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Standard approaches for variable selection in linear models are not tailored to deal properly with high-dimensional and incomplete data. Currently, methods dedicated to high-dimensional data handle missing values by ad hoc strategies, like complete case analysis or single imputation, while methods dedicated to missing values, mainly based on multiple imputation, do not discuss the imputation method to use with high-dimensional data. Consequently, both approaches appear to be limited for many modern applications. With inspiration from ensemble methods, a new variable selection method is proposed. It extends classical variable selection methods in the case of high-dimensional data with or without missing data. Theoretical properties are studied and the practical interest is demonstrated through a simulation study, as well as through an application to models specification in sequential multiple imputation. In the low-dimensional case, the procedure improves the control of the error risks, especially type I error, even without missing values for stepwise, lasso or knockoff methods. With missing values, the method performs better than reference selection methods based on multiple imputation. Similar performances are obtained in the high-dimensional case with or without missing values. [ABSTRACT FROM AUTHOR]

Generalized multipartite networks consist in the joint observation of several networks implying some common pre-specified groups of individuals. Such complex networks arise commonly in social sciences, biology, ecology, etc. We propose a flexible probabilistic model named Multipartite Block Model (MBM) able to unravel the topology of multipartite networks by identifying clusters (blocks) of nodes sharing the same patterns of connectivity across the collection of networks they are involved in. The model parameters are estimated through a variational version of the Expectation-Maximization algorithm. The numbers of blocks are chosen using an Integrated Completed Likelihood criterion specifically designed for our model. A simulation study illustrates the robustness of the inference strategy. Finally, two datasets respectively issued from ecology and ethnobiology are analyzed with the MBM in order to illustrate its flexibility and its relevance for the analysis of real datasets. [ABSTRACT FROM AUTHOR]

We propose to extend CART for bivariate marked point processes to provide a segmentation of the space into homogeneous areas for interaction between marks. While usual CART tree considers marginal distribution of the response variable at each node, the proposed algorithm, SpatCART, takes into account the spatial location of the observations in the splitting criterion. We introduce a dissimilarity index based on Ripley's intertype K-function quantifying the interaction between two populations. This index used for the growing step of the CART strategy, leads to a heterogeneity function consistent with the original CART algorithm. Therefore the new variant is a way to explore spatial data as a bivariate marked point process using binary classification trees. The proposed procedure is implemented in an R package, and illustrated on simulated examples. SpatCART is finally applied to a tropical forest example. [ABSTRACT FROM AUTHOR]

• A model of cascade of classifiers with reject option • Optimization of the reject area of the classifiers • Ranking of the features for the cascade construction • Minimization of the cost of classification • Controlling the trade-off between the accuracy and the cost of classification [Display omitted] Although the prediction performance is crucial for a classifier, its cost of use is also an essential issue for practical application. The aim of this article is to propose a prediction method that controls not only the error rate but also the cost of the construction of the classifier. The main idea is that some examples are easier to predict than others and can be predicted using fewer variables i.e. with a lower prediction cost. Our method, called CASCARO, is based on a cascade of reject classifiers of increasing cost. The first classifier of the cascade required only one variable, if the prediction is not reliable the second classifier requiring one more variable is used. The principle is repeated until the last classifier using all variables. This type of cascade raises two scientific problems: the structure of the cascade (the order of the classifiers) and the simultaneous computation of the rejection regions of the classifiers. The experiments show that CASCARO produces significant improvements in the use cost without decreasing prediction performance. [ABSTRACT FROM AUTHOR]

Graphical models allow to represent a set of random variables together with their probabilistic conditional dependencies. Various algorithms have been proposed to estimate such models from data. The focus of this paper is on individual observations diagnosis issues. The use of an influence measure is a classical diagnostic method to measure the perturbation induced by a single element, in other terms we consider stability issue through jackknife. For a given graphical model, we provide tools to perform diagnosis on observations. In a second step we propose a filtering of the dataset to obtain a stable network. All along the paper an application to a gene expression dataset illustrates the proposals. [ABSTRACT FROM AUTHOR]

This paper deals with measuring the influence of observations on the results obtained with CART classification trees. To define the influence of individuals on the analysis, we use influence measures to propose criterions to quantify the sensitivity of the CART classification tree analysis. The proposals are based on predictions and use jackknife trees. The analysis is extended to the pruned sequences of CART trees to produce CART specific notions of influence. Using the framework of influence functions, distributional results are derived. A numerical example, the well known spam dataset, is presented to illustrate the notions developed throughout the paper. A real dataset relating the administrative classification of cities surrounding Paris, France, to the characteristics of their tax revenues distribution, is finally analyzed using the new influence-based tools. [ABSTRACT FROM AUTHOR]

A two-level data set consists of entities of a higher level (say populations), each one being composed of several units of the lower level (say individuals). Observations are made at the individual level, whereas population characteristics are aggregated from individual data. Cluster analysis with subsampling of populations is a cluster analysis based on individual data that aims at clustering populations rather than individuals. In this article, we extend existing optimality criteria for cluster analysis with subsampling of populations to deal with situations where population characteristics are not the mean of individual data. A new criterion that depends on the Mahalanobis distance is also defined. The criteria are compared using simulated examples and an ecological data set of tree species in a tropical rain forest. [ABSTRACT FROM AUTHOR]

Understanding the evolutionary history of species is at the core of molecular evolution and is done using several inference methods. The critical issue is to quantify the uncertainty of the inference. The posterior probabilities in Bayesian phylogenetic inference and the bootstrap values in frequentist approaches measure the variability of the estimates due to the sampling of sites from genes and the sampling of genes from genomes. However, they do not measure the uncertainty due to taxon sampling. Taxa that experienced molecular homoplasy, recent selection, a spur of evolution, and so forth may disrupt the inference and cause incongruences in the estimated phylogeny. We define a taxon influence index to assess the influence of each taxon on the phylogeny. We found that although most taxa have a weak influence on the phylogeny, a small fraction of influential taxa strongly alter it even in clades only loosely related to them. We conclude that highly influential taxa should be given special attention and sampling them more thoroughly can lead to more dependable phylogenies. [ABSTRACT FROM PUBLISHER]

