Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : OsseoWave (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Dental implants are widely used to replace missing teeth, with more than 4 000 000 implant surgery per year in Europe. Failures still occur because of a bad timing in the implant loading with the prosthesis, inducing pain and increased costs for dental surgeons. Although implant primary and secondary stability is the main determinant of the implant success, it remains difficult to be assessed in clinical practice. OsseoWave is based on the results obtained in the ERC CoG project Boneimplant and aims at developing and validating a medical device consisting in a decision support-system allowing the surgeon to assess dental implant stability. Such medical device is needed by the clinicians in order to adapt their surgical strategy. The objective of OsseoWave is i) to achieve a minimum viable product (MVP) that will be validated in vitro and in vivo, and ii) to investigate its commercial potential and design a subsequent commercial exploitation strategy via spin-off creation or licensing of the technology. The originality of the approach is to use quantitative ultrasound, a non-invasive, non-radiating, portable and cheap technique, which constitute a technological rupture. Regulatory issues will be at the heart of the development and we will work in order to clear the regulatory pathway of the future medical device. Post-OsseoWave, the MVP will be ready to go through CE marking application. The team is constituted by members with complementary skills (including engineers, a business developer and maxillofacial and veterinary surgeons experts in implantology). OsseoWave will allow the promotion of innovative solution and services in dental implantology. The long-term vision is for the technology to become a reference in dental implant surgery. Strong impacts are associated to OsseoWave and in particular for the surgeons, the patients, the implant manufacturer, the technology and the economy.

Mots-clés : medical device,dental implant,ultrasound,biomechanics,decision support sytem,osseointegration,implant stability
Projet ERC : BG-BB-AS (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
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 : 1358925.0 €

Derived categories of coherent sheaves on a variety are a fundamental tool in algebraic geometry. They also arise in String Theory, as the category of B-branes in a quantum field theory whose target space is the variety. This connection to physics has been extraordinarily fruitful, providing deep insights and conjectures. An Artin stack is a sophisticated generalization of a variety, they encode the idea of equivariant geometry. A simple example is a vector space carrying a linear action of a Lie group. In String Theory this data defines a Gauged Linear Sigma Model, which is a basic tool in the subject. A GLSM should also give rise to a category of B-branes, but surprisingly it is not yet understood what this should be. An overarching goal of this project is to develop an understanding of this category (more accurately, system of categories), and to extend this understanding to more general Artin stacks. The basic importance of this question is that in certain limits a GLSM reduces to a sigma model, whose target is a quotient of the vector space by the group. This quotient must be taken using Geometric Invariant Theory. Thus this project is intimately connected with the question of how derived categories change under variation-of-GIT, and birational maps in general. For GLSMs with abelian groups this approach has already produced spectacular results, in the non-abelian case we understand only a few remarkable examples. We will develop these examples into a wide-ranging general theory. Our key objectives are to: - Provide powerful new tools for controlling the behaviour of derived categories under birational maps. - Understand the category of B-branes on a large class of Artin stacks. - Prove and apply a striking new duality between GLSMs. - Construct completely new symmetries of derived categories.

Mots-clés : derived categories
Projet ERC : FIDELIO (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Warwick — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 837259.5 €

Designating Protected Areas (PAs) is the most important policy tool for biodiversity conservation. Over 100 new PAs have been established in the past 36 months in European Union territory. However, effective management of PAs is often obstructed by conflicts mainly associated with the social impacts (SIs) imposed on local communities by their establishment. Despite the importance of these SIs there are certain aspects in this field that remain significantly under-researched. There is now an increasing need to incorporate SI assessments in decision making processes by providing a clear framework explaining how perceptions of these impacts are created and predicting their change in the future. This will support the achievement of international goals for biodiversity conservation and adaptation to climate change as well as better accounting for social justice issues for communities dependent on protected natural resources. The aim of FIDELIO is to develop for the first time a new paradigm in order to understand how perceptions of SIs are formulated taking into consideration the dimensions of space and time. FIDELIO will assist in increasing public engagement and the incorporation of local opinions in decision-making. It will also facilitate the process of policy development and a reduction in conflicts between different stakeholders in PAs. FIDELIO will last 5 years and its research objectives will be explored through the application of a mixed-methods approach including the implementation of two rounds of social surveys in 4 PAs across Europe and the testing of the framework in 15 additional PAs. This is an extremely timely project considering the steady increase of new PAs and the re-designation of current ones. FIDELIO will contribute to the better understanding of SIs and facilitate predictions for their change in the future, while assisting in maximizing social benefits for local communities arising from the designation of a PA.

