Algorithmes mémétiques de détection de communautés dans les réseaux complexes (techniques palliatives de la limite de résolution)

Les réseaux complexes, issus de relevés de terrain d origines trèsvariées, en biologie, science de l information ou sociologie,présentent une caractéristique remarquable dénommée structurecommunautaire. Des groupes, ou communautés, à l intérieur duréseau, ont une cohésion interne forte et des liens entre eux plusfaibles. Sans connaissance a priori du nombre de communautés, ladifficulté réside dans la caractérisation d un bon partitionnement encommunautés. La modularité est une mesure globale de qualité departitionnement très utilisée qui capture les contraintes de cohésioninterne forte et de liens externes faibles. Elle transforme le problèmede détection de communautés en problème d optimisationNP-difficile. Elle souffre d un défaut, la limite de résolution, qui tendà rendre indétectables les très petites communautés d autant plusque le réseau est grand. L algorithme le plus efficace pour optimiserla modularité, dit de Louvain, procède par fusion de communautés.Cette thèse s attache à modifier cet algorithme pour qu il réalisemajoritairement des fusions pertinentes, qui n aggravent pas lalimite de résolution, en utilisant une condition de fusion. De plus, enl associant à un algorithme mémétique, les partitions proposéessont très proches des partitions attendues pour des graphesgénérés par un modèle qui reproduit les caractéristiques desréseaux complexes. Enfin, cet algorithme mémétique réduitfortement l inconsistance de solution, défaut de la modularité selonlequel deux partitions trouvées à partir d un examen des noeudsdans un ordre aléatoire, pour le même graphe, peuvent êtrestructurellement très différentes, rendant leur interprétation délicate.From various applications, in sociology or biology for instance,complex networks exhib the remarquable property of communitystructure. Groups, sometimes called communities, has a stronginternal cohesion and poor links between them. Whithout priorknowledge of the number of communities, the difficulty lies in thecharacterization of a good clustering. Modularity is an overallmeasure of clustering quality widely used to capture the doubleconstraint, internal and external, of well formed communities. Theproblem became a NP-hard optimization problem. The main weakof modularity is the resolution limit, which tends to makeundetectable very small communities especially as the network islarge. The algorithm of Louvain, one of the most efficient one tooptimize modularity, proceeds by merging communities. This thesisattempts to modify the algorithm so that it mainly produces relevantmerges that do not make worse the effects of resolution limit, usinga merge condition. In addition, by combining it with a memeticalgorithm, proposed clusterings are very close to the expected onesfor graphs generated by a model that reproduces the characteristicsof complex networks. Finally, the memetic algorithm greatly reducesthe inconsistency of solution, another weakness of modularity suchthat, for the same graph, two partitions found from an exploration ofnodes in a random order can be structurally very different, makingthem difficult to interpret.LE MANS-BU Sciences (721812109) / SudocSudocFranceF

Predicting prognosis in hepatocellular carcinoma after curative surgery with common clinicopathologic parameters

<p>Abstract</p> <p>Background</p> <p>Surgical resection is one important curative treatment for hepatocellular carcinoma (HCC), but the prognosis following surgery differs substantially and such large variation is mainly unexplained. A review of the literature yields a number of clinicopathologic parameters associated with HCC prognosis. However, the results are not consistent due to lack of systemic approach to establish a prediction model incorporating all these parameters.</p> <p>Methods</p> <p>We conducted a retrospective analysis on the common clinicopathologic parameters from a cohort of 572 ethnic Chinese HCC patients who received curative surgery. The cases were randomly divided into training (n = 272) and validation (n = 300) sets. Each parameter was individually tested and the significant parameters were entered into a linear classifier for model building, and the prediction accuracy was assessed in the validation set</p> <p>Results</p> <p>Our findings based on the training set data reveal 6 common clinicopathologic parameters (tumor size, number of tumor nodules, tumor stage, venous infiltration status, and serum α-fetoprotein and total albumin levels) that were significantly associated with the overall HCC survival and disease-free survival (time to recurrence). We next built a linear classifier model by multivariate Cox regression to predict prognostic outcomes of HCC patients after curative surgery This analysis detected a considerable fraction of variance in HCC prognosis and the area under the ROC curve was about 70%. We further evaluated the model using two other protocols; leave-one-out procedure (n = 264) and independent validation (n = 300). Both were found to have excellent prediction power. The predicted score could separate patients into distinct groups with respect to survival (p-value = 1.8e-12) and disease free survival (p-value = 3.2e-7).</p> <p>Conclusion</p> <p>This described model will provide valuable guidance on prognosis after curative surgery for HCC in clinical practice. The adaptive nature allows easy accommodation for future new biomarker inputs, and it may serve as the foundation for future modeling and prediction for HCC prognosis after surgical treatment.</p

Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

A Systematic Review of Mosquito Coils and Passive Emanators: Defining Recommendations for Spatial Repellency Testing Methodologies.