There is much interest in predicting the impact of global warming on the genetic diversity of natural populations and the influence of climate on biodiversity is an important ecological question. Since Holocene, we face many climate perturbations and the geographical ranges of plant taxa have changed substantially. Actual genetic diversity of plant is a result of these processes and a first step to study the impact of future climate change is to understand the important features of reconstructed climate variables such as temperature or precipitation for the last 15,000 years on actual genetic diversity of forest. We model the relationship between genetic diversity in the European beech (Fagus sylvatica) forests and curves of temperature and precipitation reconstructed from pollen databases. Our model links the genetic measure to the climate curves. We adapt classical functional linear model to take into account interactions between climate variables as a bilinear form. Since the data are georeferenced, our extensions also account for the spatial dependence among the observations. The practical issues of these methodological extensions are discussed. [ABSTRACT FROM AUTHOR]

The spatial pattern of trees in forests often combines different types of structure (regularity, clustering or randomness) at different scales. Taking species or size into account leads to marked patterns. The question addressed is to model such multi-scale marked patterns using a single process. Within the category of Markov processes, the area-interaction process has the advantage of being locally stable, whether it is attractive or repulsive. This process was originally defined as a one-scale non-marked process. We propose an extension as a multi-scale marked process. Three examples are presented to show the adequacy of this process to model tree patterns: 1. A pine pattern showing anisotropic regularity and clustering at different scales. 2. A bivariate (adult/juvenile) kimboto pattern in French Guiana, showing regularity for one type, clustering for the other and repulsion between the two. 3. A marked pattern in Gabon where the mark is tree diameter. [ABSTRACT FROM AUTHOR]

After the last glacial maximum (LGM; 18,000 years. bp) plants migrated onto areas made free by the retreating ice sheets. Pollen records document changes in ecosystems and are an important proxy for the reconstruction of climate parameters. Here, we quantify changes in January temperature (Tjan) over the past 14,000 years using 216 European pollen records. We used functional principal component analysis to evaluate the patterns of change over this period of time. Between 14 and 12 ka, Tjan records show comparable changes across Europe. After this time period, northwest and southeast Europe experienced differing trends in Tjan, trends that became pronounced by 9 ka. The spatial gradient of Tjan records is well-correlated with the overall change from steppe to increasingly diverse forest ecosystems. In particular, differential incorporation of conifer vs. deciduous species into forest ecosystems, based on differential colonization out of refugia, likely resulted in albedo gradients over Europe that affected regional Tjan. [ABSTRACT FROM AUTHOR]

1. Considering that the spatial pattern of trees is a footprint of the biological processes that drive their dynamics, increasing work has been undertaken to analyse spatial patterns and fit spatial point processes to them. When diameter is taken into account, the underlying point process is a marked point process. The question then is how to correctly model the dependence between the mark and location, and the different patterns at the different scales, to gain understanding of the underlying biological processes. 2. The data used comes from the Paracou rain forest in French Guiana (5°15′ N, 52°55′ W). The spatial pattern of trees in this forest exhibits regularity at small distances ( c. 6 m) and clustering at larger distances ( c. 30 m). The pattern is linked to diameter, with a shift from clustering to regularity as trees grow. 3. Two models of spatial pattern are used. The first one is pattern-driven in the sense that it breaks down the observed pattern into a mixture of regular, clustered and random contributions. The second one is process-based and uses a simple individual-based space-dependent model of forest dynamics as a simulation algorithm. It is obtained as the limit of this spatio-temporal model when time tends to infinity. 4. Both models are consistent with the observed pattern, with a better fit provided by the second model. Moreover this second model provides a biological interpretation of the observed pattern in terms of forest dynamics. However the first model's implementation is simpler (both for simulation and for parameter estimation). 5. Synthesis. Modelling the spatial pattern of plants using spatial point processes gives insights into the biological processes that drive their dynamics. It allows the reconstruction of their dynamics given only a snapshot of plant locations. Very few solutions exist to model complex marked spatial patterns when point location and mark are dependent. We defined and compared two point processes that successfully modelled the spatial pattern of trees in a rain forest with interaction between tree location and tree size. Both models highlight competition (either symmetric or asymmetric) as a driving process towards regularity. The second model further reveals a self-organizing dynamic with a feedback effect of competition. [ABSTRACT FROM AUTHOR]

No abstract received. [ABSTRACT FROM AUTHOR]

Matrix models can incorporate demographic, environmental or sampling stochasticity. The first two have intensively been studied, and we shall focus on the latter. It comes from the uncertainty on the estimation of vital rates, that generates an uncertainty on the model predictions. When dealing with size-classified models, the continuous information brought by the size may or may not be taken into consideration to estimate vital rates. The proportion estimator is obtained in the former case, whereas the increment estimator is obtained in the latter case. We compared these two estimators on the basis of their bias, variance and probability of being null, and applied the results to a tropical rain forest in French Guiana. The proportion estimator is unbiased, whereas the increment estimator is generally biased. We specified some conditions under which the increment estimator is also unbiased. However, the increment estimator generally has a lower asymptotic variance than the proportion estimator. As a consequence, the increment estimator is generally more efficient than the proportion estimator for small samples. Moreover, the increment estimator cannot bring null estimates, contrary to the proportion estimator, which reinforces its suitability for small samples. [Copyright &y& Elsevier]

