Lifelong dynamics of human CD4+CD25+ regulatory T cells: insights from in vivo data and mathematical modeling.

Despite their limited proliferation capacity, regulatory T cells (T(regs)) constitute a population maintained over the entire lifetime of a human organism. The means by which T(regs) sustain a stable pool in vivo are controversial. Using a mathematical model, we address this issue by evaluating several biological scenarios of the origins and the proliferation capacity of two subsets of T(regs): precursor CD4(+)CD25(+)CD45RO(-) and mature CD4(+)CD25(+)CD45RO(+) cells. The lifelong dynamics of T(regs) are described by a set of ordinary differential equations, driven by a stochastic process representing the major immune reactions involving these cells. The model dynamics are validated using data from human donors of different ages. Analysis of the data led to the identification of two properties of the dynamics: (1) the equilibrium in the CD4(+)CD25(+)FoxP3(+)T(regs) population is maintained over both precursor and mature T(regs) pools together, and (2) the ratio between precursor and mature T(regs) is inverted in the early years of adulthood. Then, using the model, we identified three biologically relevant scenarios that have the above properties: (1) the unique source of mature T(regs) is the antigen-driven differentiation of precursors that acquire the mature profile in the periphery and the proliferation of T(regs) is essential for the development and the maintenance of the pool; there exist other sources of mature T(regs), such as (2) a homeostatic density-dependent regulation or (3) thymus- or effector-derived T(regs), and in both cases, antigen-induced proliferation is not necessary for the development of a stable pool of T(regs). This is the first time that a mathematical model built to describe the in vivo dynamics of regulatory T cells is validated using human data. The application of this model provides an invaluable tool in estimating the amount of regulatory T cells as a function of time in the blood of patients that received a solid organ transplant or are suffering from an autoimmune disease.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Increased audiovisual integration in cochlear-implanted deaf patients: independent components analysis of longitudinal positron emission tomography data.

It has been demonstrated in earlier studies that patients with a cochlear implant have increased abilities for audio-visual integration because the crude information transmitted by the cochlear implant requires the persistent use of the complementary speech information from the visual channel. The brain network for these abilities needs to be clarified. We used an independent components analysis (ICA) of the activation (H2 (15) O) positron emission tomography data to explore occipito-temporal brain activity in post-lingually deaf patients with unilaterally implanted cochlear implants at several months post-implantation (T1), shortly after implantation (T0) and in normal hearing controls. In between-group analysis, patients at T1 had greater blood flow in the left middle temporal cortex as compared with T0 and normal hearing controls. In within-group analysis, patients at T0 had a task-related ICA component in the visual cortex, and patients at T1 had one task-related ICA component in the left middle temporal cortex and the other in the visual cortex. The time courses of temporal and visual activities during the positron emission tomography examination at T1 were highly correlated, meaning that synchronized integrative activity occurred. The greater involvement of the visual cortex and its close coupling with the temporal cortex at T1 confirm the importance of audio-visual integration in more experienced cochlear implant subjects at the cortical level.

What spatial data do we need to develop global mammal conservation strategies?

Spatial data on species distributions are available in two main forms, point locations and distribution maps (polygon ranges and grids). The first are often temporally and spatially biased, and too discontinuous, to be useful (untransformed) in spatial analyses. A variety of modelling approaches are used to transform point locations into maps. We discuss the attributes that point location data and distribution maps must satisfy in order to be useful in conservation planning. We recommend that before point location data are used to produce and/or evaluate distribution models, the dataset should be assessed under a set of criteria, including sample size, age of data, environmental/geographical coverage, independence, accuracy, time relevance and (often forgotten) representation of areas of permanent and natural presence of the species. Distribution maps must satisfy additional attributes if used for conservation analyses and strategies, including minimizing commission and omission errors, credibility of the source/assessors and availability for public screening. We review currently available databases for mammals globally and show that they are highly variable in complying with these attributes. The heterogeneity and weakness of spatial data seriously constrain their utility to global and also sub-global scale conservation analyses.

