85 resultados para Global analysis (Mathematics)


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The competitiveness of businesses is increasingly dependent on their electronic networks with customers, suppliers, and partners. While the strategic and operational impact of external integration and IOS adoption has been extensively studied, much less attention has been paid to the organizational and technical design of electronic relationships. The objective of our longitudinal research project is the development of a framework for understanding and explaining B2B integration. Drawing on existing literature and empirical cases we present a reference model (a classification scheme for B2B Integration). The reference model comprises technical, organizational, and institutional levels to reflect the multiple facets of B2B integration. In this paper we onvestigate the current state of electronic collaboration in global supply chains focussing on the technical view. Using an indepth case analysis we identify five integration scenarios. In the subsequent confirmatory phase of the research we analyse 112 real-world company cases to validate these five integration scenarios. Our research advances and deepens existing studies by developing a B2B reference model, which reflects the current state of practice and is independent of specific implementation technologies. In the next stage of the research the emerging reference model will be extended to create an assessment model for analysing the maturity level of a given company in a specific supply chain.

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Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

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ABSTRACT: BACKGROUND: Many studies have been published outlining the global effects of 17 beta-estradiol (E2) on gene expression in human epithelial breast cancer derived MCF-7 cells. These studies show large variation in results, reporting between ~100 and ~1500 genes regulated by E2, with poor overlap. RESULTS: We performed a meta-analysis of these expression studies, using the Rank product method to obtain a more accurate and stable list of the differentially expressed genes, and of pathways regulated by E2. We analyzed 9 time-series data sets, concentrating on response at 3-4 hrs (early) and at 24 hrs (late). We found >1000 statistically significant probe sets after correction for multiple testing at 3-4 hrs, and >2000 significant probe sets at 24 hrs. Differentially expressed genes were examined by pathway analysis. This revealed 15 early response pathways, mostly related to cell signaling and proliferation, and 20 late response pathways, mostly related to breast cancer, cell division, DNA repair and recombination. CONCLUSIONS: Our results show that meta-analysis identified more differentially expressed genes than the individual studies, and that these genes act together in networks. These results provide new insight into E2 regulated mechanisms, especially in the context of breast cancer.

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Background/Purpose: Gout is a common and excruciatingly painful inflammatory arthritis caused by hyperuricemia. In addition to various lifestyle risk factors, a substantial genetic predisposition to gout has long been recognized. The Global Urate Genetics Consortium (GUGC) has aimed to comprehensively investigate the genetics of serum uric acid and gout using data from _ 140,000 individuals of European-ancestry, 8,340 individuals of Indian ancestry, 5,820 African-Americans, and 15,286 Japanese. Methods: We performed discovery GWAS meta-analyses of serum urate levels (n_110,347 individuals) followed by replication analyses (n_32,813 different individuals). Our gout analysis involved 3,151 cases and 68,350 controls, including 1,036 incident gout cases that met the American College of Rheumatology Criteria. We also examined the association of gout with fractional excretion of uric acid (n_6,799). A weighted genetic urate score was constructed based on the number of risk alleles across urate-associated loci, and their association with the risk of gout was evaluated. Furthermore, we examined implicated transcript expression in cis (expression quantitative trait loci databases) for potential insights into the gene underlying the association signal. Finally, in order to further identify urate-associated genomic regions, we performed functional network analyses that incorporated prior knowledge on molecular interactions in which the gene products of implicated genes operate. Results: We identified and replicated 28 genome-wide significant loci in association with serum urate (P 5_10_8), including all previously-reported loci as well as 18 novel genetic loci. Unlike the majority of previouslyidentified loci, none of the novel loci appeared to be obvious candidates for urate transport. Rather, they were mapped to genes that encode for purine production, transcription, or growth factors with broad downstream responses. Besides SLC2A9 and ABCG2, no additional regions contained SNPs that differed significantly (P _ 5_10_8) between sexes. Urateincreasing alleles were associated with an increased risk of gout for all loci. The urate genetic risk score (ranging from 10 to 45) was significantly associated with an increased odds of prevalent gout (OR per unit increase, 1.11; 95% CI, 1.09-1.14) and incident gout (OR, 1.10; 95% CI, 1.08-1.13). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. Detailed characterization of the loci revealed associations with transcript expression and the fractional excretion of urate. Network analyses implicated the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. Conclusion: The novel genetic candidates identified in this urate/gout consortium study, the largest to date, highlight the importance of metabolic control of urate production and urate excretion. The modulation by signaling processes that influence metabolic pathways such as glycolysis and the pentose phosphate pathway appear to be central mechanisms underpinned by the novel GWAS candidates. These findings may have implications for further research into urate-lowering drugs to treat and prevent gout.

