Alleviating abiotic and biotic soil constraints by combining Arbuscular Mycorrhizal Fungi with banana and plantain micropropagation systems

The objectives of Participant 4 were: - Establishment and maintenance of a representative collection of AM fungal species in vivo on trap plant cultures. - Study of the effects of early mycorrhizal inoculation in the growth and health of in vitro plantlets and their subsequent behaviour in the nursery. - Effect of the mycorrhization of in vitro produced bananas and plantains on plant growth and health, under biotic stress conditions (nematode and fungi)

Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

Prenatal Representations of Family in Parents and Coparental Interactions as Predictors of Triadic Interactions During Infancy

In this study, we explored the predictive role of family interactions and family representations in mothers and fathers during pregnancy for postnatal motherfatherinfant interactions during the first 2 years after birth. Families (N = 42) were seen at the fifth month of pregnancy and at 3 and 18 months after birth. During pregnancy, parents were asked to play with their baby at the first meeting by using a doll in accordance with the procedure of the prenatal Lausanne Trilogue Play (LTP; A. Corboz-Warnery & E. Fivaz-Depeursinge, 2001; E. Fivaz-Depeursinge, F. Frascarolo-Moutinot, & A. Corboz-Warnery, 2010). Family representations were assessed by administering the Family System Test (T. Gehring, 1998). Marital satisfaction and the history of the couple were assessed through self-reported questionnaires. At 3 and 18 months, family interactions were assessed in the postnatal LTP. Infant temperament was assessed through parent reports. Results show that (a) prenatal interactions and child temperament are the most important predictors of family interactions and (b) paternal representations are predictive of family interactions at 3 months. These results show that observational assessment of nascent family interactions is possible during pregnancy, which would allow early screening of family maladjustment. The findings also highlight the necessity of taking into account paternal representations as a significant variable in the development of family interactions.

Combining classification techniques to define topo-climatic landscapes

Landscape classification tackles issues related to the representation and analysis of continuous and variable ecological data. In this study, a methodology is created in order to define topo-climatic landscapes (TCL) in the north-west of Catalonia (north-east of the Iberian Peninsula). TCLs relate the ecological behaviour of a landscape in terms of topography, physiognomy and climate, which compound the main drivers of an ecosystem. Selected variables are derived from different sources such as remote sensing and climatic atlas. The proposed methodology combines unsupervised interative cluster classification with a supervised fuzzy classification. As a result, 28 TCLs have been found for the study area which may be differentiated in terms of vegetation physiognomy and vegetation altitudinal range type. Furthermore a hierarchy among TCLs is set, enabling the merging of clusters and allowing for changes of scale. Through the topo-climatic landscape map, managers may identify patches with similar environmental conditions and asses at the same time the uncertainty involved.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

Predictors of temporary and permanent work disability in patients with inflammatory bowel disease: results of the swiss inflammatory bowel disease cohort study.

BACKGROUND: Inflammatory bowel disease can decrease the quality of life and induce work disability. We sought to (1) identify and quantify the predictors of disease-specific work disability in patients with inflammatory bowel disease and (2) assess the suitability of using cross-sectional data to predict future outcomes, using the Swiss Inflammatory Bowel Disease Cohort Study data. METHODS: A total of 1187 patients were enrolled and followed up for an average of 13 months. Predictors included patient and disease characteristics and drug utilization. Potential predictors were identified through an expert panel and published literature. We estimated adjusted effect estimates with 95% confidence intervals using logistic and zero-inflated Poisson regression. RESULTS: Overall, 699 (58.9%) experienced Crohn's disease and 488 (41.1%) had ulcerative colitis. Most important predictors for temporary work disability in patients with Crohn's disease included gender, disease duration, disease activity, C-reactive protein level, smoking, depressive symptoms, fistulas, extraintestinal manifestations, and the use of immunosuppressants/steroids. Temporary work disability in patients with ulcerative colitis was associated with age, disease duration, disease activity, and the use of steroids/antibiotics. In all patients, disease activity emerged as the only predictor of permanent work disability. Comparing data at enrollment versus follow-up yielded substantial differences regarding disability and predictors, with follow-up data showing greater predictor effects. CONCLUSIONS: We identified predictors of work disability in patients with Crohn's disease and ulcerative colitis. Our findings can help in forecasting these disease courses and guide the choice of appropriate measures to prevent adverse outcomes. Comparing cross-sectional and longitudinal data showed that the conduction of cohort studies is inevitable for the examination of disability.