Lien entre durée de séjour et réadmissions en chirurgie et en obstétrique: étude de deux procédures à partir des données du PMSI = Using administrative data to assess the impact of length of stay on readmissions: study of two procedures in surgery and obstetrics

Position du problème: La mise en place de la tarification à l'activité pour les hôpitaux de court séjour pourrait entraîner une diminution des durées de séjour pour raisons financières. L'impact potentiel de ce phénomène sur la qualité des soins n'est pas connu. Les réadmissions identifiées à l'aide des données administratives hospitalières sont, pour certaines situations cliniques, des indicateurs de qualité des soins valides. Méthode: Étude rétrospective du lien entre la durée de séjour et la survenue de réadmissions imprévues liées au séjour initial, pour les cholécystectomies simples et les accouchements par voie basse sans complication, à partir des données du programme de médicalisation des systèmes d'information de l'Assistance publique-Hôpitaux de Paris des années 2002 à 2005. Résultats: Pour les deux procédures, la probabilité de réadmission suit une courbe en " J ". Après ajustement sur l'âge, le sexe, les comorbidités associées, l'hôpital et l'année d'admission, la probabilité de réadmission est plus élevée pour les durées de séjour les plus courtes : pour les cholécystectomies, odds ratio : 6,03 [IC95 % : 2,67-13,59] pour les hospitalisations d'un jour versus trois jours ; pour les accouchements, odds ratio : 1,74 [IC95 % : 1,05-2,91] pour les hospitalisations de deux jours versus trois jours. Conclusion: Pour deux pathologies communes, les durées de séjour les plus courtes sont associées à des probabilités de réadmission plus élevées. L'utilisation routinière des données du programme de médicalisation des systèmes d'information peut permettre d'assurer le suivi de la relation entre la réduction de la durée de séjour et les réadmissions. The prospective payment system for the French short-stay hospitals creates a financial incentive to reduce length of stay. The potential impact of the resulting decrease in length of stay on the quality of healthcare is unknown. Readmission rates are valid outcome indicators for some clinical procedures. Methods: Retrospective study of the association between length of stay and unplanned readmissions related to the initial stay, for two procedures: cholecystectomy and vaginal delivery. Data: Administrative diagnosis-related groups database of "Assistance publique-Hopitaux de Paris", a large teaching hospital, for years 2002 to 2005. Results: The risk of readmission according to length of stay, taking age, sex, comorbidity, hospital and year of admission into account, followed a J-shaped curve for both procedures. The probability of readmission was higher for very short stays, with odds ratios and 95% confidence intervals of 6.03 [2.67-13.59] for cholecystectomies (1- versus 3-night stays), and of 1.74 [1.05-2.91] for vaginal deliveries (2- versus 3-night stays). Conclusion: For both procedures, the shortest lengths of stay are associated with a higher readmission probability. Suitable indicators derived from administrative databases would enable monitoring of the association between length of stay and readmissions.

Use of variability in national and regional data to estimate the prevalence of lymphangioleiomyomatosis.

Background: Understanding the true prevalence of lymphangioleiomyomatosis (LAM) is important in estimating disease burden and targeting specific interventions. As with all rare diseases, obtaining reliable epidemiological data is difficult and requires innovative approaches.Aim: To determine the prevalence and incidence of LAM using data from patient organizations in seven countries, and to use the extent to which the prevalence of LAM varies regionally and nationally to determine whether prevalence estimates are related to health-care provision.Methods: Numbers of women with LAM were obtained from patient groups and national databases from seven countries (n = 1001). Prevalence was calculated for regions within countries using female population figures from census data. Incidence estimates were calculated for the USA, UK and Switzerland. Regional variation in prevalence and changes in incidence over time were analysed using Poisson regression and linear regression.Results: Prevalence of LAM in the seven countries ranged from 3.4 to 7.8/million women with significant variation, both between countries and between states in the USA. This variation did not relate to the number of pulmonary specialists in the region nor the percentage of population with health insurance, but suggests a large number of patients remain undiagnosed. The incidence of LAM from 2004 to 2008 ranged from 0.23 to 0.31/million women/per year in the USA, UK and Switzerland.Conclusions: Using this method, we have found that the prevalence of LAM is higher than that previously recorded and that many patients with LAM are undiagnosed.

