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Detection of alloreactive anti-HLA antibodies is a frequent and mandatory test before and after organ transplantation to determine the antigenic targets of the antibodies. Nowadays, this test involves the measurement of fluorescent signals generated through antibody–antigen reactions on multi-beads flow cytometers. In this study, in a cohort of 1,066 patients from one country, anti-HLA class I responses were analyzed on a panel of 98 different antigens. Knowing that the immune system responds typically to “shared” antigenic targets, we studied the clustering patterns of antibody responses against HLA class I antigens without any a priori hypothesis, applying two unsupervised machine learning approaches. At first, the principal component analysis (PCA) projections of intra-locus specific responses showed that anti-HLA-A and anti-HLA-C were the most distantly projected responses in the population with the anti-HLA-B responses to be projected between them. When PCA was applied on the responses against antigens belonging to a single locus, some already known groupings were confirmed while several new cross-reactive patterns of alloreactivity were detected. Anti-HLA-A responses projected through PCA suggested that three cross-reactive groups accounted for about 70% of the variance observed in the population, while anti-HLA-B responses were mainly characterized by a distinction between previously described Bw4 and Bw6 cross-reactive groups followed by several yet undocumented or poorly described ones. Furthermore, anti-HLA-C responses could be explained by two major cross-reactive groups completely overlapping with previously described C1 and C2 allelic groups. A second feature-based analysis of all antigenic specificities, projected as a dendrogram, generated a robust measure of allelic antigenic distances depicting bead-array defined cross reactive groups. Finally, amino acid combinations explaining major population specific cross-reactive groups were described. The interpretation of the results was based on the current knowledge of the antigenic targets of the antibodies as they have been characterized either experimentally or computationally and appear at the HLA epitope registry.

International audience; Breast cancer (BC) is the most common form of cancer among women worldwide. Despite the huge advancements in its treatment, the exact etiology of breast cancer still remains unresolved. There is an increasing interest in the role of the gut microbiome in modulating the anti-cancer therapeutic response. It seems that alteration of the microbiome-derived metabolome potentially promotes carcinogenesis. Taken together, metabolomics has arisen as a fascinating new omics field to screen promising metabolic biomarkers. In this study, fecal metabolite profiling was performed using NMR spectroscopy, to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy (NAC) for breast cancer. Metabolic profiles of feces from patients (n = 8) following chemotherapy treatment cycles were studied. Interestingly, amino acids were found to be upregulated, while lactate and fumaric acid were downregulated in patients under the second and third cycles compared with patients before treatment. Furthermore, short-chain fatty acids (SCFAs) were significantly differentiated between the studied groups. These results strongly suggest that chemotherapy treatment plays a key role in modulating the fecal metabolomic profile of BC patients. In conclusion, we demonstrate the feasibility of identifying specific fecal metabolic profiles reflecting biochemical changes that occur during the chemotherapy treatment. These data give an interesting insight that may complement and improve clinical tools for BC monitoring.

International audience; Suicide is the leading cause of non-natural death worldwide, and major depressive disorder (MDD) is the mood disorder with the highest prevalence among individuals with suicidal behaviour (SB). The role of inflammation and immunomodulation in mood disorders has raised interest in recent years, as inflammation biomarkers have been reported to be increased in mood disorder patients, suggesting a role of inflammation in their pathogenesis. The influence of inflammation on the haematopoietic production is well known; however, a comprehensive study of the haematopoietic production in patients with major depressive episodes (MDE) is lacking. We examined global haematopoietic parameters from complete blood counts (CBC) of patients with MDE, in search of prognostic patterns. MDE patients presented differences in several CBC parameters, differences that were clearly pronounced and/or significant in concurrence with suicide attempts (SA). Red and white blood cell lineage parameters were affected, suggesting general haematopoietic modulation or imbalance. We observed distinct haematological parameter changes in women versus men, with men presenting milder alterations than women. Interestingly, we found that the List of Threatening Experiences (LTE) score, but not the Childhood Trauma Questionnaire (CTQ), was associated with the haematopoietic alterations observed exclusively in women and, more importantly, served as a parameter to stratify female MDE patients based on concurrence or non-concurrence with SA. In conclusion, grades of haematopoietic modulation in MDE patients are associated with absence or presence of SA. Haematopoietic manifestations differ between men and women and, in the latter, are markedly influenced by late, and not early, traumatic events.

Biological, technical, and environmental confounders are ubiquitous in the high-dimensional, high-throughput functional genomic measurements being used to understand cellular biology and disease processes, and many approaches have been developed to estimate and correct for unmeasured confounders... High-throughput measurements of molecular phenotypes provide an unprecedented opportunity to model cellular processes and their impact on disease. These highly structured datasets are usually strongly confounded, creating false positives and reducing power. This has motivated many approaches based on principal components analysis (PCA) to estimate and correct for confounders, which have become indispensable elements of association tests between molecular phenotypes and both genetic and nongenetic factors. Here, we show that these correction approaches induce a bias, and that it persists for large sample sizes and replicates out-of-sample. We prove this theoretically for PCA by deriving an analytic, deterministic, and intuitive bias approximation. We assess other methods with realistic simulations, which show that perturbing any of several basic parameters can cause false positive rate (FPR) inflation. Our experiments show the bias depends on covariate and confounder sparsity, effect sizes, and their correlation. Surprisingly, when the covariate and confounder have ρ2≈10%, standard two-step methods all have >10-fold FPR inflation. Our analysis informs best practices for confounder correction in genomic studies, and suggests many false discoveries have been made and replicated in some differential expression analyses.

Leprosy is a human infectious disease caused by Mycobacterium leprae. A strong host genetic contribution to leprosy susceptibility is well established. However, the modulation of the transcriptional response to infection and the mechanism(s) of disease control are poorly understood. To address this gap in knowledge of leprosy pathogenicity, we conducted a genome-wide search for expression quantitative trait loci (eQTL) that are associated with transcript variation before and after stimulation with M. leprae sonicate in whole blood cells. We show that M. leprae antigen stimulation mainly triggered the upregulation of immune related genes and that a substantial proportion of the differential gene expression is genetically controlled. Indeed, using stringent criteria, we identified 318 genes displaying cis-eQTL at an FDR of 0.01, including 66 genes displaying response-eQTL (reQTL), i.e. cis-eQTL that showed significant evidence for interaction with the M. leprae stimulus. Such reQTL correspond to regulatory variations that affect the interaction between human whole blood cells and M. leprae sonicate and, thus, likely between the human host and M. leprae bacilli. We found that reQTL were significantly enriched among binding sites of transcription factors that are activated in response to infection, and that they were enriched among single nucleotide polymorphisms (SNPs) associated with susceptibility to leprosy per se and Type-I Reaction, and seven of them have been targeted by recent positive selection. Our study suggested that natural selection shaped our genomic diversity to face pathogen exposure including M. leprae infection., Author summary Each year, 200,000 new leprosy cases are reported worldwide. While there is unambiguous evidence for a role of host genetics in leprosy pathogenesis, the mechanisms by which the human host fights the infection are poorly understood. Here, we highlight the search for naturally occurring genetic variations that modulate gene expression levels following exposure to sonicate of Mycobacterium leprae, the bacterium causing the disease. Because M. leprae is not cultivable and the genuine immune cells involved in the host response during infection are still unknown, we performed a genome-wide search for such genetic variations after stimulation of whole-blood from leprosy patients with M. leprae sonicate. This design allowed to provide a general framework for the genetic control of host responses to M. leprae and outlined the contribution of host genetics to leprosy pathogenesis. Among the M. leprae-dependent genetic regulators of gene expression levels there was an enrichment of variants (i) associated with leprosy, (ii) located in transcription factor binding sites and (iii) targeted by recent positive selection.