Mots-clés : protected areas,social impacts,europe
Projet ERC : antiCSC (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Autonomous University of Madrid — Pays : Espagne — Rôle : Partner
Acronyme de l'entité : UAM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Designed, bulky metal complexes with a labile coordination position react with accessible guanines at G4 DNA quadruplexes, promoting changes in their conformation and function. Importantly, we have found that this selective reactivity leads to very interesting biological effects. In particular, some of these compounds are able to suppress the “stem”-like character of cancer stem cells, apparently by deterring their mitochondrial respiration. Preliminary experiments, including in vivo assays, confirm that these biological effects result in remarkable antitumoral activities. This proposal aims to explore the scope of the approach, confirm that the mechanism of action involves mitochondria, design more selective versions and exploit the potential of the compounds as new type of anticancer agents.

Mots-clés : synthetic metal complexes,ruthenium,coordination chemistry,anticancer chemotherapy,cancer stem cells,chemical biology,biomedicine
Projet ERC : antiCSC (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Santiago de Compostela — Pays : Espagne — Rôle : PI
Acronyme de l'entité : USC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 130000.0 €

Designed, bulky metal complexes with a labile coordination position react with accessible guanines at G4 DNA quadruplexes, promoting changes in their conformation and function. Importantly, we have found that this selective reactivity leads to very interesting biological effects. In particular, some of these compounds are able to suppress the “stem”-like character of cancer stem cells, apparently by deterring their mitochondrial respiration. Preliminary experiments, including in vivo assays, confirm that these biological effects result in remarkable antitumoral activities. This proposal aims to explore the scope of the approach, confirm that the mechanism of action involves mitochondria, design more selective versions and exploit the potential of the compounds as new type of anticancer agents.

Mots-clés : synthetic metal complexes,ruthenium,coordination chemistry,anticancer chemotherapy,cancer stem cells,chemical biology,biomedicine
Projet ERC : MHINT (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of Bristol — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1344279.18 €

Despite decades of research, and the introduction of parenting interventions, children of mentally ill mothers remain substantially more likely to have mental health problems themselves. I propose to shed new light on why mental health problems in a mother are passed on to her child, and help break this reinforcing cycle of mental health risk across generations. In order to harness the potential of modifying parenting for the prevention of child mental health risk, I will study parenting using more detailed, ecologically valid and genetically sensitive designs than have been done before. Objectives: 1: To investigate the respective role of genetic and environmental (chiefly parenting) mechanisms in explaining associations between mother and child mental health. HOW: using a consortium of international cohorts with intergenerational genetic and phenotypic data (n>10,000) and, for the first time, modeling genetic risk which is and is not transmitted from mother to child to test alternative hypotheses. 2: To identify behavioural manifestation of maternal mental health, in observed mother-infant interaction, in an ecologically valid way. HOW: recording 300 mother- child dyads at home, using novel wearable cameras, in the next generation of a key cohort (ALSPAC-G2). 3: To identify cognitive underpinnings of maternal behaviour. HOW: including cognitive tasks (with eye tracking) as new measures in ALSPAC-G2, applying computational models to cognitive and (uniquely) real life data (measured in 2). 4: To establish whether modification of maternal parenting (highlighted in 1-3), changes child mental health. HOW: systematic review of parenting intervention trials and new synthesis methods to extract which intervention components reduce child mental health problems. My study will provide critical new evidence regarding the nature of parenting interventions that have potential to improve child mental health and break intergenerational transmission of mental health problems.