Health literacy [Document électronique] : an economic perspective and data for Switzerland. Part 2, A review of health literacy measures and a cost assessment of limited health literacy

Summary : 1. Measuring health literacy in Switzerland: a review of six surveys: 1.1 Comparison of questionnaires - 1.2 Measures of health literacy in Switzerland - 1.3 Discussion of Swiss data on HL - 1.4 Description of the six surveys: 1.4.1 Current health trends and health literacy in the Swiss population (gfs-UNIVOX), 1.4.2 Nutrition, physical exercise and body weight : opinions and perceptions of the Swiss population (USI), 1.4.3 Health Literacy in Switzerland (ISPMZ), 1.4.4 Swiss Health Survey (SHS), 1.4.5 Survey of Health, Ageing and Retirement in Europe (SHARE), 1.4.6 Adult literacy and life skills survey (ALL). - 2 . Economic costs of low health literacy in Switzerland: a rough calculation. Appendix: Screenshots cost model

Decision fusion for the classification of hyperspectral data: Outcome of the 2008 GRS-S data fusion contest

The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.

Truncated robust distance for clinical laboratory safety data monitoring and assessment.

Laboratory safety data are routinely collected in clinical studies for safety monitoring and assessment. We have developed a truncated robust multivariate outlier detection method for identifying subjects with clinically relevant abnormal laboratory measurements. The proposed method can be applied to historical clinical data to establish a multivariate decision boundary that can then be used for future clinical trial laboratory safety data monitoring and assessment. Simulations demonstrate that the proposed method has the ability to detect relevant outliers while automatically excluding irrelevant outliers. Two examples from actual clinical studies are used to illustrate the use of this method for identifying clinically relevant outliers.

Comparative analysis of human and mouse expression data illuminates tissue-specific evolutionary patterns of miRNAs.

MicroRNAs (miRNAs) constitute an important class of gene regulators. While models have been proposed to explain their appearance and expansion, the validation of these models has been difficult due to the lack of comparative studies. Here, we analyze miRNA evolutionary patterns in two mammals, human and mouse, in relation to the age of miRNA families. In this comparative framework, we confirm some predictions of previously advanced models of miRNA evolution, e.g. that miRNAs arise more frequently de novo than by duplication, or that the number of protein-coding gene targeted by miRNAs decreases with evolutionary time. We also corroborate that miRNAs display an increase in expression level with evolutionary time, however we show that this relation is largely tissue-dependent, and especially low in embryonic or nervous tissues. We identify a bias of tag-sequencing techniques regarding the assessment of breadth of expression, leading us, contrary to predictions, to find more tissue-specific expression of older miRNAs. Together, our results refine the models used so far to depict the evolution of miRNA genes. They underline the role of tissue-specific selective forces on the evolution of miRNAs, as well as the potential co-evolution patterns between miRNAs and the protein-coding genes they target.

Hyperhidrosis: a new and often early symptom in Fabry disease. International experience and data from the Fabry Outcome Survey.

Hypohidrosis is a classic feature of Fabry disease; in contrast, hyperhidrosis has only been rarely described. The aim of the study is to characterise the baseline descriptive data on hyperhidrosis (frequency, age at onset, sex ratio and outcome with and without enzyme replacement therapy) in hemizygous male and heterozygous female patients with Fabry disease. We describe case histories of five patients with Fabry disease and hyperhidrosis seen at three different centres. We have also analysed a cohort of 21 paediatric patients in the UK and a large European cohort of patients enrolled in the Fabry Outcome Survey (FOS). Five patients (three female, two male) with hyperhidrosis were originally identified, although each had additional symptoms related to Fabry disease. The age at onset of hyperhidrosis was less than 18 years in four cases. In the cohort of 21 paediatric patients (12 female, nine male), one female had hyperhidrosis; the age at onset of this symptom was 11 years. In the FOS cohort, 66 of 714 patients with Fabry disease had hyperhidrosis (44 of 369 females, 11.9%; 22 of 345 males, 6.4%). The female predominance was observed in seven of nine countries from which data were analysed. Hyperhidrosis is an increasingly recognised feature of the Fabry disease phenotype. It is more prevalent in females than in males and often appears in childhood or adolescence. The efficacy of enzyme replacement therapy on this recently recognised symptom should be assessed.

