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Netrin-1 decreased in EAE and in MS patients, mainly during relapse, suggesting an anti-inflammatory role of netrin-1. Further research should be performed in a larger cohort of patients to validate netrin-1 as a biomarker of MS inflammatory activity.

BackgroundAlthough the effects of probiotics on the immune system have been extensively evaluated under disease states, their role in healthy situations remains unclear, since changes are hardly expected under immunological homeostasis. EFSA indicates that vaccination protocols could be used to evaluate the potential role of probiotics to improve the immune response against antigen challenges. The aim of the study was to evaluate the effect of Lactobacillus coryniformis CECT5711 (Lc) on the specific immunity of healthy volunteers undergoing vaccination with Hepatitis A virus (HAV).MethodsOne hundred twenty-three healthy adults were randomised into three groups to follow a 6-week (wk) intervention and all received an intramuscular HAV vaccine 2 weeks after starting the intervention: 1) PRO1 received Lc for 2weeks (1 capsule/day; 3 × 109 CFU/capsule) and placebo capsules after vaccination; 2) PRO2 received a daily capsule of Lc (3 × 109 cfu/day) before and after the challenge; 3) Control group (C) received a daily placebo capsule before and after the vaccine. Blood samples were collected at the beginning (visit 1; V1) and after 2 (V2) and 6 weeks (V3) of the intervention. At each visit, lymphocyte subset counts and cytokine levels were analysed. Specific HAV antibodies were analysed at V1 and V3. To evaluate differences between groups, one-way ANOVA with Bonferroni post-hoc test were used regarding lymphocyte subset counts and specific HAV antibodies production, and Friedman test of related samples and Kendall concordance coefficient for cytokines production. Chi square test was used to analyse seroconversion rates.ResultsSpecific HAV antibodies were significantly higher in PRO1 (50.54 ± 29.57) compared to C (36.23 ± 16.45) (P = 0.017) and showed an intermediate value in PRO2 (41.61 ± 15.74). Seroconversion rates were similar in the three groups (97.3, 92.3 and 97.4% in C, PRO1 and PRO2 respectively). Memory T-helper lymphocytes increased in V3 vs. V1 (P = 0.032) in PRO2. No differences were found in cytokine concentrations.ConclusionMixed results have been found regarding the usefulness of Lc supplementation to increase the antigen-specific antibody response to an immune challenge. Clinical trial registration number: EudraCT Number 2016-000183-42. Registered 19 January 2016. Retrospectively registered.Electronic supplementary materialThe online version of this article (doi:10.1186/s12986-016-0154-2) contains supplementary material, which is available to authorized users.

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The dynamics and diversity of human gut microbiota that can remarkably influence the wellbeing and health of the host are constantly changing through the host’s lifetime in response to various factors. The aim of the present study was to determine a set of parameters that could have a major impact on classifying subjects into a single cluster regarding gut bacteria composition. Therefore, a set of demographical, environmental, and clinical data of healthy adults aged 25–50 years (117 female and 83 men) was collected. Fecal microbiota composition was characterized using Illumina MiSeq 16S rRNA gene amplicon sequencing. Hierarchical clustering was performed to analyze the microbiota data set, and a supervised machine learning model (SVM; Support Vector Machines) was applied for classification. Seventy variables from collected data were included in machine learning analysis. The agglomerative clustering algorithm suggested the presence of four distinct community types of most abundant bacterial phyla. Each cluster harbored a statistically significant different proportion of bacterial phyla. Regarding prediction, the most important features classifying subjects into clusters were measures of obesity (waist to hip ratio, BMI, and visceral fat index), total body water, blood pressure, energy intake, total fat, olive oil intake, total fiber intake, and water intake. In conclusion, the SVM model was shown as a valuable tool to classify healthy individuals based on their gut microbiota composition.

Soft drinks are beverages composed of water and other ingredients that provide specific sensorial attributes. Soft drink consumption patterns have recently been changed partially influenced by an increased availability of different types of beverages during the last few years. Consumers' preferences to choose one drink over another are influenced, not only by genetic, psychological and environmental factors, but also by the beverage's specific attributes. In fact, beverage consumption is driven by the sensations it gives. Because the main component of soft drinks is water, an increase in the intake of soft drinks might improve fluid intake and the levels of water in the body if it is regarded as an "essential nutrient". Consumption of soft drinksA so drink is the name commonly given to a non-alcoholic carbonated or non-carbonated beverage containing caloric sweeteners and avorings. 1 The preparation and processing of a so drink includes several stages, beginning with the treatment of the water used in this process. The next step is the preparation of a simple sugar syrup, the ingredient that provides the taste of the beverage, followed by the addition of several ingredients to the simple sugar syrup in order to obtain the nal syrup: glucose or fructose, aromatic compounds, vitamins, minerals and other food additives, such as acidulants, colorants or preservatives. Finally, the completed beverage is obtained as a mixture of the nal syrup, the treated water and the carbonic gas (in carbonated drinks). 2 As a result, all so drinks have a basic compositional structure: water, considered an essential nutrient 3 and the main component that makes up about 87-92% of the beverage, and the sweetener, which represents about 8-12% of the beverage by mass. Another common ingredient in almost all so drinks is the acidulant, which is any organic or inorganic acid that contributes to the sourness of the beverage. The balance between sweetness and sourness is the basic typical taste prole of all avored so drinks. 4

Ewe's yogurt effects on inflammatory markers and microbiota were not different from those after cow's yogurt, but the attenuation of some inflammatory biomarkers with ewe's whole-milk yogurt in subjects with the highest TC/HDL-c deserves further study.

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