Primi risultati dell’uso delle fototrappole per valutare la distribuzione, i ritmi di attività e il comportamento alimentare degli ungulati nella Tenuta di Castelporziano

Silibinin-Loaded Amphiphilic PLGA–Poloxamer Nanoparticles: Physicochemical Characterization, Release Kinetics, and Bioactivity Evaluation in Lung Cancer Cells

Despite its potential against several carcinomas, the pharmacological efficacy of silibinin (SLB) is hampered by poor solubility, absorption, and oral bioavailability. To face these issues, we developed polylactic-co-glycolic acid (PLGA) nanoparticles (NPs) coated with hydrophilic polyethene oxide (PEO) for controlled and targeted SLB delivery. NPs were produced at two different SLB loadings and presented a spherical shape with smooth surfaces and stable size in water and cell culture medium....

SECURED for Health: Scaling Up Privacy to Enable the Integration of the European Health Data Space

In this paper, we present the SECURED project11Funded in part by the European Union (EU), Grant Agreement no. 10109571. Views and opinions expressed are those of the authors and do not necessarily reflect those of the EU or the Health and Digital Executive Agency. Neither the EU nor the granting authority are responsible for them., aimed at improving privacy-preserving processing of data in the health domain. The technologies developed in the project will be demonstrated in four health-relate...

NeVer2: learning and verification of neural networks

NeVer2 is an open-source, cross-platform tool aimed at designing, training, and verifying neural networks. It seamlessly integrates popular learning libraries with our verification backend, offering their functionalities via a graphical interface. Users can design the structure of a neural network by intuitively arranging blocks on a canvas. Subsequently, network training involves specifying dataset sources and hyperparameters through dialog boxes. After training, the verification process ent...