Abstract: Correspondence analysis appears to be sensitive to modalities with low margins leading to outliers. We use the notions of influence function and Hadamard differentiability to provide a criterion for deciding when such an outlier can be considered as too influential. [Copyright &y& Elsevier]

For practical reasons, estimating seed production in tropical forest is only possible by sampling. Classical sampling designs (random or systematic) give poor estimations of seed abundance. The spatial disposition of the trees, combined with nonuniform seed dispersal, leads to a highly heterogeneous spatial distribution of the seeds. We propose a random stratified sampling design based on a model that takes account of seed dispersal processes and the location of the trees. We assume a gamma distribution for dispersal distances. The overall seed dispersal area is divided into adjacent quadrats. In each quadrat, the number of seeds follows a Poisson distribution with the mean derived from the model. We estimate model parameters from the results of a previous study and give the variance of the Horvitz–Thompson estimator of population total for stratified and random sampling designs. A simulation study is used to find the optimal number of strata, and the performance of the sampling design is evaluated. For each model, we compared the variance of the estimator of population total obtained with the stratified sampling design with that obtained with the random sampling design with the same sample size. The stratified sampling design is, on average, 25 times as precise as the random sampling design. [ABSTRACT FROM AUTHOR]

Since correspondence analysis appears to be sensitive to outliers, it is important to be able to evaluate the sensitivity of the data on the results. This article deals with measuring the influence of rows and columns on the results obtained with correspondence analysis. To establish the influence of individuals on the analysis, we use the notion of influence curve and we propose a general criterion based on the mean square error to measure the sensitivity of the correspondence analysis and its robustness. A numerical example is presented to illustrate the notions developed in this article. [ABSTRACT FROM AUTHOR]

Microarrays are a popular technology to study genes that are differentially expressed between two conditions. In this Note, we propose an iterative procedure to determine the biggest subset of non-differentially expressed genes. We prove a pseudo Markov relationship that allows practical computations. We obtain explicit expressions for FDR and the level of the proposed test at each step. To cite this article: A. Bar-Hen, S. Robin, C. R. Acad. Sci. Paris, Ser. I 337 (2003). [Copyright &y& Elsevier]

Density optimization of a plantation is a classical task with important practical consequences. In this article, we present an adaptation of criss-cross design and an alternative analysis. If a tree is missing, the spacing of neighbouring trees is altered and considerable information is lost. We derive the estimate of the missing value that minimizes the residual sum of squares and obtain the analytical solution of the EM algorithm. The relationships between the two techniques are clarified. The method is applied to data from a plantation of Eucalyptus in the Congo. [ABSTRACT FROM AUTHOR]

The extension of Mahalanobis's distance to the case of a mixture of discrete and continuousvariables is useful in many applications of discriminant analysis. In this note, the asymptotic chisquared distribution of the estimator of Matusita's distance under the null hypothesis is obtained and the rate of convergence is evaluated through simulations in the case of the location model. [ABSTRACT FROM AUTHOR]

Physical and cognitive performances change across lifespan. Studying cohorts of individuals in specific age ranges and athletic abilities remains essential in assessing the underlying physiological mechanisms that result in such a drop in performance. This decline is now viewed as a unique phenotypic biomarker and a hallmark of the aging process. The rates of decline are well documented for sets of traits such as running or swimming but only a limited number of studies have examined the developmental and senescent phases together. Moreover, the few attempts to do so are merely descriptive and do not include any meaningful biological features. Here we propose an averaged and deterministic model, based on cell population dynamics, replicative senescence and functionality loss. It describes the age-related change of performance in 17 time-series phenotypic traits, including human physical and cognitive skills, mouse lemur strength, greyhound and thoroughbred speed, and mouse activity. We demonstrate that the estimated age of peak performance occurs in the early part of life (20.5% ± 6.6% of the estimated lifespan) thus emphasizing the asymmetrical nature of the relationship. This model is an initial attempt to relate performance dynamics to cellular dynamics and will lead to more sophisticated models in the future. [ABSTRACT FROM AUTHOR]

Despite improved surveillance capacities and WHO recommendations for subdistrict analysis, routine epidemic surveillance of acute bacterial meningitis in the African meningitis belt remains largely limited to the district level. We evaluated the appropriateness and performance of analyses at higher spatial resolution. We used suspected meningitis surveillance data at health centre (HC) resolution from Burkina Faso from 14 health districts spanning years 2004–2014 and analysed them using spatio-temporal statistics and generative models. An operational analysis compared epidemic signals at district and HC-level using weekly incidence thresholds. Eighty-four percent (N = 98/116) of epidemic clusters spanned only one HC-week. Spatial propagation of epidemic clusters was mostly limited to 10–30 km. During the 2004–2009 (with serogroup A meningitis) and 2010–2014 (after serogroup A elimination) period, using weekly HC-level incidence thresholds of 100 and 50 per 100,000 respectively, we found a gain in epidemic detection and timeliness in 9 (41% of total) and 10 (67%), respectively, district years with at least one HC signal. Individual meningitis epidemics expanded little in space, suggesting that a health centre level analysis is most appropriate for epidemic surveillance. Epidemic surveillance could gain in precision and timeliness by higher spatial resolution. The optimal threshold should be defined depending on the current background incidence of bacterial meningitis. [ABSTRACT FROM AUTHOR]