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Fertility and flower development are both controlled in part by jasmonates, fatty acid-derived mediators produced via the activity of 13-lipoxygenases (13-LOXs). The Arabidopsis thaliana Columbia-0 reference genome is predicted to encode four of these enzymes and it is already known that one of these, LOX2, is dispensable for fertility. In this study, the roles of the other three 13-LOXs (LOX3, LOX4 and LOX6) were investigated in single and double mutants. Four independent lox3 lox4 double mutants assembled with different mutated lox3 and lox4 alleles had fully penetrant floral phenotypes, displaying abnormal anther maturation and defective dehiscence. The plants were no longer self-fertile and pollen was not viable. Fertility in the double mutant was restored genetically by complementation with either the LOX3 or the LOX4 cDNAs and biochemically with exogenous jasmonic acid. Furthermore, deficiency in LOX3 and LOX4 causes developmental dysfunctions, compared to wild type; lox3 lox4 double mutants are taller and develop more inflorescence shoots and flowers. Further analysis revealed that developmental arrest in the lox3 lox4 inflorescence occurs with the production of an abnormal carpelloid flower. This distinguishes lox3 lox4 mutants from the wild type where developmentally typical flower buds are the terminal inflorescence structures observed in both the laboratory and in nature. Our studies of lox3 lox4 as well as other jasmonic acid biosynthesis and perception mutants show that this plant hormone is not only required for male fertility but also involved in global proliferative arrest.

