Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : FluAttack (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : PI
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 139081.0 €

With 3 to 5 million severe cases and up to 650,000 deaths per year worldwide, influenza viruses are not only major human pathogens, they are also a heavy economic burden to our societies. In addition, influenza pandemics can occur at any time with potential devastating effects in terms of lives and costs. Solutions to prevent infection, to treat severe influenza cases and to respond to a severe pandemic are currently extremely limited and rely on vaccination and on only few approved molecules. All these solutions have their limitations with respect to efficacy and all face the problem of viral resistance. Thus, the demand for new options against influenza infections is high. The World Health Organization (WHO) and influenza virus specialists agree that innovative and effective anti-influenza compounds with a reduced risk of viral escape are urgently needed. The main goal of this ERC PoC is to provide key data on a promising innovative therapeutic solution identified in the lab. Taking advantage of a powerful screening system we have developed during the ERC StG ANTIViR, we have identified a family of molecules as potent inhibitors of influenza virus (with IC50<100nM). The mode of action of these molecules is known and they actually target a cellular function essential to all influenza viruses. Preventing viral replication by targeting a cellular function is a novel approach, predicted to strongly reduce the risk of drug resistance. Importantly, one of our hits went through several phase II and III clinical trials as an anti-cancer agent, making this molecule a perfect candidate for drug repurposing. In this context, the specific objectives of this ERC PoC are: i) to further characterise and validate our best hit, in particular in commercial 3D human airway epithelial cells and in vivo in a mouse model, and ii) to secure IPR and to establish an exploitation strategy plan (patent licensing or creation of a start-up) to support future development and preclinical tests.

Mots-clés : influenza viruses,antivirals,pandemic,drug repurposing,host factor inhibition,viral escape risk reduction,first in class molecule,broad range activity
Projet ERC : STEEPclim (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : GFZ
Type d'entité : Recherche
Financement ERC de l'entité : 1847546.0 €

With global temperatures on the rise due to anthropogenic greenhouse gas emissions, one of the largest short-term threats to societies comes from a changing water cycle: changing ocean currents and atmospheric circulation patterns, increased periods of drought or extreme precipitation events directly affect the socio-economic foundation of communities. However, one of the great unknowns in state-of-the art climate models predicting future changes is the spatial distribution of changing precipitation patterns. This lack of knowledge severely limits implementation of mitigation and adaptation options to divert the most severe consequences of climate change. I propose a fundamentally new approach to understand spatial patterns and mechanisms of hydrological changes on the European continent by reconstructing such changes during past abrupt temperature and ocean circulation changes. We will develop an innovative research program integrating ideas and methods from diverse disciplines: organic geochemistry, plant physiology, event stratigraphy and geostatistical data analysis. We will generate quantitative paleohydrological data by developing a dual biomarker approach as a novel and direct proxy for fluxes in the hydrological cycle from 10 of the most precisely dated terrestrial climate records encompassing the European continent. STEEPclim will enter uncharted territory and establish master records of continental climate change, comparable in resolution and quality to the polar ice cores. We will identify continental-scale feedback mechanisms and particularly vulnerable regions in European hydroclimate relevant for the evaluation of the consequences of ongoing climate change. These mechanistic insights will be essential to validate future generations of climate models, ensuring more accurate predictions of regional effects of anthropogenic climate changes and as such enable a targeted mitigation and adaptation policy.
Projet ERC : CIRCULAR X (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Maastricht University — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499915.0 €

With increasing pressures on resources and the climate it is clear that a new business paradigm is needed. The Circular Economy has been heralded as a driver for sustainability and competitiveness. In contrast to the current linear economy, materials are kept at their highest utility at all times. Despite great policy, business and academic interest, knowledge on how to move to a Circular Economy is lacking. CIRCULAR X addresses a new and urgent issue in sustainability research: experimentation with circular service business models (CSBMs). Examples include companies shifting from selling to leasing products and introducing lifelong warrantees to extend product lifetimes. CSBMs are far from mainstream and experimentation focused on trialling new CSBMs is little understood. CIRCULAR X will develop a new field in sustainability studies: CSBM experimentation. It aims to conduct boundary-pushing and cross-sectoral interdisciplinary research in 3 continents and 5 countries – the Netherlands, UK, Sweden, China and USA - with 4 objectives: 1. Advancing understanding of CSBMs; their emergence and impacts 2. Advancing knowledge on CSBM experimentation 3. Developing CSBM experimentation tools 4. Designing and deploying CSBM experimentation labs CIRCULAR X will bridge and expand disparate knowledge on experimentation approaches across disciplines such as sustainability, design, business and entrepreneurship research. It will develop novel CSBM and experimentation concepts, catalogues, tools and labs by bridging these yet disparate fields. Through its comprehensive international approach, CIRCULAR X will deeply advance understandings on how CSBMs manifest themselves and how these can be experimented with, which will ultimately advance business activities towards a circular economy transition.