This paper presents a study of two statistical post-processing methods implemented on forecasts of Meteo-France temperatures provided by the ensemble prediction system (EPS) The results are useful in the management of electricity consumption at EDF France. Those methods are the Best-Member Method (BMM) proposed by Fortin (2006), and the Bayesian Model Averaging method (BMA) proposed by Raftery (2004). The idea behind the BMM is to design for each lead time in the data set the best forecast among all k forecasts provided by the temperature prediction system, to construct an error pattern using only the errors made by those "best members" and to then "dress" all the members of the initial prediction system with this error pattern. The BMA method is a statistical method which combines predictive distributions from different sources. The BMA predictive probability density function (PDF) of the quantity of interest is a weighted average of PDFs centered on the bias-corrected forecasts, where the weights are equal to posterior probabilities of the models generating the forecasts and reflect the accuracy (skill) of the models over the training period. The resulting forecasts implemented on our data set are compared with one another and compared to the initial forecasts, using scores which measure the accuracy and/or the spread of the EPS: the Mean Absolute Error (MAE), the Root Mean Square Error (RMSE), the Ignorance Score, the Continuous Rank Probability Score (CRPS), the Talagrand Diagram, the Bias and the Mean. The purpose is to improve the probability density function of the forecasts, preserving at the same time the quality of the mean forecasts. The presentation is accessible to readers with an intermediate level of statistics. [ABSTRACT FROM AUTHOR]

Background: The Fukushima nuclear disaster has generated worldwide concern on the risk of exposure to nuclear radiations. In Europe, health authorities had to issue statements about the lack of usefulness of iodine based preventive treatments within their borders. However a lack of confidence in official messages has developed in various European countries due to recent perceived failures in managing public health crises. The lay population preventive behaviors in this context are largely unknown. Consequently, to examine the effects of public health crisis on lay behaviors leading to pharmaceuticals purchases, we studied the sales of iodine-based products in France before, during and after the crisis. Methods: We focused our study on 58 iodine-based drugs available with and without a physician prescription. Our data came from a stratified sample of 3004 pharmacies in metropolitan France. Our study period was from January 2010 to April 2012, with a focus on March-April 2011. We differentiated sales of drugs prescribed by physicians from sales of drugs obtained without a prescription. We used a CUSUM method to detect abnormal increases in sales activity and cross-correlations to assess shifts in sales timing. Results: Sales of iodine-based nutritional complements, and later sales of iodine-based homeopathic remedies, substantially increased (up to 3-fold) during a period of 20 days. Their temporal patterns were correlated to specific events during the crisis. Prescriptions for iodine-based homeopathy increased (up to 35% of all sales). Iodine pills, strictly regulated by health authorities, have also been sold but on a very small scale. Conclusion: These results indicate uncontrolled preventive behaviors resulting in the potentially unjustifiable consumption of available drugs. They have implications in public policy, and demonstrate the usefulness of drug sales surveillance for instantaneous evaluation of population behavior during a global crisis. [ABSTRACT FROM AUTHOR]

The bacterial and fungal communities associated with dandruff were investigated using culture-independent methodologies in the French subjects. The major bacterial and fungal species inhabiting the scalp subject’s were identified by cloning and sequencing of the conserved ribosomal unit regions (16S for bacterial and 28S-ITS for fungal) and were further quantified by quantitative PCR. The two main bacterial species found on the scalp surface were Propionibacterium acnes and Staphylococcus epidermidis, while Malassezia restricta was the main fungal inhabitant. Dandruff was correlated with a higher incidence of M. restricta and S. epidermidis and a lower incidence of P. acnes compared to the control population (p<0.05). These results suggested for the first time using molecular methods, that dandruff is linked to the balance between bacteria and fungi of the host scalp surface. [ABSTRACT FROM AUTHOR]

Complex, high-dimensional data sets pose significant analytical challenges in the post-genomic era. Such data sets are not exclusive to genetic analyses and are also pertinent to epidemiology. There has been considerable effort to develop hypothesis-free data mining and machine learning methodologies. However, current methodologies lack exhaustivity and general applicability. Here we use a novel non-parametric, non-euclidean data mining tool, HyperCube®, to explore exhaustively a complex epidemiological malaria data set by searching for over density of events in m-dimensional space. Hotspots of over density correspond to strings of variables, rules, that determine, in this case, the occurrence of Plasmodium falciparum clinical malaria episodes. The data set contained 46,837 outcome events from 1,653 individuals and 34 explanatory variables. The best predictive rule contained 1,689 events from 148 individuals and was defined as: individuals present during 1992-2003, aged 1-5 years old, having hemoglobin AA, and having had previous Plasmodium malariae malaria parasite infection ≤10 times. These individuals had 3.71 times more P. falciparum clinical malaria episodes than the general population. We validated the rule in two different cohorts. We compared and contrasted the HyperCube® rule with the rules using variables identified by both traditional statistical methods and non-parametric regression tree methods. In addition, we tried all possible sub-stratified quantitative variables. No other model with equal or greater representativity gave a higher Relative Risk. Although three of the four variables in the rule were intuitive, the effect of number of P. malariae episodes was not. HyperCube® efficiently sub-stratified quantitative variables to optimize the rule and was able to identify interactions among the variables, tasks not easy to perform using standard data mining methods. Search of local over density in m-dimensional space, explained by easily interpretable rules, is thus seemingly ideal for generating hypotheses for large datasets to unravel the complexity inherent in biological systems. [ABSTRACT FROM AUTHOR]

Model selection aims to find the best model. Most of the usual criteria are based on goodness of fit and parsimony and aim to maximize a transformed version of likelihood. The situation is less clear when two models are equivalent: are they close to the unknown true model or are they far from it? Based on simulations, we study the results of Vuong's test, Cox's test, AIC and BIC and the ability of these four tests to discriminate between models. [ABSTRACT FROM AUTHOR]