Mots-clés : intergenerational,maternal mental health,parenting
Projet ERC : CADENCE (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Universidad de Zaragoza — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UNIZAR
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2483136.0 €

Despite intense research efforts in almost every branch of the natural sciences, cancer continues to be one of the leading causes of death worldwide. It is thus remarkable that little or no therapeutic use has been made of a whole discipline, heterogeneous catalysis, which is noted for its specificity and for enabling chemical reactions in otherwise passive environments. At least in part, this could be attributed to practical difficulties: the selective delivery of a catalyst to a tumour and the remote activation of its catalytic function only after it has reached its target are highly challenging objectives. Only recently, the necessary tools to overcome these problems seem within reach. CADENCE aims for a breakthrough in cancer therapy by developing a new therapeutic concept. The central hypothesis is that a growing tumour can be treated as a special type of reactor in which reaction conditions can be tailored to achieve two objectives: i) molecules essential to tumour growth are locally depleted and ii) toxic, short-lived products are generated in situ. To implement this novel approach we will make use of core concepts of reactor engineering (kinetics, heat and mass transfer, catalyst design), as well as of ideas borrowed from other areas, mainly those of bio-orthogonal chemistry and controlled drug delivery. We will explore two different strategies (classical EPR effect and stem cells as Trojan Horses) to deliver optimized catalysts to the tumour. Once the catalysts have reached the tumour they will be remotely activated using near-infrared (NIR) light, that affords the highest penetration into body tissues. This is an ambitious project, addressing all the key steps from catalyst design to in vivo studies. Given the novel perspective provided by CADENCE, even partial success in any of the approaches to be tested would have a significant impact on the therapeutic toolbox available to treat cancer.

Mots-clés : heterogeneous catalysis,photocatalysis,cancer figthing catalysts,microfluidics,reactive oxygen species,in tumour reactor,trojan horse,nir activation
Projet ERC : Stringlandscape (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Commissariat à l’énergie atomique et aux énergies alternatives — Pays : France — Rôle : PI
Acronyme de l'entité : CEA
Type d'entité : Recherche
Financement ERC de l'entité : 1669465.0 €

Despite its uniqueness, string theory has a “landscape” of low-energy solutions with very different observable physics. These solutions are usually found using low-energy effective theories which, in order to satisfy all the experimental constraints, require a number of exotic ingredients whose string theory origin is unclear. Thus, finding a solution within the effective theory compatible with experiments is far from the same as showing that such a solution is stable in string theory, to say nothing of whether it even exist. Without a string realization, there is neither a known ultraviolet completion of the effective action, nor any guarantee of its existence or consistency. The primary objective of this proposal is to deconstruct the string theory landscape, and determine what parts of it can be promoted to full-fledged string theory solutions, thus resolving the question of their consistency, and what parts are inconsistent. If the outcome of the project is that most of the phenomenologically interesting models are consistent, the landscape paradigm will be put on solid ground. Proving that most models are inconsistent would shatter it, weakening the case for a multiverse explanation of our universe, while restoring the quest for predictability in string theory. The most drastic possible outcome would be to show that none of the existing models survive consistency checks. Such a verdict would force us to search for more inventive alternatives, such as going away from the realm of geometry, and so this project will also pioneer the construction of a “non-geometric landscape”.

Mots-clés : string theory,string phenomenology,string compactifications,beyond standard model of particle physics,cosmological constant
Projet ERC : HEALIN (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : CERCA Institution — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CERCA;I-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 1448125.0 €

