A comparison of the alr and ilr transformations for kernel density estimation of compositional data

In a seminal paper, Aitchison and Lauder (1985) introduced classical kernel densityestimation techniques in the context of compositional data analysis. Indeed, they gavetwo options for the choice of the kernel to be used in the kernel estimator. One ofthese kernels is based on the use the alr transformation on the simplex SD jointly withthe normal distribution on RD-1. However, these authors themselves recognized thatthis method has some deficiencies. A method for overcoming these dificulties based onrecent developments for compositional data analysis and multivariate kernel estimationtheory, combining the ilr transformation with the use of the normal density with a fullbandwidth matrix, was recently proposed in Martín-Fernández, Chacón and Mateu-Figueras (2006). Here we present an extensive simulation study that compares bothmethods in practice, thus exploring the finite-sample behaviour of both estimators

Neuronal in vitro models for the estimation of acute systemic toxicity.

The objective of the EU funded integrated project "ACuteTox" is to develop a strategy in which general cytotoxicity, together with organ-specific endpoints and biokinetic features, are taken into consideration in the in vitro prediction of oral acute systemic toxicity. With regard to the nervous system, the effects of 23 reference chemicals were tested with approximately 50 endpoints, using a neuronal cell line, primary neuronal cell cultures, brain slices and aggregated brain cell cultures. Comparison of the in vitro neurotoxicity data with general cytotoxicity data generated in a non-neuronal cell line and with in vivo data such as acute human lethal blood concentration, revealed that GABA(A) receptor function, acetylcholine esterase activity, cell membrane potential, glucose uptake, total RNA expression and altered gene expression of NF-H, GFAP, MBP, HSP32 and caspase-3 were the best endpoints to use for further testing with 36 additional chemicals. The results of the second analysis showed that no single neuronal endpoint could give a perfect improvement in the in vitro-in vivo correlation, indicating that several specific endpoints need to be analysed and combined with biokinetic data to obtain the best correlation with in vivo acute toxicity.

Rank estimation of trajectory matrix in motion segmentation

A novel technique for estimating the rank of the trajectory matrix in the local subspace affinity (LSA) motion segmentation framework is presented. This new rank estimation is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built with LSA. The result is an enhanced model selection technique for trajectory matrix rank estimation by which it is possible to automate LSA, without requiring any a priori knowledge, and to improve the final segmentation

MDCT Arthrography of the Hip: Value of the Adaptive Statistical Iterative Reconstruction Technique and Potential for Radiation Dose Reduction

Au cours des deux dernières décennies, la technique d'imagerie arthro-scanner a bénéficié de nombreux progrès technologiques et représente aujourd'hui une excellente alternative à l'imagerie par résonance magnétique (IRM) et / ou arthro-IRM dans l'évaluation des pathologies de la hanche. Cependant, elle reste limitée par l'exposition aux rayonnements ionisants importante. Les techniques de reconstruction itérative (IR) ont récemment été mis en oeuvre avec succès en imagerie ; la littérature montre que l'utilisation ces dernières contribue à réduire la dose d'environ 40 à 55%, comparativement aux protocoles courants utilisant la rétroprojection filtrée (FBP), en scanner de rachis. A notre connaissance, l'utilisation de techniques IR en arthro-scanner de hanche n'a pas été évaluée jusqu'à présent. Le but de notre étude était d'évaluer l'impact de la technique ASIR (GE Healthcare) sur la qualité de l'image objective et subjective en arthro-scanner de hanche, et d'évaluer son potentiel en terme de réduction de dose. Pour cela, trente sept patients examinés par arthro-scanner de hanche ont été randomisés en trois groupes : dose standard (CTDIvol = 38,4 mGy) et deux groupes de dose réduite (CTDIvol = 24,6 ou 15,4 mGy). Les images ont été reconstruites en rétroprojection filtrée (FBP) puis en appliquant différents pourcentages croissants d'ASIR (30, 50, 70 et 90%). Le bruit et le rapport contraste sur bruit (CNR) ont été mesurés. Deux radiologues spécialisés en imagerie musculo-squelettique ont évalué de manière indépendante la qualité de l'image au niveau de plusieurs structures anatomiques en utilisant une échelle de quatre grades. Ils ont également évalué les lésions labrales et du cartilage articulaire. Les résultats révèlent que le bruit augmente (p = 0,0009) et le CNR diminue (p = 0,001) de manière significative lorsque la dose diminue. A l'inverse, le bruit diminue (p = 0,0001) et le contraste sur bruit augmente (p < 0,003) de manière significative lorsque le pourcentage d'ASIR augmente ; on trouve également une augmentation significative des scores de la qualité de l'image pour le labrum, le cartilage, l'os sous-chondral, la qualité de l'image globale (au delà de ASIR 50%), ainsi que le bruit (p < 0,04), et une réduction significative pour l'os trabuculaire et les muscles (p < 0,03). Indépendamment du niveau de dose, il n'y a pas de différence significative pour la détection et la caractérisation des lésions labrales (n=24, p = 1) et des lésions cartilagineuses (n=40, p > 0,89) en fonction du pourcentage d'ASIR. Notre travail a permis de montrer que l'utilisation de plus de 50% d'ASIR permet de reduire de manière significative la dose d'irradiation reçue par le patient lors d'un arthro-scanner de hanche tout en maintenant une qualité d'image diagnostique comparable par rapport à un protocole de dose standard utilisant la rétroprojection filtrée.

