Caseinomacropeptide (CMP) is a 7-kDa phosphoglycopolypeptide released from κ-casein during milk digestion and in the cheesemaking process. The objective of the study was to analyze the effect of pepsin-treated CMP from cow and goat milk on the resistance of Escherichia coli and Lactobacillus rhamnosus during acid stress. Bacterial cells in the exponential growth phase were suspended in acidified phosphate buffered saline with or without pepsin-treated CMP. Viability was determined during a 90-min incubation period. Pepsin-treated CMP exhibited bactericidal activity at pH 3.5 when added in a dose-dependent manner to E. coli, decreasing survival by more than 90% within 15 min at 0.25 mg/mL. At pH >4.5, the bactericidal activity disappeared, indicating that pepsin-treated CMP was efficient at low pH only. The effectiveness of pepsin-treated CMP at pH 3.5 was not affected by the presence of glycoconjugates linked to CMP or by the bovine or caprine origin of milk. In contrast, L. rhamnosus, a probiotic, was more resistant to acid stress when pepsin-treated bovine or caprine CMP was added to the media. Viability reached 50% after 60 min of incubation at pH 3 compared with 5% survival in the media without added pepsin-treated CMP. Neither glycosylation extent nor sequence variations between CMP from bovine milk and caprine milk affected the protective activity of hydrolyzed CMP toward L. rhamnosus. This suggests that encrypted bioactive peptides released by the pepsin treatment of CMP had an antibacterial effect on E. coli in acidic media, but improved the resistance of L. rhamnosus to acid stress. The peptide fragment accountable for bactericidal activity is the N-terminal region κ-casein f(106-124).
Acrylamide (AA) is a probable human carcinogen found in several foods. Little information is available regarding exposure of adolescents, a subgroup potentially consuming more AA-rich foods. We investigated the relationship between dietary AA intake and levels of biomarkers of exposure (urinary metabolites and hemoglobin adducts) in 195 non-smoking teenagers of Montreal Island aged 10-17 years. Dietary habits and personal characteristics were documented by questionnaire. AA and its metabolites were quantified in 12-h urine collections by LC-MS/MS. Hemoglobin adducts from 165 blood samples were also analyzed by LC-MS/MS. Most prevalent urinary metabolites were NACP and NACP-S, with respective geometric mean concentrations of 31.2 and 14.2 μmol/mol creatinine. Geometric mean concentrations of AAVal and GAVal (hemoglobin adducts of AA and glycidamide (GA) with N-terminal valine residues) were 45.4 and 45.6 pmol/g globin, respectively. AA intake during the 2 days before urine collection was a significant predictor of NACP+NACP-S urinary concentrations (P<0.0001). AA intakes during the month before blood collection (P<0.0001) and passive smoking (P<0.05) were associated with adduct levels. Levels of hemoglobin adducts were above biomonitoring equivalent values corresponding to a 1 × 10(-4) excess cancer risk, which may indicate the need to reduce AA exposure in the population.
To assess exposure to pyrethroids in the general population, one of most widely used method nowadays consists of measuring urinary metabolites. Unfortunately, interpretation of data is limited by the unspecified relation between dose and levels in biological tissues and excreta. The objective of this study was to develop a common multi-compartment toxicokinetic model to predict the time courses of two mainly used pyrethroid pesticides, permethrin and cypermethrin, and their metabolites (cis-DCCA, trans-DCCA and 3-PBA) in the human body and in accessible biological matrices following different exposure scenarios. Toxicokinetics was described mathematically by systems of differential equations to yield the time courses of these pyrethroids and their metabolites in the different compartments. Unknown transfer rate values between compartments were determined from best fits to available human data on the urinary excretion time courses of metabolites following an oral and dermal exposure to cypermethrin in volunteers. Since values for these coefficients have not yet been determined, a mathematical routine was programmed in MathCad to establish the possible range of values on the basis of physiological and mathematical considerations. The best combination of parameter values was then selected using a statistic measure (reliability factor) along with a statistically acceptable range of values for each parameter. With this approach, simulations provided a close approximation to published time course data. This model allows to predict urinary time courses of trans-DCCA, cis-DCCA and 3-PBA, whatever the exposure route. It can also serve to reconstruct absorbed doses of permethrin or cypermethrin in the population using measured biomarker data.
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