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The widespread use of combination antiretroviral therapy (ARVs) has considerably improved the prognosis of patients infected with HIV. Conversely, considerable advances have been recently realized for the therapy of hepatitis C infection with the recent advent of potent new anti-HCV drugs that allow an increasing rate HCV infection cure. Despite their overall efficacy, a significant number of patients do not achieve or maintain adequate clinical response, defined as an undetectable viral load for HIV, and a sustained virological response (or cure) in HCV infection. Treatment failure therefore still remains an important issue besides drugs toxicities and viral resistance which is not uncommon in a significant percentage of patients who do not reach adequate virological suppression. The reasons of variability in drug response are multifactorial and apart from viral genetics, other factors such as environmental factors, drug- drug interactions, and imperfect compliance may have profound impact on antiviral drugs' clinical response. The possibility of measuring plasma concentration of antiviral drugs enables to guide antiviral drug therapy and ensure optimal drug exposure. The overall objective of this research was to widen up the current knowledge on pharmacokinetic and pharmacogenetic factors that influence the clinical response and toxicity of current and newly approved antiretroviral and anti-HCV drugs. To that endeavour, analytical methods using liquid chromatography coupled with tandem mass spectrometry have been developed and validated for the precise and accurate measurement of new antiretroviral and anti-HCV drugs . These assays have been applied for the TDM of ARVs and anti-HCV in patients infected with either HIV or HCV respectively, and co-infected with HIV- HCV. A pharmacokinetic population model was developed to characterize inter and intra-patient variability of rilpivirine, the latest marketed Non Nucleoside Reverse transcriptase (NNRTI) Inhibitor of HIVand to identify genetic and non genetic covariates influencing rilpivirine exposure. None of the factors investigated so far showed however any influence of RPV clearance. Importantly, we have found that the standard daily dosage regimen (25 mg QD) proposed for rilpivirine results in concentrations below the proposed therapeutic target in about 40% of patients. In these conditions, virologie escape is a potential risk that remains to be further investigated, notably via the TDM approach that can be a useful tool to identify patients who are at risk for being exposed to less than optimal levels of rilpivirine in plasma. Besides the last generation NNRTI rilpivirine, we have studied efavirenz, the major NNRTI clinically used so far. Namely for efavirenz, we aimed at identifying a potential new marker of toxicity that may be incriminated for the neuropsychological sides effects and hence discontinuation of efavirenz therapy. To that endeavour, a comprehensive analysis of phase I and phase II metabolites profiles has been performed in plasma, CSF and in urine from patients under efavirenz therapy. We have found that phase II metabolites of EFV constitute the major species circulating in blood, sometimes exceeding the levels of the parent drug efavirenz. Moreover we have identified a new metabolite of efavirenz in humans, namely the 8-OH-EFV- sulfate which is present at high concentrations in all body compartments from patients under efavirenz therapy. These investigations may open the way to possible alternate phenotypic markers of efavirenz toxicity. Finally, the specific influence of P-glycoprotein on the cellular disposition of a series ARVs (NNRTIs and Pis] has been studies in in vitro cell systems using the siRNA silencing approach. -- Depuis l'introduction de la thérapie antirétrovirale (ARVs) la morbidité et la mortalité liées au VIH ont considérablement diminué. En parallèle le traitement contre le virus de l'hépatite C (VHC) a connu récemment d'énormes progrès avec l'arrivée de nouveaux médicaments puissants, ce qui a permis une augmentation considérable de la guérison de l'infection par le VHC. En dépit de l'efficacité de ces traitements antiviraux, les échecs thérapeutiques ainsi que les effets secondaires des traitements restent un problème important. Une réponse imparfaite ou la toxicité du traitement est certainement multifactorielle. Le suivi thérapeutique des médicaments [Therapeutic Drug Monitoring TDM) à travers la mesure des concentrations plasmatiques constitue une approche importante pour guider le traitement médicamenteux et de s'assurer que les patients sont exposés à des concentrations optimales des médicaments dans le sang, et puissent tirer tout le bénéfice potentiel du traitement. L'objectif global de cette thèse était d'étudier les facteurs pharmacocinétiques et pharmacogénétiques qui influencent l'exposition des médicaments antiviraux (ARVs et anti- VHC) récemment approuvés. A cet effet, des méthodes de quantification des concentrations plasmatiques des médicaments antirétroviraux, anti-VHC ainsi que pour certains métabolites ont été développées et validées en utilisant la Chromatographie liquide couplée à la spectrométrie de masse tandem. Ces méthodes ont été utilisées pour le TDM des ARVs et pour les agents anti-VHC chez les patients infectés par le VIH, et le VHC, respectivement, mais aussi chez les patients co-infectés par le VIH-VHC. Un modèle de pharmacocinétique de population a été développé pour caractériser la variabilité inter-et intra-patient du médicament rilpivirine, un inhibiteur non nucléosidique de la transcriptase de VIH et d'identifier les variables génétiques et non génétiques influençant l'exposition au médicament. Aucun des facteurs étudiés n'a montré d'influence notable sur la clairance de la rilpivirine. Toutefois, la concentration résiduelle extrapolée selon le modèle de pharmacocinétique de population qui a été développé, a montré qu'une grande proportion des patients présente des concentrations minimales inférieures à la cible thérapeutique proposée. Dans ce contexte, la relation entre les concentrations minimales et l'échappement virologique nécessite une surveillance étroite des taux sanguins des patients recevant de la rilpivirine. A cet effet, le suivi thérapeutique est un outil important pour l'identification des patients à risque soient sous-exposés à lai rilpivirine. Pour identifier de nouveaux marqueurs de la toxicité qui pourraient induire l'arrêt du traitement, le profil des métabolites de phase I et de phase II a été étudié dans différentes matrices [plasma, LCR et urine) provenant de patients recevant de l'efavirenz. Les métabolites de phase II, qui n'avaient à ce jour jamais été investigués, constituent les principales espèces présentes dans les matrices étudiées. Au cours de ces investigations, un nouveau métabolite 8- OH-EFV-sulfate a été identifié chez l'homme, et ce dernier est. présent à des concentrations importantes. L'influence de certains facteurs pharmacogénétique des patients sur le profil des métabolites a été étudiée et ouvre la voie à de possibles nouveaux marqueurs phénotypiques alternatifs qui pourraient possiblement mieux prédire la toxicité associée au traitement par l'efavirenz. Finalement, nous nous sommes intéressés à étudier dans un modèle in vitro certains facteurs, comme la P-glycoprotéine, qui influencent la disposition cellulaire de certains médicaments antirétroviraux, en utilisant l'approche par la technologie du siRNA permettant de bloquer sélectivement l'expression du gène de cette protéine d'efflux des médicaments. -- Depuis l'introduction de la thérapie antiretrovirale (ARVs] la morbidité et la mortalité liées au VIH ont considérablement diminué. En parallèle le traitement contre le virus de l'hépatite C (VHC) a connu récemment d'énormes progrès avec l'arrivée de nouveaux médicaments puissants, ce qui a permis une augmentation considérable de la guérison de l'infection par le VHC. En dépit de l'efficacité de ces traitements antiviraux, les échecs thérapeutiques ainsi que les effets secondaires des traitements restent un problème important. Il a pu être démontré que la concentration de médicament présente dans l'organisme est corrélée avec l'efficacité clinique pour la plupart des médicaments agissant contre le VIH et contre le VHC. Les médicaments antiviraux sont généralement donnés à une posologie fixe et standardisée, à tous les patients, il existe cependant une importante variabilité entre les concentrations sanguines mesurées chez les individus. Cette variabilité peut être expliquée par plusieurs facteurs démographiques, environnementaux ou génétiques. Dans ce contexte, le suivi des concentrations sanguines (ou Therapeutic Drug Monitoring, TDM) permet de contrôler que les patients soient exposés à des concentrations suffisantes (pour bloquer la réplication du virus dans l'organisme) et éviter des concentrations excessives, ce qui peut entraîner l'apparition d'intolérence au traitement. Le but de ce travail de thèse est d'améliorer la compréhension des facteurs pharmacologiques et génétiques qui peuvent influencer l'efficacité et/ou la toxicité des médicaments antiviraux, dans le but d'améliorer le suivi des patients. A cet effet, des méthodes de dosage très sensibles et ont été mises au point pour permettre de quantifier les médicaments antiviraux dans le sang et dans d'autres liquides biologiques. Ces méthodes de dosage sont maintenant utilisées d'une part dans le cadre de la prise en charge des patients en routine et d'autre part pour diverses études cliniques chez les patients infectés soit par le HIV, le HCV ou bien coinfectés par les deux virus. Une partie de ce travail a été consacrée à l'investigation des différents facteurs démographiques, génétiques et environnementaux qui pourraient l'influencer la réponse clinique à la rilpivirine, un nouveau médicament contre le VIH. Toutefois, parmi tous les facteurs étudiés à ce jour, aucun n'a permis d'expliquer la variabilité de l'exposition à la rilpivirine chez les patients. On a pu cependant observer qu'à la posologie standard recommandée, un pourcentage relativement élevé de patients pourrait présenter des concentrations inférieures à la concentration sanguine minimale actuellement proposée. Il est donc utile de surveiller étroitement les concentrations de rilpivirine chez les patients pour identifier sans délai ceux qui risquent d'être sous-exposés. Dans l'organisme, le médicament subit diverses transformations (métabolisme) par des enzymes, notamment dans le foie, il est transporté dans les cellules et tissus par des protéines qui modulent sa concentration au site de son action pharmacologique. A cet effet, différents composés (métabolites) produits dans l'organisme après l'administration d'efavirenz, un autre médicament anti-VIH, ont été étudiés. En conclusion, nous nous sommes intéressés à la fois aux facteurs pharmacologiques et génétiques des traitements antiviraux, une approche qui s'inscrit dans l'optique d'une stratégie globale de prise en charge du patient. Dans ce contexte, le suivi des concentrations sanguines de médicaments constitue une des facettes du domaine émergent de la Médecine Personnalisée qui vise à maximiser le bénéfice thérapeutique et le profil de tolérance des médicaments antiviraux