International audience; Infectious diseases are one of the most common threats for both domestic and wild animals, but little is known about the effects on the physiological condition and survival of wild animals. Here, we have tested for the first time in a wild vertebrate facing a viral disease possibly due to herpesvirus (i) whether nestlings with either low levels of oxidative damage or high levels of antioxidant protection are less susceptible to develop visible clinical signs, (ii) whether the disease is associated with the nestlings' oxidative status, (iii) whether the association between the disease and oxidative status is similar between males and females (iv), and whether cloacal and tracheal swabs might be used to detect herpesvirus. To address our questions, we took advantage of a population of Magnificent frigatebirds (Fregata magnificens) whose nestlings have experienced high mortality rates in recent times. Our work shows that (i) blood lipid oxidative damage is associated with observable clinical signs and survival probabilities of nestling frigatebirds, and (ii) that high glutathione levels in red blood cells are associated with the emergence of visible clinical signs of the disease. Our work provides evidence that differences in the oxidative status of nestlings might underlie individual health and survival.

The architecture of plant roots affects essential functions including nutrient and water uptake, soil anchorage, and symbiotic interactions. Root architecture comprises many features that arise from the growth of the primary and lateral roots. These root features are dictated by the genetic background but are also highly responsive to the environment. Thus, root system architecture (RSA) represents an important and complex trait that is highly variable, affected by genotype × environment interactions, and relevant to survival/performance. Quantification of RSA in Arabidopsis (Arabidopsis thaliana) using plate-based tissue culture is a very common and relatively rapid assay, but quantifying RSA represents an experimental bottleneck when it comes to medium- or high-throughput approaches used in mutant or genotype screens. Here, we present RootScape, a landmark-based allometric method for rapid phenotyping of RSA using Arabidopsis as a case study. Using the software AAMToolbox, we created a 20-point landmark model that captures RSA as one integrated trait and used this model to quantify changes in the RSA of Arabidopsis (Columbia) wild-type plants grown under different hormone treatments. Principal component analysis was used to compare RootScape with conventional methods designed to measure root architecture. This analysis showed that RootScape efficiently captured nearly all the variation in root architecture detected by measuring individual root traits and is 5 to 10 times faster than conventional scoring. We validated RootScape by quantifying the plasticity of RSA in several mutant lines affected in hormone signaling. The RootScape analysis recapitulated previous results that described complex phenotypes in the mutants and identified novel gene × environment interactions.

International audience; A fundamental condition for any work with free-ranging animals is correct species identification. However, in case of bats, information on local species assemblies is frequently limited especially in regions with high biodiversity such as the Neotropics. The bat genus Molossus is a typical example of this, with morphologically similar species often occurring in sympatry. We used a multi-method approach based on molecular, morphometric and acoustic information collected from 962 individuals of Molossus bondae, M. coibensis, and M. molossus captured in Panama. We distinguished M. bondae based on size and pelage coloration. We identified two robust species clusters composed of M. molossus and M. coibensis based on 18 microsatellite markers but also on a more stringently determined set of four markers. Phylogenetic reconstructions using the mitochondrial gene co1 (DNA barcode) were used to diagnose these microsatellite clusters as M. molossus and M. coibensis. To differentiate species, morphological information was only reliable when forearm length and body mass were combined in a linear discriminant function (95.9% correctly identified individuals). When looking in more detail at M. molossus and M. coibensis, only four out of 13 wing parameters were informative for species differentiation, with M. coibensis showing lower values for hand wing area and hand wing length and higher values for wing loading. Acoustic recordings after release required categorization of calls into types, yielding only two informative subsets: approach calls and two-toned search calls. Our data emphasizes the importance of combining morphological traits and independent genetic data to inform the best choice and combination of discriminatory information used in the field. Because parameters can vary geographically, the multi-method approach may need to be adjusted to local species assemblies and populations to be entirely informative.

This work was conducted in the environmental immunotoxicology laboratory at Institut Armand Frappier (IAF-INRS). Financial support has been provided by the Canada Research Chair in Environmental Immunotoxicology (Dr. Michel Fournier) and Collège Doctoral International de l'Université européenne de Bretagne. This study was also supported by the INTERREG IV program (DIESE): 50 % of the Ph.D. grant was obtained by the first author, for the development of immune markers in ecotoxicology.; International audience; A multibiomarker approach was developed on juvenile Atlantic tomcod (Microgadus tomcod) to evaluate the pertinence of this approach for low-cost screening assessment of the environmental quality of various coastal sites within estuaries. Several biometric indices and biomarkers (ethoxyresorufin-O-deethylase (EROD) activity, metallothionein concentration, and immune responses) were investigated on immature and maturing tomcods (≤ 31 months) collected in four environmentally contrasted sites in the St. Lawrence Estuary (SLE). Simultaneous examination of various age classes provides the opportunity to detect short-term responses in sensitive young-of-the-year fish (e.g., EROD induction) and longer-time effects associated with chronic exposure and bioaccumulation (e.g., metallothionein induction). Principal component analysis was helpful to discriminate between responses possibly related to contaminant exposure (EROD, metallothionein) and responses that could be affected by upstream-downstream gradient (immune response, biometric indices). Measurement of a battery of biomarkers in young tomcods at several sites along the shore of the SLE is a low-cost screening investigation useful to identify hot spots requiring further investigation with chemical analysis and additional reference sites.

International audience; BACKGROUND: In the field of nutritional epidemiology, principal component analysis (PCA) has been used to derive patterns, but the robustness of interpretation might be an issue when the sample size is small. The authors proposed the alternative use of confirmatory factor analysis (CFA) to define such patterns. OBJECTIVE: The aim was to compare dietary patterns derived through PCA and CFA used as equivalent approaches in terms of stability and relevance. DESIGN: PCA and CFA were performed in 2 different studies: the Epidemiological Study on the Genetics and Environment of Asthma 2-France (EGEA2-France; n = 1236) and the Phenotype and Course of Chronic Obstructive Pulmonary Disease study-Spain (n = 274). To check for stability, PCA and CFA were also performed in 2 subsamples from the EGEA2 study (n = 618 and 309). Statistical proprieties were evaluated by 1000 bootstrapped random sets of observations for each of the 4 subsamples. For each random set of observations, the distribution of the factor loading for each pattern was obtained and represented by using box-plots. To check for relevance, partial correlations between different nutrients and the different patterns derived by either PCA or CFA were calculated. RESULTS: With the use of CFA, 2 consistent dietary patterns were derived in each subsample (the Prudent and the Western patterns), whereas dietary factors were less interpretable with the use of PCA (smaller median of factor loadings and higher dispersion), especially for the smallest subsample. Higher correlations were reported among total fiber, vitamins, minerals, and total lipids with patterns derived by using CFA than with patterns derived by using PCA. CONCLUSION: The current study shows that CFA may be a useful alternative to PCA in epidemiologic studies, especially when the sample size is small.

