Technologies

The assessment of bio-humoral markers beyond clinical evaluation would allow a more comprehensive pheno/endotyping of patients affected by chronic inflammatory diseases. Therapy personalization would require a profile of the mediators that are relevant in the disease pathogenesis and that well correlate with prognosis. Currently, the measurement of multiple biomarkers is not included in patient evaluation because it has high costs,  requires centralized laboratories, experienced personnel and bulky equipment and is time-consuming.

Our idea come from the improving of the traceability technique in agro-food fisheries industries through the application of omics technologies in microbiota studies.  These latter would be capable of exploiting the huge pool of biological molecules contained in fishery resources (e.g. nucleic acids, proteins, metabolites) and use them as a powerful tools for the identification and reconstruction of fishery history, from the sea to the table.

Integrative omics has posed new challenges in modern precision medicine, particularly in oncology, including i) the identification of new tumor markers for early, precise, and non-invasive diagnostics, and ii) the discovery of innovative molecular targets for therapeutic applications. Our studies on medulloblastoma, a highly malignant childhood tumor, have contributed to identifying RNA molecules that meet these criteria.

In our recent publication we identified a group of  bladder cancer-specific ncRNA, called T-UCRs that are the most up-regulated in bladder cancer patient samples compared with normal bladder urothelium.

We have identified the presence of the poorly characterized precursor proNGF-A in human tissues, deposited its coding nucleotide sequence (GenBank MH358394) and demonstrated its neuroprotective and neurotrophic activity in vitro and in vivo. We inserted mutations into the native molecule, identified through computational analysis, which allow proNGF-A production by eukaryotic expression systems, through a method currently validated on a laboratory scale.

SITODIET is an innovative software that supports a translational approach to health’s state. It integrates various sources of physiological, behavioral, and psychological data to reduce the risks associated with the onset of lifestyle-related diseases (primary prevention), to support health professionals in early diagnosis (secondary prevention) or to manage the personalized therapy’s patient (tertiary prevention). SITODIETcollects data automatically, through actigraphy tools, as wristband or smartwatch, or manually