Assessing food allergy risks from residual peanut protein in highly refined vegetable oil.

Refined vegetable oils including refined peanut oil are widely used in foods. Due to shared production processes, refined non-peanut vegetable oils can contain residual peanut proteins. We estimated the predicted number of allergic reactions to residual peanut proteins using probabilistic risk assessment applied to several scenarios involving food products made with vegetable oils.

Food Consumption and Nutrient Intake by Children Aged 10 to 48 Months Attending Day Care in The Netherlands.

The diet of young children is an important determinant of long-term health effects, such as overweight and obesity. We analyzed two-day food consumption records from 1526 young children (10-48 months old) attending 199 daycare centers across The Netherlands. Data were observed and recorded in diaries by caregivers at the day nursery and by parents at home on days that the children attended the daycare center.

Metabolomic biomarkers for personalised glucose lowering drugs treatment in type 2 diabetes.

We aimed to identify metabolites to predict patients' response to glucose lowering treatment during the first 5 years after detection of type 2 diabetes. Metabolites were measured by GC-MS in baseline samples from 346 screen-detected type 2 diabetes patients in the ADDITION-NL study. The response to treatment with metformin and/or sulphonylurea (SU) was analysed to identify metabolites predictive of 5 year HbA1c change by multiple regression analysis.

Dietary medium chain fatty acid supplementation leads to reduced VLDL lipolysis and uptake rates in comparison to linoleic acid supplementation.

Dietary medium chain fatty acids (MCFA) and linoleic acid follow different metabolic routes, and linoleic acid activates PPAR receptors. Both these mechanisms may modify lipoprotein and fatty acid metabolism after dietary intervention. Our objective was to investigate how dietary MCFA and linoleic acid supplementation and body fat distribution affect the fasting lipoprotein subclass profile, lipoprotein kinetics, and postprandial fatty acid kinetics.

Food allergy population thresholds: an evaluation of the number of oral food challenges and dosing schemes on the accuracy of threshold dose distribution modeling.

For most allergenic foods, limited availability of threshold dose information within the population restricts the advice on action levels of unintended allergenic foods which should trigger advisory labeling on packaged foods. The objective of this paper is to provide guidance for selecting an optimal sample size for threshold dosing studies for major allergenic foods and to identify factors influencing the accuracy of estimation. A simulation study was performed to evaluate the effects of sample size and dosing schemes on the accuracy of the threshold distribution curve.

Controlling false discovery rates in factorial experiments with between-subjects and within-subjects tests.

Background: The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P-values for different tests in one and the same response along with P-values for the same test and different responses.

Fish oil and inflammatory status alter the n-3 to n-6 balance of the endocannabinoid and oxylipin metabolomes in mouse plasma and tissues.

It is well established that dietary intake of n-3 fatty acids is associated with anti-inflammatory effects, and this has been linked to modulation of the oxylipin and endocannabinoid metabolomes. However, the amount of data on specific tissue effects is limited, and it is not known how inflammation affects this relation. In the present study we systematically explored the combined effects of n-3 fatty acid diets and inflammation on the in vivo endocannabinoid and oxylipin metabolomes using a multicompartment, detailed targeted lipidomics approach.

The Stokes number approach to support scale-up and technology transfer of a mixing process.

Transferring processes between different scales and types of mixers is a common operation in industry. Challenges within this operation include the existence of considerable differences in blending conditions between mixer scales and types. Obtaining the correct blending conditions is crucial for the ability to break up agglomerates in order to achieve the desired blend uniformity.

Time-dependent effect of in vivo inflammation on eicosanoid and endocannabinoid levels in plasma, liver, ileum and adipose tissue in C57BL/6 mice fed a fish-oil diet.

Eicosanoids and endocannabinoids/N-acylethanolamines (NAEs) are fatty acid derived compounds with a regulatory role in inflammation. Considering their complex metabolism, it is likely that inflammation affects multiple compounds at the same time, but how lipid profiles change in plasma and other tissues after an inflammatory stimulus has not been described in detail. In addition, dietary fish oil increases levels of several n-3 fatty acid derived eicosanoids and endocannabinoids, and this may lead to a broader change in the profiles of bioactive lipids.

Plasma metabolomics and proteomics profiling after a postprandial challenge reveal subtle diet effects on human metabolic status.

We introduce the metabolomics and proteomics based Postprandial Challenge Test (PCT) to quantify the postprandial response of multiple metabolic processes in humans in a standardized manner. The PCT comprised consumption of a standardized 500 ml dairy shake containing respectively 59, 30 and 12 energy percent lipids, carbohydrates and protein. During a 6 h time course after PCT 145 plasma metabolites, 79 proteins and 7 clinical chemistry parameters were quantified.

