Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Records 1 - 2 / 2

  • help
  • print

    Print search results

  • export

    Export search results

  • alert
    We will mail you new results for this query: q=Bub
Check title to add to marked list
Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies
Ulaszewska, Marynka M. ; Weinert, Christoph H. ; Trimigno, Alessia ; Portmann, Reto ; Andres Lacueva, Cristina ; Badertscher, René ; Brennan, Lorraine ; Brunius, Carl ; Bub, Achim ; Capozzi, Francesco ; Cialiè Rosso, Marta ; Cordero, Chiara E. ; Daniel, Hannelore ; Durand, Stéphanie ; Egert, Bjoern ; Ferrario, Paola G. ; Feskens, Edith J.M. ; Franceschi, Pietro ; Garcia-Aloy, Mar ; Giacomoni, Franck ; Giesbertz, Pieter ; González-Domínguez, Raúl ; Hanhineva, Kati ; Hemeryck, Lieselot Y. ; Kopka, Joachim ; Kulling, Sabine E. ; Llorach, Rafael ; Manach, Claudine ; Mattivi, Fulvio ; Migné, Carole ; Münger, Linda H. ; Ott, Beate ; Picone, Gianfranco ; Pimentel, Grégory ; Pujos-Guillot, Estelle ; Riccadonna, Samantha ; Rist, Manuela J. ; Rombouts, Caroline ; Rubert, Josep ; Skurk, Thomas ; Sri Harsha, Pedapati S.C. ; Meulebroek, Lieven Van; Vanhaecke, Lynn ; Vázquez-Fresno, Rosa ; Wishart, David ; Vergères, Guy - \ 2018
Molecular Nutrition & Food Research 63 (2018)1. - ISSN 1613-4125
GC–MS - LC–MS - metabolomics - NMR - nutrition
The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative “A Healthy Diet for a Healthy Life” (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful “tips and tricks” along the analytical workflow.
Prediction of fruit and vegatable intake from biomarkers using individual participant data of diet-controntrolled intervantion studies
Souverein, O.W. ; Vries, J.H.M. de; Freese, R. ; Waltz, B. ; Bub, A. ; Winkels, R.M. ; Voet, H. van der; Boshuizen, H.C. - \ 2015
The British journal of nutrition 113 (2015)9. - ISSN 0007-1145 - p. 1396 - 1409.
food-frequency questionnaire - beta-carotene - plasma carotenoids - homocysteine concentrations - fractional polynomials - lipid-peroxidation - healthy nonsmokers - serum carotenoids - oxidative stress - controlled-trial
Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose–response curve between fruit and vegetable consumption and carotenoid (a-carotene, ß-carotene, ß-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures of performance for the prediction model were calculated using cross-validation. For the prediction model of fruit, vegetable and juice intake, the root mean squared error (RMSE) was 258·0 g, the correlation between observed and predicted intake was 0·78 and the mean difference between observed and predicted intake was - 1·7 g (limits of agreement: - 466·3, 462·8 g). For the prediction of fruit and vegetable intake (excluding juices), the RMSE was 201·1 g, the correlation was 0·65 and the mean bias was 2·4 g (limits of agreement: - 368·2, 373·0 g). The prediction models which include the biomarkers and subject characteristics may be used to estimate average intake at the group level and to investigate the ranking of individuals with regard to their intake of fruit and vegetables when validating questionnaires that measure intake.
Check title to add to marked list

Show 20 50 100 records per page

 
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.