Structure, maintenance and management of a databse for drought tolerance phenotyping.

2008

Anatomical biomarkers of body composition in oncological population: application and development of artificial intelligences

In the Era of precision medicine and big medical data sharing, it is necessary to solve the work-flow of digital radiological big data in a productive and effective way. In particular, nowadays, it is possible to extract information “hidden” in digital images, in order to create diagnostic algorithms helping clinicians to set up more personalized therapies, which are in particular targets of modern oncological medicine. Digital images generated by the patient have a “texture” structure that is not visible but encrypted; it is “hidden” because it cannot be recognized by sight alone. Thanks to artificial intelligence, pre- and post-processing software and generation of mathematical calculation algorithms, we could perform a classification based on non-visible data contained in radiological images. Being able to calculate the volume of tissue body composition could lead to creating clasterized classes of patients inserted in standard morphological reference tables, based on human anatomy distinguished by gender and age, and maybe in future also by race. Furthermore, the branch of “morpho-radiology" is a useful modality to solve problems regarding personalized therapies, which is particularly needed in the oncological field. Actually oncological therapies are no longer based on generic drugs but on target personalized therapy. The lack of gender and age therapies table could be filled thanks to morpho-radiology data analysis application.

Mappatura degli habitat bentonici dei canali di marea della Laguna di Venezia tramite strumenti acustici e tecniche di ground-truth

The Venice Lagoon is a complex, heterogeneous and highly dynamic system, subject to anthropogenic and natural pressures that deeply affect the functioning of this ecosystem. Thanks to the development of acoustic technologies, it is possible to obtain maps with a high resolution that describe the characteristics of the seabed. With this aim, a high resolution Multibeam Echosounder (MBES) bathymetry and backscatter survey was carried out in 2021 within the project Research Programme Venezia 2021. Ground-truthing samples were collected in 24 sampling sites to characterize the seafloor and validate the maps produced with the MBES acoustic data. Ground-truthing included the collection of sediment samples for particle size analysis and video footage of the seabed to describe the biological component. The backscatter data was analysed using the unsupervised Jenks classification. We created a map of the habitats integrating morphological, granulometric and biological data in a GIS environment. The results obtained in this study were compared to those collected in 2015 as part of the National Flagship Project RITMARE. Through the comparison of the repeated morpho-bathymetric surveys over time we highlighted the changes of the seafloor geomorphology, sediment, and habitat distribution. We observed different type of habitats and the presence of areas characterized by erosive processes and others in which deposition occurred. These effects led to changes in the benthic communities and in the type of sediment. The combination of the MBES surveys, the ground truth data and the GIS methodology, permitted to construct high-resolution maps of the seafloor and proved to be effective implement for monitoring an extremely dynamic area. This work can contribute not only to broaden the knowledge of transitional environments, but also to their monitor and protection.