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While the morphological and electrophysiological changes underlying diabetic peripheral neuropathy (DPN) are relatively well described, the involved molecular mechanisms remain poorly understood. In this study, we investigated whether phenotypic changes associated with early DPN are correlated with transcriptional alterations in the neuronal (dorsal root ganglia [DRG]) or the glial (endoneurium) compartments of the peripheral nerve. We used Ins2(Akita/+) mice to study transcriptional changes underlying the onset of DPN in type 1 diabetes mellitus (DM). Weight, blood glucose and motor nerve conduction velocity (MNCV) were measured in Ins2(Akita/+) and control mice during the first three months of life in order to determine the onset of DPN. Based on this phenotypic characterization, we performed gene expression profiling using sciatic nerve endoneurium and DRG isolated from pre-symptomatic and early symptomatic Ins2(Akita/+) mice and sex-matched littermate controls. Our phenotypic analysis of Ins2(Akita/+) mice revealed that DPN, as measured by reduced MNCV, is detectable in affected animals already one week after the onset of hyperglycemia. Surprisingly, the onset of DPN was not associated with any major persistent changes in gene expression profiles in either sciatic nerve endoneurium or DRG. Our data thus demonstrated that the transcriptional programs in both endoneurial and neuronal compartments of the peripheral nerve are relatively resistant to the onset of hyperglycemia and hypoinsulinemia suggesting that either minor transcriptional alterations or changes on the proteomic level are responsible for the functional deficits associated with the onset of DPN in type 1 DM.