Bayesian forecasting with highly correlated predictors

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.

I want to quit education: a longitudinal study of stress and optimism as predictors of school dropout intention

Prior research on school dropout has often focused on stable person- and institution-level variables. In this research, we investigate longitudinally perceived stress and optimism as predictors of dropout intentions over a period of four years, and distinguish between stable and temporary predictors of dropout intentions. Findings based on a nationally representative sample of 16e20 year-olds in Switzerland (N ¼ 4312) show that both average levels of stress and optimism as well as annually varying levels of stress and optimism affect dropout intentions. Additionally, results show that optimism buffers the negative impact of annually varying stress (i.e., years with more stress than usual), but not of stable levels of stress (i.e., stress over four years). The implications of the results are discussed according to a dynamic and preventive approach of school dropout.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

Predictors of weight change in sedentary smokers receiving a standard smoking cessation intervention

L'arrêt de la cigarette est généralement associé à une prise de poids. Celle-ci peut menacer la motivation des fumeurs à s'engager dans un processus d'arrêt du tabac et constitue un motif de rechute. L'ordre de grandeur et la cinétique de la prise de poids liée à une tentative d'arrêt chez les fumeurs pris en charge selon les recommandations cliniques actuelles est peu décrite dans la littérature médicale. Le but de cette étude était de quantifier cette prise de poids, d'en déterminer la cinétique ainsi que les facteurs qui l'influencent, chez des fumeurs sédentaires bénéficiant d'une intervention d'aide à l'arrêt du tabac individualisée, composée de conseils individuels et d'une substitution nicotinique associant plusieurs modes d'administration. Nous avons analysé des données récoltées durant un essai clinique randomisé contrôlé au cours duquel était étudié l'impact d'une activité physique modérée sur les taux d'arrêt du tabac après un an chez des fumeurs sédentaires. Nous avons modélisé l'évolution du poids de l'ensemble des participants au cours du temps, selon la technique statistique des « modèles mixtes longitudinaux ». En séparant les périodes d'abstinence de la cigarette de celles de rechute et de l'utilisation reportée de substituts nicotiniques. Cette approche nous a permis de prendre en compte chaque participant à l'étude, par opposition à un modèle plus simple qui séparerait les sujets abstinents de ceux qui rechutent à n'importe quel moment de la période de suivi. Nous avons également ajusté ces modèles pour l'âge, le sexe, le niveau de dépendance à la nicotine et le niveau de formation des participants. Parmi l'ensemble des participants, nous avons noté une augmentation du poids durant les trois premiers mois de l'intervention, suivie d'une stabilisation. Au total, la prise de poids moyenne s'est élevée à 3.3 kg pour les femmes et 3.9 kg pour les hommes. Durant les périodes d'abstinence, les caractéristiques suivantes étaient associées à la prise de poids : sexe masculin et forte dépendance nicotinique. Un âge supérieur à 43 ans était associé à une prise de poids également durant les périodes de rechute. Nous avons observé une tendance, non statistiquement significative, vers une réduction de la prise des poids avec l'utilisation de substituts nicotiniques. Notre étude apporte de nouvelles données sur l'évolution du poids chez les fumeurs sédentaires qui bénéficient d'une intervention d'aide à l'arrêt du tabac. Ils prennent donc du poids, de manière modérée et limitée aux premiers mois. Parmi eux, les hommes, les individus les plus dépendants à la nicotine et les plus âgés doivent s'attendre à une prise de poids supérieure à la moyenne.

Predictors of early hospital readmission after acute pulmonary embolism.

