Marzia Bedoni

Dr. Marzia Bedoni

IRCCS Fondazione Don Carlo Gnocchi, Milan, Lombardy, Italy
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Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 March 2021 in Scientific Reports
Verified
Journal Article
Open access
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CCCristiano Carlomagno
Cristiano Carlomagno
DBD. Bertazioli
D. Bertazioli
AGA. Gualerzi
A. Gualerzi
SPS. Picciolini
S. Picciolini
PBP. I. Banfi
P. I. Banfi
MBMarzia Bedoni
Marzia Bedoni
The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able to significantly discriminate the signal of patients with a current infection by COVID-19 from healthy subjects and/or subjects with a past infection. Our results demonstrated the differences in saliva biochemical composition of the three experimental groups, with modifications grouped in specific attributable spectral regions. The Raman-based classification model was able to discriminate the signal collected from COVID-19 patients with accuracy, precision, sensitivity and specificity of more than 95%. In order to translate this discrimination from the signal-level to the patient-level, we developed a Deep Learning model obtaining accuracy in the range 89–92%. These findings have implications for the creation of a potential Raman-based diagnostic tool, using saliva as minimal invasive and highly informative biofluid, demonstrating the efficacy of the classification model.

4 July 2018 in Analytical Chemistry
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Journal Article
Closed access
SPSilvia Picciolini
Silvia Picciolini
Alice GualerziAlice Gualerzi
Alice Gualerzi
RVRenzo Vanna
Renzo Vanna
ASAndrea Sguassero
Andrea Sguassero
FGFurio Gramatica
Furio Gramatica
Carlo Francesco MorassoCarlo Francesco Morasso
Carlo Francesco Morasso

29 August 2017 in Scientific Reports
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Journal Article
Open access
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Alice GualerziAlice Gualerzi
Alice Gualerzi
SNStefania Niada
Stefania Niada
CGChiara Giannasi
Chiara Giannasi
SPSilvia Picciolini
Silvia Picciolini
Carlo Francesco MorassoCarlo Francesco Morasso
Carlo Francesco Morasso
FGFurio Gramatica
Furio Gramatica
Extracellular vesicles (EVs) from mesenchymal stromal cells (MSC) are emerging as valuable therapeutic agents for tissue regeneration and immunomodulation, but their clinical applications have so far been limited by the technical restraints of current isolation and characterisation procedures. This study shows for the first time the successful application of Raman spectroscopy as label-free, sensitive and reproducible means of carrying out the routine bulk characterisation of MSC-derived vesicles before their use in vitro or in vivo, thus promoting the translation of EV research to clinical practice. The Raman spectra of the EVs of bone marrow and adipose tissue-derived MSCs were compared with human dermal fibroblast EVs in order to demonstrate the ability of the method to distinguish the vesicles of the three cytotypes automatically with an accuracy of 93.7%. Our data attribute a Raman fingerprint to EVs from undifferentiated and differentiated cells of diverse tissue origin, and provide insights into the biochemical characteristics of EVs from different sources and into the differential contribution of sphingomyelin, gangliosides and phosphatidilcholine to the Raman spectra themselves.

27 January 2019 in Journal of Extracellular Vesicles
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Journal Article
Open access
Alice GualerziAlice Gualerzi
Alice Gualerzi
SKSander Alexander Antonius Kooijmans
Sander Alexander Antonius Kooijmans
SNStefania Niada
Stefania Niada
SPSilvia Picciolini
Silvia Picciolini
ABAnna Teresa Brini
Anna Teresa Brini
MBMarzia Bedoni
Marzia Bedoni
Extracellular vesicles (EVs) from a variety of stem cell sources are believed to harbour regenerative capacity, which may be exploited for therapeutic purposes. Because of EV interaction with other soluble secreted factors, EV activity may depend on the employed purification method, which limits cross‐study comparisons and therapeutic development. Raman spectroscopy (RS) is a quick and easy method to assess EV purity and composition, giving in‐depth biochemical overview on EV preparation. Hereby, we show how this method can be used to characterise EVs isolated from human liver stem cells and bone marrow mesenchymal stem/stromal cells by means of conventional ultracentrifugation (UC) and size exclusion chromatography (SEC) protocols. The obtained EV preparations were demonstrated to be characterised by different degrees of purity and a specific Raman fingerprint that represents both the cell source and the isolation procedure used. Moreover, RS provided useful hints to explore the factors underlying the functional diversity of EV preparations from the same cell source, thus representing a valuable tool to assess EV quality prior to functional assays or therapeutic application.

17 April 2020 in Journal of Extracellular Vesicles
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Journal Article
Open access
AGAlessandro Gori
Alessandro Gori
ARAlessandro Romanato
Alessandro Romanato
GBGreta Bergamaschi
Greta Bergamaschi
ASAlessandro Strada
Alessandro Strada
PGPaola Gagni
Paola Gagni
Marina CretichMarina Cretich
Marina Cretich
Small extracellular vesicles (sEVs) present fairly distinctive lipid membrane features in the extracellular environment. These include high curvature, lipid‐packing defects and a relative abundance in lipids such as phosphatidylserine and ceramide. sEV membrane could be then considered as a “universal” marker, alternative or complementary to traditional, characteristic, surface‐associated proteins. Here, we introduce the use of membrane‐sensing peptides as new, highly efficient ligands to directly integrate sEV capturing and analysis on a microarray platform. Samples were analysed by label‐free, single‐particle counting and sizing, and by fluorescence co‐localisation immune staining with fluorescent anti‐CD9/anti‐CD63/anti‐CD81 antibodies. Peptides performed as selective yet general sEV baits and showed a binding capacity higher than anti‐tetraspanins antibodies. Insights into surface chemistry for optimal peptide performances are also discussed, as capturing efficiency is strictly bound to probes surface orientation effects. We anticipate that this new class of ligands, also due to the versatility and limited costs of synthetic peptides, may greatly enrich the molecular toolbox for EV analysis.

1 June 2012 in Sensors and Actuators A: Physical
Verified
Journal Article
Closed access
EFElena Forvi
Elena Forvi
MBMarzia Bedoni
Marzia Bedoni
RCRoberta Carabalona
Roberta Carabalona
Monica SonciniMonica Soncini
Monica Soncini
PMPaolo Mazzoleni
Paolo Mazzoleni
FGFurio Gramatica
Furio Gramatica