Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : HOPE (Horizon 2020, appel 2020, Synergy grants)
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : CO-PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 5944088.05 €

We aim at shedding a unique light on hippocampal function at circuit level through the design of a novel method to trace the construction of brain circuits in health and disease based on hybrid multiphoton in vivo longitudinal color imaging of the dynamics and structure of genetically-tagged neuronal clones from birth into adulthood. This is made possible by the exceptional interdisciplinary collaboration of three labs with expertise in advanced optical microscopy, genetic engineering and systems developmental neuroscience. Our novel methodology, applied here to the hippocampus, will pioneer a new way to track the emergence and plasticity of heterogeneous neuronal circuits as these progressively give rise to function in physiological and pathological contexts, thus bridging the gap between early development and adult circuit physio-pathology. This will enable us to revisit adult hippocampal function from a developmental perspective. The hippocampus is classically described as providing a cognitive map of space, involved in navigation, learning, and episodic memory. However, a more computational and less representational vision of its role presently emerges in which its circuits are best described as producing sequences of neuronal activation arising from the interaction between external contextual inputs and internally-generated preconfigured dynamics. Converging work including ours leads us to hypothesize that internally preconfigured assemblies, shaped by their developmental journey, are the basic modules of hippocampal function. In this context, we will use our new approach to address three interrelated questions: 1) Are assemblies shaped by specific circuits in the adult hippocampus (objective A)? 2) Are they prewired or shaped by experience (objective B)? 3) What is their patho-physiological significance (objective C)? Addressing these major issues raises a timely challenge in both optics and genetic engineering at the core of this synergistic proposal.

Mots-clés : nonlinear microscopy,multiphoton microscopy,adaptive optics,light sheet microscopy,tissue imaging,harmonic generation microscopy,bioimage informatics,large image data,cell lineage,clonal analysis,connectomics,neurodevelopement,brainbow,genetic engineering,calcium imaging,hippocampus,development,circuits,neuronal dynamics
Projet ERC : HYDRER (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : Institut Català d'Investigació Química — Pays : Espagne — Rôle : PI
Acronyme de l'entité : ICIQ;ICIQ-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

We aim to determine the technical and economic viability of a novel water electrolyzer technology based in inexpensive catalysts from transition metal coordination polymers. Industrial water electrolyzers currently need the use of corrosive alkaline electrolytes or expensive noble-metal catalysts to reach reasonable efficiencies. Because of this, they cannot compete with low cost hydrogen production using fossil fuels through steam reforming. We have discovered that coordination polymers of earth-abundant metals are active water oxidation catalyst, competitive, fast and more robust than the best heterogeneous catalyst ever reported, able to reach over one million cycles working at neutral pH and ambient conditions. This suggests that our catalysts could be the basis of an efficient and affordable electrolyzer able to function using natural waters. The simplicity of operation and the inexpensive construction materials suggest that this new electrolyzer technology could have good market penetration. We expect to reach high efficiency and low costs for hydrogen production by combining this electrolyzer with a commercially available photovoltaic cell. The results will be analyzed and compared to current electrolyzers and hydrogen production technologies to further assess its viability and identify its competitive advantages. This electrolyzer technology will be protected (IP) and, if the results are positive, targeted to market.

Mots-clés : water electrolysis,water splitting,hydrogen
Projet ERC : TALE (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of Basel — Pays : Suisse — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 184859.0 €

We are currently witnessing a revolution in cell therapies that are routed in decades of basic research in genetics, cell biology and immunology. A deep understanding of mammalian, and in particular immune, cells is currently being translated into highly efficient cell-based therapeutics. Technologic breakthroughs in genetic and genome engineering are further fueling the generation of customized, high precision therapies that are based on cells as “smart drugs”. For instance, reprogramming immune killer cells to recognize B cell leukemias resulted in unprecedented clinical responses in treatment-resistant and relapsed patients. However, currently only very few, highly selected patients benefit from these developments. A fundamental problem of today’s cell therapies is that transferred cells cannot be distinguished from host cells. We have developed “allele engineering”, a new technology that solves this challenge. Here, we outline how allele engineering will improve the safety and efficacy of cell therapies. We will 1) generate a non-viral, DNA-free safety/shielding switch 2) develop a radically new curative approach to acute myeloid leukemia 3) rationally design a safe allele engineering solution for human therapy and 4) use allele engineering as a curative therapy of scurfy syndrome, a lethal monogenic autoimmune disease. Allele engineering enables completely new treatment strategies and can be applied to any surface protein. Therefore, I anticipate that the results will have a major impact on the field.

