Francesco Ursini

Dr. Francesco Ursini

Medicine and Rheumatology Unit, IRCCS Istituto Ortopedico Rizzoli (IOR), Bologna, Italy
orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

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

Representative Publications

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1 May 2009 in Journal of Clinical Investigation
Verified
Journal Article
Open access
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TLTadepally Lakshmikanth
Tadepally Lakshmikanth
SBShannon Burke
Shannon Burke
TATalib Hassan Ali
Talib Hassan Ali
SKSilvia Kimpfler
Silvia Kimpfler
FUFrancesco Ursini
Francesco Ursini
FCFrancesco Colucci
Francesco Colucci
NK cells use a variety of receptors to detect abnormal cells, including tumors and their metastases. However, in the case of melanoma, it remains to be determined what specific molecular interactions are involved and whether NK cells control metastatic progression and/or the route of dissemination. Here we show that human melanoma cell lines derived from LN metastases express ligands for natural cytotoxicity receptors (NCRs) and DNAX accessory molecule-1 (DNAM-1), two emerging NK cell receptors key for cancer cell recognition, but not NK group 2 member D (NKG2D). Compared with cell lines derived from metastases taken from other anatomical sites, LN metastases were more susceptible to NK cell lysis and preferentially targeted by adoptively transferred NK cells in a xenogeneic model of cell therapy. In mice, DNAM-1 and NCR ligands were also found on spontaneous melanomas and melanoma cell lines. Interference with DNAM-1 and NCRs by antibody blockade or genetic disruption reduced killing of melanoma cells. Taken together, these results show that DNAM-1 and NCRs are critical for NK cell–mediated innate immunity to melanoma cells and provide a background to design NK cell–based immunotherapeutic strategies against melanoma and possibly other tumors.

4 June 2018 in Frontiers in Immunology
Verified
Journal Article
Open access
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FUFrancesco Ursini
Francesco Ursini
EREmilio Russo
Emilio Russo
Gianluca PellinoGianluca Pellino
Gianluca Pellino
SDSalvatore D'Angelo
Salvatore D'Angelo
ACAgostino Chiaravalloti
Agostino Chiaravalloti
RGRoberto De Giorgio
Roberto De Giorgio
Metformin (dimethyl biguanide) is a synthetic derivative of guanidine, isolated from the extracts of Galega officinalis, a plant with a prominent antidiabetic effect. Since its discovery more than 50 years ago, metformin represents a worldwide milestone in treatment of patients with type 2 diabetes (T2D). Recent evidence in humans indicates novel pleiotropic actions of metformin which span from its consolidated role in T2D management up to various regulatory properties, including cardio- and nephro-protection, as well as antiproliferative, antifibrotic, and antioxidant effects. These findings, together with ground-breaking studies demonstrating its ability to prolong healthspan and lifespan in mice, provided the basis for defining metformin as a potential antiaging molecule. Moreover, emerging in vivo and in vitro evidence support the novel hypothesis that metformin can exhibit immune-modulatory features. Studies suggest that metformin interferes with key immunopathological mechanisms involved in systemic autoimmune diseases, such as the T helper 17/regulatory T cell balance, germinal centers formation, autoantibodies production, macrophage polarization, cytokine synthesis, neutrophil extracellular traps release, and bone or extracellular matrix remodeling. These effects may represent a powerful contributor to antiaging and anticancer properties exerted by metformin and, from another standpoint, may open the way to assess whether metformin can be a candidate molecule for clinical trials involving patients with immune-mediated diseases. In this article, we will review the available preclinical and clinical evidence regarding the effect of metformin on individual cells of the immune system, with emphasis on immunological mechanisms related to the development and maintenance of autoimmunity and its potential relevance in treatment of autoimmune diseases.