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In this work we analyze how patchy distributions of CO2 and brine within sand reservoirs may lead to significant attenuation and velocity dispersion effects, which in turn may have a profound impact on surface seismic data. The ultimate goal of this paper is to contribute to the understanding of these processes within the framework of the seismic monitoring of CO2 sequestration, a key strategy to mitigate global warming. We first carry out a Monte Carlo analysis to study the statistical behavior of attenuation and velocity dispersion of compressional waves traveling through rocks with properties similar to those at the Utsira Sand, Sleipner field, containing quasi-fractal patchy distributions of CO2 and brine. These results show that the mean patch size and CO2 saturation play key roles in the observed wave-induced fluid flow effects. The latter can be remarkably important when CO2 concentrations are low and mean patch sizes are relatively large. To analyze these effects on the corresponding surface seismic data, we perform numerical simulations of wave propagation considering reservoir models and CO2 accumulation patterns similar to the CO2 injection site in the Sleipner field. These numerical experiments suggest that wave-induced fluid flow effects may produce changes in the reservoir's seismic response, modifying significantly the main seismic attributes usually employed in the characterization of these environments. Consequently, the determination of the nature of the fluid distributions as well as the proper modeling of the seismic data constitute important aspects that should not be ignored in the seismic monitoring of CO2 sequestration problems.

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DNA methylation is involved in a diversity of processes in bacteria, including maintenance of genome integrity and regulation of gene expression. Here, using Caulobacter crescentus as a model, we exploit genome-wide experimental methods to uncover the functions of CcrM, a DNA methyltransferase conserved in most Alphaproteobacteria. Using single molecule sequencing, we provide evidence that most CcrM target motifs (GANTC) switch from a fully methylated to a hemi-methylated state when they are replicated, and back to a fully methylated state at the onset of cell division. We show that DNA methylation by CcrM is not required for the control of the initiation of chromosome replication or for DNA mismatch repair. By contrast, our transcriptome analysis shows that >10% of the genes are misexpressed in cells lacking or constitutively over-expressing CcrM. Strikingly, GANTC methylation is needed for the efficient transcription of dozens of genes that are essential for cell cycle progression, in particular for DNA metabolism and cell division. Many of them are controlled by promoters methylated by CcrM and co-regulated by other global cell cycle regulators, demonstrating an extensive cross talk between DNA methylation and the complex regulatory network that controls the cell cycle of C. crescentus and, presumably, of many other Alphaproteobacteria.

