Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ProPlantStress (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : Forschungszentrum Jülich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : FZJ
Type d'entité : Recherche
Financement ERC de l'entité : 1804663.0 €

Site-specific proteolytic processing is an irreversible post-translational protein modification that generates distinct protein species with new functions, interactions and subcellular locations. In plants, proteolytic processing regulates hormonal and stress signaling leading to adaptation of metabolic pathways and is implicated in plant-pathogen interactions. Despite their importance, proteolytic processes have largely been identified serendipitously, specific cleavage sites have rarely been identified and only a few of the hundreds of proteases encoded in plant genomes (>800 in Arabidopsis) have been linked to any substrates. Positional proteomics enables system-wide identification of proteolytic processing and protease substrate repertoires through quantitative determination of protein N- or C-termini. ProPlantStress will employ these approaches, which I co-developed during my postdoctoral research, to two linked abiotic and biotic stress conditions: i) Time-resolved mapping of chloroplast protein processing induced by high intensity light will reveal novel mechanisms of retrograde signal transduction, stress response and acclimation; ii) Profiling of protein processing triggered by pathogen recognition, combined with substrate identification for selected host and bacterial pathogen effector proteases will identify proteins with novel functions in plant immune responses and systemic signaling. Importantly, ProPlantStress will not merely catalogue termini and substrates: Mapping of cleavage sites to the protein domains and correlation with other modifications, such as phosphorylation, generates testable hypotheses on the function of processed protein species that will be examined in detail. ProPlantStress will thereby provide fundamental insights into proteolytic mechanisms underlying plant stress responses that are unattainable by other means. In the long term such knowledge is needed to develop new strategies for crop protection and mitigation of harvest loss.

Mots-clés : degradomics,proteolysis,proteolytic processing,plant stress responses,plant pathogen interactions,systemic acquired resistance,signaling crosstalk
Projet ERC : MemoSleep (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Fribourg — Pays : Suisse — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499565.0 €

Sleep is critical for optimal cognitive functioning and health. Sleep disturbances are highly frequent in our society and strongly influenced by cognitive factors, e.g. rumination, expectations and thoughts. However, the mechanism of how cognition influences sleep architecture is not yet understood. To explain how cognition influences sleep, I propose the “Memories-of-Sleep” (MemoSleep)-Hypothesis. Based on the theory of embodied cognition and evidence that memories are reactivated during sleep, the MemoSleep-Hypothesis makes the following assumptions: (1) Cognitions related to sleep/wake states are embodied. I will call them embodied sleep/wake memories. Embodied sleep/wake memories encompass not only their semantic meaning, but also their sensorimotor body representation. Thus, the mental representation of the word ‘wake’ is directly linked to our body sensation of wakefulness. (2) If embodied sleep/wake memories are activated before sleep, they will have a higher probability of being reactivated during sleep. (3) During sleep, increased reactivation of embodied sleep/wake memories activates associated body responses and thereby affects sleep architecture. Thus, increased reactivation of the mental representation of ‘wake’ will activate wake-related physiological responses and disrupt sleep. Here I aim at empirically testing these assumptions using brain imaging (high-density EEG, EEG/fMRI) and cognitive testing in humans. I will show that activation of embodied sleep/wake memories before and during sleep influences sleep architecture and affects post-sleep cognitive performance. In addition, I will apply these findings to the elderly and patients with sleep disorders. The results will greatly enhance our theoretical understanding of how cognition influences sleep. Furthermore, they will provide a solid basis for the development of effective cognitive interventions for sleep disorders, with a high potential to improve sleep and cognition also in every-day life.
Projet ERC : SLEEPCONTROL (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 922949.61 €

