Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Polysaccharide-based membrane for sublingual vaccination (PolyVac)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-07-07
End date: 2019-07-06
Duration (months): 24.0
Total project cost (EUR): 173076.0
EU funding (EUR): 173076.0
Participants: 1
Project status: CLOSED

Vaccination has been acknowledged as one of the most effective methods against life-threatening diseases. Vaccines administered by the mucosal route (oral, vaginal…) present the advantage to be needle-free and reduce the risk of pathogen transmission. Among the existing mucosal vaccines, the sublingual ones are an interesting way of immunization since the sublingual mucosa is particularly thin and would allow easy penetration of antigens. Also, this administration allows to bypass the gastrointestinal tract, has better safety record than intranasal vaccines and have better compliance for vaccinating infants and children. Additionally, they have a fast removal by body fluids and enzymes. PolyVac introduces a pioneering system for controlled targeted delivery of bioactive molecules and, for the proof of concept envisages the development of a sublingual vaccine for HIV. This concept comprises the development of a free-standing (FS) multilayer membrane that will present the double specificity to be immunoactive and specifically target the immune cells. To achieve this end, the FS will be loaded with a model antigen for immunotherapy and a chemotactic cytokine to specifically target the antigen presenting cells. Once loaded with the proteins, the FS membrane will become a bioactive patch. This patch will permit to deliver subunit vaccine components both spatially and temporally as dendritic cells will be attracted at the sublingual mucosa/patch interface ensuring efficient immune responses. Preclinical studies will follow in mice, by monitoring their immune response, for clinical translation and commercialisation of the proposed technology. It is expected to have, as final product, an innovative sublingual patch for human immunotherapy that among the advantages presented above will also overcome one of the main drawbacks of injected vaccines that is the storage at around 4°C. Overcoming this issue they could be widely used for immunotherapy in the developing countries.

Keywords: polysaccharide membrane,layer by layer technology,mucosal vaccination,drug delivery,biomimetic system
Orchestration and Reconfguration Control Architecture (ORCA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Germany,Ireland,Belgium,Switzerland,United States
Call: Future Internet Experimentation - Building a European experimental Infrastructure (H2020-ICT-2016-1, 2016)
Start date: 2017-01-01
End date: 2020-06-30
Duration (months): 42.0
Total project cost (EUR): 5586725.0
EU funding (EUR): 4996475.0
Participants: 7
Project status: CLOSED

ORCA offers experimentation facilities to promote wireless innovation in several market segments, including manufacturing, automotive industry, healthcare, ambient assistant living, public events, home automation, and utilities. Within the manufacturing market, for instance, application requirements vary from very low latency, up to real-time 3D video-driven interaction between collaborative robots and humans, to non-time critical downloads of large data volumes for updating the software of machines. Different applications and services often have to share the wireless infrastructure and the spectral bands, making it very challenging to meet the diverging QoS requirements simultaneously. The control mechanisms that are provided today in wireless technologies are not adequate to deal with extreme (ultra-low latency, ultra-high throughput, ultra-high reliability) and diverging (low AND high data rate, time-critical AND non-time critical) communication needs. Interesting evolutions are happening at different levels, enabling the creation of parallel on demand wireless network slices optimized for a specific set of requirements. The overall ORCA objective is to bridge those interesting evolutions at different levels, making them mature enough to enable end-to-end networking experiments going from Software-Defined Radio (SDR), with Software-Defined Networking (SDN) to Dynamic Spectrum Sharing (DSS). We will open novel frequency bands, by proposing SDR technology at mmWave frequencies, that is mature and fast enough to be included in end-to-end networking experiments. We will bridge SDR with SDN technology, enabling the creation of multiple virtual networks that operate on the same infrastructure but meet the most diverse and stringent application requirements. We will finally enable advanced reprogramming of the SDR infrastructure, needed for offering versatile testbed facilities, paving the way towards, ultimately, on demand wireless networking and experimentation.