GB and PNL contributed equally to this paper.; International audience; AIM: To evaluate a standardised MRI acquisition protocol and a new image rating scale for disease severity in patients with progressive supranuclear palsy (PSP) and multiple systems atrophy (MSA) in a large multicentre study. METHODS: The MRI protocol consisted of two-dimensional sagittal and axial T1, axial PD, and axial and coronal T2 weighted acquisitions. The 32 item ordinal scale evaluated abnormalities within the basal ganglia and posterior fossa, blind to diagnosis. Among 760 patients in the study population (PSP = 362, MSA = 398), 627 had per protocol images (PSP = 297, MSA = 330). Intra-rater (n = 60) and inter-rater (n = 555) reliability were assessed through Cohen's statistic, and scale structure through principal component analysis (PCA) (n = 441). Internal consistency and reliability were checked. Discriminant and predictive validity of extracted factors and total scores were tested for disease severity as per clinical diagnosis. RESULTS: Intra-rater and inter-rater reliability were acceptable for 25 (78%) of the items scored (≥ 0.41). PCA revealed four meaningful clusters of covarying parameters (factor (F) F1: brainstem and cerebellum; F2: midbrain; F3: putamen; F4: other basal ganglia) with good to excellent internal consistency (Cronbach α 0.75-0.93) and moderate to excellent reliability (intraclass coefficient: F1: 0.92; F2: 0.79; F3: 0.71; F4: 0.49). The total score significantly discriminated for disease severity or diagnosis; factorial scores differentially discriminated for disease severity according to diagnosis (PSP: F1-F2; MSA: F2-F3). The total score was significantly related to survival in PSP (p

Objective: To study, in a sample of French Family Practitioners (FPs), beliefs and attitudes toward depression and how they vary according to training received in mental health. Methods: The Depression Attitude Questionnaire (DAQ) was completed by 468 FPs from all regions of France, recruited by pharmaceutical company representatives to attend focus groups on the management of depression in general practice. Results: A three-factor model was derived from the DAQ, accounting for 37.7% of the total variance. The correlations between individual items of each component varied from 0.4 to 0.65, with an overall internal consistency of 0.47 (Cronbach's alpha). FPs had an overall neutral position on component 1, professional ease, a positive view on the origins of depression and its amenability to change (component 2), and a belief in the necessity of medication and the benefit of antidepressant therapy (component 3). Training in mental health, specifically through continuing medical education and postgraduate psychiatric hospital training, was significantly and positively associated with both professional ease and a medication approach to treating depression. Conclusion: This study is the first description of the beliefs and attitudes of French FPs toward depression using a standardized measure, the DAQ, despite the instrument's limited psychometric properties. It shows the positive effect of training in mental health on attitudes toward depression.

International audience; Sleep spindles are approximately 1 s bursts of 10-16 Hz activity that occur during stage 2 sleep. Spindles are highly synchronous across the cortex and thalamus in animals, and across the scalp in humans, implying correspondingly widespread and synchronized cortical generators. However, prior studies have noted occasional dissociations of the magnetoencephalogram (MEG) from the EEG during spindles, although detailed studies of this phenomenon have been lacking. We systematically compared high-density MEG and EEG recordings during naturally occurring spindles in healthy humans. As expected, EEG was highly coherent across the scalp, with consistent topography across spindles. In contrast, the simultaneously recorded MEG was not synchronous, but varied strongly in amplitude and phase across locations and spindles. Overall, average coherence between pairs of EEG sensors was approximately 0.7, whereas MEG coherence was approximately 0.3 during spindles. Whereas 2 principle components explained approximately 50% of EEG spindle variance, >15 were required for MEG. Each PCA component for MEG typically involved several widely distributed locations, which were relatively coherent with each other. These results show that, in contrast to current models based on animal experiments, multiple asynchronous neural generators are active during normal human sleep spindles and are visible to MEG. It is possible that these multiple sources may overlap sufficiently in different EEG sensors to appear synchronous. Alternatively, EEG recordings may reflect diffusely distributed synchronous generators that are less visible to MEG. An intriguing possibility is that MEG preferentially records from the focal core thalamocortical system during spindles, and EEG from the distributed matrix system.

International audience; In a series of highly influential publications, Cavalli-Sforza and colleagues used principal component (PC) analysis to produce maps depicting how human genetic diversity varies across geographic space. Within Europe, the first axis of variation (PC1) was interpreted as evidence for the demic diffusion model of agriculture, in which farmers expanded from the Near East approximately 10,000 years ago and replaced the resident hunter-gatherer populations with little or no interbreeding. These interpretations of the PC maps have been recently questioned as the original results can be reproduced under models of spatially covarying allele frequencies without any expansion. Here, we study PC maps for data simulated under models of range expansion and admixture. Our simulations include a spatially realistic model of Neolithic farmer expansion and assume various levels of interbreeding between farmer and resident hunter-gatherer populations. An important result is that under a broad range of conditions, the gradients in PC1 maps are oriented along a direction perpendicular to the axis of the expansion, rather than along the same axis as the expansion. We propose that this surprising pattern is an outcome of the "allele surfing" phenomenon, which creates sectors of high allele-frequency differentiation that align perpendicular to the direction of the expansion.

International audience; BACKGROUND AND OBJECTIVES: Neural blockade techniques are associated with a risk of acute cardiac toxicity after accidental intravenous (IV) injection of local anesthetics. The aim of this study was to compare electrocardiographic (ECG) and hemodynamic (HEM) effects induced by IV infusion of local anesthetics in an anesthetized ewe model. METHODS: Thirty-two anesthetized ewes received IV bupivacaine (BUPI), ropivacaine (ROPI), or levobupivacaine (S-BUPI) at an equimolar dose, or lidocaine (LIDO) at a 3-fold higher rate (n = 8 in each group). RR, PR, QRS, and QT intervals (QTc), changes (Delta) in systolic and diastolic arterial pressure (SAP and DAP), and in myocardial contractility (dP/dt), were assessed every 30 seconds for 7 minutes. From main ECG variables (RR, PR, QRS, QT), we proposed to use multiple correspondence analysis and hierarchical ascending classification to explore the structure of statistical dependencies among those measurements, and to determine the different patterns of ECG and HEM changes induced by infusion of BUPI, ROPI, S-BUPI, and LIDO. RESULTS: Graphic representation of multiple correspondence analysis associated BUPI with the most pronounced modifications in ECG and HEM variables, followed by in decreasing order ROPI, S-BUPI, and LIDO. Comparisons of clusters identified by hierarchical ascending classification confirmed this classification for ECG variables. Ventricular tachycardia occurred only in the BUPI group. CONCLUSIONS: In our anesthetized ewe model, high dose IV infusion of BUPI induced the most marked changes in RR, PR, QRS, QT, QTc intervals, DeltaSAP, and DeltadP/dt. ROPI altered ECG variables less than BUPI but more than S-BUPI. LIDO was associated with the smallest changes.