Mots-clés : cell therapy,car t cell,safety switch
Projet ERC : DEMED (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Gothenburg — Pays : Suède — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 209153.75 €

We are currently witnessing an unprecedented rise of authoritarian leaders, backed by popular support, who defy democracy. Challenging existing paradigms and an elite-focused literature, DEMED will take an individual-level perspective to study the causes of democratic backsliding and identify solutions to build more resilient democratic societies. Thereby, DEMED will have a transformative effect on the study of democracies and autocracies as well as the dynamics between the two. DEMED is a ground-breaking project that transforms our knowledge about the process of democratisation and backsliding. Work packages (WP) are divided along four objectives: 1) Establish causes of democratic backsliding, focusing on the role of indoctrination; 2) Demonstrate the effects of indoctrination on democratic political cultures and democratic survival; 3) Identify solutions to prevent democratic recessions through innovative online civic education programmes; and 4) provide a new theoretical and empirically validated paradigm to lead to more stable democracies. WP1 develops the first unifying theoretical framework of societal drivers predicting democratic (in)stability. Based on this theoretical and conceptual work, WP1 creates the first-ever global dataset on strategies of indoctrination by 180 countries from 1900 to today. WP2 uses cutting-edge methods to test for the first time how these educational drivers create democratic and authoritarian political cultures. This quantitative approach will be complemented with original qualitative data. Finally, WP3 uses pioneering online randomised experiments to test the impact of newly developed civic education interventions to promote democracy. This is an ambitious research agenda, with theoretical and methodological innovations. DEMED revolutionises our understanding of the causes, effects and solutions of democratic backsliding. It presents risks, but with the potential for ground-breaking scientific and societal impact.

Mots-clés : democratic backsliding,authoritarian regimes,indoctrination,civic education,experiments,mixed method approach
Projet ERC : DEMED (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Glasgow — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1785870.0 €

We are currently witnessing an unprecedented rise of authoritarian leaders, backed by popular support, who defy democracy. Challenging existing paradigms and an elite-focused literature, DEMED will take an individual-level perspective to study the causes of democratic backsliding and identify solutions to build more resilient democratic societies. Thereby, DEMED will have a transformative effect on the study of democracies and autocracies as well as the dynamics between the two. DEMED is a ground-breaking project that transforms our knowledge about the process of democratisation and backsliding. Work packages (WP) are divided along four objectives: 1) Establish causes of democratic backsliding, focusing on the role of indoctrination; 2) Demonstrate the effects of indoctrination on democratic political cultures and democratic survival; 3) Identify solutions to prevent democratic recessions through innovative online civic education programmes; and 4) provide a new theoretical and empirically validated paradigm to lead to more stable democracies. WP1 develops the first unifying theoretical framework of societal drivers predicting democratic (in)stability. Based on this theoretical and conceptual work, WP1 creates the first-ever global dataset on strategies of indoctrination by 180 countries from 1900 to today. WP2 uses cutting-edge methods to test for the first time how these educational drivers create democratic and authoritarian political cultures. This quantitative approach will be complemented with original qualitative data. Finally, WP3 uses pioneering online randomised experiments to test the impact of newly developed civic education interventions to promote democracy. This is an ambitious research agenda, with theoretical and methodological innovations. DEMED revolutionises our understanding of the causes, effects and solutions of democratic backsliding. It presents risks, but with the potential for ground-breaking scientific and societal impact.

