[vc_row][vc_column][vc_column_text] Authors  Alessia Trimigno, Bekzod Khakimov, Francesco Savorani, Sanne Kellebjerg Poulsen, Arne Astrup D, Lars O. Dragsted, Søren Balling Engelsen  Abstract  The aim of this study was to investigate the alteration of the human urine metabolome by means of diet and to compare the metabolic effects of the nutritionally healthy New Nordic Diet (NND) with an Average Danish Diet (ADD). The NND was designed a decade ago by scientists and...

[vc_row][vc_column][vc_column_text] Authors  Leila Khorraminezhad, Mickael Leclercq, Arnaud Droit, Jean-François Bilodeau and Iwona Rudkowska  Abstract  Machine Learning (ML) can be used for data mining, sample clustering, and classification to produce predictive models and algorithms for integration of multi-OMICs in response to dietary intake. The objective of this review was to investigate the strategies used for the analysis of multi-OMICs data in nutrition studies.  Importance of the article for the Red Tecnomifood  Diet...

[vc_row][vc_column][vc_column_text] Authors  Iris Samarra, Clara Masdevall, Elisabet Foguet-Romero, Maria Guirro, Marc Riu, Pol Herrero, Núria Canela*, Antoni Delpino-Rius  Abstract  One hundred UHT milks (52 conventional/ 48 organic) where analyzed by chromatographic methods coupled to mass spectrometry. Several oxylipins allowed to distinguish between organic and conventional origin. Arachidonic and linoleic acid derived do not correlate with their fatty acid precursors; therefore, these oxylipins could be promising as not only diet-dependent biomarkers but also for organic milk assessment. [/vc_column_text][vc_empty_space height="19px"][/vc_column][/vc_row][vc_row][vc_column css=".vc_custom_1605866005580{padding-top: 20px !important;}"][qodef_button size=""...

[vc_row][vc_column][vc_column_text] Authors  Armand Valsesia, Anirikh Chakrabarti, Jörg Hager, Dominique Langin, Wim H. M. Saris, Arne Astrup, Ellen E. Blaak, Nathalie Viguerie & Mojgan Masoodi   Abstract  Weight loss aims to improve glycemic control in obese but strong variability is observed. Using a multiomics approach, we investigated differences between 174 responders and 201 non-responders, that had lost >8% body weight following a low-caloric diet (LCD, 800 kcal/d for 8 weeks). These findings are useful for clinical practice to better characterize non-responders both prior and during weight loss.  In this study, a...

[vc_row][vc_column][vc_column_text] Authors  Sarah Berry, Ana Valdes, Nicola Segata, Andrew Chan, Richard Davies, David Drew, Paul Franks and Tim Spector.   Abstract  Glycemic, insulinemic and lipemic postprandial responses are multi-factorial and contribute to diabetes, obesity and CVD. The aim of the PREDICT I study is to assess the genetic, metabolic, metagenomic, and meal-context contribution to postprandial responses, integrating the metabolic burden and gut microbiome to predict individual responses to food using a machine learning algorithm.  The integration of...