Analyzing repeated data collected by mobile phones and frequent text messages. An example of Low back pain measured weekly for 18 weeks

BACKGROUND: Repeated data collection is desirable when monitoring fluctuating conditions. Mobile phones can be used to gather such data from large groups of respondents by sending and receiving frequently repeated short questions and answers as text messages. The analysis of repeated data involves some challenges. Vital issues to consider are the within-subject correlation, the between measurement occasion correlation and the presence of missing values. The overall aim of this commentary is to describe different methods of analyzing repeated data. It is meant to give an overview for the clinical researcher in order for complex outcome measures to be interpreted in a clinically meaningful way. METHODS: A model data set was formed using data from two clinical studies, where patients with low back pain were followed with weekly text messages for 18 weeks. Different research questions and analytic approaches were illustrated and discussed, as well as the handling of missing data. In the applications the weekly outcome “number of days with pain” was analyzed in relation to the patients’ “previous duration of pain” (categorized as more or less than 30 days in the previous year). Research questions with appropriate analytical methods 1: How many days with pain do patients experience? This question was answered with data summaries. 2: What is the proportion of participants “recovered” at a specific time point? This question was answered using logistic regression analysis. 3: What is the time to recovery? This question was answered using survival analysis, illustrated in Kaplan-Meier curves, Proportional Hazard regression analyses and spline regression analyses. 4: How is the repeatedly measured data associated with baseline (predictor) variables? This question was answered using generalized Estimating Equations, Poisson regression and Mixed linear models analyses. 5: Are there subgroups of patients with similar courses of pain within the studied population? A visual approach and hierarchical cluster analyses revealed different subgroups using subsets of the model data. CONCLUSIONS: We have illustrated several ways of analysing repeated measures with both traditional analytic approaches using standard statistical packages, as well as recently developed statistical methods that will utilize all the vital features inherent in the data

Regulation of ovulation rate in mammals: contribution of sheep genetic models

Ovarian folliculogenesis in mammals from the constitution of primordial follicles up to ovulation is a reasonably well understood mechanism. Nevertheless, underlying mechanisms that determine the number of ovulating follicles were enigmatic until the identification of the fecundity genes affecting ovulation rate in sheep, bone morphogenetic protein-15 (BMP-15), growth and differentiation factor-9 (GDF-9) and BMP receptor-1B (BMPR-1B). In this review, we focus on the use of these sheep genetic models for understanding the role of the BMP system as an intra-ovarian regulator of follicular growth and maturation, and finally, ovulation rate

Phosphorylation of CLEC-2 is dependent on lipid rafts, actin polymerization,secondary mediators, and Rac

The C-type lectin-like receptor 2 (CLEC-2)activates platelets through Src and Syk tyrosine kinases via a single cytoplasmic YxxL motif known as a hem immunoreceptor tyrosine-based activation motif (hemITAM).Here, we demonstrate using sucrose gradient ultracentrifugation and methyl--cyclodextrin treatment that CLEC-2 translocates to lipid rafts upon ligand engagement and that translocation is essential for hemITAM phosphorylation and signal initiation. HemITAM phosphorylation, but not translocation, is also critically dependent on actin polymerization,Rac1 activation, and release of ADP and thromboxane A2 (TxA2). The role of ADP and TxA2 in mediating hosphorylation is dependent on ligand engagement and rac activation but is independent of platelet aggregation. In contrast,tyrosine phosphorylation of the GPVIFcR -chain ITAM, which has 2 YxxL motifs,is independent of actin polymerization and secondary mediators. These results reveal a unique series of proximal events in CLEC-2 phosphorylation involving actin polymerization, secondary mediators,and Rac activation

Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

Modelling and optimization strategy of ultrafiltration performances for the fractionation of protein hydrolysates

Les hydrolysats protéiques ont une haute valeur ajoutée pour des secteurs industriels variés, de par leurs propriétés nutritives, fonctionnelles et / ou nutraceutiques. Pour améliorer les propriétés des hydrolysats, l’ultrafiltration est utilisée. Cependant, le manque d’outils de modélisation lié à la complexité des mélanges est un verrou pour une mise en œuvre rationnelle du procédé. Ces travaux ont permis de valider une stratégie de prédiction basée sur des caractéristiques classiques des hydrolysats et un étalonnage expérimental de la membrane d’ultrafiltration. Cette méthode permet de prédire les rendements et enrichissements en fraction(s) ou peptide(s) cible(s), ainsi que la productivité du procédé. Le modèle global de prédiction de l’ultrafiltration obtenu est alors utilisé afin d’optimiser la mise en œuvre de ce procédé. La démarche d’optimisation consiste à maximiser l’enrichissement de fractions ou de peptides cibles en minimisant la consommation d’eau et la durée du procédéProtein hydrolysates are high added value mixtures for various industrial areas, thanks to their nutritive, functional or nutraceutical properties. To enhance hydrolysates performances, fractionation processes such as ultrafiltration are used. However, the lack of tools to predict ultrafiltration performances is a major bottleneck for a rational implementation of the process. This research thesis work enables to validate a prediction strategy based on classical characteristics of hydrolysates and an experimental calibration of the membrane. Yields and enrichment factors in targeted peptides or fractions during ultrafiltration as well as the productivity of the process can be predicted. This global methodology of performances prediction is then used to optimize the implementation modes of ultrafiltration. The multiobjective optimization approach consists in maximizing the enrichment in targeted peptides or fractions while water consumption and / or process duration is minimize

Stratégie de modélisation et d’optimisation des performances de l’ultrafiltration pour le fractionnement d’hydrolysats protéiques

Protein hydrolysates are high added value mixtures for various industrial areas, thanks to their nutritive, functional or nutraceutical properties. To enhance hydrolysates performances, fractionation processes such as ultrafiltration are used. However, the lack of tools to predict ultrafiltration performances is a major bottleneck for a rational implementation of the process. This research thesis work enables to validate a prediction strategy based on classical characteristics of hydrolysates and an experimental calibration of the membrane. Yields and enrichment factors in targeted peptides or fractions during ultrafiltration as well as the productivity of the process can be predicted. This global methodology of performances prediction is then used to optimize the implementation modes of ultrafiltration. The multiobjective optimization approach consists in maximizing the enrichment in targeted peptides or fractions while water consumption and / or process duration is minimizedLes hydrolysats protéiques ont une haute valeur ajoutée pour des secteurs industriels variés, de par leurs propriétés nutritives, fonctionnelles et / ou nutraceutiques. Pour améliorer les propriétés des hydrolysats, l’ultrafiltration est utilisée. Cependant, le manque d’outils de modélisation lié à la complexité des mélanges est un verrou pour une mise en œuvre rationnelle du procédé. Ces travaux ont permis de valider une stratégie de prédiction basée sur des caractéristiques classiques des hydrolysats et un étalonnage expérimental de la membrane d’ultrafiltration. Cette méthode permet de prédire les rendements et enrichissements en fraction(s) ou peptide(s) cible(s), ainsi que la productivité du procédé. Le modèle global de prédiction de l’ultrafiltration obtenu est alors utilisé afin d’optimiser la mise en œuvre de ce procédé. La démarche d’optimisation consiste à maximiser l’enrichissement de fractions ou de peptides cibles en minimisant la consommation d’eau et la durée du procéd

Size-exclusion HPLC as a sensitive and calibrationless method for complex peptide mixtures quantification

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