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Laval, France

Since milk fat is mainly consumed as cheeses, this category of dairy products represents important vectors to consider from a nutritional point of view. Cheeses are dynamic systems which evolve from a structural and compositional point of view under mechanical and biochemical mechanisms. Technological processes used during the manufacture of cheeses may alter the structure of milk fat globules and change the composition of their surface which affect the structure of the gel after renneting or acidification of milk. Cheeses consumption has not been correlated to the risk of cardiovascular diseases. Over the fat content and the fatty acid composition, the other components of cheeses such as calcium, proteins and phospholipids should be considered to explain the nutritional properties of milk fat. This notion of "matrix effect" requires further scientific investigations through human interventional studies to elucidate the mechanisms. © Lavoisier - La photocopie non autorisee est un delit. Source

Du Q.,BioMet | Du Q.,Aix - Marseille University | Martin J.-C.,BioMet | Martin J.-C.,Aix - Marseille University | And 5 more authors.
Journal of Nutritional Biochemistry | Year: 2012

Achieving an appropriate docosahexaenoic acid (DHA) status in the neonatal brain is an important goal of neonatal nutrition. We evaluated how different dietary fat matrices improved DHA content in the brains of both male and female rats. Forty rats of each gender were born from dams fed over gestation and lactation with a low α-linolenic acid (ALA) diet (0.4% of fatty acids) and subjected for 6 weeks after weaning to a palm oil blend-based diet (10% by weight) that provided either 1.5% ALA or 1.5% ALA and 0.12% DHA with 0.4% arachidonic acid or to an anhydrous dairy fat blend that provided 1.5% or 2.3% ALA. Fatty acids in the plasma, red blood cells (RBCs) and whole brain were determined by gas chromatography. The 1.5% ALA dairy fat was superior to both the 1.5% ALA palm oil blends for increasing brain DHA (14.4% increase, P<.05), and the 2.3% ALA dairy blend exhibited a further increase that could be ascribed to both an ALA increase and n-6/n-3 ratio decrease. Females had significantly higher brain DHA due to a gender-to-diet interaction, with dairy fats attenuating the gender effect. Brain DHA was predicted with a better accuracy by some plasma and RBC fatty acids when used in combination (R2 of 0.6) than when used individually (R2=0.47 for RBC n-3 docosapentaenoic acid at best). In conclusion, dairy fat blends enriched with ALA appear to be an interesting strategy for achieving optimal DHA levels in the brain of postweaning rats. Human applications are worth considering. © 2012 Elsevier Inc. Source

Geurts L.,Catholic University of Leuven | Everard A.,Catholic University of Leuven | Le Ruyet P.,Lactalis | Delzenne N.M.,Catholic University of Leuven | Cani P.D.,Catholic University of Leuven
Journal of Agricultural and Food Chemistry | Year: 2012

Growing evidence suggests that the consumption of dairy products may contribute to a reduced incidence of cardiovascular risk factors, such as obesity, dyslipidemia, and type 2 diabetes. The fatty acid composition in milk fat, the duration of ripening, and the complexity of the food matrices are important factors that may interfere with the physiological impact. In this study, we treated genetic obese and type 2 diabetic mice (db/db) for 4 weeks with different dairy (cheese-based) products, differing by the duration of ripening (0, 15, or 35 days). We found that 35 days ripened product significantly improved glucose tolerance, an effect associated with a decreased adipose tissue lipid peroxide markers (TBARS and NAPDH-oxidase mRNA expression), without affecting body weight, food intake, and fat mass. Both fermented matrices significantly decreased the hepatic lipid content, without modifying plasma triglycerides or plasma total cholesterol. These data suggest that dairy products issued from longer ripening positively impact glucose tolerance, hepatic steatosis, and adipose tissue oxidative stress. Further investigations are warranted to decipher the interactions between milk products fermentation, lipids, and host metabolism. © 2012 American Chemical Society. Source

Malpuech-Brugere C.,French National Institute for Agricultural Research | Malpuech-Brugere C.,Clermont University | Mouriot J.,French National Institute for Agricultural Research | Mouriot J.,Clermont University | And 10 more authors.
European Journal of Clinical Nutrition | Year: 2010

Background/Objectives: The objective of this study was to evaluate the impact of three specific ruminant (R) milk fats resulting from modification of the cow's diet on cardiovascular risk factors in healthy volunteers. R-milk fats were characterized by increased content in total trans fatty acids (R-TFAs) and parallel decrease in saturated fatty acids (SFAs).Subjects/Methods:A total of 111 healthy, normolipemic men and women have been recruited for a monocentric, randomized, double-blind and parallel intervention, 4-week controlled study. Volunteers consumed three experimental products (butter, dessert cream and cookies) made with one of the three specific milk fats (55 g fat per day). During the first week (run-in period), the subjects consumed on a daily basis dairy products containing 72% SFA/2.85% R-TFA (called ′L0′). For the next 3 weeks of the study (intervention period), the first group continued to consume L0 products. The second group received dairy products containing 63.3% SFA/4.06% R-TFA (called ′L4′), and the third group received dairy products containing 56.6% SFA/12.16% R-TFA (called ′L9′).Results: Plasma concentrations of high-density lipoprotein (HDL)-cholesterol were not significantly altered by either diet (P0.38). Compared to L0 diet, L4 diet contributed to reduce low-density lipoprotein (LDL)-cholesterol (0.140±38 mmol/l, P0.04), total cholesterol (0.130±50 mmol/l, P0.04), LDL-cholesterol/HDL-cholesterol (0.140±36, P0.03) and total cholesterol/HDL-cholesterol (0.180±44, P0.02).Conclusions:Different milk fat profiles can change cardiovascular plasma parameters in human healthy volunteers. A limited increase of the R-TFA/SFA ratio in dairy products is associated with an improvement in some cardiovascular risk factors. However, a further increase in R-TFA/SFA ratio has no additional benefit. © 2010 Macmillian Publishers limited. Source

Semmar N.,French National Institute for Agricultural Research | Semmar N.,French Institute of Health and Medical Research | Semmar N.,University of Tunis | Canlet C.,French National Institute for Agricultural Research | And 6 more authors.
Current Drug Metabolism | Year: 2014

Metabolic pools of biological matrices can be extensively analyzed by NMR. Measured data consist of hundreds of NMR signals with different chemical shifts and intensities representing different metabolites' types and levels, respectively. Relevant predictive NMR signals need to be extracted from the pool using variable selection methods. This paper presents both a review and research on this metabolomics field. After reviews on discriminant potentials and statistical analyses of NMR data in biological fields, the paper presents an original approach to extract a small number of NMR signals in a biological matrix A (BM-A) in order to predict metabolic levels in another biological matrix B (BM-B). Initially, NMR dataset of BM-A was decomposed into several row-column homogeneous blocks using hierarchical cluster analysis (HCA). Then, each block was subjected to a complete set of Jackknifed correspondence analysis (CA) by removing separately each individual (row). Each CA condensed the numerous NMR signals into some principal components (PCs). The different PCs representing the (n - 1) active individuals were used as latent variables in a stepwise multi-linear regression to predict metabolic levels in BM-B. From the built regression model, metabolite level in the outside individual was predicted (for next model validation). From all the PCs-based regression models resulting from all the jackknifed CA applied on all the individuals, the most contributive NMR signals were identified by their highest absolute contributions to PCs. Finally, these selected NMR signals (measured in BMA) were used to build final population and sub-population regression models predicting metabolite levels in BM-B. © 2014 Bentham Science Publishers. Source

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