Mosquito coils, vaporizer mats and emanators confer protection against mosquito bites through the spatial action of emanated vapor or airborne pyrethroid particles. These products dominate the pest control market; therefore, it is vital to characterize mosquito responses elicited by the chemical actives and their potential for disease prevention. The aim of this review was to determine effects of mosquito coils and emanators on mosquito responses that reduce human-vector contact and to propose scientific consensus on terminologies and methodologies used for evaluation of product formats that could contain spatial chemical actives, including indoor residual spraying (IRS), long lasting insecticide treated nets (LLINs) and insecticide treated materials (ITMs). PubMed, (National Centre for Biotechnology Information (NCBI), U.S. National Library of Medicine, NIH), MEDLINE, LILAC, Cochrane library, IBECS and Armed Forces Pest Management Board Literature Retrieval System search engines were used to identify studies of pyrethroid based coils and emanators with key-words "Mosquito coils" "Mosquito emanators" and "Spatial repellents". It was concluded that there is need to improve statistical reporting of studies, and reach consensus in the methodologies and terminologies used through standardized testing guidelines. Despite differing evaluation methodologies, data showed that coils and emanators induce mortality, deterrence, repellency as well as reduce the ability of mosquitoes to feed on humans. Available data on efficacy outdoors, dose-response relationships and effective distance of coils and emanators is inadequate for developing a target product profile (TPP), which will be required for such chemicals before optimized implementation can occur for maximum benefits in disease control

Fingerprint-based Wi-Fi indoor localization using map and inertial sensors

It is a common understanding that the localization accuracy can be improved by indoor maps and inertial sensors. However, there is a lack of concrete and generic solutions that combine these two features together and practically demonstrate its validity. This article aims to provide such a solution based on the mainstream fingerprint-based indoor localization approach. First, we introduce the theorem called reference points placement, which gives a theoretical guide to place reference points. Second, we design a Wi-Fi signal propagation-based cluster algorithm to reduce the amount of computation. The paper gives a parameter called reliability to overcome the skewing of inertial sensors. Then we also present Kalman filter and Markov chain to predict the system status. The system is able to provide high-accuracy real-time tracking by integrating indoor map and inertial sensors with Wi-Fi signal strength. Finally, the proposed work is evaluated and compared with the previous Wi-Fi indoor localization systems. In addition, the effect of inertial sensors’ reliability is also discussed. Results are drawn from a campus office building which is about 80 m×140 m with 57 access points

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Inertio-elastic focusing of bioparticles in microchannels at high throughput

Controlled manipulation of particles from very large volumes of fluid at high throughput is critical for many biomedical, environmental and industrial applications. One promising approach is to use microfluidic technologies that rely on fluid inertia or elasticity to drive lateral migration of particles to stable equilibrium positions in a microchannel. Here, we report on a hydrodynamic approach that enables deterministic focusing of beads, mammalian cells and anisotropic hydrogel particles in a microchannel at extremely high flow rates. We show that on addition of micromolar concentrations of hyaluronic acid, the resulting fluid viscoelasticity can be used to control the focal position of particles at Reynolds numbers up to Re≈10,000 with corresponding flow rates and particle velocities up to 50 ml min[superscript −1] and 130 m s[superscript −1]. This study explores a previously unattained regime of inertio-elastic fluid flow and demonstrates bioparticle focusing at flow rates that are the highest yet achieved.National Institute for Biomedical Imaging and Bioengineering (U.S.) (P41 BioMicroElectroMechanical Systems Resource Center)National Institute for Biomedical Imaging and Bioengineering (U.S.) (P41 EB002503)National Science Foundation (U.S.). Graduate Research FellowshipUnited States. Army Research Office (Institute for Collaborative Biotechnologies Grant W911NF-09-0001

A Variant of Fibroblast Growth Factor Receptor 2 (Fgfr2) Regulates Left-Right Asymmetry in Zebrafish

Many organs in vertebrates are left-right asymmetrical located. For example, liver is at the right side and stomach is at the left side in human. Fibroblast growth factor (Fgf) signaling is important for left-right asymmetry. To investigate the roles of Fgfr2 signaling in zebrafish left-right asymmetry, we used splicing blocking morpholinos to specifically block the splicing of fgfr2b and fgfr2c variants, respectively. We found that the relative position of the liver and the pancreas were disrupted in fgfr2c morphants. Furthermore, the left-right asymmetry of the heart became random. Expression pattern of the laterality controlling genes, spaw and pitx2c, also became random in the morphants. Furthermore, lefty1 was not expressed in the posterior notochord, indicating that the molecular midline barrier had been disrupted. It was also not expressed in the brain diencephalon. Kupffer's vesicle (KV) size became smaller in fgfr2c morphants. Furthermore, KV cilia were shorter in fgfr2c morphants. We conclude that the fgfr2c isoform plays an important role in the left-right asymmetry during zebrafish development

Evaluation of Greenbug and Yellow Sugarcane Aphid Feeding Behavior on Resistant and Susceptible Switchgrass Cultivars

Switchgrass (Panicum virgatum L.) is an emerging biofuel crop that serves as host for aphids. To discern the effects of plant age and possible resistance mechanisms, the feeding behavior of greenbugs (Schizaphis graminum Rondani.) and the yellow sugarcane aphid (Sipha flava Forbes.) was monitored on three diverse switchgrasses by the electrical penetration graph (EPG) technique. Callose deposition and genes associated with callose metabolism were also analyzed to discern their association with plant resistance. There was a strong host effect on greenbugs feeding on lowland cultivar Kanlow at the V3 stage of development, as compared to the greenbug-susceptible upland cultivar Summer and plants derived from Kanlow (♂) × Summer (♀) (K×S) crosses. These data confirmed that Kanlow at the V3 stage had antibiosis to greenbugs, which was absent in the Summer and K×S plants. In contrast, similar effects were not observed for yellow sugarcane aphids, excluding significant differences in the time to first probe on Kanlow plants at the V1 stage and reduction in time spent on pathway processes on Kanlow plants at the V3 stage. These data demonstrated that Kanlow plants may have multiple sources of resistance to the two aphids, and possibly some were phloem based. Microscopy of leaf sections stained with aniline blue for callose was suggestive of increased callose deposition in the sieve elements in Kanlow plants relative to Summer and K×S plants. RT-qPCR analysis of several genes associated with callose metabolism in infested plants was equivocal. Overall, these studies suggest the presence of multiple defense mechanisms against aphids in Kanlow plants, relative to Summer and K×S plants