Mots-clés : democratic backsliding,authoritarian regimes,indoctrination,civic education,experiments,mixed method approach
Projet ERC : PROJESTOR (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : IBM Research - Zurich — Pays : Suisse — Rôle : PI
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 2555525.0 €

We are entering the third era of computing: cognitive computing, which holds great promise in terms of deriving intelligence/knowledge from huge volumes of data. Today’s cognitive computers are based on the von Neumann architecture, in which the computing and the memory units are separated. Cognitive computing, however, is inherently data-centric, meaning that huge amounts of data need to be shuttled back and forth at high speeds, a task at which that architecture is highly inefficient. It is becoming increasingly clear that to build efficient cognitive computers, we need to transition to non-von Neumann architectures where memory and logic coexist in some form. Brain-inspired neuromorphic computing and the fascinating new area of memcomputing are two key non-von Neumann approaches being researched. The critical element in these novel computing paradigms is a very-high-density, low power, variable-state, programmable and non-volatile nanoscale memory device. A technological breakthrough that will lead us to this device will be a game-changer for cognitive computing. The goal of this project is to explore one such device concept that I co-invented at IBM Research - Zurich and which we have dubbed “projected memristor” or “projestor” for short. The projestor is indeed a memristor, i.e., a resistive element that remembers the history of the current that previously flowed through the device. The distinguishing feature of a projestor is that the physical mechanism of resistance storage is decoupled from the information retrieval process. In the first part of the project, we will design and fabricate projestor devices to establish the concept of projection and assess its merits and drawbacks. In the second part, we will expand the concept substantially to explore highly innovative projestor devices. In the third part, we will explore various applications of projestors in neuromorphic computing and memcomputing, with a particular focus on real-time data analytics.

Mots-clés : memristors,nanoscale devices,phase change materials,neuromorphic engineering,memcomputing,cognitive computing,artificial intelligence,statistical inference,machine learning
Projet ERC : LiquOrg (Horizon 2020, appel 2020, Synergy grants)
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3339375.0 €

We are in the midst of a revolution in our understanding of the internal organization of cells. In the 1950s we learned that lipid bilayer-based membranes serve as containers (organelles) within the cytoplasm. Now we are learning that liquid-like “membrane-less” organelles i.e. without any container, self-assemble based on “liquid-liquid” phase separations. We propose the seemingly radical idea that membrane-bounded organelles– like their membrane-less counterparts- are stabilized or even templated by analogous phase separations of their surface proteins into largely planar liquids akin to liquid crystals. Our unique Synergy team is organized specifically to test this “liquid crystal hypothesis” on the cell’s secretory compartments - ER exit sites (ERES) and the Golgi stack - by employing our complementary skills in physics, physical chemistry, biochemistry and cell biology. We hypothesize based on pilot experiments evidence that the ERES and Golgi self-organize as a multi-layered series of adherent liquid crystal-like phases of “golgin” and similar proteins which surround and enclose their membranes. Their differential adhesion and repulsion would specify the topology and dynamics of the membrane compartments. If this is true, it will literally rewrite the history of cell biology. We will test the ‘liquid crystal’ hypothesis directly, systematically, and quantitatively on an unprecedented scale to either modify/disprove it or place it on a firm rigorous footing. Experiments (Aim 1) with 13 pure golgins in cis and trans pairwise combinations will establish their foundational physical chemistry. Surgically engineered changes in golgins/ERES proteins will alter the rank order (hierarchy) of their affinities for each other and link phase separation physics to cell biology (Aim 2) and be used to establish the structural basis of phase separations and their specificity, and the potential for self-assembly of wholly synthetic biological organelles (Aim 3).

Mots-clés : 2d phase separation,protein liquid crystals,synthetic golgi,atomic force microscopy,surface forces apparatus,giant unilamellar vesicles,er exit site,golgin
Projet ERC : SYMELS (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : TU Wien — Pays : Autriche — Rôle : PI
Acronyme de l'entité : TUW
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

