Interaction between tobacco and alcohol use and the risk of head and neck cancer: pooled analysis in the International Head and Neck Cancer Epidemiology Consortium.

BACKGROUND: The magnitude of risk conferred by the interaction between tobacco and alcohol use on the risk of head and neck cancers is not clear because studies have used various methods to quantify the excess head and neck cancer burden. METHODS: We analyzed individual-level pooled data from 17 European and American case-control studies (11,221 cases and 16,168 controls) participating in the International Head and Neck Cancer Epidemiology consortium. We estimated the multiplicative interaction parameter (psi) and population attributable risks (PAR). RESULTS: A greater than multiplicative joint effect between ever tobacco and alcohol use was observed for head and neck cancer risk (psi = 2.15; 95% confidence interval, 1.53-3.04). The PAR for tobacco or alcohol was 72% (95% confidence interval, 61-79%) for head and neck cancer, of which 4% was due to alcohol alone, 33% was due to tobacco alone, and 35% was due to tobacco and alcohol combined. The total PAR differed by subsite (64% for oral cavity cancer, 72% for pharyngeal cancer, 89% for laryngeal cancer), by sex (74% for men, 57% for women), by age (33% for cases <45 years, 73% for cases >60 years), and by region (84% in Europe, 51% in North America, 83% in Latin America). CONCLUSIONS: Our results confirm that the joint effect between tobacco and alcohol use is greater than multiplicative on head and neck cancer risk. However, a substantial proportion of head and neck cancers cannot be attributed to tobacco or alcohol use, particularly for oral cavity cancer and for head and neck cancer among women and among young-onset cases.

Exploration of the visual system : Part 2. In vivo analysis methods : virtual-reality optomotor system, fundus examination and fluorescent angiography

The mouse has emerged as an animal model for many diseases. At IRO, we have used this animal to understand the development of many eye diseases and treatment of some of them. Precise evaluation of vision is a prerequisite for both these approaches. In this unit we describe three ways to measure vision: testing the optokinetic response, and evaluating the fundus by direct observation and by fluorescent angiography.

Interaction analysis and psychology: A dialogical perspective

Interaction analysis is not a prerogative of any discipline in social sciences. It has its own history within each disciplinary field and is related to specific research objects. From the standpoint of psychology, this article first draws upon a distinction between factorial and dialogical conceptions of interaction. It then briefly presents the basis of a dialogical approach in psychology and focuses upon four basic assumptions. Each of them is examined on a theoretical and on a methodological level with a leading question: to what extent is it possible to develop analytical tools that are fully coherent with dialogical assumptions? The conclusion stresses the difficulty of developing methodological tools that are fully consistent with dialogical assumptions and argues that there is an unavoidable tension between accounting for the complexity of an interaction and using methodological tools which necessarily "monologise" this complexity.

Rapid bacterial genome sequencing: methods and applications in clinical microbiology.

The recent advances in sequencing technologies have given all microbiology laboratories access to whole genome sequencing. Providing that tools for the automated analysis of sequence data and databases for associated meta-data are developed, whole genome sequencing will become a routine tool for large clinical microbiology laboratories. Indeed, the continuing reduction in sequencing costs and the shortening of the 'time to result' makes it an attractive strategy in both research and diagnostics. Here, we review how high-throughput sequencing is revolutionizing clinical microbiology and the promise that it still holds. We discuss major applications, which include: (i) identification of target DNA sequences and antigens to rapidly develop diagnostic tools; (ii) precise strain identification for epidemiological typing and pathogen monitoring during outbreaks; and (iii) investigation of strain properties, such as the presence of antibiotic resistance or virulence factors. In addition, recent developments in comparative metagenomics and single-cell sequencing offer the prospect of a better understanding of complex microbial communities at the global and individual levels, providing a new perspective for understanding host-pathogen interactions. Being a high-resolution tool, high-throughput sequencing will increasingly influence diagnostics, epidemiology, risk management, and patient care.

Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts.

BACKGROUND: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. METHODS AND FINDINGS: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m(2) higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10⁻²⁷). The BMI allele score was associated both with BMI (p = 6.30×10⁻⁶²) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10⁻⁵⁷ for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). CONCLUSIONS: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

Oxylipin analysis methods.

Practical guidelines for monitoring and measuring compounds such as jasmonates, ketols, ketodi(tri)enes and hydroxy-fatty acids as well as detecting the presence of novel oxylipins are presented. Additionally, a protocol for the penetrant analysis of non-enzymatic lipid oxidation is described. Each of the methods, which employ gas chromatography/mass spectrometry, can be applied without specialist knowledge or recourse to the latest analytical instrumentation. Additional information on oxylipin quantification and novel protocols for preparing oxygen isotope-labelled internal standards are provided. Four developing areas of research are identified: (i) profiling of the unbound cellular pools of oxylipins; (ii) profiling of esterified oxylipins and/or monitoring of their release from parent lipids; (iii) monitoring of non-enzymatic lipid oxidation; (iv) analysis of unstable and reactive oxylipins. The methods and protocols presented herein are designed to give technical insights into the first three areas and to provide a platform from which to enter the fourth area.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Pharmacokinetic interaction between methotrexate and chloral hydrate.

We report the case of a drug interaction between methotrexate (MTX) and chloral hydrate (CH) observed in a child treated for acute leukemia. Significantly slower MTX clearance and increased MTX exposure occurred on the first three courses of a high-dose chemotherapy when co-administered with CH despite normal renal function, adequate hydration, and alkalinization. Mean MTX area under the curve associated with CH administration was 1,134 µmol hours/L, compared to 608 µmol hours/L after discontinuation of CH. This interaction possibly resulted from a competition between anionic CH metabolites and MTX for renal tubular excretion.