Projection matrix models are intensely used in ecology to model the dynamics of structured populations. When dealing with size-structured populations, there is no satisfactory algorithm to partition size into discrete classes. We show that the Vandermeer–Moloney algorithm for choosing classes is inconsistent with the Usher model, and systematically selects the finest classes. Considering that the matrix model is a discrete approximation of a continuous model, we define an approximation error as the sum of a distribution error (the difference between the discrete distribution and its continuous counterpart), and a sample error. The optimal partition of size into classes is the one that minimizes the approximation error. This method for choosing classes also shows that the choice of the class width cannot be disconnected from the choice of the time step. When applied to 520 trees of Dicorynia guianensis in French Guiana, this algorithm identified 8 classes of 11.4cm in width, which is in agreement with the empirical choice of foresters. [Copyright &y& Elsevier]

Background: Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis) allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data. Results: We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2. Conclusion: The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples. [ABSTRACT FROM AUTHOR]

Background: Drug iatrogeny is important but could be decreased if contraindications, cautions for use, drug interactions and adverse effects of drugs described in drug monographs were taken into account. However, the physician's time is limited during consultations, and this information is often not consulted. We describe here the design of "Mister VCM", a graphical interface based on the VCM graphical language, facilitating access to drug monographs. We also provide an assessment of the usability of this interface. Methods: The "Mister VCM" interface was designed by dividing the screen into two parts: a graphical interactive one including VCM icons and synthetizing drug properties, a textual one presenting on demand drug monograph excerpts. The interface was evaluated over 11 volunteer general practitioners, trained in the use of "Mister VCM". They were asked to answer clinical questions related to fictitious randomly generated drug monographs, using a textual interface or "Mister VCM". When answering the questions, correctness of the responses and response time were recorded. Results: "Mister VCM" is an interactive interface that displays VCM icons organized around an anatomical diagram of the human body with additional mental, etiological and physiological areas. Textual excerpts of the drug monograph can be displayed by clicking on the VCM icons. The interface can explicitly represent information implicit in the drug monograph, such as the absence of a given contraindication. Physicians made fewer errors with "Mister VCM" than with text (factor of 1.7; p = 0.034) and responded to questions 2.2 times faster (p < 0.001). The time gain with "Mister VCM" was greater for long monographs and questions with implicit replies. Conclusion: "Mister VCM" seems to be a promising interface for accessing drug monographs. Similar interfaces could be developed for other medical domains, such as electronic patient records. [ABSTRACT FROM AUTHOR]

Background: Many medication errors are encountered in drug prescriptions, which would not occur if practitioners could remember the drug properties. They can refer to drug monographs to find these properties, however drug monographs are long and tedious to read during consultation. We propose a two-step approach for facilitating access to drug monographs. The first step, presented here, is the design of a graphical language, called VCM. Methods: The VCM graphical language was designed using a small number of graphical primitives and combinatory rules. VCM was evaluated over 11 volunteer general practitioners to assess if the language is easy to learn, to understand and to use. Evaluators were asked to register their VCM training time, to indicate the meaning of VCM icons and sentences, and to answer clinical questions related to randomly generated drug monograph-like documents, supplied in text or VCM format. Results: VCM can represent the various signs, diseases, physiological states, life habits, drugs and tests described in drug monographs. Grammatical rules make it possible to generate many icons by combining a small number of primitives and reusing simple icons to build more complex ones. Icons can be organized into simple sentences to express drug recommendations. Evaluation showed that VCM was learnt in 2 to 7 hours, that physicians understood 89% of the tested VCM icons, and that they answered correctly to 94% of questions using VCM (versus 88% using text, p = 0.003) and 1.8 times faster (p < 0.001). Conclusion: VCM can be learnt in a few hours and appears to be easy to read. It can now be used in a second step: the design of graphical interfaces facilitating access to drug monographs. It could also be used for broader applications, including the design of interfaces for consulting other types of medical document or medical data, or, very simply, to enrich medical texts. [ABSTRACT FROM AUTHOR]

Biodiversity has undergone a major decline throughout recent decades, particularly in farmland. Agricultural practices are recognized to be an important pressure on farmland biodiversity, and pesticides are suspected to be one of the main causes of this decline in biodiversity. As part of the national plan for reduction of pesticides use (Ecophyto), the French ministry of agriculture launched the 500 ENI (nonintended effects) monitoring program in 2012 in order to assess the unintended effects of agricultural practices, including pesticide use, on biodiversity represented by several taxonomic groups of interest for farmers. This long‐term program monitors the biodiversity of nontargeted species (earthworms, plants, coleoptera, and birds), together with a wide range of annual data on agricultural practices (crop rotation, soil tillage, weed control, fertilizers, chemical treatments, etc.). Other parameters (e.g., landscape and climatic characteristics) are also integrated as covariates during the analyses. This monitoring program is expected to improve our understanding of the relative contribution of the different drivers of population and community trends. Here, we present the experience of setting up the 500 ENI network for this ambitious and highly complex monitoring program, as well as the type of data it collects. The issue of data quality control and some first results are discussed. With the aim of being useful to readers who would like to set up similar monitoring schemes, we also address some questions that have arisen following the first five years of the implementation phase of the program. [ABSTRACT FROM AUTHOR]

Dandruff is a scalp disorder characterized by the formation of flaky white-yellowish scales due to an altered proliferation and differentiation status; a disrupted barrier function; a decrease in the level of hydration and of natural moisturizing factors ( NMF) in the scalp, with a persistent and relapsing inflammatory condition. It was recently reported that an imbalance between bacterial and fungal species colonizing the scalp of French volunteers was associated with dandruff condition. The purpose of the present study was to analyze the major bacterial and fungal species present on the scalp surface of Chinese volunteers and to investigate possible region-related variation in the microbiota linked to dandruff condition. The data obtained from the Chinese populations were highly similar to those obtained in France, confirming that dandruff scalps are associated with a higher incidence of Malassezia restricta and Staphylococcal sp. The ratios of Malassezia to Propionibacterium and Propionibacterium to Staphylococcus were also significantly higher in the dandruff volunteers as compared to normal volunteers, suggesting that equilibrium between the major bacterial and fungal taxa found on the normal scalps is perturbed in the dandruff scalps. The main difference between the French and Shanghai subjects was in their Staphylococcal biota. The results obtained in China and in France suggest that targeting one particular Malassezia sp. by antifungals instead of using large spectrum antifungals and rebalancing the dandruff scalp microbiota could be common approach to improve dandruff condition in the two countries. [ABSTRACT FROM AUTHOR]