We are living in a world that is increasingly run by software. Daily activities, such as online banking, mobile communications and air traffic use, are controlled by software. This software is growing in size and functionality, but its reliability is hardly improving. We are getting used to the fact that that computer systems are error-prone and insecure. To (re)gain the trust of end-users in software and Web services, formal automated reasoning is one of the main investments made by ICT companies in preventing software errors. To improve in this area, one should answer some important questions, such as - Which methods in automated reasoning are the most appropriate for proving software error-free? - What needs to be done to apply research in automated reasoning to large-scale code bases? Our SYMELS project aims at answering these questions by bringing our symbol elimination method to the ICT market. The key innovation brought in by SYMELS is the ability to automatically generate and prove first-order properties of software that prevent programmers from introducing errors while making changes in this software. Our initial results show that symbol elimination can be a breakthrough method: e.g. when testing programs manipulating computer memory it was able to prove that over 80% of test cases are guaranteed to have the expected behavior. Most of these test problems were coming from industry, where similar proofs required very costly human work. Analyzing such programs requires reasoning about program properties in full first-order logic. No other method can reason about such properties with the same accuracy and expressiveness as SYMELS. For the proof-of-concept, SYMELS gives ICT customers and investors a tool-supported methodology for ensuring continuous growth in software functionality, thus increasing software reliability and user's trust in software technologies.

Mots-clés : software verification,system engineering,formal methods,automated reasoning
Projet ERC : MInfla-Tilc (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : Aix-Marseille Université — Pays : France — Rôle : PI
Acronyme de l'entité : amU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

We are proposing to target Innate Lymphoid Cells 2 (ILC2s), a subset that has been frequently implicated in inflammatory diseases, such as severe asthma. ILC2s are major players in allergic asthma and are abundantly present as tissue resident cells in the lung, both in human and mouse. Strikingly, the induction of allergic asthma in a mouse model deficient in ILC2s is abolished. In addition, the transfer of ILC2s back in the same mouse recapitulates the pathology. Mechanistically, activated ILC2s are the main producer of type 2 cytokines that sustain the chronicity of asthma by recruiting other inflammatory and pathogenic cells, notably eosinophils, and finally drive hyperresponsiveness and mucous hypersecretion. In humans, ILC2s are increased in the peripheral blood mononuclear cells (PBMCs) of patients with allergic asthma compared to healthy controls. They are also found in sputum and PBMCs of patients with severe, eosinophilic asthma compared to mild forms of asthma. Collectively, these data highlight the significance of ILC2s in allergic inflammation and emphasize the idea to target those cells for therapeutic purposes. MInfla-Tilc is a translational and integrated project aiming to launch an innovative therapeutic monoclonal antibody (mAb) treatment against ILC2s to control severe asthma.

Mots-clés : innate lymphoid cell,ilc2,inflammation,lung,monoclonal therapeutic antibody,crth2,asthma,cell depletion therapy
Projet ERC : WhiteMech (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 618996.1 €

We are witnessing an increasing availability of mechanisms that operate in nondeterministic (uncertain) environments and offer some form of programmability. These include manufacturing devices, smart objects and spaces, intelligent robots, dynamic business process management systems, and many others. All these mechanisms are currently being revolutionized by advancements in sensing (vision, language understanding) and actuation components (autonomous mobile manipulators, automated storage and retrieval systems). However, such mechanisms are held back by the fact that their logic is still based on hard-wired rules encoded in hand-crafted programs. WhiteMech aims at developing the science and the tools for a new generation of mechanisms to emerge: mechanisms that are able to program themselves, automatically tailor their behavior so as to achieve desired goals, maintain themselves within safe boundaries in a changing environment, and follow regulations and conventions that evolve over time. Crucially, empowering mechanisms with self-programming carries significant risks and therefore we must be able to balance power with safety. For this reason WhiteMech intends to realize mechanisms that are white-box, that is, whose behavior is at any moment fully analyzable and comprehensible in human terms, and guarded by human oversight. Remarkable recent discoveries by the applicant in Reasoning about Action and Generalized Planning in Artificial Intelligence, and their connections to Verification and Synthesis in Formal Methods, and Data-Aware Processes in Databases, chart an unanticipated novel path to produce a breakthrough in realizing powerful self-programming mechanisms, while keeping them human- comprehensible and safe by design. WhiteMech will ground its scientific results upon three driving applications: smart manufacturing (Industry 4.0), smart spaces (IoT) and business process management systems (BPM).

Mots-clés : knowledge representation,reasoning about action and generalized planning in artificial intelligence,verification and synthesis in formal methods,data aware processes in databases