Comment in : Fusion of field studies and the laboratory solves a puzzle in antimalarial resistance. [Proc Natl Acad Sci U S A. 2015]; International audience; In regions with high malaria endemicity, the withdrawal of chloroquine (CQ) as first-line treatment of Plasmodium falciparum infections has typically led to the restoration of CQ susceptibility through the reexpansion of the wild-type (WT) allele K76 of the chloroquine resistance transporter gene (pfcrt) at the expense of less fit mutant alleles carrying the CQ resistance (CQR) marker K76T. In low-transmission settings, such as South America, drug resistance mutations can attain 100% prevalence, thereby precluding the return of WT parasites after the complete removal of drug pressure. In French Guiana, despite the fixation of the K76T allele, the prevalence of CQR isolates progressively dropped from >90% to

International audience; Principal component analysis (PCA) has been used extensively to derive dietary patterns. We proposed to use confirmatory factor analysis (CFA) in the same context as PCA--as a one-step approach--to derive dietary patterns. The first aim of this study was methodologic and was to compare dietary patterns derived with the use of PCA and CFA, used as equivalent one-step approaches. The second aim of this study was to study these patterns in association with individual characteristics and new adult-onset asthma. We included 30,589 French women from the E3N (epidemiologic prospective cohort study of women from the MGEN national insurance plan) with 1177 reported cases of adult-onset asthma between 1993 and 2005. PCA and CFA were used in the same context, on 27 food groups, to derive dietary patterns. Associations between dietary patterns and adult-onset asthma were assessed by Cox proportional hazards models. Whether we used PCA or CFA, 3 similar factors were found and labeled "Prudent," "Western," and "Aperitif." Correlations between patterns derived with the use of PCA and CFA were high. For the "Prudent" and "Aperitif" patterns, we observed comparable patterns in terms of associations with food groups, individual characteristics, and the onset of asthma. For the "Western" patterns, the one derived with the use of CFA was more related to an unhealthy diet than the one derived with the use of PCA, with higher correlations with the food groups "processed meat" (0.73 vs. 0.51) and "dough and pastry" (0.63 vs. 0.40), and negative associations with physical activity and with having parents who were farmers. Regarding associations with adult-onset asthma, a significant positive association was observed for the "Western" pattern derived with the use of CFA [multivariate RR for highest vs. lowest quintile: 1.30 (1.02, 1.67), P-trend: 0.03], whereas no association was reported when using PCA [RR: 1.14 (0.89, 1.47), P-trend: 0.40]. Although quite similar dietary patterns were derived with the use of PCA and CFA, this study supports the alternative use of CFA to PCA for the identification of dietary patterns in epidemiologic studies.

The White-browed Warbler Basileuterus leucoblepharus, a common bird of the BrazilianAtlantic forest, emits only one distinct song type in the context of territorial defense. Individual or neighbor-stranger recognition may be more difficult when birds share similar songs. In fact, the analysis of songs of different individuals reveals slight differences in the temporal and the frequency domains. Effectively, a careful examination of the signals of different individuals (21) by 5 complementary methods of analysis reveals first, that one or two gaps in frequency occur between two successive notes at different moments of the song, and second, that their temporal and frequency positions are stereotyped for each individual. Playback experiments confirm these findings. By propagation experiments, we show that this individual information can be only transmitted at short range (< 100 m) in the forest. In regard to the size and the repartition of territories, this communication process appears efficient and adaptive.O Pula-pula-assobiador Basileuterus leucoblepharus, um pássaro comum da Mata Atlântica, emite um único e distintivo tipo de canto para defesa territorial. O reconhecimento individual ou entre vizinho e estranho pode ser mais difícil quando as aves compartilham cantos semelhantes. De fato, a análise dos cantos de diferentes indivíduos revelou ligeiras diferenças nos domínios temporal e das freqüências. Efetivamente, um exame cuidadoso dos sinais de 21 indivíduos diferentes por 5 métodos complementares de análise revelou que, primeiro, um ou dois espaços na série tonal ocorrem entre duas notas sucessivas em determinados momentos do canto e, segundo, ocupam posições em tempo e freqüência estereotipadas para cada indivíduo. Experiências de "play-back" confirmam esses dados. Através de experiências de propagação, mostramos que esta informação individual pode ser transmitida somente a curta distância ( < 100 m) na mata. Considerando o tamanho e a repartição dos territórios, este processo de comunicação mostra-se eficiente e bem adaptado.

Chagas disease is caused by the parasite Trypanosoma cruzi, and it begins with a short acute phase characterized by high parasitemia followed by a life-long chronic phase with scarce parasitism. Cardiac involvement is the most prominent manifestation, as 30% of infected subjects will develop abnormal ventricular repolarization with myocarditis, fibrosis and cardiomyocyte hypertrophy by undefined mechanisms. Nevertheless, follow-up studies in chagasic patients, as well as studies with murine models, suggest that the intensity of clinical symptoms and pathophysiological events that occur during the acute phase of disease are associated with the severity of cardiac disease observed during the chronic phase. In the present study we investigated the role of microRNAs (miRNAs) in the disease progression in response to T. cruzi infection, as alterations in miRNA levels are known to be associated with many cardiovascular disorders. We screened 641 rodent miRNAs in heart samples of mice during an acute infection with the Colombiana T.cruzi strain and identified multiple miRNAs significantly altered upon infection. Seventeen miRNAs were found significantly deregulated in all three analyzed time points post infection. Among these, six miRNAs had their expression correlated with clinical parameters relevant to the disease, such as parasitemia and maximal heart rate-corrected QT (QTc) interval. Computational analyses identified that the gene targets for these six miRNAs were involved in networks and signaling pathways related to increased ventricular depolarization and repolarization times, important factors for QTc interval prolongation. The data presented here will guide further studies about the contribution of microRNAs to Chagas heart disease pathogenesis., Author Summary Chagas’ disease is caused by the protozoan parasite Trypanosoma cruzi and affects 8 million individuals worldwide. The life-long infection begins with a short acute phase, which is associated to parasites circulating in the bloodstream, tissue parasitism, and various signs and symptoms including those related to myocarditis. After resolution of the acute phase, about 30% of those chronically infected will develop abnormal ventricular repolarization with hypertrophy, myocarditis and fibrosis by yet undefined mechanisms. MicroRNAs play a key role in silencing gene expression and are essential elements of the physiology and pathophysiology of the cardiovascular system. Here we describe for the first time the effect of acute T. cruzi infection on host miRNA expression by screening 641 rodent miRNAs in heart samples. A number of miRNAs have significantly altered expression upon infection and several of them correlate with T. cruzi parasitism and electrocardiographic changes. Pathway analysis results suggest that these dysregulated miRNAs can potentially affect gene networks and signaling pathways related to increased ventricular depolarization and repolarization times. Our study provides new insights on miRNA regulation of genes relevant to parasitological and cardiological outcomes.

International audience; Many human traits are highly correlated. This correlation can be leveraged to improve the power of genetic association tests to identify markers associated with one or more of the traits. Principal component analysis (PCA) is a useful tool that has been widely used for the multivariate analysis of correlated variables. PCA is usually applied as a dimension reduction method: the few top principal components (PCs) explaining most of total trait variance are tested for association with a predictor of interest, and the remaining components are not analyzed. In this study we review the theoretical basis of PCA and describe the behavior of PCA when testing for association between a SNP and correlated traits. We then use simulation to compare the power of various PCA-based strategies when analyzing up to 100 correlated traits. We show that contrary to widespread practice, testing only the top PCs often has low power, whereas combining signal across all PCs can have greater power. This power gain is primarily due to increased power to detect genetic variants with opposite effects on positively correlated traits and variants that are exclusively associated with a single trait. Relative to other methods, the combined-PC approach has close to optimal power in all scenarios considered while offering more flexibility and more robustness to potential confounders. Finally, we apply the proposed PCA strategy to the genome-wide association study of five correlated coagulation traits where we identify two candidate SNPs that were not found by the standard approach.

