Gut and blood microbiomics for studying the effect of a polyphenol-rich dietary pattern on intestinal permeability in the elderly (MaPLE). WHAT: The MaPLEproject aims to test the hypothesis that an increased intake of polyphenol-rich foods reduces IP and lowers inflammogenic bacterial factors in the bloodstream, promoting a protective metabolic phenotype in older subjects. WHO: The consortium consists of research groups from 3 countries (Italy, Spain and The United Kingdom). Patrizia Riso and Simone Guglielmetti (IT) are the coordinators. HOW: A polyphenol-rich diet versus a control diet has been tested in a randomised, controlled cross-over intervention study. Blood, urine, and faecal samples have been collected before and after each intervention period to evaluate blood bacterial and LPS loads, blood and faecal microbiota composition, short chain fatty acids and polyphenol-derived metabolites, urine metabolites, and markers of inflammation, oxidative stress and vascular function.
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Jan 29, 2021 - DNAemia and Zonulin correlation study
Guglielmetti, Simone, 2021, "Zonulin levels",, UNIMI Dataverse, V1, UNF:6:P/zCAJabEeqj+k14nqbDsA== [fileUNF]
Data including: list of Subjects, Sex, Age, BMI, Bacterial load (16S rRNA g.c./μl) and Zonulin level (ng/ml), for sample sets 1 and 2.
Jan 29, 2021 - DNAemia and Zonulin correlation study
Guglielmetti, Simone, 2021, "16S rRNA gene profiling of blood samples and controls",, UNIMI Dataverse, V1
FASTQ data (R1 and R2) generated by metataxonomics of blood samples and controls. In brief, DNA extracted from whole blood and controls were used for 16S rRNA gene profiling using MiSeq Illumina technology (2 x 300 paired-end MiSeq kit V3, set to encompass 467-bp amplicon).
Jan 29, 2021
Related to manuscript: doi: 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...
Jan 20, 2021
Guglielmetti, Simone, 2019, "Blood Microbiomics data at baseline",, UNIMI Dataverse, V2
16S rRNA gene profiling data of DNA extracted from 50 blood samples collected from heatlhy elederly people.\r\nBacterial populations contained in the samples were determined using next generation high throughput sequencing of variable regions (V3-V4) of the 16S rRNA bacterial gen...
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