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Created the first database to analyse the molecular mechanisms causing Rett syndrome

The study was conducted by the Biology and Computer Science Departments of the University of Pisa and published in the Oxford Academic Journal Database.

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RettDb, the first database for the analysis of the molecular mechanisms that cause Rett syndrome, was launched. The web resource is accessible to the entire scientific community and will enable in silico experimentation, i.e. through data analysis, thus reducing the use of animal testing. This is the result of a study published in Database, a journal of Oxford Academic, and conducted by the Biology and Computer Science Departments of the University of Pisa.

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From the left, Ugo Borello Nico Cillari e Giuseppe Neri

“Rett syndrome,” explains Professor Ugo Borello, author of the study, “is a rare neurodevelopmental disorder that occurs almost exclusively in females, with an incidence of 1 in 10,000 births, and is the second most common cause of severe intellectual disability in girls after Down syndrome. It is known to be caused by mutations in the MECP2 gene on the X chromosome in more than 95% of cases, but the molecular mechanisms that cause the syndrome are currently unknown”.

RettDb was therefore created precisely to unravel these mechanisms and to serve as a reference tool for all researchers studying this pathology. The research started in Professor Borello’s laboratory where the molecular mechanisms of cerebral cortex development are studied in different experimental systems and with different techniques, ranging from bioinformatics to molecular biology and neuroanatomy.

“A considerable amount of work was carried out by two thesis students, Nico Cillari and Giuseppe Neri, who took on this challenge, the success of which was not to be taken for granted,” Borello pointed out. “The inherent complexity of biological systems requires a multidisciplinary approach, hence the fruitful collaboration with Professors Paolo Milazzo and Nadia Pisanti of the Computer Science Department, with the help of PhD student Marta Scalisi, who was in charge of web development, and thanks to the invaluable support of Fabio Pratelli and Maurizio Davini, Head of the Green Data Centre of the University of Pisa”.

The study was financed by the European Commission with funds from the PNRR NextGeneration Program under THE’s Spoke 6, Tuscany Health Ecosystem, Precision Medicine & Personalised Healthcare.

 

 

 

 

 

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  • November 18th 2024

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