International audience; Fossil-based estimates of diversity and evolutionary dynamics mainly rely on the study of morphological variation. Unfortunately, organism remains are often altered by post-mortem taphonomic processes such as weathering or distortion. Such a loss of information often prevents quantitative multivariate description and statistically-controlled comparisons of extinct species based on morphometric data. A common way to deal with missing data involves imputation methods that directly fill the missing cases with model estimates. Over the last years, several empirically-determined thresholds for the maximum acceptable proportion of missing values have been proposed in the literature, whereas other studies showed that this limit actually depends on various properties of the study data set and of the selected imputation method, and is by no way generalizable. We evaluate the relative performances of seven multiple imputation (MI) techniques through a simulation-based analysis under three distinct patterns of missing data distribution. Overall, Fully Conditional Specification and Expectation-Maximization algorithms provide the best compromises between imputation accuracy and coverage probability. MI techniques appear remarkably robust to the violation of basic assumptions such as the occurrence of taxonomically or anatomically biased patterns of missing data distribution, making differences in simulation results between the three patterns of missing data distribution much smaller than differences between the individual MI techniques. Based on these results, rather than proposing a new (set of) threshold value(s), we develop an approach combining the use of MIs with procrustean superimposition of principal component analysis results, in order to directly visualize the effect of individual missing data imputation on an ordinated space. We provide an R function for users to implement the proposed procedure.

International audience; Protein-protein interactions (PPI) are involved in vital cellular processes and are therefore associated to a growing number of diseases. But working with them as therapeutic targets comes with some major hurdles that require substantial mutations from our way to design drugs on historical targets such as enzymes and G-Protein Coupled Receptor (GPCR). Among the numerous ways we could improve our methodologies to maximize the potential of developing new chemical entities on PPI targets, is the fundamental question of what type of compounds should we use to identify the first hits and among which chemical space should we navigate to optimize them to the drug candidate stage. In this review article, we cover different aspects on PPI but with the aim to gain some insights into the specific nature of the chemical space of PPI inhibitors. We describe the work of different groups to highlight such properties and discuss their respective approach. We finally discuss a case study in which we describe the properties of a set of 115 PPI inhibitors that we compare to a reference set of 1730 enzyme inhibitors. This case study highlights interesting properties such as the unfortunate price that still needs to be paid by PPI inhibitors in terms of molecular weight, hydrophobicity, and aromaticity in order to reach a critical level of activity. But it also shows that not all PPI targets are equivalent, and that some PPI targets can demonstrate a better druggability by illustrating the better drug likeness of their associated inhibitors.

The origin of Plasmodium falciparum in South America is controversial. Some studies suggest a recent introduction during the European colonizations and the transatlantic slave trade. Other evidence—archeological and genetic—suggests a much older origin. We collected and analyzed P. falciparum isolates from different regions of the world, encompassing the distribution range of the parasite, including populations from sub-Saharan Africa, the Middle East, Southeast Asia, and South America. Analyses of microsatellite and SNP polymorphisms show that the populations of P. falciparum in South America are subdivided in two main genetic clusters (northern and southern). Phylogenetic analyses, as well as Approximate Bayesian Computation methods suggest independent introductions of the two clusters from African sources. Our estimates of divergence time between the South American populations and their likely sources favor a likely introduction from Africa during the transatlantic slave trade.

International audience; A new automatic model-based segmentation scheme that combines level set shape modeling and active appearance modeling (AAM) is presented. Since different MR image contrasts can yield complementary information, multi-contrast images can be incorporated into the active appearance modeling to improve segmentation performance. During active appearance modeling, the weighting of each contrast is optimized to account for the potentially varying contribution of each image while optimizing the model parameters that correspond to the shape and appearance eigen-images in order to minimize the difference between the multi-contrast test images and the ones synthesized from the shape and appearance modeling. As appearance-based modeling techniques are dependent on the initial alignment of training data, we compare (i) linear alignment of whole brain, (ii) linear alignment of a local volume of interest and (iii) non-linear alignment of a local volume of interest. The proposed segmentation scheme can be used to segment human hippocampi (HC) and amygdalae (AG), which have weak intensity contrast with their background in MRI. The experiments demonstrate that non-linear alignment of training data yields the best results and that multimodal segmentation using T1-weighted, T2-weighted and proton density-weighted images yields better segmentation results than any single contrast. In a four-fold cross validation with eighty young normal subjects, the method yields a mean Dice к of 0.87 with intraclass correlation coefficient (ICC) of 0.946 for HC and a mean Dice к of 0.81 with ICC of 0.924 for AG between manual and automatic labels.

International audience; In French Guiana, severe cases of toxoplasmosis in immunocompetent patients are associated with atypical strains of Toxoplasma gondii linked to a wild neotropical rainforest cycle and a higher genetic diversity than usually observed for T. gondii isolates from anthropized environment. This raises the question of the impact of anthropization of the natural environment, on genetic diversity and on the population structure of T. gondii. However, few data are available on strains circulating in the anthropized areas from French Guiana. Seropositive animals originating mainly from anthropized sub-urban areas and punctually from wild environment in French Guiana were analyzed for T. gondii isolation and genotyping. Thirty-three strains were obtained by bioassay in mice and compared with 18 previously reported isolates chiefly originating from the Amazon rainforest. The genotyping analysis performed with 15 microsatellite markers located on 12 different chromosomes revealed a lower genetic diversity in the anthropized environment. Results were analyzed in terms of population structure by clustering methods, Neighbor-joining trees reconstruction based on genetic distances, F(ST,) Mantel's tests and linkage disequilibrium. They clearly showed a genetic differentiation between strains associated to the anthropized environment and those associated to the wild, but with some inbreeding between them. The majority of strains from the anthropized environment were clustered into additional lineages of T. gondii that are common in the Caribbean. In conclusion the two environmental populations "wild" and "anthropized" were genetically well differentiated. The anthropization of the environment seems to be accompanied with a decreased diversity of T. gondii associated with a greater structure of the populations. We detected potential interpenetration and genetic exchanges between these two environmental populations. As a higher pathogenicity in human of "wild" genotypes has been described, the interpenetration of both environments leads to hybridization between strains that may be at risk for human health.

Background Improvements in the techniques for metabolomics analyses and growing interest in metabolomic approaches are resulting in the generation of increasing numbers of metabolomic profiles. Platforms are required for profile management, as a function of experimental design, and for metabolite identification, to facilitate the mining of the corresponding data. Various databases have been created, including organism-specific knowledgebases and analytical technique-specific spectral databases. However, there is currently no platform meeting the requirements for both profile management and metabolite identification for nuclear magnetic resonance (NMR) experiments. Description MeRy-B, the first platform for plant 1H-NMR metabolomic profiles, is designed (i) to provide a knowledgebase of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata, (ii) for queries and visualization of the data, (iii) to discriminate between profiles with spectrum visualization tools and statistical analysis, (iv) to facilitate compound identification. It contains lists of plant metabolites and unknown compounds, with information about experimental conditions, the factors studied and metabolite concentrations for several plant species, compiled from more than one thousand annotated NMR profiles for various organs or tissues. Conclusion MeRy-B manages all the data generated by NMR-based plant metabolomics experiments, from description of the biological source to identification of the metabolites and determinations of their concentrations. It is the first database allowing the display and overlay of NMR metabolomic profiles selected through queries on data or metadata. MeRy-B is available from http://www.cbib.u-bordeaux2.fr/MERYB/index.php.