Keywords: software defined radio,cognitive radio,real time sdr,end to end operation,integration with sdn,open calls
Neural Pathways from Recognition to Perception (Neuroception)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Greece,United States
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-05-01
End date: 2024-04-30
Duration (months): 36.0
Total project cost (EUR): 259808.64
EU funding (EUR): 259808.64
Participants: 2
Project status: SIGNED

Object recognition is essential to our interaction with the external world. Our brain is able to effortlessly identify objects even under the highly dynamic conditions of natural vision. This is a remarkable achievement of our visual system. Nevertheless, how the brain creates invariant object representations in the perceptual/visual domain remains elusive. In this project, I will combine novel large-scale electrophysiological recordings and advanced behavioral methods to investigate the neural information processing in higher cortical areas during object recognition. Firstly, I will investigate how cortical representations of visual stimuli progressively evolve across the cortical hierarchy to incorporate semantic information. For this, I will use simultaneous large-scale recordings with Neuropixels probes in mice engaged in a visual discrimination task. Secondly, I will characterize the selectivity of the neuronal populations in each cortical area. Here, I will take a deep-learning approach to model the neural responses of single cells to optimal stimuli. Finally, sophisticated statistical modelling and analysis techniques will be used to resolve how dynamic inter-areal interactions shape the neural representations of visual stimuli. Collectively, these objectives are an unprecedented attempt to disentangle the roles of different higher cortical areas in object recognition. This is fundamental towards enhancing our understanding of how the brain solves perceptual inference. Moreover the multidisciplinary nature of this project will provide a holistic understanding of natural vision during ethologically relevant behaviors. My findings will also motivate new artificial vision algorithms with improved object recognition capabilities under highly dynamic visual conditions. Particularly, the use in assistive devices for blind people will have major social impacts by improving their mobility, quality of life and reducing their dependency on the society.

Keywords: systems neuroscience,object recognition,object manifold,mouse model,visual discrimination task,visual processing,conceptual representation
Beating Goliath: Generation Of NoveL, Integrated and Internationally Harmonised Approaches for Testing Metabolism Disrupting Compounds (GOLIATH)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Understanding health, wellbeing and disease
Action type: Research and Innovation actions
Countries involved: Spain,Germany,Sweden,Sweden,Sweden,Belgium,France,France,France,United States,Netherlands,United Kingdom,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: New testing and screening methods to identify endocrine disrupting chemicals (H2020-SC1-2018-Single-Stage-RTD, 2018)
Start date: 2019-01-01
End date: 2024-12-31
Duration (months): 72.0
Total project cost (EUR): 6761833.75
EU funding (EUR): 6761833.75
Participants: 17
Project status: SIGNED

GOLIATH addresses the work programme topic ‘SC1-BHC-27-2018: New testing and screening methods to identify endocrine disrupting chemicals (EDCs)’ by focussing on one of the most urgent regulatory needs, namely the lack of methods for testing EDCs that disrupt metabolism – chemicals collectively referred to as ‘metabolism disrupting chemicals’ (MDCs). MDCs are natural and anthropogenic chemicals that have the ability to promote metabolic changes that can ultimately result in obesity, diabetes and/or fatty liver in humans. GOLIATH will generate the world’s first integrated approach to testing and assessment (IATA) specifically tailored to MDCs. With a focus on the main cellular targets of metabolic disruption – hepatocytes, pancreatic endocrine cells, myocytes and adipocytes - GOLIATH will develop new methods and optimise existing methods that span the entire adverse outcome pathway (AOP) spectrum, using in silico predictive modelling and high throughput screening, (pre-)validated ready-to-use in vitro assays and optimised in vivo toxicity testing guidelines. GOLIATH will provide key information on the endocrine mode of action by which MDCs disrupt metabolic pathways and induce adverse effects on human health by incorporating multi-omics technologies, and translating results from in vitro and in vivo assays to adverse metabolic health outcomes in humans at real life exposures. Given the importance of international acceptance of the developed test methods for regulatory use, GOLIATH will link with ongoing initiatives of the OECD for test method (pre-)validation, IATA and AOP development. With a consortium comprised of world-leading experts in endocrinology, molecular biology, toxicology, epidemiology, test method development, validation and chemical regulation, GOLIATH will be pivotal in the development of an internationally harmonised strategy for testing MDCs, and help to reduce the worldwide rise in metabolic disorders that have reached ‘Goliathan’ proportions.

Keywords: test method development
A multimodal AI-based toolbox and an interoperable health imaging repository for the empowerment of imaging analysis related to the diagnosis, prediction and follow-up of cancer (INCISIVE)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Methods and data
Action type: Research and Innovation actions
Countries involved: Spain,Italy,Italy,Spain,Italy,Italy,Cyprus,Greece,Serbia,Finland,Greece,Serbia,Belgium,Greece,Greece,United Kingdom,Luxembourg,United Kingdom
Call: AI for Health Imaging (H2020-SC1-FA-DTS-2019-1, 2019)
Start date: 2020-10-01
End date: 2024-03-31
Duration (months): 42.0
Total project cost (EUR): 9995727.5
EU funding (EUR): 9995727.5
Participants: 30
Project status: SIGNED