Visualization and identification of health space, based on personalized molecular phenotype and treatment response to relevant underlying biological processes.

Background: Being able to visualize multivariate biological treatment effects can be insightful. However the axes in visualizations are often solely defined by variation and thus have no biological meaning. This makes the effects of treatment difficult to interpret.

Kinetic energy density and agglomerate abrasion rate during blending of agglomerates into powders.

Problems related to the blending of a cohesive powder with a free flowing bulk powder are frequently encountered in the pharmaceutical industry. The cohesive powder often forms lumps or agglomerates which are not dispersed during the mixing process and are therefore detrimental to blend uniformity. Achieving sufficient blend uniformity requires that the blending conditions are able to break up agglomerates, which is often an abrasion process.

An antiinflammatory dietary mix modulates inflammation and oxidative and metabolic stress in overweight men: a nutrigenomics approach.

Background: Low-grade chronic inflammation in overweight subjects is thought to play an important role in disease development.

Objective: It was hypothesized that specific dietary components are able to reduce low-grade inflammation as well as metabolic and oxidative stress.

Design: Dietary products [resveratrol, green tea extract, alpha-tocopherol, vitamin C, n-3 (omega-3) polyunsaturated fatty acids, and tomato extract] selected for their evidence-based antiinflammatory properties were combined and given as supplements to 36 healthy overweight men with mildly elevated plasma C-reactive protein concentrations in a double-blind, placebo-controlled, crossover study with treatment periods of 5 wk.

Metabolomics data exploration guided by prior knowledge.

In metabolomics research, it is often important to focus the data analysis to specific areas of interest within the metabolome. In this paper, we describe the application of consensus principal component analysis (CPCA) and canonical correlation analysis (CCA) as a means to explore the relation between metabolome data and (i) biochemically related metabolites and (ii) an amino acid biosynthesis pathway. CPCA searches for major trends in the behavior of metabolite concentrations that are in common for the metabolites of interest and the remainder of the metabolome.

Analyzing longitudinal microbial metabolomics data.

A longitudinal experimental design in combination with metabolomics and multiway data analysis is a powerful approach in the identification of metabolites whose correlation with bioproduct formation shows a shift in time. In this paper, a strategy is presented for the analysis of longitudinal microbial metabolomics data, which was performed in order to identify metabolites that are likely inducers of phenylalanine production by Escherichia coli. The variation in phenylalanine production as a function of differences in metabolism induced by the different environmental conditions in time was described by a validated multiway statistical model.

Metabolic profiling of the response to an oral glucose tolerance test detects subtle metabolic changes.

Background: The prevalence of overweight is increasing globally and has become a serious health problem. Low-grade chronic inflammation in overweight subjects is thought to play an important role in disease development. Novel tools to understand these processes are needed.

The effect of Korean pine nut oil on in vitro CCK release, on appetite sensations and on gut hormones in post-menopausal overweight women.

Appetite suppressants may be one strategy in the fight against obesity. This study evaluated whether Korean pine nut free fatty acids (FFA) and triglycerides (TG) work as an appetite suppressant. Korean pine nut FFA were evaluated in STC-1 cell culture for their ability to increase cholecystokinin (CCK-8) secretion vs.

How to distinguish healthy from diseased? Classification strategy for mass spectrometry-based clinical proteomics.

SELDI-TOF-MS is rapidly gaining popularity as a screening tool for clinical applications of proteomics. Application of adequate statistical techniques in all the stages from measurement to information is obligatory. One of the statistical methods often used in proteomics is classification: the assignment of subjects to discrete categories, for example healthy or diseased.

Risk estimation for carcinogens based on epidemiological data: a structured approach, illustrated by an example on chromium.

It is generally recognized that human, epidemiological data, if available, are preferred as the starting point for quantitative risk analysis above the use of data from animal studies. Although methods to obtain proper risk estimates from epidemiological data are available, several impediments prevent their widespread application. These impediments include unfamiliarity with epidemiological methods and the lack of a structured and transparent approach.

Assessing the performance of statistical validation tools for megavariate metabolomics data.

Statistical model validation tools such as cross-validation, jack-knifing model parameters and permutation tests are meant to obtain an objective assessment of the performance and stability of a statistical model. However, little is known about the performance of these tools for megavariate data sets, having, for instance, a number of variables larger than 10 times the number of subjects. The performance is assessed for megavariate metabolomics data, but the conclusions also carry over to proteomics, transcriptomics and many other research areas.