Sleep is essential for human and animal life and is broadly conserved. The nervous system induces sleep through the activation of sleep-active sleep-promoting neurons but the key mechanisms of sleep control remain to be elucidated. Recent work from my lab showed that the C. elegans nervous system contains a single sleep-active sleep-promoting neuron, called RIS, which is GABAergic and peptidergic as is its vertebrate counterpart. C. elegans shows sleep behavior and allows the easy combination of behavioral assays with functional neural imaging and genetics. Here I propose to study the single neuron RIS as a highly simplified model of a sleep-active neuron. This is a unique and novel approach to sleep research and my expertise on sleep behavior in C. elegans puts me into a pole position to study sleep. I will elucidate the molecular mechanism of activation of sleep-active neurons, analyze the mechanism of homeostasis of sleep-active neurons, and determine the molecular mechanisms by which sleep-active neurons induce sleep in the nervous system. I will combine transcriptional profiling of sleep-active neurons with physiological assays such as functional neural imaging, genetic screening, optogenetics, and functional molecular analysis of mutants. Using the highly simplified C. elegans model, I will boost sleep research and gain mechanistic insight into the regulation of sleep behavior through sleep-active neurons. This will be the first time that sleep-active neurons have been dissected in this way and I expect to identify novel conserved molecular and circuitry mechanisms. This work should provide the basis for understanding the more complex systems that control sleep in vertebrates and for understanding human sleep disorders.

Mots-clés : c  elegans,calcium imaging
Projet ERC : MicroDisco (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
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 : 1994500.0 €

Small-scale flow reactors for electro- and photochemistry support the shift in chemical manufacture towards green and sustainable processes based on renewable energy sources. However, the industrial application of these small-scale flow reactors is significantly limited by their currently achieved throughput and productivity. The MICRODISCO project aims to overcome these productivity limitations by exploiting the synergistic effect of ultrasound on intensified electro- and photochemical reactors. Specifically, we will gain a fundamental understanding of the underlying ultrasound physics and their interplay with reactor geometry, material and fluid properties, based on beyond state-of-the-art modeling and experiments (Objective 1). Subsequently, we will exploit this fundamental understanding to controllably excite ultrasound resonance modes to overcome species and electron/photon transport limitations in rationally designed intensified reactors. We will eliminate the diffusion limitation of electrochemical reactors for high-throughput self-supported organic synthesis by inducing active mixing via ultrasound resonance (Objective 2). Furthermore, we will increase light utilization and mass transfer in two-phase photochemical reactors by inducing the gas-liquid atomization phenomenon (i.e. to nebulize liquid droplets from the liquid slug into the illuminated gas bubble) via ultrasound resonance (Objective 3). The MICRODISCO project will provide fundamental understanding of ultrasound resonance modes and a theoretical tool for their prediction, leading to innovative and intensified electro- and photochemical reactors promoting green and sustainable chemistry.

Mots-clés : microfluidics,ultrasound,flow chemistry,mass transfer
Projet ERC : PROCONTRA (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : École polytechnique — Pays : France — Rôle : Partner
Acronyme de l'entité : X
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 18000.0 €

Smart contracts are formal agreements that take the form of computer programs. They are typically written down, and automatically executed, on blockchains. Smart-contract protocols are algorithms that describe how these contracts operate in multiparty settings. Due to the large number of potential applications, interest in this field has exploded in the last few years. Also, the PI has generated important results through his work in this area. The ambitious goal of PROCONTRA is to transfigure this emerging field into a mature science. Our main research hypothesis is that smart-contract protocols will be used in real life and many of them will strongly rely on advanced cryptographic techniques and will need to be developed using modeling methods from theoretical cryptography. We will work in this direction by proposing new solutions in this area, providing formal models and security proofs. Given the importance of these protocols, it is crucial to fully analyze their security before they are deployed in real life. Therefore, the first pillar of this project is to design a complete security model for analyzing them. The second pillar is to propose new smart-contract protocols and to extend the existing ones. Our protocols will be proven secure in the model we propose in the first pillar. This will be done using traditional “pen-and-paper” methods. However, the most important proofs will also be machine-checked using proof assistants. On a more theoretical side, we will also work on characterizing what tasks are in general achievable using smart contracts, and under what assumptions. Throughout the project, we will closely interact with the smart-contract practitioners, and with the industry, in order to understand what are the practically-relevant problems in this field and to ensure that the project’s outcome will have an impact beyond academia. This will also take a form of participation in the standardization efforts in this area.