The increasing amount and availability of collected data (cancer imaging) and the development of novel technological tools based on Artificial Intelligence (AI) and Machine Learning (ML), provide unprecedented opportunities for better cancer detection and classification, image optimization, radiation reduction, and clinical workflow enhancement. The INCISIVE project aims to address three major open challenges in order to explore the full potential of AI solutions in cancer imaging: (1) AI challenges unique to medical imaging, (2) Image labelling and annotation and (3) Data availability and sharing. In order to do that INCISIVE plans to develop and validate: (1) an AI-based toolbox that enhances the accuracy, specificity, sensitivity, interpretability and cost-effectiveness of existing cancer imaging methods, (2) an automated-ML based annotation mechanism to rapidly produce training data for machine learning research and (3) a pan-European repository federated repository of medical images, that will enable the secure donation and sharing of data in compliance with ethical, legal and privacy demands, increasing accessibility to datasets and enabling experimentation of AI-based solutions. The INCISIVE models and analytics will utilize various cancer imaging scans, biological data and EHRs, and will be trained with 1 PB of available data provided by 8 partners within the project. INCISIVE solution will be investigated in four validation studies for Breast, Prostate, Colorectal and Lung Cancer, taking place in 8 pilot sites, from 5 countries (Cyprus, Greece, Italy, Serbia and Spain), with participation of at least 2,600 patients and a total duration of 1.5 year. INCISIVE moves beyond the state of the art, by improving sensitivity and specificity of lower cost scanning methods, accurately predicting the tumor spread, evolution and relapse, enhancing interpretability of results and “democratizing” imaging data.

Keywords: breast cancer,colorectal cancer,lung cancer,deep learning,neural networks,data analytics maas,federated learning,interoperability,blockchain,data donation,standardization
Gaia-Wind's Advanced Small Wind Turbine FortyForty (GW-FortyForty)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: United Kingdom
Call: Stimulating the innovation potential of SMEs for a low carbon and efficient energy system (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-07-01
End date: 2016-12-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Small onshore wind turbines have become increasingly accepted as an alternative to powering many homes, farms and businesses offering on-site electricity generation and increased security of energy supply. However, a number of barriers are preventing wide spread uptake: high cost; performance predictability issues; small wind currently fails to compete with low usage high retail electricity pricing without subsidisation from feed-in tariffs (FiT) or without a very high retail price of electricity. Governments are under immense political pressure to significantly reduce/cut subsidies for renewable technologies, creating a market for small wind which is increasingly unsustainable. To address the need for innovations that overcome principal barriers to small wind, this project seeks to advance Gaia- Wind’s innovative small wind turbine from a prototype demonstrated in a relevant environment (TRL6) to complete and qualified commercial prototype (TRL8). Gaia-Wind’s ‘FortyForty’ is the first low cost, highly efficient small wind turbine that can compete with the retail price of electricity globally and deliver an excellent ROI for customers, independent of financial subsidy. End-users include farms, rural land owners, investors, communities and rural businesses. Gaia-Wind has an existing and extensive customer base in these markets to ensure rapid roll out. Also targeted towards: residential, commercial and industrial, fish farms, hybrid systems, remote villages, pumping, water desalination and purification, remote monitoring, research and education, telecom base stations hospitals, College/Universities. Study Objectives: Technology and manufacturing process optimisation, market analysis, economic and business assessment, operational capacity analysis. Activities will be delivered within a 6 month period and result in a comprehensive feasibility report detailing the next steps towards development and commercialisation, forming the basis of the SMEI Phase 2 Business Plan.

Keywords: wind turbine,small wind turbine,renewable energy,energy generation,sustainability,low carbon,energy efficiency
Real Smart Cities (ReaLsMs)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Ecuador,Ireland,France,France,United Kingdom
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2017, 2017)
Start date: 2017-12-01
End date: 2022-05-31
Duration (months): 54.0
Total project cost (EUR): 463500.0
EU funding (EUR): 463500.0
Participants: 8
Project status: CLOSED