International audience; As part of Genetic Analysis Workshop 17 (GAW17), our group considered the application of novel and standard approaches to the analysis of genotype-phenotype association in next-generation sequencing data. Our group identified a major issue in the analysis of the GAW17 next-generation sequencing data: type I error and false-positive report probability rates higher than those expected based on empirical type I error levels (as high as 90%). Two main causes emerged: population stratification and long-range correlation (gametic phase disequilibrium) between rare variants. Population stratification was expected because of the diverse sample. Correlation between rare variants was attributable to both random causes (e.g., nearly 10,000 of 25,000 markers were private variants, and the sample size was small [n = 697]) and nonrandom causes (more correlation was observed than was expected by random chance). Principal components analysis was used to control for population structure and helped to minimize type I errors, but this was at the expense of identifying fewer causal variants. A novel multiple regression approach showed promise to handle correlation between markers. Further work is needed, first, to identify best practices for the control of type I errors in the analysis of sequencing data and then to explore and compare the many promising new aggregating approaches for identifying markers associated with disease phenotypes.

Background Picoeukaryotes represent an important, yet poorly characterized component of marine phytoplankton. The recent genome availability for two species of Ostreococcus and Micromonas has led to the emergence of picophytoplankton comparative genomics. Sequencing has revealed many unexpected features about genome structure and led to several hypotheses on Ostreococcus biology and physiology. Despite the accumulation of genomic data, little is known about gene expression in eukaryotic picophytoplankton. Results We have conducted a genome-wide analysis of gene expression in Ostreococcus tauri cells exposed to light/dark cycles (L/D). A Bayesian Fourier Clustering method was implemented to cluster rhythmic genes according to their expression waveform. In a single L/D condition nearly all expressed genes displayed rhythmic patterns of expression. Clusters of genes were associated with the main biological processes such as transcription in the nucleus and the organelles, photosynthesis, DNA replication and mitosis. Conclusions Light/Dark time-dependent transcription of the genes involved in the main steps leading to protein synthesis (transcription basic machinery, ribosome biogenesis, translation and aminoacid synthesis) was observed, to an unprecedented extent in eukaryotes, suggesting a major input of transcriptional regulations in Ostreococcus. We propose that the diurnal co-regulation of genes involved in photoprotection, defence against oxidative stress and DNA repair might be an efficient mechanism, which protects cells against photo-damage thereby, contributing to the ability of O. tauri to grow under a wide range of light intensities.

International audience; INTRODUCTION: Breast carcinoma is the main malignant tumor occurring in patients with Cowden disease, a cancer-prone syndrome caused by germline mutation of the tumor suppressor gene PTEN characterized by the occurrence throughout life of hyperplastic, hamartomatous and malignant growths affecting various organs. The absence of known histological features for breast cancer arising in a PTEN-mutant background prompted us to explore them for potential new markers. METHODS: We first performed a microarray study of three tumors from patients with Cowden disease in the context of a transcriptomic study of 74 familial breast cancers. A subsequent histological and immunohistochemical study including 12 additional cases of Cowden disease breast carcinomas was performed to confirm the microarray data. RESULTS: Unsupervised clustering of the 74 familial tumors followed the intrinsic gene classification of breast cancer except for a group of five tumors that included the three Cowden tumors. The gene expression profile of the Cowden tumors shows considerable overlap with that of a breast cancer subgroup known as molecular apocrine breast carcinoma, which is suspected to have increased androgenic signaling and shows frequent ERBB2 amplification in sporadic tumors. The histological and immunohistochemical study showed that several cases had apocrine histological features and expressed GGT1, which is a potential new marker for apocrine breast carcinoma. CONCLUSIONS: These data suggest that activation of the ERBB2-PI3K-AKT pathway by loss of PTEN at early stages of tumorigenesis promotes the formation of breast tumors with apocrine features.

International audience; An extension of the original implementation of JADE, named eJADE((1)) hereafter, was proposed in 2001 to perform independent component analysis for any combination of statistical orders greater than or equal to three. More precisely, eJADE((1)) relies on the joint diagonalization of a set of several cumulant matrices corresponding to different matrix slices of one or several higher order cumulant tensors. An efficient way, without lose of statistical information, of reducing the number of third and fourth order cumulant matrices to be jointly diagonalized is proposed in this paper. The resulting approach, named eJADE(3,4)((2)), can be interpreted as an improvement of the eJADE(3,4)((1)) method. A performance comparison with classical methods is conducted in the context of MRS and EEG signals showing the good behavior of our technique.

High milk proteins powders are common ingredients in many food products. The surface composition of these powders is expected to play an essential role during their storage, handling and/or final application. Therefore, an eventual control of the surface composition by modifying the spray-drying temperature could be very useful in the improvement of powder quality and the development of new applications. For this purpose, the influence of five spray-drying temperatures upon the surface composition of the powders was investigated by X-ray photoelectron spectroscopy. The major milk proteins were studied: native micellar casein and native whey, both more or less enriched in lactose. The results show a surface enrichment in lipids for all the powders and in proteins for many powders. Whatever the drying temperature, lipids and proteins are preferentially located near the surface whereas lactose is found in the core. This surface enrichment is also highly affected by the spray-drying temperature. More lipids, more proteins and less lactose are systematically observed at the surface of powders spray-dried at lower outlet air temperatures. The nature of proteins is also found essential; surface enrichment in lipids being much stronger for whey proteins containing powders than for casein containing powders. Additionally, we found a direct correlation between the lipids surface concentration and the wetting ability for the 25 powders studied.

International audience; Syndecan-1 is a proteoglycan that concentrates heparin-binding factors on the surface of multiple myeloma cells, and probably plays a major role in multiple myeloma biology. As heparan sulphate and chondroitin sulphate are the bioactive components of syndecan-1, we analysed the signature of genes encoding 100 proteins involved in synthesis of these chains, i.e. from precursor uptake to post-translational modifications, using Affymetrix microarrays. The expression of enzymes required for heparan sulphate and chondroitin sulphate biosynthesis was shown to increase in parallel with syndecan-1 expression, throughout the differentiation of memory B cells into plasmablasts and normal bone marrow plasma cells. Sixteen genes were significantly different between normal and malignant plasma cells, nine of these genes -EXT2, CHSY3, CSGALNACT1, HS3ST2, HS2ST1, CHST11, CSGALNACT2, HPSE, SULF2 - encode proteins involved in glycosaminoglycan chain synthesis or modifications. Kaplan-Meier analysis was performed in two independent series of patients: B4GALT7, CSGALNACT1, HS2ST1 were associated with a good prognosis whereas EXT1 was linked to a bad prognosis. This study provides an overall picture of the major genes encoding for proteins involved in heparan sulphate and chondroitin sulphate synthesis and modifications that can be implicated in normal and malignant plasma cells.

