Adapter dimer contamination in sRNA-sequencing datasets predicts sequencing failure and batch effects and hampers extracellular vesicle-sRNA analysis.

Small RNA (sRNA) profiling of Extracellular Vesicles (EVs) by Next-Generation Sequencing (NGS) often delivers poor outcomes, independently of reagents, platforms or pipelines used, which contributes to poor reproducibility of studies. Here we analysed pre/post-sequencing quality controls (QC) to predict issues potentially biasing biological sRNA-sequencing results from purified human milk EVs, human and mouse EV-enriched plasma and human paraffin-embedded tissues. Although different RNA isolation protocols and NGS platforms were used in these experiments, all datasets had samples characterized by a marked removal of reads after pre-processing.

Organisational models supported by technology for the management of diabetic disease and its complications in a diabetic clinic setting: study protocol for a randomised controlled trial targeting type 2 diabetes individuals with non-ideal glycaemic values (Telemechron study).

Introduction: Type 2 diabetes mellitus (T2DM) is a non-communicable disease representing one of the most serious public health challenges of the twenty-first century. Its incidence continues to rise in both developed and developing countries, causing the death of 1.5 million people every year.

A Combined Western and Bead-Based Multiplex Platform to Characterize Extracellular Vesicles.

In regenerative medicine, extracellular vesicles (EVs) are considered as a promising cell-free approach. EVs are lipid bilayer-enclosed vesicles secreted by cells and are key players in intercellular communication. EV-based therapeutic approaches have unique advantages over the use of cell-based therapies, such as a high biological, but low immunogenic and tumorigenic potential.

Surface protein profiling of milk and serum extracellular vesicles unveils body fluid-specific signatures.

Cell-derived extracellular vesicles (EVs) are currently in the limelight as potential disease biomarkers. The promise of EV-based liquid biopsy resides in the identification of specific disease-associated EV signatures. Knowing the reference EV profile of a body fluid can facilitate the identification of such disease-associated EV-biomarkers.