The Swiss cohort of elderly patients with venous thromboembolism (SWITCO65+): rationale and methodology.

Venous thromboembolism (VTE) is common and has a high impact on morbidity, mortality, and costs of care. Although most of the patients with VTE are aged ≥65 years, there is little data about the medical outcomes in the elderly with VTE. The Swiss Cohort of Elderly Patients with VTE (SWITCO65+) is a prospective multicenter cohort study of in- and outpatients aged ≥65 years with acute VTE from all five Swiss university and four high-volume non-university hospitals. The goal is to examine which clinical and biological factors and processes of care drive short- and long-term medical outcomes, health-related quality of life, and medical resource utilization in elderly patients with acute VTE. The cohort also includes a large biobank with biological material from each participant. From September 2009 to March 2012, 1,863 elderly patients with VTE were screened and 1003 (53.8 %) were enrolled in the cohort. Overall, 51.7 % of patients were aged ≥75 years and 52.7 % were men. By October 16, 2012, after an average follow-up time of 512 days, 799 (79.7 %) patients were still actively participating. SWITCO65+ is a unique opportunity to study short- and long-term outcomes in elderly patients with VTE. The Steering Committee encourages national and international collaborative research projects related to SWITCO65+, including sharing anonymized data and biological samples.

Body composition: overview of methods and future directions of research.

A short overview is given on the most important analytical body composition methods. Principles of the methods and advantages and limitations of the methods are discussed also in relation to other fields of research such as energy metabolism. Attention is given to some new developments in body composition research such as chemical multiple-compartment models, computerized tomography or nuclear magnetic resonance imaging (tissue level), and multifrequency bioelectrical impedance. Possible future directions of body composition research in the light of these new developments are discussed.

Probable metabolic interaction between methadone and fluvoxamine in addict patients.

We report five cases where fluvoxamine (FLVX) was added to maintenance treatment with methadone (MTD) in addict patients with affective disorders. In view of the implication of FLVX in several metabolic drug interactions, MTD plasma levels were measured before and after treatment with FLVX. A slight increase (approximately 20% of the MTD plasma level/dose ratio) occurred in two cases. In the remaining three patients, the interaction was more pronounced (40-100% increase of the MTD plasma level/dose ratio), with clinical manifestations of opiate withdrawal after stopping FLVX therapy in one case. Caution is needed when starting or stopping treatment with FLVX in patients receiving maintenance treatment with methadone.

Cognitive issues in fingerprint analysis: Inter- and intra-expert consistency and the effect of a "target" comparison

Deciding whether two fingerprint marks originate from the same source requires examination and comparison of their features. Many cognitive factors play a major role in such information processing. In this paper we examined the consistency (both between- and within-experts) in the analysis of latent marks, and whether the presence of a 'target' comparison print affects this analysis. Our findings showed that the context of a comparison print affected analysis of the latent mark, possibly influencing allocation of attention, visual search, and threshold for determining a 'signal'. We also found that even without the context of the comparison print there was still a lack of consistency in analysing latent marks. Not only was this reflected by inconsistency between different experts, but the same experts at different times were inconsistent with their own analysis. However, the characterization of these inconsistencies depends on the standard and definition of what constitutes inconsistent. Furthermore, these effects were not uniform; the lack of consistency varied across fingerprints and experts. We propose solutions to mediate variability in the analysis of friction ridge skin.

Combined transesophageal and surface MRI provides optimal imaging in aortic atherosclerosis.

OBJECTIVE: Surface magnetic resonance imaging (MRI) for aortic plaque assessment is limited by the trade-off between penetration depth and signal-to-noise ratio (SNR). For imaging the deep seated aorta, a combined surface and transesophageal MRI (TEMRI) technique was developed 1) to determine the individual contribution of TEMRI and surface coils to the combined signal, 2) to measure the signal improvement of a combined surface and TEMRI over surface MRI, and 3) to assess for reproducibility of plaque dimension analysis. METHODS AND RESULTS: In 24 patients six black blood proton-density/T2-weighted fast-spin echo images were obtained using three surface and one TEMRI coil for SNR measurements. Reproducibility of plaque dimensions (combined surface and TEMRI) was measured in 10 patients. TEMRI contributed 68% of the signal in the aortic arch and descending aorta, whereas the overall signal gain using the combined technique was up to 225%. Plaque volume measurements had an intraclass correlation coefficient of as high as 0.97. CONCLUSION: Plaque volume measurements for the quantification of aortic plaque size are highly reproducible for combined surface and TEMRI. The TEMRI coil contributes considerably to the aortic MR signal. The combined surface and TEMRI approach improves aortic signal significantly as compared to surface coils alone. CONDENSED ABSTRACT: Conventional MRI aortic plaque visualization is limited by the penetration depth of MRI surface coils and may lead to suboptimal image quality with insufficient reproducibility. By combining a transesophageal MRI (TEMRI) with surface MRI coils we enhanced local and overall image SNR for improved image quality and reproducibility.

The molecular basis of social behavior: models, methods and advances.

Elucidating the molecular and neural basis of complex social behaviors such as communal living, division of labor and warfare requires model organisms that exhibit these multi-faceted behavioral phenotypes. Social insects, such as ants, bees, wasps and termites, are attractive models to address this problem, with rich ecological and ethological foundations. However, their atypical systems of reproduction have hindered application of classical genetic approaches. In this review, we discuss how recent advances in social insect genomics, transcriptomics, and functional manipulations have enhanced our ability to observe and perturb gene expression, physiology and behavior in these species. Such developments begin to provide an integrated view of the molecular and cellular underpinnings of complex social behavior.