Background The first week of human pre-embryo development is characterized by the induction of totipotency and then pluripotency. The understanding of this delicate process will have far reaching implication for in vitro fertilization and regenerative medicine. Human mature MII oocytes and embryonic stem (ES) cells are both able to achieve the feat of cell reprogramming towards pluripotency, either by somatic cell nuclear transfer or by cell fusion, respectively. Comparison of the transcriptome of these two cell types may highlight genes that are involved in pluripotency initiation. Results Based on a microarray compendium of 205 samples, we compared the gene expression profile of mature MII oocytes and human ES cells (hESC) to that of somatic tissues. We identified a common oocyte/hESC gene expression profile, which included a strong cell cycle signature, genes associated with pluripotency such as LIN28 and TDGF1, a large chromatin remodelling network (TOP2A, DNMT3B, JARID2, SMARCA5, CBX1, CBX5), 18 different zinc finger transcription factors, including ZNF84, and several still poorly annotated genes such as KLHL7, MRS2, or the Selenophosphate synthetase 1 (SEPHS1). Interestingly, a large set of genes was also found to code for proteins involved in the ubiquitination and proteasome pathway. Upon hESC differentiation into embryoid bodies, the transcription of this pathway declined. In vitro, we observed a selective sensitivity of hESC to the inhibition of the activity of the proteasome. Conclusion These results shed light on the gene networks that are concurrently overexpressed by the two human cell types with somatic cell reprogramming properties.

Background Genome size and gene content in bacteria are associated with their lifestyles. Obligate intracellular bacteria (i.e., mutualists and parasites) have small genomes that derived from larger free-living bacterial ancestors; however, the different steps of bacterial specialization from free-living to intracellular lifestyle have not been studied comprehensively. The growing number of available sequenced genomes makes it possible to perform a statistical comparative analysis of 317 genomes from bacteria with different lifestyles. Results Compared to free-living bacteria, host-dependent bacteria exhibit fewer rRNA genes, more split rRNA operons and fewer transcriptional regulators, linked to slower growth rates. We found a function-dependent and non-random loss of the same 100 orthologous genes in all obligate intracellular bacteria. Thus, we showed that obligate intracellular bacteria from different phyla are converging according to their lifestyle. Their specialization is an irreversible phenomenon characterized by translation modification and massive gene loss, including the loss of transcriptional regulators. Although both mutualists and parasites converge by genome reduction, these obligate intracellular bacteria have lost distinct sets of genes in the context of their specific host associations: mutualists have significantly more genes that enable nutrient provisioning whereas parasites have genes that encode Types II, IV, and VI secretion pathways. Conclusion Our findings suggest that gene loss, rather than acquisition of virulence factors, has been a driving force in the adaptation of parasites to eukaryotic cells. This comparative genomic analysis helps to explore the strategies by which obligate intracellular genomes specialize to particular host-associations and contributes to advance our knowledge about the mechanisms of bacterial evolution. Reviewers This article was reviewed by Eugene V. Koonin, Nicolas Galtier, and Jeremy Selengut.

International audience; BACKGROUND: To explore clinical heterogeneity of Duchenne muscular dystrophy (DMD), viewed as a major obstacle to the interpretation of therapeutic trials METHODOLOGY/PRINCIPAL FINDINGS: A retrospective single institution long-term follow-up study was carried out in DMD patients with both complete lack of muscle dystrophin and genotyping. An exploratory series (series 1) was used to assess phenotypic heterogeneity and to identify early criteria predicting future outcome; it included 75 consecutive steroid-free patients, longitudinally evaluated for motor, respiratory, cardiac and cognitive functions (median follow-up: 10.5 yrs). A validation series (series 2) was used to test robustness of the selected predictive criteria; it included 34 more routinely evaluated patients (age>12 yrs). Multivariate analysis of series 1 classified 70/75 patients into 4 clusters with distinctive intellectual and motor outcomes: A (early infantile DMD, 20%): severe intellectual and motor outcomes; B (classical DMD, 28%): intermediate intellectual and poor motor outcome; C (moderate pure motor DMD, 22%): normal intelligence and delayed motor impairment; and D (severe pure motor DMD, 30%): normal intelligence and poor motor outcome. Group A patients had the most severe respiratory and cardiac involvement. Frequency of mutations upstream to exon 30 increased from group A to D, but genotype/phenotype correlations were restricted to cognition (IQ>71: OR 7.7, 95%CI 1.6-20.4, p6 at 8 yrs" with "normal or borderline mental status" reliably assigned patients to group C (sensitivity: 1, specificity: 0.94). These criteria were also predictive of "early infantile DMD" and "moderate pure motor DMD" in series 2. CONCLUSIONS/SIGNIFICANCE: DMD can be divided into 4 sub-phenotypes differing by severity of muscle and brain dysfunction. Simple early criteria can be used to include patients with similar outcomes in future therapeutic trials.

SUMMARY Song geographic variation and Neighbour–Stranger (N–S)discrimination have been intensively but separately studied in bird species,especially in those with small- to medium-sized repertoires. Here, we establish a link between the two phenomena by showing that dialect features are used for N–S recognition in a territorial species with a large repertoire, the skylark Alauda arvensis. In this species, during the breeding season, many pairs settle in stable and adjoining territories gathered in locations spaced by a few kilometres. In a first step, songs produced by males established in different locations were recorded, analyzed and compared to identify possible microgeographic variation at the syntax level. Particular common sequences of syllables (phrases) were found in the songs of all males established in the same location (neighbours), whereas males of different locations (strangers) shared only few syllables and no sequences. In a second step, playback experiments were conducted and provided evidence for N–S discrimination consistent with the dear-enemy effect,i.e. reduced aggression from territorial birds towards neighbours than towards strangers. In addition, a similar response was observed when a `chimeric'signal (shared phrases of the location artificially inserted in the song of a stranger) and a neighbour song were broadcast, indicating that shared sequences were recognized and identified as markers of the group identity. We thus show experimentally that the shared phrases found in the songs of neighbouring birds constitute a group signature used by birds for N–S discrimination, and serve as a basis for the dear-enemy effect.

Background Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks in order to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation. Results We propose a method to integrate a priori the knowledge of a gene network in the analysis of gene expression data. The approach is based on the spectral decomposition of gene expression profiles with respect to the eigenfunctions of the graph, resulting in an attenuation of the high-frequency components of the expression profiles with respect to the topology of the graph. We show how to derive unsupervised and supervised classification algorithms of expression profiles, resulting in classifiers with biological relevance. We illustrate the method with the analysis of a set of expression profiles from irradiated and non-irradiated yeast strains. Conclusion Including a priori knowledge of a gene network for the analysis of gene expression data leads to good classification performance and improved interpretability of the results.

International audience; The aim of this paper is to present the collection of attitude sensor data from an epilepsy monitoring unit and the results of standard exploration using principal component analysis. The collection of data from attitude sensors positioned on three limbs of epileptic patients at their bedside is described. The analysis of the data focuses, on one hand, on motor features extraction from attitude sensor data and on the other hand, on visual segmentation of seizures into events corresponding to motor manifestations classes by an expert. Principal component analysis is then realized over these features and groups of data are localized according to the expert classification. This exploration indicates a possible discrimination between these motor manifestation classes.