Mots-clés : sustainability,circular economy,sustainable innovation,sustainable innovation tools,sustainable business experiments,sustainable business models,business experimentation,product service systems
Projet ERC : Host-TB (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Amsterdam University Medical Centers — Pays : Pays-Bas — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 793985.51 €

With more than 10 million cases annually, tuberculosis (TB) remains a global health problem. TB epidemic is exacerbated by the spread of multidrug-resistant TB. Host-directed therapies (HDTs) can improve immune mechanisms by augmenting the ability of host cells to kill M. tuberculosis (Mtb) or by modulating the immune response to prevent excessive inflammation, cell death and tissue damage. Progress with HDT development has been slowed down by the limited understanding of host-pathogen interactions during Mtb infection. Screens of the whole human genome can identify novel genes involved in the immune responses to Mtb infection and susceptibility to TB. Previously, we successfully used genome-wide association studies to identify human genes associated with susceptibility to TB. Here, we will for the first time use the groundbreaking CRISPR technology to screen the human genome in macrophages infected with Mtb and discover genes that are critically involved in host-pathogen interactions. Then, we will comprehensively characterise pathways that mediate impacts of these genes on both the human macrophage and the intracellular Mtb bacilli using dual transcriptome analyses and high-throughput microscopy assays. This novel approach will dissect crucial mechanisms of host-pathogen interaction during Mtb infection and will point to new targets for HDTs of TB.

Mots-clés : tuberculosis
Projet ERC : Hyperfoods (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Imperial College London — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

With rapidly ageing populations, the world is experiencing an unsustainable healthcare and economic burden from chronic diseases such as cancer, cardiovascular, metabolic and neurodegenerative disorders. Diet and nutritional factors play an essential role in the prevention of these diseases and significantly influence disease outcome in patients during and after therapy. Everyday food ingredients contain multiple drug-like molecules that can potentially prevent or beat diseases. For example, it is estimated that up to half of oncological diseases can be prevented by dietary choices. The wide adoption of tailored health-promoting diets potentially has a revolutionary impact on the population wellbeing and long-term sustainability of the healthcare systems. However, due to an exponentially large number of combinations of the ingredients, their sourcing, processing, preparation, and preservation methods, it is virtually impossible to use traditional experimental approaches to optimise the health-promoting molecular profiles of foods. Hyperfoods will use novel graph-based ML methods to provide the technological capabilities for the computational discovery and design of personalised nutrition. We will explore the commercial opportunities of our technology for currently unmet business needs in global health, in particular cancer treatments.

Mots-clés : geometric deep learning,graph ml,precision nutrition,digital therapeutic,cancer
Projet ERC : MULTIPLES (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Acronyme de l'entité : KUL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1991243.0 €

With stellar masses in the range of eight to several hundreds of solar masses, massive stars are among the most important cosmic engines, each individual object strongly impacting its local environment and populations of massive stars driving the evolution of galaxies throughout the history of the universe. Recently, I have shown that stars more massive than 15 Msun rarely, if at all, form and live in isolation but rather as part of a binary or higher-order multiple system. Understanding the life cycle of massive multiple systems, from their birth to their death as supernovae and long-duration gamma ray bursts, is one of the most pressing scientific questions in modern astrophysics. To obtain the key observational breakthroughs needed to revolutionize our understanding of high-mass stars, my research program is developed along three themes: (i) investigate the physical processes that set the multiplicity properties of massive stars, (ii) establish the multiplicity properties of unevolved massive stars across the entire mass range, (iii) identify and uniquely characterize post-interaction products. The implementation of the MULTIPLES program involves ambitious time-resolved observational campaigns targeting large populations of massive stars at key stages of their pre-supernova evolution and in different metallicity environments. These campaigns will combine state-of-the-art spectroscopy and high-angular resolution techniques with novel multiplicity and atmosphere analysis methods appropriate for multiple systems. Upon completion, the observational constraints that will be obtained in this project will have implications that extend well beyond the sole domain of stellar astrophysics.