23 August 2021 in RMD Open
Verified
Journal Article
Open access
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FUFrancesco Ursini
Francesco Ursini
JCJacopo Ciaffi
Jacopo Ciaffi
LMLuana Mancarella
Luana Mancarella
LLLucia Lisi
Lucia Lisi
VBVeronica Brusi
Veronica Brusi
RMRiccardo Meliconi
Riccardo Meliconi
Objective Postacute COVID-19 syndrome (PACS) is an emerging entity characterised by a large array of manifestations, including musculoskeletal complaints, fatigue and cognitive or sleep disturbances. Since similar symptoms are present also in patients with fibromyalgia (FM), we decided to perform a web-based cross-sectional survey aimed at investigating the prevalence and predictors of FM in patients who recovered from COVID-19. Methods Data were anonymously collected between 5 and 18 April 2021. The collection form consisted of 28 questions gathering demographic information, features and duration of acute COVID-19, comorbid diseases, and other individual’s attributes such as height and weight. The American College of Rheumatology (ACR) Survey Criteria and the Italian version of the Fibromyalgia Impact Questionnaire completed the survey. Results A final sample of 616 individuals (77.4% women) filled the form 6±3 months after the COVID-19 diagnosis. Of these, 189 (30.7%) satisfied the ACR survey criteria for FM (56.6% women). A multivariate logistic regression model including demographic and clinical factors showed that male gender (OR: 9.95, 95% CI 6.02 to 16.43, p<0.0001) and obesity (OR: 41.20, 95% CI 18.00 to 98.88, p<0.0001) were the strongest predictors of being classified as having post-COVID-19 FM. Hospital admission rate was significantly higher in men (15.8% vs 9.2%, p=0.001) and obese (19.2 vs 10.8%, p=0.016) respondents. Conclusion Our data suggest that clinical features of FM are common in patients who recovered from COVID-19 and that obesity and male gender affect the risk of developing post-COVID-19 FM.

8 April 2011 in Rheumatology International
Verified
Journal Article
Closed access
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FUFrancesco Ursini
Francesco Ursini
SNSaverio Naty
Saverio Naty
Rosa Daniela GrembialeRosa Daniela Grembiale
Rosa Daniela Grembiale

1 September 2017 in Autoimmunity Reviews
Verified
Journal Article
Closed access
RGRoberto Giacomelli
Roberto Giacomelli
AAAntonella Afeltra
Antonella Afeltra
AAAlessia Alunno
Alessia Alunno
CBChiara Baldini
Chiara Baldini
RGRoberto Gerli
Roberto Gerli
ATAthanasios G. Tzioufas
Athanasios G. Tzioufas

1 January 2019 in Autoimmunity Reviews
Verified
Journal Article
Open access
RGRoberto Giacomelli
Roberto Giacomelli
AAAntonella Afeltra
Antonella Afeltra
AAAlessia Alunno
Alessia Alunno
EBElena Bartoloni-Bocci
Elena Bartoloni-Bocci
OBOnorina Berardicurti
Onorina Berardicurti
ATAthanasios G. Tzioufas
Athanasios G. Tzioufas
Autoimmune rheumatic diseases are characterised by an abnormal immune system response, complement activation, cytokines dysregulation and inflammation. In last years, despite many progresses in managing these patients, it has been shown that clinical remission is reached in less than 50% of patients and a personalised and tailored therapeutic approach is still lacking resulting in a significant gap between guidelines and real-world practice. In this context, the need for biomarkers facilitating early diagnosis and profiling those individuals at the highest risk for a poor outcome has become of crucial interest. A biomarker generally refers to a measured characteristic which may be used as an indicator of some biological state or condition. Three different types of medical biomarkers has been suggested: i. mechanistic markers; ii. clinical disease markers; iii. therapeutic markers. A combination of biomarkers from these different groups could be used for an ideal more accurate diagnosis and treatment. However, although a growing body of evidence is focused on improving biomarkers, a significant amount of this information is not integrated on standard clinical care. The overarching aim of this work was to clarify the meaning of specific biomarkers during autoimmune diseases; their possible role in confirming diagnosis, predicting outcome and suggesting specific treatments.