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Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

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In Pseudomonas aeruginosa, the CbrA/CbrB two-component system is instrumental in the maintenance of the carbon-nitrogen balance and for growth on carbon sources that are energetically less favorable than the preferred dicarboxylate substrates. The CbrA/CbrB system drives the expression of the small RNA CrcZ, which antagonizes the repressing effects of the catabolite repression control protein Crc, an RNA-binding protein. Dicarboxylates appear to cause carbon catabolite repression by inhibiting the activity of the CbrA/CbrB system, resulting in reduced crcZ expression. Here we have identified a conserved palindromic nucleotide sequence that is present in upstream activating sequences (UASs) of promoters under positive control by CbrB and σ(54) RNA polymerase, especially in the UAS of the crcZ promoter. Evidence for recognition of this palindromic sequence by CbrB was obtained in vivo from mutational analysis of the crcZ promoter and in vitro from electrophoretic mobility shift assays using crcZ promoter fragments and purified CbrB protein truncated at the N terminus. Integration host factor (IHF) was required for crcZ expression. CbrB also activated the lipA (lipase) promoter, albeit less effectively, apparently by interacting with a similar but less conserved palindromic sequence in the UAS of lipA. As expected, succinate caused CbrB-dependent catabolite repression of the lipA promoter. Based on these results and previously published data, a consensus CbrB recognition sequence is proposed. This sequence has similarity to the consensus NtrC recognition sequence, which is relevant for nitrogen control.

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Low socioeconomic status has been reported to be associated with head and neck cancer risk. However, previous studies have been too small to examine the associations by cancer subsite, age, sex, global region, and calendar time, and to explain the association in terms of behavioural risk factors. Individual participant data of 23,964 cases with head and neck cancer and 31,954 controls from 31 studies in 27 countries pooled with random effects models. Overall, low education was associated with an increased risk of head and neck cancer (OR = 2·50; 95%CI 2·02- 3·09). Overall one-third of the increased risk was not explained by differences in the distribution of cigarette smoking and alcohol behaviours; and it remained elevated among never users of tobacco and non-drinkers (OR = 1·61; 95%CI 1·13 - 2·31). More of the estimated education effect was not explained by cigarette smoking and alcohol behaviours: in women than in men, in older than younger groups, in the oropharynx than in other sites, in South/Central America than in Europe/North America, and was strongest in countries with greater income inequality. Similar findings were observed for the estimated effect of low vs high household income. The lowest levels of income and educational attainment were associated with more than 2-fold increased risk of head and neck cancer, which is not entirely explained by differences in the distributions of behavioural risk factors for these cancers, and which varies across cancer sites, sexes, countries, and country income inequality levels. © 2014 Wiley Periodicals, Inc.

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Purpose: Previous studies of the visual outcome in bilateral non-arteritic anterior ischemic optic neuropathy (NAION) have yielded conflicting results, specifically regarding congruity between fellow eyes. Prior studies have used measures of acuity and computerized perimetry but none has compared Goldmann visual field outcomes between fellow eyes. In order to better define the concordance of visual loss in this condition, we reviewed our cases of bilateral sequential NAION, including measures of visual acuity, pupillary function and both pattern and severity of visual field loss.Methods: We performed a retrospective chart review of 102 patients with a diagnosis of bilateral sequential NAION. Of the 102 patients, 86 were included in the study for analysis of final visual outcome between the affected eyes. Visual function was assessed using visual acuity, Goldmann visual fields, color vision and RAPD. A quantitative total visual field score and score per quadrant was analyzed for each eye using the numerical Goldmann visual field scoring method previously described by Esterman and colleagues. Based upon these scores, we calculated the total deviation and pattern deviation between fellow eyes and between eyes of different patients. Statistical significance was determined using nonparametric tests.Results: A statistically significant correlation was found between fellow eyes for multiple parameters, including logMAR visual acuity (P = 0.0101), global visual field (P = 0.0001), superior visual field (P = 0.0001), and inferior visual field (P = 0.0001). In addition, the mean deviation of both total (P = 0.0000000007) and pattern (P = 0.000000004) deviation analyses was significantly less between fellow eyes ("intra"-eyes) than between eyes of different patients ("inter"-eyes).Conclusions: Visual function between fellow eyes showed a fair to moderate correlation that was statistically significant. The pattern of vision loss was also more similar in fellow eyes than between eyes of different patients. These results may help allow better prediction of visual outcome for the second eye in patients with NAION. These findings may also be useful for evaluating efficacy of therapeutic interventions.

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This paper describes methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way.

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The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.