Adaptive business intelligence for an open negotiation environment

Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

Estimation de la fonction rénale par l'equation MDRD: intérêt et limites pour l'adaptation des doses de médicaments [Renal function estimation by MDRD equation: interest and limitations for drug dosing].

The MDRD (Modification of diet in renal disease) equation enables glomerular filtration rate (GFR) estimation from serum creatinine only. Thus, the laboratory can report an estimated GFR (eGFR) with each serum creatinine assessment, increasing therefore the recognition of renal failure. Predictive performance of MDRD equation is better for GFR < 60 ml/min/1,73 m2. A normal or near-normal renal function is often underestimated by this equation. Overall, MDRD provides more reliable estimations of renal function than the Cockcroft-Gault (C-G) formula, but both lack precision. MDRD is not superior to C-G for drug dosing. Being adjusted to 1,73 m2, MDRD eGFR has to be back adjusted to the patient's body surface area for drug dosing. Besides, C-G has the advantage of a greater simplicity and a longer use.

Implementation of zonal control algorithms in adaptive optical systems with sparse control matrices

Miralls deformables més i més grans, amb cada cop més actuadors estan sent utilitzats actualment en aplicacions d'òptica adaptativa. El control dels miralls amb centenars d'actuadors és un tema de gran interès, ja que les tècniques de control clàssiques basades en la seudoinversa de la matriu de control del sistema es tornen massa lentes quan es tracta de matrius de dimensions tan grans. En aquesta tesi doctoral es proposa un mètode per l'acceleració i la paral.lelitzacó dels algoritmes de control d'aquests miralls, a través de l'aplicació d'una tècnica de control basada en la reducció a zero del components més petits de la matriu de control (sparsification), seguida de l'optimització de l'ordenació dels accionadors de comandament atenent d'acord a la forma de la matriu, i finalment de la seva posterior divisió en petits blocs tridiagonals. Aquests blocs són molt més petits i més fàcils de fer servir en els càlculs, el que permet velocitats de càlcul molt superiors per l'eliminació dels components nuls en la matriu de control. A més, aquest enfocament permet la paral.lelització del càlcul, donant una com0onent de velocitat addicional al sistema. Fins i tot sense paral. lelització, s'ha obtingut un augment de gairebé un 40% de la velocitat de convergència dels miralls amb només 37 actuadors, mitjançant la tècnica proposada. Per validar això, s'ha implementat un muntatge experimental nou complet , que inclou un modulador de fase programable per a la generació de turbulència mitjançant pantalles de fase, i s'ha desenvolupat un model complert del bucle de control per investigar el rendiment de l'algorisme proposat. Els resultats, tant en la simulació com experimentalment, mostren l'equivalència total en els valors de desviació després de la compensació dels diferents tipus d'aberracions per als diferents algoritmes utilitzats, encara que el mètode proposat aquí permet una càrrega computacional molt menor. El procediment s'espera que sigui molt exitós quan s'aplica a miralls molt grans.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Birth and adaptive evolution of a hominoid gene that supports high neurotransmitter flux.