The overarching objective of the ReaLsMs is to develop and implement a perspective on the Smart City through critical humanities research and innovation in the context of the Digital Studies. The joint research fields of ReaLsMs will be the development of historical and philosophical underpinnings of the Data City and the implementation of the Smart City within local governance structures, including Dublin City Council and Plaine Commune (Paris North). Consisting of a network of three academic partners in the EU, Technological University of Dublin - School of Creative Arts, Computer Science and Architecture, (TU Dublin, IE), the Institut de Recherche et d’Innovation (IRI) at the Centre Pompidou (FR) and Durham University, the Centre for Humanities Innovation (DU, UK). The 2 non-academic partners located in the EU are Dublin City Council (DCC, IE) and Plaine Commune (FR). The Third Country academic partners is the Universidad de las Artes in Ecuador (UARTES, Ecuador). The purpose of developing this consortium as a Marie Sklodowska-Curie Research and Innovation Staff Exchange is to share knowledge across disciplines in order to develop a transdisciplinary model for “real smart city,” which is defined as a Smart City that is based on a critical humanities perspective, where citizens are the proper data brokers, engaging through public fora for debate and new technologies that enable citizen participation. Through an international and cross-sectoral network, the aim is to across sectors, allowing academic researchers to work with civic government and data collection while non-academic partners can benefit from the insights of academic partners to create new forms of education that illuminate the “black box” of Smart City technology. The expected outcome of research are a new transdisciplinary episteme of the Smart and Data City that is rooted in Digital Studies and subsequently informed methods for handling data collected through Smart City infrastructure.

Keywords: smart city,citizen engagement,digital studies,critical software studies,philosophy of technology,shared economies contributive economy
Mechanism and vulnerability of BAP1 loss in tumor metastasis (VulneraBAP1)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-07-01
End date: 2020-06-30
Duration (months): 24.0
Total project cost (EUR): 171460.8
EU funding (EUR): 171460.8
Participants: 1
Project status: CLOSED

Kidney cancer is among the ten most prevalent cancers arising in Western countries, with clear-cell renal cell carcinoma (ccRCC) being the most frequent subtype (75%). About 30% of ccRCC patients present with metastatic disease at diagnosis, and another 30% will develop metastases after surgery. When metastatic, ccRCC remains largely incurable. I recently discovered that the tumor suppressor BAP1 (BRCA1-associated protein 1) is inactivated in 15% of ccRCCs (Peña-Llopis et al. Nat. Genet. 2012). Notably, I found that mutations in BAP1 are mutually exclusive with mutations of the tumor suppressor gene PBRM1, and loss of BAP1 was associated with higher tumor grade, activation of mTORC1, and poorer overall patient survival, whereas tumors with PBRM1 loss were associated with lower tumor grade and better overall survival. This first molecular genetic classification of ccRCC may have tangible clinical implications, since tumors with BAP1 loss display in general more aggressive pathological features and are more prone to metastasize. However, the molecular mechanism through which BAP1 loss induces metastasis and tumor aggressiveness remains elusive. In this study, I aim to investigate the molecular mechanism of repression of a miRNA cluster involved in metastasis by BAP1 and identify therapeutic opportunities. Specifically, I will (1) supervise a PhD student (supported by a grant I was recently been awarded) in the identification and characterization of the BAP1 protein complex that binds at the miRNA cluster promoter; and (2) I will uncover the genetic vulnerabilities of BAP1 loss by a synthetic lethality strategy. These studies will facilitate attainment of my long term career goal to become a group leader and a fully independent investigator.

Keywords: metastasis,micrornas,functional genomics,epigenetic genes,synthetic lethality,cancer genomics
New Heterogeneous Catalyst Materials for Hydrogenation of CO2 to Formic Acid: Metallophthalocyanine-Based 2D- and 3D Covalent Organic Frameworks (CO2COFs)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Career Restart panel
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Portugal
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-07-01
End date: 2022-06-30
Duration (months): 36.0
Total project cost (EUR): 239722.56
EU funding (EUR): 239722.56
Participants: 1
Project status: CLOSED

In CO2COFs project we will meet the world’s need for new heterogeneous catalyst materials for catalytic CO2 hydrogenation to formic acid (FA) by developing novel metallophthalocyanine (MPc)-based covalent organic frameworks (COFs) with high crystallinity and large surface area for renewable hydrogen storage in formic acid (FA). Althought heterocatalytic CO2 hydrogenation to FA is one of the most promising conversions, relatively few catalytic materials have been reported for this transformation. Furthermore, there are many studies of the development of the homogeneous catalyst for CO2 hydrogenation to FA, but heterogenization of homogeneous Ru complexes by incorporating them onto supporting material is essentially unexplored. In CO2COFs project we will answer the demand by synthesizing MPc-based 2D- and 3D COFs which are highly crystalline materials offering a defined porous structure with definite binding sites for organometallic complexes. Prepared materials will be fully characterized and investigated in hydrogenation of CO2 to FA. One of the main targets of CO2COFs is to achieve recyclable heterogeneous catalysts with catalytic activities and efficiencies among the best reported worldwide. The results of CO2COFs project is expected attract the attention of companies related with catalysts and formic acid processing.

Keywords: phtahlocyanine,catalytic co2 hydrogenation to formic acid