set of images, a problem called source identification. This paper studies recent developments in the field and proposes the mixture of two techniques (Sensor Imperfections and Wavelet Transforms) to get better source identification of images generated with mobile devices. Our results show that Sensor Imperfections and Wavelet Transforms can jointly serve as good forensic features to help trace the source camera of images produced by mobile phones. Furthermore, the model proposed here can also determine with high precision both the brand and model of the device