The enzyme glutamate dehydrogenase (GDH) is important for recycling the chief excitatory neurotransmitter, glutamate, during neurotransmission. Human GDH exists in housekeeping and brain-specific isotypes encoded by the genes GLUD1 and GLUD2, respectively. Here we show that GLUD2 originated by retroposition from GLUD1 in the hominoid ancestor less than 23 million years ago. The amino acid changes responsible for the unique brain-specific properties of the enzyme derived from GLUD2 occurred during a period of positive selection after the duplication event.

Adaptive search and information updating in sequential mate choice

Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.

Pédiatrie 1. Formule Quadratique: une nouveauté pédiatrique et pratique pour estimer le taux de filtration glomérulaire [Quadratic formula: a new pediatric advance for glomerular filtration rate estimation].

A new formula for glomerular filtration rate estimation in pediatric population from 2 to 18 years has been developed by the University Unit of Pediatric Nephrology. This Quadratic formula, accessible online, allows pediatricians to adjust drug dosage and/or follow-up renal function more precisely and in an easy manner.

Monitoring of innate and adaptive immune responses in the context of human immunotherapy

Summary1 SummaryCancer patients have a better clinical outcome when their tumours display marked infiltration by memory Τ cells. Moreover, the overrepresentation of Th1 gene signatures in primary tumours correlates with favourable prognosis. Thus, vaccination to induce Τ cells capable of infiltrating and eradicating the tumour seems a promising strategy for the treatment of cancer. Here, I monitored CD4 Τ cell responses in melanoma patients vaccinated with the long synthetic peptides Melan- A16-35(A27L) and NY-ESO-179.108. Most of the patients developed strong and diverse peptide antigen specific CD4 Τ cell responses. Analysis of the fine specificity of CD4 Τ cell antigen recognition led to the identification of two new epitopes. The peptide Melan-A16_35(A27L) was delivered by virus-like particles (VLPs) derived from bacteriophage Οβ, which themselves displayed strong immunogenicity. I show evidence for induction of Οβ- and Melan-A specific CD4 Τ cell responses that developed a Th1 functional profile after repeated vaccination cycles. They also specifically released the chemokines CCL-3 and CCL-4, which play important roles in attracting CD8 Τ cells to the APC surface for priming and formation of Τ cell memory. We further found induction of robust humoral IgG responses upon VLP vaccination, and the lgG1-lgG4 isotype composition depended on the adjuvant used. Since heavy chain class switching largely dépends on the presence of CD4 Τ cell help, this result suggests that the adjuvant can influence the differentiation of elicited CD4 Τ cells, thereby contributing to the quality and function of both Β cells and CD8 Τ cells. The nature of the inflammatory processes in the tumour microenvironment can modulate CD8 Τ cell function. A collaboration was established for the investigation regulation of inflammasome activation in human primary monocytes. We identified IL- 4 and TGF-β as strong inhibitors of IL-1 β secretion, Indicating some level of regulation from effector Th2 and Treg responses. We further found a potent inhibition of inflammasome activation by type I interferon, and demonstrated in vivo inhibition of IL-1 β responses in monocytes from active multiple sclerosis patients under IFN-β therapy. This finding further offers a possible explanation for its success, which mechanism of action is still largely unclear. Interestingly, type I interferon is also being used as adjuvant treatment for tumour free metastatic cutaneous melanoma patients. While its clinical benefit has remained controversial, recent data suggest that the subset of patients with ulcerated primary melanoma lesions can benefit from this therapy. Future investigations will shed light on the implication of the inflammasome in this context, and may offer new strategies for improved adjuvant treatments of melanoma.2 RésuméLes patients atteints de cancer ont une meilleure chance de survie si leurs tumeurs s'avèrent être largement infiltrées par des cellules Τ mémoires. De plus, la surreprésentation d'une signature génique Th1 est en corrélation avec un pronostic favorable. Ainsi, la vaccination visant à induire des cellules Τ capables d'infiltrer et de détruire la tumeur parait être une stratégie prometteuse pour le traitement du cancer. Dans ce travail, j'ai procédé au monitoring de la réponse des cellules Τ CD4 dans des patients atteints de mélanome vaccinés avec les longs peptides synthétiques Melan-A16_35(A27L) et NY-ESO-179_108. Ces peptides représentent des antigènes tumoraux reconnus par des lymphocytes T. La majorité des patients a développé une réponse forte et diversifiée des cellules Τ CD4 spécifiques contre les peptides. L'analyse de la spécificité fine de la reconnaissance antigénique des cellules Τ CD4 nous a conduits à l'identification de deux nouveaux épitopes. Le peptide Melan-Aie. 35(A27L) a été délivré par des particules de type viral (VLPs) dérivés de bactériophages Qβ, qui ont eux-mêmes démontré une forte immunogénicité. Mon travail montre les preuves d'une induction de réponses spécifiques des cellules Τ CD4 contre les Qβ et Melan-A développant un profil fonctionnel Th1 après plusieurs cycles de vaccination. Elles secrètent aussi spécifiquement les chimiokines CCL-3 et CCL-4, qui jouent un rôle important dans l'attraction des cellules Τ CD8 à la surface des cellules présentatrices d'antigènes et contribuent ainsi à induire et former la mémoire cellulaire Τ CD8. Nous avons également remarqué une induction de fortes réponses humorales IgG après vaccination avec les VLPs, et que la composition des isotypes lgG1-lgG4 dépendait de l'adjuvant utilisé. Etant donné qu'une commutation de classe de la chaîne lourde dépend largement ùie l'aide des cellules Τ CD4, ce résultat suggère que l'adjuvant puisse influencer la différeritiation de cellules Τ CD4 en différent types, contribuant ainsi à la qualité et à la fonction des cellules Β et des cellules Τ CD8.La nature des processus d'inflammation dans le microenvironnement tumoral peut moduler la fonction des cellules Τ CD8. Une collaboration a été établie pour investiguer la régulation de l'activation de l'inflammasome dans des monocytes primaires humains. Nous avons identifié l'IL-4 et le TGF-β comme étant de puissants inhibiteurs de la sécrétion de IL-Ιβ, indiquant une certaine régulation de la réponse inflammatoire induite par les cellules Th2 et Τ régulatrices. Nous avons également trouvé une forte inhibition de l'activation de l'inflammasome par l'interféron type I, et nous avons démontré une inhibition in vivo de la réponse IL-1 β dans des monocytes de patients atteints d'une sclérose en plaque active sous traitement IFN-β. Ce résultat nous offre une possible explication du succès de cette thérapie, dont le mécanisme reste à ce jour encore largement obscur. Il est intéressant de noter que l'interféron de type I est également utilisé pour le traitement de patients atteints de mélanome cutané métastasique sans tumeurs. Bien que le bénéfice clinique de ce traitement reste controversé, des études récentes montrent qu'une partie des patients atteints de mélanome primaire ulcéré peut tirer bénéfice de cette thérapie. De futures investigations pourront mieux nous renseigner sur l'implication de l'inflammasome dans ce contexte et offrir de nouvelles stratégies pour améliorer les traitements adjuvants du mélanome.

