Organotypic models of ovarian cancer are 3D models containing defined extracellular matrices, such as collagen and fibronectin, ovarian cancer cells with specific genetic/molecular characteristics, and one or more cancer-associated stromal cell types (fibroblasts, mesothelial cells, endothelial cells) to mimic specific metastatic niches of ovarian cancer (omentum, peritoneum, interstitial stroma) and the complex interactions within tumor tissues.
Technologies
In this section it is possible to view, also through targeted research, the technologies inserted in the PROMO-TT Database. For further information on the technologies and to contact the CNR Research Teams who developed them, it is necessary to contact the Project Manager (see the references at the bottom of each record card).
Displaying results 1 - 5 of 5
A biosensor based on magnetic microspheres functionalized with a DNA-aptamer was developed for the specific biomonitoring of biological contaminants (mycotoxins) in urine.
The technology for organic thin film transistors (OTFTs) is suitable for large area electronics, disposable electronics and "Internet of Things" applications. Circuits employing OTFTs can be realized by using very cheap printing technologies. The electrical behavior of these devices is essentially different from the behavior of silicon MOSFETs and, in order to enable circuit design, compact models specific for OTFTs are needed.
The presented technology is an electrical compact model for OTFTs that:
AIDD is an integrated tool and a radically new way to discovery new drugs for neurodegenerative diseases (Alzheimer’s, Epilepsy, Ageing, etc.).
The platform allows the deployment of a sensor network with peripheral nodes spread on the crop fields or on the environment for the monitoring of crop parameters/environmental parameters. The network architecture integrated LoRa peripheral nodes for short-medium range communication and star-center NB-IoT based for long range communication. It includes a web server and MySQL database for data storage and visualization. The network architecture is scalable to adapt to the area to monitor.