Mots-clés : universal composability framework,multiparty computation protocols,smart contracts,blockchain
Projet ERC : FairSocialComputing (Horizon 2020, appel 2017, Advanced 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 : 2487500.0 €

Social computing represents a societal-scale symbiosis of humans and computational systems, where humans interact via and with computers, actively providing inputs to influence and being influenced by, the outputs of the computations. Recently, several concerns have been raised about the unfairness of social computations pervading our lives ranging from the potential for discrimination in machine learning based predictive analytics and implicit biases in online search and recommendations to their general lack of transparency on what sensitive data about users they use or how they use them. In this proposal, I propose ten fairness principles for social computations. They span across all three main categories of organizational justice, including distributive (fairness of the outcomes or ends of computations), procedural (fairness of the process or means of computations), and informational fairness (transparency of the outcomes and process of computations) and they cover a variety of unfairness perceptions about social computations. I describe the fundamental and novel technical challenges that arise when applying these principles to social computations. These challenges are related to operationalization (measurement), synthesis and analysis of fairness in computations. Tackling these requires applying methodologies from a number of sub-areas within CS, including learning, datamining, IR, game-theory, privacy, and distributed systems. I discuss our recent breakthroughs in tackling some of these challenges, particularly our idea of fairness constraints, a flexible mechanism that allows us to constrain learning models to synthesize fair computations that are non-discriminatory, the first of our ten principles. I outline our plans to build upon our results to tackle the challenges that arise from the other nine fairness principles. Successful execution of the proposal will provide the foundations for fair social computing in the future.

Mots-clés : social computing,computational social science,fairness,accountability,and transparency in ml
Projet ERC : HEALTHINEQ (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : University of Helsinki — Pays : Finlande — Rôle : PI
Acronyme de l'entité : UH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499422.0 €

Social inequalities in health are observed in all societies. These inequalities have grown markedly over the past 30 years, with those in less advantaged social positions currently expected to live 5–10 years less than those in more advantaged positions. The study aims to establish the root causes of these inequalities by (1) assessing the drivers of long-term changes in health inequalities and establishing the contribution of family factors and macro-level social and economic conditions to these changes; (2) examining multigenerational interdependencies of social position and health in up to four generations; (3) estimating the causal effects of social position on health by employing molecular genetic information and assessing whether genetic associations are mediated or modified by social position; (4) evaluating the generalisability of explanations of social inequalities in health through international comparative research. The study will integrate research scattered in multiple disciplines by establishing how family background – both social as experienced through living conditions and social resources in families, and genetic as inherited from biological parents – affects health and social disadvantage within and across generations. The project will go beyond standard observational research through new conceptual insight and by using a unique combination of longitudinal register-based and genetically informed data sources. We will take advantage of natural experiments – educational and alcohol policy reforms and rapid economic changes – to identify pivotal social processes in the production of health inequalities. Our results will be ground-breaking because we will establish how family and genetic factors are intertwined with individual social characteristics and how they manifest in health outcomes in different macro-level social conditions. The power to test causal hypotheses will advance science and help devise policies to reduce health inequalities.

