75 research outputs found

    A mission management system for a fleet of gliders

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    International audienceThe objective of AGLIMMS project, whose acronym stands for Acoustic GLIders Mission Management System, is to efficiently coordinate a fleet of underwater gliders whose missions are to obtain physical, chemical, biological and/or acoustic measurements on a large 3D sea area. This paper describes planning and supervision functions under development and their integration in a global centralised architecture. A demonstration with three SeaExplorer from Alseamar is planned late 2019

    PET/CT in Inflammatory and Auto-immune Disorders:Focus on Several Key Molecular Concepts, FDG, and Radiolabeled Probe Perspectives

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    Chronic immune diseases mainly include autoimmune and inflammatory diseases. Managing chronic inflammatory and autoimmune diseases has become a significant public health concern, and therapeutic advancements over the past 50 years have been substantial. As therapeutic tools continue to multiply, the challenge now lies in providing each patient with personalized care tailored to the specifics of their condition, ushering in the era of personalized medicine. Precise and holistic imaging is essential in this context to comprehensively map the inflammatory processes in each patient, identify prognostic factors, and monitor treatment responses and complications. Imaging of patients with inflammatory and autoimmune diseases must provide a comprehensive view of the body, enabling the whole-body mapping of systemic involvement. It should identify key cellular players in the pathology, involving both innate immunity (dendritic cells, macrophages), adaptive immunity (lymphocytes), and microenvironmental cells (stromal cells, tissue cells). As a highly sensitive imaging tool with vectorized molecular probe capabilities, PET/CT can be of high relevance in the management of numerous inflammatory and autoimmune diseases. Relying on key molecular concepts of immunity, the clinical usefulness of FDG-PET/CT in several relevant inflammatory and immune-inflammatory conditions, validated or emerging, will be discussed in this review, together with radiolabeled probe perspectives.</p

    A Glider-Compatible Optical Sensor for the Detection of Polycyclic Aromatic Hydrocarbons in the Marine Environment

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    This study presents the MiniFluo-UV, an ocean glider-compatible fluorescence sensor that targets the detection of polycyclic aromatic hydrocarbons (PAHs) in the marine environment. Two MiniFluos can be installed on a glider, each equipped with two optical channels (one PAH is measured per channel). This setup allows the measurement of up to 4 different fluorescent PAHs: Naphthalene, Phenanthrene, Fluorene and Pyrene. Laboratory tests on oil products (Maya crude oil and Diesel fuel) as well as on marine samples near industrial areas (urban harbor and offshore installations) revealed that the concentration of the four PAHs targeted accounted for 62–97% of the total PAH concentration found in samples (∑16 PAHs determined by standard international protocols). Laboratory tests also revealed that for marine applications, the calibration on Water Accommodated Fraction (WAF) of crude oil is more appropriate than the one on pure standards (STD). This is because PAH fluorescence is constituted in large part of alkylated compounds that are not considered with STD calibration. Results from three glider deployments with increasing levels of complexity (a laboratory trial, a field mission in non-autonomous mode and a fully autonomous mission) are also presented. During field deployments, the MiniFluo-glider package was able to detect concentration gradients from offshore marine waters toward the head of a Mediterranean harbor (&lt; 80 ng L−1) as well as hydrocarbon patches at the surface waters of an oil and gas exploitation field in the North Sea (&lt; 200 ng L−1, mainly Naphthalene). It is suggested that using only the WAF calibration, the concentration derived with the MiniFluo agrees within one order of magnitude with the concentration determined by Gas Chromatography coupled with Mass Spectrometry (overestimation by a factor 7 on average). These performances can be improved if the calibration is made with a WAF with PAH proportions similar to the one find in the environment. Finally, it is shown that the use of in situ calibration on water samples collected during the glider deployment, when possible, gives the best results

    IntĂ©gration dynamique TEP-IRM pour une nouvelle approche multiparamĂ©trique de l’hĂ©tĂ©rogĂ©nĂ©itĂ© tumorale dans le cancer bronchique non Ă  petites cellules (CBNPC)

