The increased presence of bacteria in blood is a plausible contributing factor in the development and progression of aging-associated diseases. In this context, we performed the quantification and the taxonomic profiling of the bacterial DNA in blood samples collected from forty-three older subjects enrolled in a nursing home. Quantitative PCR targeting the 16S rRNA gene revealed that all samples contained detectable amounts of bacterial DNA with a concentration that varied considerably between subjects. Correlation analyses revealed that the bacterial DNAemia (expressed as concentration of 16S rRNA gene copies in blood) significantly associated with the serum levels of zonulin, a marker of intestinal permeability. This result was confirmed by the analysis of a second set of blood samples collected from the same subjects. 16S rRNA gene profiling revealed that most of the bacterial DNA detected in blood was ascribable to the phylum Proteobacteria with a predominance of the genus Pseudomonas. Several control samples were also analyzed to assess the influence of contaminant bacterial DNA potentially originating from reagents and materials. The data reported here suggest that para-cellular permeability of epithelial (and, potentially, endothelial) cell layers may play an important role in bacterial migration into the bloodstream. Bacterial DNAemia is likely to impact on several aspects of host physiology and could underpin the development and prognosis of various diseases in older subjects.

Purpose: Chlorogenic acid (CGA) and caffeic acid (CA) are bioactive compounds in whole grains, berries, apples, some citrus fruits and coffee, which are hypothesized to promote health-beneficial effects on the cardiovascular system. This study aimed to evaluate the capacity of CGA and CA to reduce lipid accumulation in macrophages, recognized as a critical stage in the progression of atherosclerosis. Furtherly, the modulation of CCAAT/enhancer-binding protein β (C/EBPβ) and peroxisome proliferator-activated receptor-γ1 (PPAR-γ1), as transcription factors involved in lipid metabolism, was evaluated.Methods: THP-1 derived macrophages were treated for 24 h with 0.03, 0.3, 3 and 30 μM of CGA and CA, tested alone or in combination, and a solution of oleic/palmitic acid (500 μM, 2:1 ratio). Lipid storage was assessed spectrophotometrically through fluorescent staining of cells with Nile red. C/EBPβ and PPAR-γ1 mRNA and protein levels were evaluated by RT-PCR and enzyme-linked immunosorbent assay, respectively. Results:The mix of CGA+CA (1:1 ratio) reduced lipid accumulation at all concentrations tested, except for the highest one. The greatest effect (-65%; p<0.01) was observed at the concentration of 0.3 μM for each compound.The same concentration significantly (p<0.01) downregulated C/EBPβ and PPAR-γ1 gene expression and reduced their protein levels at 2 h and 24 h, respectively. Conclusion:The results indicate that the capacity of CGA + CA mix to reduce lipid storage in macrophages is reduced by transcription factors C/EBPβ and PPAR-γ1.

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Surface layers (S-layers) are proteinaceous arrays covering the cell walls of numerous bacteria. Their suggested properties, such as interactions with the host immune system, have been only poorly described. Here, we aimed to elucidate the role of the S-layer from the probiotic bacterial strain Lactobacillus helveticus MIMLh5 in the stimulation of murine bone-marrow-derived dendritic cells (DCs). MIMLh5 induced greater production of interferon beta (IFN-β), interleukin 10 (IL-10), and IL-12p70, compared to S-layer-depleted MIMLh5 (naked MIMLh5 [n-MIMLh5]), whereas the isolated S-layer was a poor immunostimulator. No differences in the production of tumor necrosis factor alpha (TNF-α) or IL-1β were found. Inhibition of the mitogen-activated protein kinases JNK1/2, p38, and ERK1/2 modified IL-12p70 production similarly in MIMLh5 and n-MIMLh5, suggesting the induction of the same signaling pathways by the two bacterial preparations. Treatment of DCs with cytochalasin D to inhibit endocytosis before the addition of fluorescently labeled MIMLh5 cells led to a dramatic reduction in the proportion of fluorescence-positive DCs and decreased IL-12 production. Endocytosis and IL-12 production were only marginally affected by cytochalasin D pretreatment when fluorescently labeled n-MIMLh5 was used. Treatment of DCs with fluorescently labeled S-layer-coated polystyrene beads (Sl-beads) resulted in much greater uptake of beads, compared to noncoated beads. Prestimulation of DCs with cytochalasin D reduced the uptake of Sl-beads more than plain beads. These findings indicate that the S-layer plays a role in the endocytosis of MIMLh5 by DCs. In conclusion, this study provides evidence that the S-layer of L. helveticus MIMLh5 is involved in endocytosis of the bacterium, which is important for strong Th1-inducing cytokine production. IMPORTANCE Beneficial microbes may positively affect host physiology at various levels, e.g., by participating in immune system maturation and modulation, boosting defenses and dampening reactions, thus affecting the whole homeostasis. As a consequence, the use of probiotics is increasingly regarded as suitable for more extended applications for health maintenance, not only microbiota balancing. This implies a deep knowledge of the mechanisms and molecules involved in host-microbe interactions, for the final purpose of fine tuning the choice of a probiotic strain for a specific outcome. With this aim, studies targeted to the description of strain-related immunomodulatory effects and the identification of bacterial molecules responsible for specific responses are indispensable. This study provides new insights in the characterization of the food-origin probiotic bacterium L. helveticus MIMLh5 and its S-layer protein as a driver for the cross-talk with DCs.

This paper studies the strategic interaction of algorithms in economic games. We analyze games where learning algorithms play against each other while searching for the best strategy. We first establish a fluid approximation technique that enables us to characterize the learning outcomes in continuous time. This tool allows to identify the equilibria of games played by Artificial Intelligence algorithms and perform comparative statics analysis. Thus, our results bridge a gap between traditional learning theory and applied models, allowing quantitative analysis of traditionally experimental systems. We describe the outcomes of a social dilemma, and we provide analytical guidance for the design of pricing algorithms in a Bertrand game. We uncover a new phenomenon, the coordination bias, which explains how algorithms may fail to learn dominant strategies.