Acoustic population monitoring is a noninvasive method that can be deployed continuously over long periods of time and at large spatial scales. One of the newly discovered threats acting on biological diversity is anthropogenic noise. High levels of anthropogenic noise occur in aquatic environments, yet their effects on animals living in freshwater habitats have very rarely been investigated.Here, we used acoustic monitoring and automatic detection to assess the acoustic activity of a population of a soniferous freshwater insect.The sounds emitted by the corixid Micronecta scholtzi were recorded in a Mediterranean pond with an array of 12 hydrophones. An automatic analysis based on a measure of the amplitude found in the frequency band of M. scholtzi was developed to assess the level of acoustic activity. We used functional linear models, accounting for the periodicity of the calling behaviour, to estimate the possible effect of temperature, vegetation and a noise due to an immersed engine.The automatic analysis was validated as an efficient method to measure the acoustic activity. The monitoring revealed a clear 24‐hr pattern in the acoustic activity of M. scholtzi and three peaks of activity during the morning. Functional linear models revealed negative effects of both temperature and vegetation and showed that an engine noise, played back for 2 hr during the night, elicited an increase in the level of acoustic activity of the population. Moreover, a cross‐correlation procedure showed that noise delayed the acoustic activity of the population.Our results suggest that acoustic survey and automatic detection are efficient methods to monitor the acoustic activity of an insect population especially in response to an anthropogenic disturbance. [ABSTRACT FROM AUTHOR]

BACKGROUND: Bacterial meningitis causes a high burden of disease in the African meningitis belt, with regular seasonal hyperendemicity and sporadic short, but intense, localized epidemics during the late dry season occurring at a small spatial scale [i.e., below the district level, in individual health centers (HCs)]. In addition, epidemic waves with larger geographic extent occur every 7-10 y. Although atmospheric dust load is thought to be an essential factor for hyperendemicity, its role for localized epidemics remains hypothetic. OBJECTIVES: Our goal was to evaluate the association of localized meningitis epidemics in HC catchment areas with the dust load and the occurrence of cases in the same population early in the dry season. METHODS: We compiled weekly reported cases of suspected bacterial meningitis at the HC resolution for 14 districts of Burkina Faso for the period 2004-2014. Using logistic regression, we evaluated the association of epidemic HC-weeks with atmospheric dust [approximated by the aerosol optical thickness (AOT) satellite product] and with the observation of early meningitis cases during October-December. RESULTS: Although AOT was strongly associated with epidemic HC-weeks in crude analyses across all HC-weeks during the meningitis season [odds ratio (OR) = 6:82; 95% CI: 4.90, 9.50], the association was no longer apparent when controlling for calendar week (OR = 0:92; 95% CI: 0.60, 1.50). The number of early meningitis cases reported during October-December was associated with epidemic HC-weeks in the same HC catchment area during January-May of the following year (OR for each additional early case =1:14; 95% CI: 1.06, 1.21). CONCLUSIONS: Spatial variations of atmospheric dust load do not seem to be a factor in the occurrence of localized meningitis epidemics, and the factor triggering them remains to be identified. The pathophysiological mechanism linking early cases to localized epidemics is not understood, but their occurrence and number of early cases could be an indicator for epidemic risk. [ABSTRACT FROM AUTHOR]

The aim of this study was to quantify the impact of selections and shared selections in the rugby union. Players’ names, positions, and number of selections were collected for all XV de France’s games (1906–2014). Every team’s percentage of renewal of workforce was calculated for backs and forwards. During the 1987–2014 period, all second row forwards (locks), halfbacks, and centres’ shared selections (number of times when two players have competed together) were recreated. The Best vs. Rest method was applied to these remodelled dyads. They were analysed and compared with surrounding teammates as well as opponents. Head coaches similarly change their workforce for upcoming matches after winning or losing (around 30%), but losing teams renew significantly more positions in their line-ups. The recreated halfbacks, locks, and centres reveal a common pattern. Whether victorious or not, the ‘renewed couples’ victory percentage will congregate towards the XV de France’s victory percentage. For all the best recreated couples, the cumulated number of selections for forwards’ is always higher than the ones part of less efficient teams: 231.3 ± 80 vs. 212.9 ± 91 selections for locks’ teammates (Effect sizes (ES) small, possibly positive, 54.8%). In best recreated couples, number 8’s are significantly more experienced than their counterparts in less efficient pairs (ES small, likely positive, 76.3%). The XV de France’s collective effectiveness relies on a balance between stability and workforce renewal, which allows the building of specific position interactions and builds on experimented forwards packs. Selections and shared selections are serious collective performance parameters associated with performance. [ABSTRACT FROM PUBLISHER]