Examining the information content of time-lapse crosshole GPR data collected under different infiltration conditions to estimate unsaturated soil hydraulic properties

Time-lapse geophysical data acquired during transient hydrological experiments are being increasingly employed to estimate subsurface hydraulic properties at the field scale. In particular, crosshole ground-penetrating radar (GPR) data, collected while water infiltrates into the subsurface either by natural or artificial means, have been demonstrated in a number of studies to contain valuable information concerning the hydraulic properties of the unsaturated zone. Previous work in this domain has considered a variety of infiltration conditions and different amounts of time-lapse GPR data in the estimation procedure. However, the particular benefits and drawbacks of these different strategies as well as the impact of a variety of key and common assumptions remain unclear. Using a Bayesian Markov-chain-Monte-Carlo stochastic inversion methodology, we examine in this paper the information content of time-lapse zero-offset-profile (ZOP) GPR traveltime data, collected under three different infiltration conditions, for the estimation of van Genuchten-Mualem (VGM) parameters in a layered subsurface medium. Specifically, we systematically analyze synthetic and field GPR data acquired under natural loading and two rates of forced infiltration, and we consider the value of incorporating different amounts of time-lapse measurements into the estimation procedure. Our results confirm that, for all infiltration scenarios considered, the ZOP GPR traveltime data contain important information about subsurface hydraulic properties as a function of depth, with forced infiltration offering the greatest potential for VGM parameter refinement because of the higher stressing of the hydrological system. Considering greater amounts of time-lapse data in the inversion procedure is also found to help refine VGM parameter estimates. Quite importantly, however, inconsistencies observed in the field results point to the strong possibility that posterior uncertainties are being influenced by model structural errors, which in turn underlines the fundamental importance of a systematic analysis of such errors in future related studies.

Segmentation and grid generation for numerical simulations of vad connections with patient-specific data

Objectives: We are interested in the numerical simulation of the anastomotic region comprised between outflow canula of LVAD and the aorta. Segmenta¬tion, geometry reconstruction and grid generation from patient-specific data remain an issue because of the variable quality of DICOM images, in particular CT-scan (e.g. metallic noise of the device, non-aortic contrast phase). We pro¬pose a general framework to overcome this problem and create suitable grids for numerical simulations.Methods: Preliminary treatment of images is performed by reducing the level window and enhancing the contrast of the greyscale image using contrast-limited adaptive histogram equalization. A gradient anisotropic diffusion filter is applied to reduce the noise. Then, watershed segmentation algorithms and mathematical morphology filters allow reconstructing the patient geometry. This is done using the InsightToolKit library (www.itk.org). Finally the Vascular Model¬ing ToolKit (www.vmtk.org) and gmsh (www.geuz.org/gmsh) are used to create the meshes for the fluid (blood) and structure (arterial wall, outflow canula) and to a priori identify the boundary layers. The method is tested on five different patients with left ventricular assistance and who underwent a CT-scan exam.Results: This method produced good results in four patients. The anastomosis area is recovered and the generated grids are suitable for numerical simulations. In one patient the method failed to produce a good segmentation because of the small dimension of the aortic arch with respect to the image resolution.Conclusions: The described framework allows the use of data that could not be otherwise segmented by standard automatic segmentation tools. In particular the computational grids that have been generated are suitable for simulations that take into account fluid-structure interactions. Finally the presented method features a good reproducibility and fast application.

A multidimensional segmentation evaluation for medical image data.

Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.