Mots-clés : social epidemiology,genetic epidemiology
Projet ERC : FACESYNTAX (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : University of Glasgow — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1490050.0 €

Social interactions are critical to all societies. One of the most powerful tools for social interaction is the face – a complex system comprising variations of movement (expressions), morphology (shape/structure) and complexion (color/texture). Consequently, the face can elicit myriad rapid social judgments (e.g. personality, emotion, group membership, age, health, social status) with significant consequences (e.g. sentencing/voting decisions, social isolation, job offers). Yet, little is known about how the complex, dynamic face transmits the myriad messages that regulate social interactions in different cultures, how these complex face signals map onto psychological processes (e.g. categorical/dimensional perception) or which signals facilitate or hinder cross-culture communication. This is largely due to fragmented research on social concepts (mental states, personality, emotions), face signals (morphology, movements, complexion) and culture, which, consequently, has overlooked a possible latent algebraic, syntactical structure to social face signals across cultures. My own work hints at such a structure. My ambitious program will unify these fragments to derive the first generative, algebraic and syntactical model of social face signals using innovative methods combining social/cultural psychology, 3D dynamic computer graphics, vision science psychophysical methods, and mathematical psychology. It will thus test and validate a new theoretical framework of social face signals that will unite both categorical/dimensional and universal/culture-specific accounts of social face perception. This framework is highly relevant in the context of globalization and cultural integration where social communication using virtual agents is integral to modern society. It is thus imperative to equip digital agents with the tools to flexibly generate socially and culturally sophisticated face signals. FACESYNTAX will thus transfer the generative model to social robotics.

Mots-clés : social communication,face perception,culture,psychophysics,modelling,dynamic signals
Projet ERC : Becoming Social (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Bangor University — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : BU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Social interactions are multifaceted and subtle, yet we can almost instantaneously discern if two people are cooperating or competing, flirting or fighting, or helping or hindering each other. Surprisingly, the development and brain basis of this remarkable ability has remained largely unexplored. At the same time, understanding how we develop the ability to process and use social information from other people is widely recognized as a core challenge facing developmental cognitive neuroscience. The Becoming Social project meets this challenge by proposing the most complete investigation to date of the development of the behavioural and neurobiological systems that support complex social perception. To achieve this, we first systematically map how the social interactions we observe are coded in the brain by testing typical adults. Next, we investigate developmental change both behaviourally and neurally during a key stage in social development in typically developing children. Finally, we explore whether social interaction perception is clinically relevant by investigating it developmentally in autism spectrum disorder. The Becoming Social project is expected to lead to a novel conception of the neurocognitive architecture supporting the perception of social interactions. In addition, neuroimaging and behavioural tasks measured longitudinally during development will allow us to determine how individual differences in brain and behaviour are causally related to real-world social ability and social learning. The planned studies as well as those generated during the project will enable the Becoming Social team to become a world-leading group bridging social cognition, neuroscience and developmental psychology.

Mots-clés : social perception,social cognition,social development
Projet ERC : chemech (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
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 : 1676106.28 €

Soft materials are irreplaceable in engineering applications where large reversible deformations are needed, and in life sciences to mimic ever more closely or replace a variety of living tissues. While mechanical strength may not be essential for all applications, excessive brittleness is a strong limitation. Yet predicting if a soft material will be tough or brittle from its molecular composition or structure relies on empirical concepts due to the lack of proper tools to detect the damage occurring to the material before it breaks. Taking advantage of the recent advances in materials science and mechanochemistry, we propose a ground-breaking method to investigate the mechanisms of fracture of tough soft materials. To achieve this objective we will use a series of model materials containing a variable population of internal sacrificial bonds that break before the material fails macroscopically, and use a combination of advanced characterization techniques and molecular probes to map stress, strain, bond breakage and structure in a region ~100 µm in size ahead of the propagating crack. By using mechanoluminescent and mechanophore molecules incorporated in the model material in selected positions, confocal laser microscopy, digital image correlation and small-angle X-ray scattering we will gain an unprecedented molecular understanding of where and when bonds break as the material fails and the crack propagates, and will then be able to establish a direct relation between the architecture of soft polymer networks and their fracture energy, leading to a new molecular and multi-scale vision of macroscopic fracture of soft materials. Such advances will be invaluable to guide materials chemists to design and develop better and more finely tuned soft but tough and sometimes self-healing materials to replace living tissues (in bio engineering) and make lightweight tough and flexible parts for energy efficient transport.

Mots-clés : fracture,mechanical properties,polymer physics