Mechanisms involved in down-regulation of intestinal IgA in rats by high cocoa intake

Previous studies have shown that rat intestinal immunoglobulin A (IgA) concentration and lymphocyte composition of the intestinal immune system were influenced by a highly enriched cocoa diet. The aim of this study was to dissect the mechanisms by which a long-term high cocoa intake was capable of modifying gut secretory IgA in Wistar rats. After 7 weeks of nutritional intervention, Peyer's patches, mesenteric lymph nodes and the small intestine were excised for gene expression assessment of IgA, transforming growth factor ß, C-C chemokine receptor-9 (CCR9), interleukin (IL)-6, CD40, retinoic acid receptors (RAR¿ and RARß), C-C chemokine ligand (CCL)-25 and CCL28 chemokines, polymeric immunoglobulin receptor and toll-like receptors (TLR) expression by real-time polymerase chain reaction. As in previous studies, secretory IgA concentration decreased in intestinal wash and fecal samples after cocoa intake. Results from the gene expression showed that cocoa intake reduced IgA and IL¿6 in Peyer's patches and mesenteric lymph nodes, whereas in small intestine, cocoa decreased IgA, CCR9, CCL28, RAR¿ and RARß. Moreover, cocoa-fed animals presented an altered TLR expression pattern in the three compartments studied. In conclusion, a high-cocoa diet down-regulated cytokines such as IL-6, which is required for the activation of B cells to become IgA-secreting cells, chemokines and chemokine receptors, such as CCL28 and CCR9 together with RAR¿ and RARß, which are involved in the gut homing of IgA-secreting cells. Moreover, cocoa modified the cross-talk between microbiota and intestinal cells as was detected by an altered TLR pattern. These overall effects in the intestine may explain the intestinal IgA down-regulatory effect after the consumption of a long-term cocoa-enriched diet.

Complications following an accidental sodium hypochlorite extrusion: A report of two cases

Sodium hypochlorite (NaOCl) is the most commonly used solution in root canal treatments, as it is a low-cost method that displays a very effective antimicrobial activity against microbiota of infected root canals. However, this solution can cause complications especially due to its cytotoxic features. When this solution is injected into the adjacent tissues, the patient usually experiences intense pain, and an urgent treatment should be implemented in order to prevent a long-term sequelae. This paper describes the clinical features of two patients that experienced an accidental extrusion of NaOCl after endodontic treatment of varying severity and with different treatments. Furthermore, it shows the long-term neurologic injuries that this type of accidents may cause and a treatment protocol for these situations will be suggested.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.