Natural genetic variation of root system architecture from Arabidopsis to Brachypodium: towards adaptive value.

Root system architecture is a trait that displays considerable plasticity because of its sensitivity to environmental stimuli. Nevertheless, to a significant degree it is genetically constrained as suggested by surveys of its natural genetic variation. A few regulators of root system architecture have been isolated as quantitative trait loci through the natural variation approach in the dicotyledon model, Arabidopsis. This provides proof of principle that allelic variation for root system architecture traits exists, is genetically tractable, and might be exploited for crop breeding. Beyond Arabidopsis, Brachypodium could serve as both a credible and experimentally accessible model for root system architecture variation in monocotyledons, as suggested by first glimpses of the different root morphologies of Brachypodium accessions. Whether a direct knowledge transfer gained from molecular model system studies will work in practice remains unclear however, because of a lack of comprehensive understanding of root system physiology in the native context. For instance, apart from a few notable exceptions, the adaptive value of genetic variation in root system modulators is unknown. Future studies should thus aim at comprehensive characterization of the role of genetic players in root system architecture variation by taking into account the native environmental conditions, in particular soil characteristics.

Adaptive integral assessment package for the A2UN@ project

This paper presents a first approach of Evaluation Engine Architecture (EEA) as proposal to support adaptive integral assessment, in the context of a virtual learning environment. The goal of our research is design an evaluation engine tool to assist in the whole assessment process within the A2UN@ project, linking that tool with the other key elements of a learning design (learning task, learning resources and learning support). The teachers would define the relation between knowledge, competencies, activities, resources and type of assessment. Providing this relation is possible obtain more accurate estimations of student's knowledge for adaptive evaluations and future recommendations. The process is supported by usage of educational standards and specifications and for an integral user modelling