Mots-clés : massive stars,binary stars,observational astrophysics
Projet ERC : HumanML (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 1495000.0 €

With the advent of mass-scale digitization of information and virtually limitless computational power, an increasing number of social, information and cyber-physical systems evaluate, support or even replace human decisions using machine learning models and algorithms. Machine learning models and algorithms have been traditionally designed to take decisions autonomously, without human intervention, on the basis of passively collected data. However, in most social, information and cyber-physical systems, algorithmic and human decisions feed on and influence each other. As these decisions become more consequential to individuals and society, machine learning models and algorithms have been blamed to play a major role in an increasing number of missteps, from discriminating minorities, causing car accidents and increasing polarization to misleading people in social media. In this project, we will develop human-centric machine learning models and algorithms for evaluating, supporting and enhancing decision making processes where algorithmic and human decisions feed on and influence each other. These models and algorithms will account for the feedback loop between algorithmic and human decisions, which currently perpetuates or even amplifies biases and inequalities, and they will learn to operate under different automation levels. Moreover, they will anticipate how individuals will react to their algorithmic decisions, often strategically, to receive beneficial decisions and they will provide actionable insights about their algorithmic decisions. Finally, we will perform observational and interventional experiments as well as realistic simulations to evaluate their effectiveness in a wide range of applications, from content moderation, recidivism prediction, and credit scoring to medical diagnosis and autonomous driving.

Mots-clés : decision making,fairness in machine learning,strategic machine learning,human ai collaboration,human centric machine learning,social aspects of machine learning
Projet ERC : RadNu (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Vrije Universiteit Brussel — Pays : Belgique — Rôle : PI
Acronyme de l'entité : VUB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1410000.0 €

With the detection of the high-energy cosmic-neutrino flux by the IceCube neutrino observatory at the South-Pole, IceCube opened the field of neutrino astronomy. Nevertheless, due to the steeply falling energy spectrum, IceCube runs low in statistics at energies above a few PeV. To probe this flux at the highest energies (>PeV), therefore asks for an even larger detection volume than the cubic-kilometer currently instrumented by IceCube. Due to its long attenuation length the radio signal is an ideal probe to cover such a large volume. When a high-energy cosmic neutrino interacts in a dense medium like ice, a relativistic particle cascade is induced. In 1962 Askaryan already predicted that due to the net charge build-up inside the cascade, coherent radio emission is expected. However, this signal is only detectable for initial neutrino energies in access of a few EeV. Therefore, currently there is a sensitivity gap to probe the high-energy cosmic neutrino flux in the PeV – EeV energy range. This project aims to fill this sensitivity gap by the development of a novel radio detection technique to measure high-energy particle cascades in dense media, the radar detection technique. By directly probing the ionization plasma which is left behind after the neutrino induced particle cascade propagates through the medium, the radio detection energy threshold is lowered to a few PeV. The feasibility of the radar detection technique, was shown in a recent experiment. To determine the radar scattering efficiency more accurately, a new beam-test at the SLAC facility is planned as part of this proposal. Once the scattering parameters have been determined accurately, a detailed modeling and sensitivity study will be performed to achieve the main goal of this research proposal: The construction of an in-nature experiment at the South-Pole with the sensitivity to observe 1-10 cosmic neutrino events per year in the PeV – EeV energy range.