BACKGROUND: Risk factors for early mortality after pulmonary embolism (PE) are widely known. However, it is uncertain which factors are associated with early readmission after PE. We sought to identify predictors of readmission after an admission for PE. METHODS: We studied 14 426 patient discharges with a primary diagnosis of PE from 186 acute care hospitals in Pennsylvania from January 1, 2000, to November 30, 2002. The outcome was readmission within 30 days of presentation for PE. We used a discrete proportional odds model to study the association between time to readmission and patient factors (age, sex, race, insurance, discharge status, and severity of illness), thrombolysis, and hospital characteristics (region, teaching status, and number of beds). RESULTS: Overall, 2064 patient discharges (14.3%) resulted in a readmission within 30 days of presentation for PE. The most common reasons for readmission were venous thromboembolism (21.9%), cancer (10.8%), pneumonia (5.2%), and bleeding (5.0%). In multivariable analysis, African American race (odds ratio [OR], 1.19; 95% confidence interval [CI], 1.02-1.38), Medicaid insurance (OR, 1.54; 95% CI, 1.31-1.81), discharge home with supplemental care (OR, 1.40; 95% CI, 1.27-1.54), leaving the hospital against medical advice (OR, 2.84; 95% CI, 1.80-4.48), and severity of illness were independently associated with readmission; readmission also varied by hospital region. CONCLUSIONS: Early readmission after PE is common. African American race, Medicaid insurance, severity of illness, discharge status, and hospital region are significantly associated with readmission. The high readmission rates for venous thromboembolism and bleeding suggest that readmission may be linked to suboptimal quality of care in the management of PE.

A systematic review of longitudinal population-based studies on the predictors of smoking cessation in adolescent and young adult smokers

Le tabagisme est responsable de plus de 5 million de décès par an à travers le monde. En Suisse (2010), la prévalence de fumeurs chez les 14-19 ans était de 22% et la prévalence d'ex-fumeurs de 3%, taux qui reste relativement stable au fil des dernières années. La plupart des jeunes fumeurs désirant arrêter de fumer rencontrent des difficultés pour y parvenir. Les revues empiriques ont conclu que les programmes ayant pour but l'arrêt du tabagisme chez les jeunes ont une efficacité limitée. Afin de fournir une base solide de connaissances pour les programmes d'interventions contre le tabagisme, les déterminants de l'auto-cessation ont besoin d'être compris. Nous avons systématiquement recherché dans PUBMED et EMBASE des études longitudinales, basées sur la population, portant sur les déterminants de l'auto-cessation chez des adolescents et des jeunes adultes fumeurs. Nous avons passé en revue 4'502 titres et 871 abstracts, tous examinés indépendamment par deux et trois examinateurs, respectivement. Les critères d'inclusion étant : articles publiés entre janvier 1984 et août 2010, concernant les jeunes entre 10 et 29 ans et avoir une définition de cessation de fumer d'au moins 6 mois. Neuf articles ont été retenus pour une analyse détaillée. Les données suivantes ont été extraites de chaque article : le lieu de l'étude, la période étudiée, la durée du suivi, le nombre de collecte de données, la taille de l'échantillon, l'âge ou l'année scolaire des participants, le nombre de participants qui arrêtent de fumer, le status tabagique lors de la première collecte, la définition de cessation, les co-variantes et la méthode analytique. Le nombre d'études qui montrent une association significativement significative entre un déterminant et l'arrêt du tabagisme a été tabulé à partir de toutes les études qui ont évalués ce déterminant. Trois des neufs articles retenus ont défini l'arrêt du tabagisme comme une abstinence de plus de 6 mois et les six autres comme 12 mois d'abstinence. Malgré l'hétérogénéité des méthodes utilisées, cinq facteurs principaux ressortent comme prédicteur de l'arrêt du tabagisme : 1) ne pas avoir d'amis qui fument, 2) ne pas avoir l'intention de continuer de fumer dans le futur, 3) résister à la pression sociale, 4) être âgé de plus de 18 ans lors de la première cigarette, et 5) avoir un avis négatif au sujet du tabagisme. D'autres facteurs sont significatifs mais ne sont évalués que dans peu d'articles. La littérature au sujet des prédicteurs de cessation chez les adolescents et les jeunes adultes est peu développée. Cependant, nous remarquons que les facteurs que nous avons mis en évidence ne dépendent pas que de l'individu, mais aussi de l'environnement. La prévention du tabagisme peut se centrer sur les bienfaits de l'arrêt (p.ex., par rapport à l'asthme ou les performances sportives) et ainsi motiver les jeunes gens à songer d'arrêter de fumer. Une taxation plus lourde sur le prix des cigarettes peut être envisagée afin de retarder l'âge de la première cigarette. Les publicités anti-tabagiques (non sponsorisées par les entreprises de tabac) peuvent influencer la perception des jeunes par rapport au tabagisme, renforçant ou créant une attitude anti-tabagique. Les prochaines campagnes anti- tabac devraient donc tenir compte de ces différents aspects.