The era of genome-wide association studies (GWAS) has led to the discovery of numerous genetic variants associated with disease. Better understanding of whether these or other variants interact leading to differential risk compared with individual marker effects will increase our understanding of the genetic architecture of disease, which may be investigated using the family-based study design. We present M-TDT (the multi-locus transmission disequilibrium test), a tool for detecting family-based multi-locus multi-allelic effects for qualitative or quantitative traits, extended from the original transmission disequilibrium test (TDT). Tests to handle the comparison between additive and epistatic models, lack of independence between markers and multiple offspring are described. Performance of M-TDT is compared with a multifactor dimensionality reduction (MDR) approach designed for investigating families in the hypothesis-free genome-wide setting (the multifactor dimensionality reduction pedigree disequilibrium test, MDR-PDT). Other methods derived from the TDT or MDR to investigate genetic interaction in the family-based design are also discussed. The case of three independent biallelic loci is illustrated using simulations for one- to three-locus alternative hypotheses. M-TDT identified joint-locus effects and distinguished effectively between additive and epistatic models. We showed a practical example of M-TDT based on three genes already known to be implicated in malaria susceptibility. Our findings demonstrate the value of M-TDT in a hypothesis-driven context to test for multi-way epistasis underlying common disease etiology, whereas MDR-PDT-based methods are more appropriate in a hypothesis-free genome-wide setting. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented about a study that compared Internet search trends based on a list of Google queries related to influenza-like illness, gastroenteritis and chickenpox with clinical surveillance data from the French Sentinel Network.

Background: This systematic literature review aimed to summarize evidence for the added value of drug sales data analysis for the surveillance of infectious diseases. Methods: A search for relevant publications was conducted in Pubmed, Embase, Scopus, Cochrane Library, African Index Medicus and Lilacs databases. Retrieved studies were evaluated in terms of objectives, diseases studied, data sources, methodologies and performance for real-time surveillance. Most studies compared drug sales data to reference surveillance data using correlation measurements or indicators of outbreak detection performance (sensitivity, specificity, timeliness of the detection). Results: We screened 3266 articles and included 27 in the review. Most studies focused on acute respiratory and gastroenteritis infections. Nineteen studies retrospectively compared drug sales data to reference clinical data, and significant correlations were observed in 17 of them. Four studies found that over-the-counter drug sales preceded clinical data in terms of incidence increase. Five studies developed and evaluated statistical algorithms for selecting drug groups to monitor specific diseases. Another three studies developed models to predict incidence increase from drug sales. Conclusions: Drug sales data analyses appear to be a useful tool for surveillance of gastrointestinal and respiratory disease, and OTC drugs have the potential for early outbreak detection. Their utility remains to be investigated for other diseases, in particular those poorly surveyed. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: To assess the impact of a hygiene-encouragement program on reducing infection rates (primary end point) by 5%. Design: A cluster randomized study was carried out over a 5-month period. Settings and participants: Fifty nursing homes (NHs) with 4345 beds in France were randomly assigned by stratified-block randomization to either a multicomponent intervention (25 NHs) or an assessment only (25 NHs). Intervention: The multicomponent intervention was targeted to caregivers and consisted of implementing a bundle of infection prevention consensual measures. Interactive educational meetings using a slideshow were organized at the intervention NHs. The NHs were also provided with color posters emphasizing hand hygiene and a kit that included hygienic products such as alcoholic-based hand sanitizers. Knowledge surveys were performed periodically and served as reminders. Measurements: The primary end point was the total infection rate (urinary, respiratory, and gastrointestinal infections) in those infection cases classified either as definite or probable. Analyses corresponded to the underlying design and were performed according to the intention-to-treat principle. This study was registered (#NCT01069497). Results: Forty-seven NHs (4515 residents) were included and followed. The incidence rate of the first episode of infection was 2.11 per 1000 resident-days in the interventional group and 2.15 per 1000 resident-days in the control group; however, the difference between the groups did not reach statistical significance in either the unadjusted (Hazard Ratio [HR] = 1.00 [95% confidence interval (CI) 0.89–1.13]; P = .93]) or the adjusted (HR = 0.99 [95% CI 0.87–1.12]; P = .86]) analysis. Conclusion: Disentangling the impact of this type of intervention involving behavioral change in routine practice in caregivers from the prevailing environmental and contextual determinants is often complicated and confusing to interpret the results. [Copyright &y& Elsevier]

Despite considerable success of genome wide association (GWA) studies in identifying causal variants for many human diseases, their success in unraveling the genetic basis to complex diseases has been more mitigated. Pathogen population structure may impact upon the infectious phenotype, especially with the intense short-term selective pressure that drug treatment exerts on pathogens. Rigorous analysis that accounts for repeated measures and disentangles the influence of genetic and environmental factors must be performed. Attempts should be made to consider whether pathogen diversity will impact upon host genetic responses to infection. We analyzed the heritability of two Plasmodium falciparum phenotypes, the number of clinical malaria episodes (PFA) and the proportion of these episodes positive for gametocytes (Pfgam), in a family-based cohort followed for 19 years, during which time there were four successive drug treatment regimes, with documented appearance of drug resistance. Repeated measures and variance components analyses were performed with fixed environmental, additive genetic, intra-individual and maternal effects for each drug period. Whilst there was a significant additive genetic effect underlying PFA during the first drug period of study, this was lost in subsequent periods. There was no additive genetic effect for Pfgam. The intra-individual effect increased significantly in the chloroquine period. The loss of an additive genetic effect following novel drug treatment may result in significant loss of power to detect genes in a GWA study. Prior genetic analysis must be a pre-requisite for more detailed GWA studies. The temporal changes in the individual genetic and the intra-individual estimates are consistent with those expected if there were specific host-parasite interactions. The complex basis to the human response to malaria parasite infection likely includes dominance/epistatic genetic effects encompassed within the intra-individual variance component. Evaluating their role in influencing the outcome of infection through host genotype by parasite genotype interactions warrants research effort. [ABSTRACT FROM AUTHOR]