Mots-clés : neutrinos,radio detection,radar,high energy particle cascades
Projet ERC : DEMBIB (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : Humboldt-Universität zu Berlin — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

With the discovery of numerous papyri in Egyptian Demotic script during the last two decades, a whole new corpus of Egyptian literature has become available. Based on 25 years of research of the Principle Investigator (PI) on Egypt and the Hebrew Bible, this project, for the first time ever, correlates the newly accessible Demotic papyri with Biblical literature. Since the Demotic literature comes from the exact historical period when the Hebrew Bible received its final form – the Persian and Hellenistic Age – the Egyptian papyri are nothing less than the extra-Biblical evidence Biblical scholarship has asked for over decades. Like the Hebrew Bible, the Demotic literature is rooted in a scribal culture, and thus displays significant parallels to Biblical literature. The DEMBIB project aims 1) to investigate the structural parallels in Demotic literature and the Hebrew Bible; 2) to identify the compositional strategies of Demotic and Biblical literature; and 3) to contextualize these literary characteristics in the socio-historical situation of the 6th–3rd c. BCE when a scribal elite in Egypt and “Israel” faced similar challenges such as a changing socio-cultural environment and a marginalization of traditional temples. The groundbreaking character of DEMBIB lies in: 1) the cross-cultural comparison of newly discovered Egyptian papyri and the Hebrew Bible; 2) the analysis of similar literary processes in Egyptian Demotic and Biblical literature; 3) the understanding of the dynamics between a distinct scribal culture and its socio-historical context. The main goal of DEMBIB is to offer a new paradigm for the understanding of the transformation of textual traditions into complex forms of literature in Egypt and Israel during the Persian and Hellenistic Period. By doing so, one of the most crucial questions in Hebrew Bible scholarship today should be answered: the intellectual and historical context for the final formation of the Hebrew Bible.

Mots-clés : demotic literature and the hebrew bible,formation of the hebrew bible,cross cultural comparison,scribal culture,egypt and the southern levant under foreign rule,persian and ptolemaic age
Projet ERC : SILENT (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Université Libre de Bruxelles — Pays : Belgique — Rôle : Partner
Acronyme de l'entité : ULB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 498800.0 €

With the first direct detection of gravitational waves on the 14th of September 2015, a new window has been opened on the Universe. This was the starting point of new science, complementary to the measurement of electromagnetic signals by optical telescopes. Since that date, several detections have been made, offering wonderful validation of Einstein’s theory of general relativity, and extraordinary insight on the dynamics of heavy black hole binaries and binaries of neutron stars. The exploration of the Universe through this new window using Earth-based instruments will continue with more sensitive instruments, but will ultimately depend on our capability to isolate them from the two main sources of low-frequency disturbances on Earth: seismic activity and fluctuations of gravity field (Newtonian noise). Due to the extremely small amplitude of gravitational waves, it is a prior concern to carefully isolate the detector from any type of disturbance. In order to address the aforementioned limitations, this project proposes to develop a completely novel platform, controlled by optical seismometers, liquid inclinometers and a gravimeter. It will virtually float in the inertial space, decoupled from ground motion for periods at least as large as 100 seconds. The controlled platform will be the most stable ever build on Earth. Such performance will be obtained thanks to a revolutionary approach, combining three major innovations: (1) Novel optical inertial sensors, (2) Efficient controllers, combining sensor fusion methods, and dedicated mechatronic architectures, (3) Direct measurement of Newtonian noise. This project will contribute to prepare the third generation of low-frequency gravitational wave detectors. The outcomes will be also applicable to a large class of other instruments (e.g. particle colliders, atomic force microscopes, lithography machines, medical imaging instruments), ensuring a generic character to this project, and a major scientific impact.
Projet ERC : MicrobioS (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : European Molecular Biology Laboratory — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : EMBL
Type d'entité : Recherche
Financement ERC de l'entité : 2184432.5 €

With the genome sequencing of hundreds of bacterial isolates per day and a vast and growing number of metagenomic sequencing projects on gut microbiomes in healthy and diseased people all over the world, it becomes feasible to explore the microbial diversity in us not only at the level of genera and species, but at strains. As two different strains of a prokaryotic species might only share 40% of the genes and can also have vastly differ in single nucleotide polymorphism (SNP) many aspects of a proper understanding of the microbial communities we host in the gut might only be revealed at this high resolution level. This proposal aims (i) to develop a robust methodology to characterize the SNP and gene content landscape from metagenomic shotgun data (ii) to explore patterns of variation in the human population to stratify geographically, but also in subpopulations such as families and to understand spreading patterns and the evolution of microbial strains as well as iii) to work towards medical applications, for example by monitoring fecal microbiota transplantation (FMT) at strain resolution or monitoring particular strain of interest in the population

Mots-clés : human microbiome,gut metagenomics,microbiomics