Image_1_Shifts on Gut Microbiota Associated to Mediterranean Diet Adherence and Specific Dietary Intakes on General Adult Population.TIF

<p>There is increasing evidence for the interaction between gut microbiome, diet, and health. It is known that dysbiosis is related to disease and that most of the times this imbalances in gut microbial populations can be promoted through diet. Western dietary habits, which are characterized by high intakes of calories, animal proteins, saturated fats, and simple sugars have been linked with higher risk of obesity, diabetes, cancer, and cardiovascular disease. However, little is known about the impact of dietary patterns, dietary components, and nutrients on gut microbiota in healthy people. The aim of our study is to determine the effect of nutrient compounds as well as adherence to a dietary pattern, as the Mediterranean diet (MD) on the gut microbiome of healthy adults. Consequently, gut microbiota composition in healthy individuals, may be used as a potential biomarker to identify nutritional habits as well as risk of disease related to these habits. Dietary information from healthy volunteers (n = 27) was recorded using the Food Frequency Questionnaire. Adherence to the MD was measured using the PREDIMED test. Microbiota composition and diversity were obtained by 16S rRNA gene sequencing and specific quantitative polymerase chain reaction. Microbial metabolic activity was determined by quantification of short chain fatty acids (SCFA) on high performance liquid chromatography (HPLC). The results indicated that a higher ratio of Firmicutes–Bacteroidetes was related to lower adherence to the MD, and greater presence of Bacteroidetes was associated with lower animal protein intake. High consumption of animal protein, saturated fats, and sugars affected gut microbiota diversity. A significant higher presence of Christensenellaceae was found in normal-weight individuals compared to those who were overweight. This was also the case in volunteers with greater adherence to the MD compared to those with lower adherence. Butyricimonas, Desulfovibrio, and Oscillospira genera were associated with a BMI <25 and the genus Catenibacterium with a higher PREDIMED score. Higher bifidobacterial counts, and higher total SCFA were related to greater consumption of plant-based nutrients, such as vegetable proteins and polysaccharides. Better adherence to the MD was associated with significantly higher levels of total SCFA. Consequently, diet and specific dietary components could affect microbiota composition, diversity, and activity, which may have an effect on host metabolism by increasing the risk of Western diseases.</p

Experiment 2: Mean positional variability of the COP during viewing of the nearby target and the horizon, as a function of days.

<p>The figure illustrates the statistically significant interaction between target distance (nearby target vs. horizon) and days. The error bars represent standard error of the mean.</p

Experiment 2: Mean positional variability of the COP as a function of days.

<p>The figure illustrates the statistically significant effect of days. The error bars represent standard error of the mean.</p

Motion sickness history.

<p>Experience at sea was rated on a 4-point scale, where 4 =  no previous experience. Seasickness history was rated on a 5-point scale, where 5 =  I have never been motion sick. General susceptibility to motion sickness was rated on a 5-point scale where 1 =  maximum susceptibility.</p

Experiment 2: Meanα of DFA as a function of days.

<p>The figure illustrates the statistically significant effect of days. The error bars represent standard error of the mean.</p

Experiment 3: Meanα of DFA on Day 0 (before the voyage began) during viewing of the nearby target and the horizon, for the three seasickness severity groups.

<p>The figure illustrates the statistically significant interaction between seasickness severity groups and visual targets (near target vs. horizon). The error bars represent standard error of the mean.</p

Experiment 3: Mean stance width (distance between the midlines of the heels) on Day 1 at sea, as a function of seasickness severity groups.

<p>The figure illustrates the statistically significant effect of seasickness severity groups. The error bars represent standard error of the mean.</p

Experiment 3: Meanα of DFA on Day 0 (before the voyage began) for the three seasickness severity groups.

<p>The figure illustrates the statistically significant effect of seasickness severity groups. The error bars represent standard error of the mean.</p

Experiment 4: Mean positional variability in the AP and ML axes for participants who experienced mal de debarquement for less than 30 minutes (the Low-MD group) or more than 120 minutes (the High-MD group).

<p>The figure illustrates the statistically significant main effect of groups (<30 minutes vs. >120 minutes), and the statistically significant interaction between groups and body axes (AP vs. ML). The error bars represent standard error of the mean.</p

Setting and conditions for body sway testing.

<p>A. Viewing of the nearby target and the horizon at the dock. B. Viewing of the nearby target and the horizon at sea.</p