The aim of this study was to compare eight methods for the estimation of the image-derived input function (IDIF) in [18F]-FDG positron emission tomography (PET) dynamic brain studies. The methods were tested on two digital phantoms and on four healthy volunteers. Image-derived input functions obtained with each method were compared with the reference input functions, that is, the activity in the carotid labels of the phantoms and arterial blood samples for the volunteers, in terms of visual inspection, areas under the curve, cerebral metabolic rates of glucose (CMRglc), and individual rate constants. Blood-sample-free methods provided less reliable results as compared with those obtained using the methods that require the use of blood samples. For some of the blood-sample-free methods, CMRglc estimations considerably improved when the IDIF was calibrated with a single blood sample. Only one of the methods tested in this study, and only in phantom studies, allowed a reliable calculation of the individual rate constants. For the estimation of CMRglc values using an IDIF in [18F]-FDG PET brain studies, a reliable absolute blood-sample-free procedure is not available yet. [ABSTRACT FROM AUTHOR]

The article focuses on a study which developed a set of clinical and paraclinical diagnostic criteria for polyarteritis nodosa (PAN). The study analyzed the ability of individual descriptive items to diagnose PAN. After such analysis, the items were evaluated for usefulness in predicting PAN diagnosis. The study concluded that the use of positive and negative discriminant criteria can create a basis for developing a diagnostic tool for PAN.

The aim was to estimate the association between dairy products (total and their subgroups), calcium intake and the risk of breast cancer. As few studies have considered menopausal status, we also investigated stratified analyses. This analysis included 3,627 women from the French SU.VI.MAX study, among whom 92 developed breast cancer during the follow-up period. Food consumption was assessed based on five 24-hour records completed during the previous 18 months to follow-up. Calcium intake was calculated using an ad-hoc food composition database. Cox proportional hazards models were used to estimate relative risk (RR), comparing 4th quartile vs. 1st quartile, and 95% confidence intervals (95% CI). A lower risk of breast cancer was observed with high total dairy product consumption in the whole population (RR = 0.55, 95% CI = 0.29–1.03, ptrend = 0.03) and among premenopausal women with a RR of 0.35 (95% CI = 0.12–0.95, ptrend = 0.01). None of these associations remained after control for calcium intake. Increasing calcium intake was inversely associated with breast cancer risk considering the whole population (RR = 0.50, 95% CI = 0.27–0.91, ptrend = 0.04) and among the subgroup of premenopausal women (RR = 0.26, 95% CI = 0.10–0.71, ptrend = 0.01) respectively. Our data support the hypothesis that dairy products, through calcium content or a correlated component, might have a negative association with the risk of breast cancer, particularly among premenopausal women. Copyright © 2007 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

In human obesity, white adipose tissue (WAT) is enriched in macrophages. How macrophage infiltration in WAT contributes to the complications of obesity is unknown. This study tested the hypothesis that recruitment of macrophages in omental WAT is associated with hepatic damage in obese patients. Paired biopsies of subcutaneous and omental WAT and a liver biopsy were collected during gastric surgery in 46 obese women and 9 obese men (BMI 47.9 ± 0.93 kg/m²). The number of HAM56+ macrophages in WAT was quantified microscopically, and correlations with clinical and biological parameters and histological liver pathology were investigated. There were twice as many macrophages in omental as in subcutaneous WAT (P < 0.0001). After adjustment for age, omental WAT macrophage infiltration was correlated to fasting glucose and insulin, quantitative insulin sensitivity check index, triglycerides, aspartate aminotransferase (AST), and γ-glutamyltranspeptidase. We propose an easy equation to estimate the amount of macrophages in omental WAT. Increased macrophage accumulation specifically in omental WAT was associated with hepatic fibroinflammatory lesions (P = 0.01). The best predictive model for the severity of hepatic damage includes adiponectinemia, AST, and omental WAT macrophages. These data suggest that the presence of macrophages in omental WAT participates in the cellular mechanisms favoring hepatic fibroinflammatory lesions in obese patients. [ABSTRACT FROM AUTHOR]

The Velay sequence (France) provides a unique, continuous, palynological record spanning the last four climatic cycles. A pollen-based reconstruction of temperature and precipitation displays marked climatic cycles. An analysis of the climate and vegetation changes during the interglacial periods reveals comparable features and identical major vegetation successions. Although Marine Isotope Stage (MIS) 11.3 and the Holocene had similar earth precessional variations, their correspondence in terms of vegetation dynamics is low. MIS 9.5, 7.5, and especially 5.5 display closer correlation to the Holocene than MIS 11.3. Ecological factors, such as the distribution and composition of glacial refugia or postglacial migration patterns, may explain these discrepancies. Comparison of ecosystem dynamics during the past five interglacials suggests that vegetation development in the current interglacial has no analogue from the past 500,000 years. [ABSTRACT FROM AUTHOR]

Background: This systematic literature review aimed to summarize evidence for the added value of drug sales data analysis for the surveillance of infectious diseases.Methods: A search for relevant publications was conducted in Pubmed, Embase, Scopus, Cochrane Library, African Index Medicus and Lilacs databases. Retrieved studies were evaluated in terms of objectives, diseases studied, data sources, methodologies and performance for real-time surveillance. Most studies compared drug sales data to reference surveillance data using correlation measurements or indicators of outbreak detection performance (sensitivity, specificity, timeliness of the detection).Results: We screened 3266 articles and included 27 in the review. Most studies focused on acute respiratory and gastroenteritis infections. Nineteen studies retrospectively compared drug sales data to reference clinical data, and significant correlations were observed in 17 of them. Four studies found that over-the-counter drug sales preceded clinical data in terms of incidence increase. Five studies developed and evaluated statistical algorithms for selecting drug groups to monitor specific diseases. Another three studies developed models to predict incidence increase from drug sales.Conclusions: Drug sales data analyses appear to be a useful tool for surveillance of gastrointestinal and respiratory disease, and OTC drugs have the potential for early outbreak detection. Their utility remains to be investigated for other diseases, in particular those poorly surveyed. [ABSTRACT FROM AUTHOR]