1. Challenge tests and standardized test meals Time-resolved changes in the metabolome after a challenge test may provide a measure of „metabolic flexibility“ and may be indicative for disease susceptibility and onset The need for a standardized „test diet“ was expressed. This may be helpful in particular for studies on bioavailability and metabolism (transformation) of secondary plant compounds Depending on the frame/size of the human studies there is the need to adjust the challenges to real life conditions (feasibility)

2. A GOLD STANDARD DEFINED liquid meal defined by all means for its constituents defined by all means for its constituents including a mixture of secondary plant constituents for assessing human responses and variance of the microbiota Energy content and density per volume Lipids (amount, classes, fatty acid pattern) Protein (amount, source, amino acid pattern) Carbohydrates (amount, class, type) Vitamins (amount, class, specific form) Minerals and trace elements (all, specific form) A GOLD STANDARD liquid diet for comprehensive phenotyping approaches in human cohort studies

3. Challenge tests and standardized test meals An extended fasting period of a total of 16 hours may be acceptable for study participants as a minimum. Whereever possible, a longer period of fasting does provide better information on the catabolic response. The OGTT (50g/75g of Glucose: to be defined) seems a sensible approach for driving the „endogenous metabolome“ out of steady state and measure its return. It can be standardized best : however, per kg, lean mass or absolute need to be defined! Depending on the frame/size of the human studies there is the need to adjust the number of samples collected during/after the challeng to real life conditions (feasibility) to 3 or 4 and those should be at best minimal invasive. What should be in the liquid test meal (primary nutrients, secondary plant compounds) ? Who would like to join a „definition group“ ????? Should it be administered per body weight, lean mass, BMR, or absolute volume ?

4. Univariate time series analysis time Multiple testing when huge data sets Univariate versus bonferroni correction (the latter kills significance) Check on Peter et al, Trend analysis …. 2010, 98-104, Analytica Chimica Acta And Rubingh, J Proteome Research 2009 4319-4327