Biology subjects

Bartoletti, R.

Publications and source records attributed to Bartoletti, R..

2 recordsLinked to original sources

bioRxiv2021

Boosting annotation in nutrimetabolomics by Feature-Based Molecular Networking: analytical and computational strategies applied to human urine samples from an untargeted LC-MS/MS based bilberry-blueberry intervention study.

Urine represents a challenging metabolite mixture to decipher. Yet, it contains valuable information on dietary intake patterns as typically investigated using randomized, single-blinded, intervention studies. This research demonstrates how the use of Feature-Based Molecular Networking in combination with public spectral libraries, further expanded with an "In-house" library of metabolite spectra, improved the non-trivial annotation of metabolites occurring in human urine samples following bilberry and blueberry intake. Following this approach, 65 berry-related and human endogenous metabolites were annotated, increasing the annotation coverage by 72% compared to conventional annotation approaches. Furthermore, the structures of 15 additional metabolites were hypothesized by spectral analysis. Then, by leveraging the MzMine quantitative information, several molecular families of phase II (e.g., glucuronidated phenolics) and phase I (e.g., phenylpropionic acid and hydroxybenzoic acid molecular scaffolds) metabolism were identified by correlation analysis of postprandial kinetics, and the dietary impact of endogenous and exogenous metabolites following bilberry-blueberry intake was estimated.

bioinformatics↗

bioRxiv2020

Use of Bioelectric Impedance Analysis (BIA) as a new method to detect prostate cancer

BackgroundTo determine the accuracy of a novel BIA test endorectal probe. MethodsOne hundred-forty consecutive patient candidates to prostate biopsy and 40 healthy volunteers were selected (NCT03428087). Total PSA and PSA density (PSAD) determinations, digital rectal examination (DRE), and the BIA test were analysed in patients and controls. A 16 cores trans rectal prostate biopsy was performed on all patients with clinical suspicion of PCa after a multiparametric MRI (mMRI) test. The study endpoints were to determine accuracy of BIA test in comparison to PSA, PSAD levels, and mMRI and obtain PCa prediction in candidates to prostate biopsy by BIA test. The Mann-Withney U test, the Wilkoxon rank test, and Holm-Bonferronis method were adopted for statistical analyses, and a computational approach was also applied to differentiate patients with PCa from those with benign disease (BPH). ResultsCombined DRE, TRUS, PSA, and PSAD alone failed to satisfactorily discern patients with PCa from those with BPH (62.86% of discrimination accuracy) and mMRI PIRADS [≥]3 showed a sensitivity of 83% and a specificity of 59%. The accuracy in discerning PCa and BPH increased up to 75% by BIA test (sensitivity 63.33% and specificity 83.75%). ConclusionsThe BIA test is a simple, promising, cheap, and reliable test for PCa non-invasive diagnosis. The novel finger probe may improve PCa detection also in patients with low-risk PCa, thus reducing the need of useless biopsies.

biophysics↗