AIMS/HYPOTHESIS: We devised a practical continuous score to assess the metabolic syndrome, and assessed whether this syndrome score predicts incident diabetes and cardiovascular disease. SUBJECTS AND METHODS: Among 5,024 participants of the Data from an Epidemiological Study on the Insulin Resistance Syndrome (D.E.S.I.R.) cohort, we defined a metabolic syndrome score by the first principal component (PC1), using only the correlations between continuous metabolic syndrome measures (glucose, waist circumference, triglycerides, and systolic blood pressure). This metabolic syndrome score was highly correlated with a similar score also including insulin and HDL cholesterol (r ( s )=0.94). Over 9 years of follow-up, incident diabetes and cardiovascular disease (CVD) were predicted by logistic regression using the simpler metabolic syndrome score. RESULTS: The means of the metabolic syndrome measures differed between men and women. Nevertheless, as the degree of variance explained and the PC1 coefficients were remarkably similar, we used a common metabolic syndrome score. The metabolic syndrome score explained 50% of the variance of the metabolic syndrome measures, and waist circumference had the highest correlation (0.59) with this score. Each standard deviation increase in the metabolic syndrome score was associated with a markedly increased age-adjusted risk of developing diabetes (odds ratios: men 3.4 [95% CI 2.6-4.4]; women 5.1 [3.6-7.2]) and with increased incident CVD of 1.7 (1.4-2.1) in men and 1.7 (1.0-2.7) in women. CONCLUSIONS/INTERPRETATION: Our results, which should be confirmed in other populations, suggest that it is possible to evaluate the risk of the metabolic syndrome in a pragmatic fashion with a continuous score, obtained from principal components analysis of the basic, continuous syndrome measures.

Background Starvation triggers a complex array of adaptative metabolic responses including energy-metabolic responses, a process which must imply tissue specific alterations in gene expression and in which the liver plays a central role. The present study aimed to describe the evolution of global gene expression profiles in liver of 4-week-old male chickens during a 48 h fasting period using a chicken 20 K oligoarray. Results A large number of genes were modulated by fasting (3532 genes with a pvalue corrected by Benjamini-Hochberg < 0.01); 2062 showed an amplitude of variation higher than +/- 40% among those, 1162 presented an human ortholog, allowing to collect functional information. Notably more genes were down-regulated than up-regulated, whatever the duration of fasting (16 h or 48 h). The number of genes differentially expressed after 48 h of fasting was 3.5-fold higher than after 16 h of fasting. Four clusters of co-expressed genes were identified by a hierarchical cluster analysis. Gene Ontology, KEGG and Ingenuity databases were then used to identify the metabolic processes associated to each cluster. After 16 h of fasting, genes involved in ketogenesis, gluconeogenesis and mitochondrial or peroxisomal fatty acid beta-oxidation, were up-regulated (cluster-1) whereas genes involved in fatty acid and cholesterol synthesis were down-regulated (cluster-2). For all genes tested, the microarray data was confirmed by quantitative RT-PCR. Most genes were altered by fasting as already reported in mammals. A notable exception was the HMG-CoA synthase 1 gene, which was up-regulated following 16 and 48 h of fasting while the other genes involved in cholesterol metabolism were down-regulated as reported in mammalian studies. We further focused on genes not represented on the microarray and candidates for the regulation of the target genes belonging to cluster-1 and -2 and involved in lipid metabolism. Data are provided concerning PPARa, SREBP1, SREBP2, NR1H3 transcription factors and two desaturases (FADS1, FADS2). Conclusion This study evidences numerous genes altered by starvation in chickens and suggests a global repression of cellular activity in response to this stressor. The central role of lipid and acetyl-CoA metabolisms and its regulation at transcriptional level are confirmed in chicken liver in response to short-term fasting. Interesting expression modulations were observed for NR1H3, FADS1 and FADS2 genes. Further studies are needed to precise their role in the complex regulatory network controlling lipid metabolism.

International audience; Collagen and myosin fibrils are endogenous harmonophores that both give rise to Second Harmonic Generation (SHG). By combining four polarization SHG images provided by a scanning microscope, we show that the orientation of the principal axis of the nonlinear susceptibility tensor chi(2) can be determined for each pixel of the image. The ratio rho = chi33/chi15 of the principal components of chi(2) of collagen and myosin was obtained with the same method, and found within the range 1.6-1.8 and 0.5-0.6 respectively. The orientation of the principal axis of chi(2) is shown to be correlated to the orientation of the fibrils themselves. This provides a straightforward method, which we call Orientation Field-Second Harmonic Microscopy (OF-SHM), to reconstruct orientation fields of fibrils at various scales and resolutions in different biological systems (from muscle sarcomere to the whole embryo).

International audience; Monocytes are active at the crossroads between inflammation and coagulation processes since they can secrete pro-inflammatory cytokines and express tissue factor (TF), a major initiator of coagulation. Cobalt-chrome (CoCr), a metal alloy, used as a biomaterial for vascular stents, has been shown to be potentially pro-thrombotic and pro-inflammatory. Research work with a polymer from a family of degradable-polar hydrophobic ionic polyurethanes (D-PHI), called HHHI, has been shown to exhibit anti-inflammatory responses from human monocytes. We have generated multifunctional polyurethane thin films (MPTF) based on the HHHI chemistry, as a thin coating for CoCr and have evaluated the reactivity of blood with MPTF-coated CoCr. The results showed that the coating of CoCr with MPTF derived from HHHI prevents thrombin generation, reduces coagulation activation, and suppresses fibrin formation in whole blood. Activation of monocytes was also suppressed at the surface of MPTF-coated CoCr and specifically the decrease in thrombin generation was accompanied by a significant decrease in TF and pro-inflammatory cytokine levels. Mass spectroscopy of the adsorbed proteins showed lower levels of fibrinogen, fibronectin and complement C3, C4, and C8 when compared to CoCr. We can conclude that MPTFs reduce the pro-thrombotic and pro-inflammatory phenotype of monocytes and macrophages on CoCr, and prevent clotting in whole blood.

Objective In PsA, the treatment objective is remission or low disease activity (LDA), but patients’ perception of remission is poorly studied. This analysis aimed to identify factors associated with patient-defined remission. Methods This analysis uses ReFlaP data, an international PsA study, with remission defined as ‘At this time, is your psoriatic arthritis in remission, if this means: you feel your disease is as good as gone?’. Variables associated with, first, patient-defined remission and, second, LDA were identified using multivariable logistic regression and principal component analysis (PCA) to explore correlated variables. Results Of 424 patients (50.2% male, mean age 52 years) with established disease, 94 (22.2%) reported themselves as being in remission and 191 (45.0%) as LDA alone. In multivariable analysis pain, psoriasis, impact of disease, physician opinion of symptoms from joint damage and Groll comorbidity index were independent predictors of remission. For LDA, results were similar. Using PCA, variance explained was 74% by five components for men and 80% by six components for women. The key component from PCA for remission was, for both sex, disease impact (Psoriatic Arthritis Impact of Disease, pain and HAQ) explaining 22.2–27.5% of variance. Other factors included musculoskeletal disease activity, chronicity/joint damage, psoriasis, enthesitis and CRP. For LDA, similar factors were identified but the variance explained was lower (64–68%). Conclusion Many factors impact on patients’ opinion of remission, dominated by disease impact. Disease activity in multiple domains, chronicity/age, comorbidities and symptoms due to other conditions contribute to a robust model highlighting that patient-defined remission is multifaceted. Trials registration Clinicaltrials.gov, http://clinicaltrials.gov, NCT 03119805.