Possible Adverse Effects of Food Additive E171 (Titanium Dioxide) Related to Particle Specific Human Toxicity, Including the Immune System.

Titanium dioxide (TiO2) is used as a food additive (E171) and can be found in sauces, icings, and chewing gums, as well as in personal care products such as toothpaste and pharmaceutical tablets. Along with the ubiquitous presence of TiO2 and recent insights into its potentially hazardous properties, there are concerns about its application in commercially available products. Especially the nano-sized particle fraction (<100 nm) of TiO2 warrants a more detailed evaluation of potential adverse health effects after ingestion. A workshop organized by the Dutch Office for Risk Assessment and Research (BuRO) identified uncertainties and knowledge gaps regarding the gastrointestinal absorption of TiO2, its distribution, the potential for accumulation, and induction of adverse health effects such as inflammation, DNA damage, and tumor promotion. This review aims to identify and evaluate recent toxicological studies on food-grade TiO2 and nano-sized TiO2 in ex-vivo, in-vitro, and in-vivo experiments along the gastrointestinal route, and to postulate an Adverse Outcome Pathway (AOP) following ingestion. Additionally, this review summarizes recommendations and outcomes of the expert meeting held by the BuRO in 2018, in order to contribute to the hazard identification and risk assessment process of ingested TiO2.

Potential cofactors in accidental food allergic reactions are frequently present but may not influence severity and occurrence.

BACKGROUND: Cofactors, such as physical exercise and alcohol intake, might be associated with the severity or occurrence of food allergic reactions. OBJECTIVE: To gain insight into the frequency of presence of potential cofactors in accidental food allergic reactions in adults and to what extent these factors influence the severity and occurrence of allergic reactions. METHODS: A prospective cohort study was conducted, with a 1-year follow-up in adult patients with a physician-diagnosed food allergy. Patients were required to fill in a questionnaire after every accidental allergic reactions to food over a 1-year period. The primary outcome measure was the frequency that potential cofactors were present in these allergic reactions. RESULTS: A total of 157 patients were included, of which 46% reported a total of 153 reactions during a 1-year follow-up period. In 74% of the reactions, ≥1 potential cofactor was reported to be present: tiredness (38%), alcohol intake (16%), stress (14%), symptoms of pollinosis (16%), symptoms of asthma (9%), sickness/flu (3%), physical exercise (3%) and use of analgesics (2%). More than one potential cofactor was reported in almost half of all reactions (47%). There was no significant difference in the presence of these factors between mild, moderate and severe reactions (P = 0.522). In the total study population, 9% of the patients used medication that might act as cofactor (antacids, angiotensin receptor blockers [ARBs], beta blockers and angiotensin-converting enzyme inhibitors [ACEIs]) on a daily basis, which however did not influence the occurrence of reactions. Furthermore, 38% daily used allergy-suppressing medication. CONCLUSIONS: Although factors suggested to be cofactors were frequently present during accidental food allergic reactions, we found no evidence for an association between the potential cofactors examined and reaction severity, in a population where most reactions were of mild to moderate severity.

Accidental food allergy reactions: Products and undeclared ingredients.

BACKGROUND: Accidental allergic reactions to food are frequent and can be severe and even fatal. OBJECTIVE: We sought to analyze the culprit food products and levels of unexpected allergens in accidental reactions. METHODS: A prospective cohort study was conducted in adults (n = 157) with a physician-confirmed diagnosis of food allergy. During a 1-year follow-up, 73 patients reported accidental allergic reactions and the culprit food products. Food samples received (n = 51) were analyzed for a wide range of suspected noningredient allergens, and risk was quantified. RESULTS: A very diverse range of food products was responsible for the unexpected allergic reactions. Thirty-seven percent (19/51) of products analyzed had 1 to 4 culprit allergens identified that were not supposed to be present according to the ingredient declaration. Concentrations varied from 1 to 5000 mg of protein of the allergenic food per kilogram of food product and were greatest for peanut, milk, and sesame. Milk proteins posed the highest estimated risk for objective allergic reactions. The intake of culprit allergens by patients varied considerably. For those cases in which culprit allergens were detected, the intake of at least 1 allergen exceeded the reference dose or a culprit allergen with a yet unknown reference dose was present. Both patient neglect of precautionary allergen labeling statements and omission of using a precautionary allergen labeling statement by food manufacturers seem to contribute to accidental reactions. CONCLUSION: A wide range of food products are causing accidental reactions in patients with food allergy. Eight different allergens not declared on the ingredient lists were detected in the culprit food products, all of which were representative of allergens regulated in the European Union.

Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies.

Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, ß-carotene, ß-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures of performance for the prediction model were calculated using cross-validation. For the prediction model of fruit, vegetable and juice intake, the root mean squared error (RMSE) was 258.0 g, the correlation between observed and predicted intake was 0.78 and the mean difference between observed and predicted intake was - 1.7 g (limits of agreement: - 466.3, 462.8 g). For the prediction of fruit and vegetable intake (excluding juices), the RMSE was 201.1 g, the correlation was 0.65 and the mean bias was 2.4 g (limits of agreement: -368.2, 373.0 g). The prediction models which include the biomarkers and subject characteristics may be used to estimate average intake at the group level and to investigate the ranking of individuals with regard to their intake of fruit and vegetables when validating questionnaires that measure intake.

The 6-a-day study: effects of fruit and vegetables on markers of oxidative stress and antioxidative defense in healthy nonsmokers.

BACKGROUND: Fruit and vegetables contain both nutritive and nonnutritive factors that might contribute to redox (antioxidant and prooxidant) actions. OBJECTIVE: We investigated the relative influence of nutritive and nonnutritive factors in fruit and vegetables on oxidative damage and enzymatic defense. DESIGN: A 25-d intervention study with complete control of dietary intake was performed in 43 healthy male and female nonsmokers who were randomly assigned to 1 of 3 groups. In addition to a basic diet devoid of fruit and vegetables, the fruit and vegetables (Fruveg) group received 600 g fruit and vegetables/d; the placebo group received a placebo pill, and the supplement group received a vitamin pill designed to contain vitamins and minerals corresponding to those in 600 g fruit and vegetables. Biomarkers of oxidative damage to protein and lipids and of antioxidant nutrients and defense enzymes were determined before and during intervention. RESULTS: Plasma lipid oxidation lag times increased during intervention in the Fruveg and supplement groups, and the increase was significantly higher in the former. Plasma protein carbonyl formation at lysine residues also increased in both of these groups. Glutathione peroxidase activity increased in the Fruveg group only. Other markers of oxidative damage, oxidative capacity, or antioxidant defense were largely unaffected by the intervention. CONCLUSIONS: Fruit and vegetables increase erythrocyte glutathione peroxidase activity and resistance of plasma lipoproteins to oxidation more efficiently than do the vitamins and minerals that fruit and vegetables are known to contain. Plasma protein carbonyl formation at lysine residues increases because of the vitamins and minerals in fruit and vegetables.

Intestinal absorption of different types of folate in healthy subjects with an ileostomy.

Our knowledge on the absorption of folate is incomplete. The deconjugation process as a possible limiting factor in the absorption of folates was investigated. The study also attempted to validate the use of the area under the serum response curve (AUC) from food compared with folic acid as a proxy variable for food folate bioavailability. Folate absorption was determined in healthy ileostomy volunteers (n 11) using a single-dose short-term protocol. In a randomised crossover design, volunteers received spinach meals and a supplement. Based on analysis of test meals and ileostomy effluents, there was no difference in folate absorption between spinach with a mono-:polyglutamate ratio 40:60 and the same spinach with a 100:0 ratio. The absolute absorption of spinach folate (79 %) calculated from the difference between folate intake and folate content of ileostomy effluents was approximately equal to the relative absorption (81 %) calculated from the AUC after consumption of spinach meals in relation to the AUC after consumption of the folic acid supplement. We conclude that the deconjugation process is not a limiting factor in the absorption of spinach folates. Comparison of AUC of food folate v. folic acid in a short-term protocol may be suitable for assessing food folate bioavailability.