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    Tumor heterogeneity is an important factor of progression and resistance to treatment. Multiparametric PET-MRI imaging offers unique opportunities to characterize biological cellular processes, but has never been evaluated at the regional level in Non-Small Cell Lung Cancer (NSCLC), the leading cause of oncological death. A simultaneous dynamic multiparametric 18F-FDG PET-MRI approach has been developed to this end. This approach required the “in-house” implementation of the reference absolute PET quantitative method of glucose metabolism (Sokoloff's tri-compartmental model); the development of a method for correcting geometric distortions in diffusion weighted imaging, validated on phantom and clinically tested; the phantom validation of quantitative MRI methods (T1/T2 relaxometry), also clinically tested; and the "in-house" implementation of the Tofts compartmental model (extended version) for the evaluation of tumor vascularization by dynamic perfusion MRI. The results of our work, performed at the regional intra-tumor level, illustrate the heterogeneity of the regional interlinks between glucose metabolism and vascularization in NSCLC, two fundamental biological hallmarks of tumor progression, and show that an unsupervised tumor partitioning by Gaussian mixture model, integrating all the PET-MRI biomarkers of this project, individualizes 3 types of supervoxels, whose biological signature can be predicted with 97% accuracy by 4 dominant PET-MRI biomarkers, revealed by metaheuristic machine learning methods.L'hĂ©tĂ©rogĂ©nĂ©itĂ© tumorale est un facteur important de progression et de rĂ©sistance au traitement. L'imagerie multiparamĂ©trique TEP-IRM offre des opportunitĂ©s uniques de caractĂ©risation biologique cellulaire, mais n’a jamais Ă©tĂ© Ă©valuĂ© Ă  l’échelle rĂ©gionale intra-tumorale dans le cancer du poumon non Ă  petites cellules (CBNPC), premiĂšre cause de dĂ©cĂšs oncologique. Une approche multiparamĂ©trique dynamique simultanĂ©e TEP-IRM au 18F-FDG a Ă©tĂ© dĂ©veloppĂ©e en ce sens. Cette approche a nĂ©cessitĂ© l’implĂ©mentation « maison » de la mĂ©thode de rĂ©fĂ©rence de quantification TEP du mĂ©tabolisme glucidique (modĂšle tri-compartimental de Sokoloff); le dĂ©veloppement d’une mĂ©thode de correction inĂ©dite des distorsions gĂ©omĂ©triques en imagerie de diffusion, validĂ©e sur fantĂŽme et testĂ©e cliniquement ; la validation sur fantĂŽme de mĂ©thodes d’IRM quantitative (relaxomĂ©trie T1/T2), Ă©galement testĂ©es cliniquement; et l’implĂ©mentation « maison » du modĂšle compartimental de Tofts (version Ă©tendue) pour l’évaluation de la vascularisation tumorale en IRM dynamique de perfusion. Les rĂ©sultats de nos travaux expĂ©rimentaux effectuĂ©s Ă  l’échelle intra-tumorale rĂ©gionale illustrent l’hĂ©tĂ©rogĂ©nĂ©itĂ© des rapports entre mĂ©tabolisme glucidique et vascularisation dans le CBNPC, deux caractĂ©ristiques biologiques fondamentales de progression tumorale, et montrent qu’un partitionnement tumoral non supervisĂ© par modĂšle de mĂ©lange gaussien, intĂ©grant l’ensemble des biomarqueurs TEP-IRM de ce projet, individualise 3 types de supervoxels, dont la signature biologique peut ĂȘtre prĂ©dite avec une exactitude de 97% par 4 biomarqueurs TEP-IRM dominants, rĂ©vĂ©lĂ©s par mĂ©thodes mĂ©taheuristiques d'apprentissage machine

    Confusion de Type en C++: État de l'Art et DifficultĂ©s de DĂ©tection

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    National audienceLe langage C++ s'est imposĂ© comme une rĂ©fĂ©rence dans les domaines oĂč la modularitĂ© du dĂ©veloppement ne doit pas empiĂ©ter sur les performances du logiciel final. Les principaux navigateurs, les interprĂ©teurs et mĂȘme certaines parties du systĂšme d'exploitation de Microsoft utilisent le langage C++.L'Ă©tude des bases de donnĂ©es de vulnĂ©rabilitĂ©s montre que ces logiciels sont sujets Ă  une catĂ©gorie de vulnĂ©rabilitĂ©s particuliĂšres, les confusions de type, qui sont tout aussi exploitables que les vulnĂ©rabilitĂ©s plus connues.Cet article prĂ©sente les mĂ©canismes Ă  l'origine des confusions de type et dresse un Ă©tat de l'art des mĂ©thodes servant Ă  les dĂ©tecter dans du code source ou du binaire seul. Il met aussi en avant les principales difficultĂ©s que rencontrent les analyses de binaire, et propose les grandes lignes d'une nouvelle approche pour dĂ©tecter des confusions de type dans du binaire

    PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology

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    PET/CT molecular imaging has been imposed in clinical oncological practice over the past 20 years, driven by its two well-grounded foundations: quantification and radiolabeled molecular probe vectorization. From basic visual interpretation to more sophisticated full kinetic modeling, PET technology provides a unique opportunity to characterize various biological processes with different levels of analysis. In clinical practice, many efforts have been made during the last two decades to standardize image analyses at the international level, but advanced metrics are still under use in practice. In parallel, the integration of PET imaging with radionuclide therapy, also known as radiolabeled theranostics, has paved the way towards highly sensitive radionuclide-based precision medicine, with major breakthroughs emerging in neuroendocrine tumors and prostate cancer. PET imaging of tumor immunity and beyond is also emerging, emphasizing the unique capabilities of PET molecular imaging to constantly adapt to emerging oncological challenges. However, these new horizons face the growing complexity of multidimensional data. In the era of precision medicine, statistical and computer sciences are currently revolutionizing image-based decision making, paving the way for more holistic cancer molecular imaging analyses at the whole-body level
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