Despite its widespread use and popularity, life expectancy (LE) has two shortcomings. First, its definition only takes into consideration mortality levels, thus ignoring the health status of those who remain alive. Second, LE is an average that does not explain how length of life is distributed across the population. These limitations have generated two strands of research (i.e. the study of ‘health expectancies’ (HE) and ‘lifespan inequality’ (LI)) that, so far, have developed independently from each other. The overarching objective of the HEALIN project is to bring together these research avenues into a coherent whole to get a more comprehensive understanding of contemporary population health dynamics. To attain this goal, I put forward the new concept of ‘healthy lifespan inequality’ (HLI), which is designed to investigate the extent to which healthy lifespans are unequally distributed across the population. The HEALIN project will (i) investigate the trends and determinants of HLI, (ii) assess whether the specific ages and causes that drive changes in HLI are the same ones determining the changes in LE, HE and LI indicators, and (iii) investigate how these indicators behave across and within countries and socio-economic groups. In addition, the project aims at making innovative contributions to the measurement of co-morbidity and to our understanding on how the latter can in turn influence the measurement of health expectancy and healthy lifespan inequality. To attain these objectives, the project will develop path-breaking analytical methods inspired in the models applied for the study of inequality and multidimensional poverty. Besides traditional socio-economic and health data sources, the project will complementary draw from the vastly underutilized health registers for the entire population in Catalonia (7.5 million residents). Their huge size and micro-level design allow investigating trends in HLI and co-morbidity with unprecedented detail.

Mots-clés : life expectancy,health expectancy,lifespan inequality
Projet ERC : AGING MATTERS (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Erasmus University Rotterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : EUR
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Despite neuroscientific advances and innovative treatment efforts, for most people addiction remains chronic. Adolescence marks rapid surges in alcohol and cannabis addiction, but also remarkable recovery rates, as most adolescent addictions naturally resolve over time. Brain development holds an import key to understanding the brain’s recovery potential. However, the impact of age on the mechanisms underlying addiction is largely unknown. Capitalizing on adolescents’ unique socio-cognitive sensitivity and learning flexibility, my goal is to unravel common and unique mechanisms of addiction risk and resilience in adolescents and adults. At the core of my innovative developmental-translational research line is a 3-year longitudinal neuroimaging study in adolescent and adult alcohol and cannabis users. This study will uncover the predictive value of social learning flexibility, motivation, self-control and the brain systems underlying changes in use and problem severity over time. Using the same neuroimaging paradigm, causality will be evaluated in rats that start using alcohol and cannabis either during adolescence or adulthood. Finally, a third set of studies will focus on the development of new methods to capture the complex role of social context and learning in pulling adolescents towards and young adults away from alcohol and cannabis use. Ultimately, these studies will lead to a long-sought socio-cognitive developmental framework of addiction, including novel markers of risk and resilience and novel paradigms to study the role of social context and in addiction. My approach effectively addresses multiple research gaps at once and the theoretical and methodological advances made through this high risk-high gain proposal will not only advance addiction knowledge and treatment, but also set the stage for a new approach to solving psychopathology: an approach in which aging brain matter matters.

Mots-clés : addiction,brain development,neuroimaging,resilience,social cognition,motivation,self control,proteomics
Projet ERC : ResiBots (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 1499501.0 €

Despite over 50 years of research in robotics, most existing robots are far from being as resilient as the simplest animals: they are fragile machines that easily stop functioning in difficult conditions. The goal of this proposal is to radically change this situation by providing the algorithmic foundations for low-cost robots that can autonomously recover from unforeseen damages in a few minutes. The current approach to fault tolerance is inherited from safety-critical systems (e.g. spaceships or nuclear plants). It is inappropriate for low-cost autonomous robots because it relies on diagnostic procedures, which require expensive proprioceptive sensors, and contingency plans, which cannot cover all the possible situations that an autonomous robot can encounter. It is here contended that trial-and-error learning algorithms provide an alternate approach that does not require diagnostic, nor pre-defined contingency plans. In this project, we will develop and study a novel family of such learning algorithms that make it possible for autonomous robots to quickly discover compensatory behaviors. We will thus shed a new light on one of the most fundamental questions of robotics: how can a robot be as adaptive as an animal? The techniques developed in this project will substantially increase the lifespan of robots without increasing their cost and open new research avenues for adaptive machines.

Mots-clés : damage recovery,robot learning