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University of Trento

Country: Italy

University of Trento

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4,820 Projects, page 1 of 964
  • Funder: Wellcome Trust Project Code: 223061

    Vascular endothelial growth factor receptor 3 (VEGFR3) is a transmembrane protein found on the surface of cells that line the lymphatic vessels of the body. Its primary role is regulating the growth of new lymph vessels by interacting with its ligands, vascular endothelial growth factor (VEGF) C and D. Recently, VEGFR3 was reported to function in blood vessel development, particularly in cancer (cancer angiogenesis), supporting tumour growth and metastasis. However, our coverage of VEGFR3 pharmacology and signalling in living cells, is poor. Although typically assembled in homodimers, VEGFR3 can also form heterodimers with a different VEGFR isoform, VEGFR2. Comparative analyses of homodimer versus heterodimer configuration, relating to protein signalling and pharmacology is limited due to the difficulty in defining specific complexes. This project will combine the use of two powerful analytical tools, bioluminescence resonance energy transfer (BRET) and BioID to further understanding of the molecular pharmacology of the VEGFRs including Neuropilin receptors. These complementary approaches will allow the interaction of fluorescently labelled VEGF with VEGFR3 to be characterised in real time in living cells with the VEGFR3 ‘interactome’ to mapped, in vivo. Split tags of BioID and NanoBRET will also be used to define the molecular pharmacology of VEGFR2/3 heterodimers.

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  • Funder: UK Research and Innovation Project Code: G0800129-2/1
    Funder Contribution: 53,930 GBP

    Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

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  • Funder: European Commission Project Code: 788793
    Overall Budget: 2,499,820 EURFunder Contribution: 2,499,820 EUR

    I will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. I will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, I will control the synaptic strengthen-ing and the neuron activity. Deep learning algorithms will model the biological network functionality, initial-ly within a separate artificial network and, then, in an integrated hybrid artificial-biological network. My project aims at: 1. Developing a photonic integrated reservoir-computing network (RCN); 2. Developing dynamic memories in photonic integrated circuits using RCN; 3. Developing hybrid interfaces between a neuronal network and a photonic integrated circuit; 4. Developing a hybrid electronic, photonic and biological network that computes jointly; 5. Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval; 6. Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathologi-cal brain conditions such as amnesia and epilepsy. The long-term vision is that hybrid neuromorphic photonic networks will (a) clarify the way brain thinks, (b) compute beyond von Neumann, and (c) control and supplement specific neuronal functions.

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  • Funder: Wellcome Trust Project Code: 200970
    Funder Contribution: 100,757 GBP

    Pancreatic cancer is the 12th most common cancer in the world and is almost always fatal. More recently immunotherapy (stimulation of the patient’s immune response to recognised and kill their own cancer) has shown show great promise in other cancers. This makes identification of new targets and approaches for pancreatic cancer very important. Many different sugars are attached to proteins and lipids to enhance their function but in cancer they are significantly altered making them specific targets for immunotherapy. Prof Durrant and her group at the University of Nottingham have developed monoclonal antibodies (mAbs: protein drugs) that specifically target the sugars expressed on pancreatic cancers. These mAbs can directly kill cancer cells and can also stimulate the patient’s own immune response to prevent the cancer from coming back. Although, our sugars are excellent targets as they have high expression on cancers and extremely low expression on a very limited number of normal tissues, the normal expression can still lead to side effects. To reduce these side effects, without compromising efficacy, we will combine two mAbs allowing us to target two different sugars expressed on cancers but not on normal cells. This should lead to a new therapy for pancreatic cancer.

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  • Funder: Wellcome Trust Project Code: 103884
    Funder Contribution: 933,419 GBP
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