Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PLANT BIOACOUSTICS (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université de Tel Aviv — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

The communication of plants with their environment is crucial for their survival. Plants are known to use light, odours, and touch to communicate with other plants, with pollinators, seed dispersers and herbivores. However, one sensory modality – acoustic communication – is almost unexplored in plants, despite its potential adaptive value. This is the focus of the current proposal. Our long-term goal is to understand the roles of acoustic communication in the life of plants: what plants hear, and what they “say”. The proposed research builds on recent results that strongly suggest the use of airborne sound in plants: We have demonstrated that flowers increase their nectar concentration within minutes in response to the sound of a bee’s wingbeat. Furthermore, we have shown that different species of plants emit brief ultrasonic signals with acoustic characteristics that vary under different conditions. Towards general understanding of plant bioacoustics we will investigate: 1.Plant hearing. We will investigate plant responses to pollinator sounds to uncover their temporal dynamics, mechanism, and evolution. 2.Plant sound emission. We will record the sounds emitted by different plants under different conditions, and use advanced AI to interpret these sounds. 3.Functionality of plant sounds. We will test if and when other organisms – both plants and animals - response to plant sounds, and the potential adaptive value of these responses. The proposed project has the potential to revolutionize our understanding of plants and plant communication. Our results are expected to open entirely new avenues of research such as the evolution of sound communication by plants, and the bio-mechanics of sound emission and sound reception in plants. Our results might also have great applicative implications in precision agriculture, including remote plant monitoring and functional sound emission. These may play a role in fighting the global food-security problem and pollination crisis.

Mots-clés : sound,airborne,signaling,communication,pollination,nectar,plant pollinator interactions,vibration,drought stress,machine learning,phytoacoustics
Projet ERC : HEALTHINEQ (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : London School of Economics and Political Science — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : LSE
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2439999.5 €

HEALTHINEQ addresses the persistent and complex issue of health inequalities across socio-economic groups. Despite significant efforts in healthcare and public policy, these disparities remain a critical challenge. The proposal aims to explore and mitigate these inequalities by investigating the underlying mechanisms, from social determinants to disparities in healthcare access and technology. HEALTHINEQ aims to achieve this through three key objectives: 1/ Measurement and Data Integration: HEALTHINEQ integrates detailed health records and administrative data at a population scale in the Netherlands and Sweden and develops comprehensive, dynamic measures of health. This exceptional data allows for robust analysis of gaps in health and healthcare, how they arise over the life-course and interact with different socio-economic factors. 2/ Mechanism Exploration: HEALTHINEQ leverages the rich data in combination with advanced empirical methods in a comprehensive framework. This will provide a clear understanding of the dynamic mechanisms involved, distinguishing underlying drivers from mediators, and differentiating between the incidence versus survival of diseases. The project will examine each mechanism’s relationship with prevention, detection, and treatment policies, as well as with health insurance and healthcare innovation. 3/ Policy Impact: HEALTHINEQ aims to inform more effective and equitable health policies. By offering actionable recommendations and influencing high-level debates, it seeks to support data-driven policy reforms to address and mitigate health inequalities. In summary, HEALTHINEQ represents a significant advancement in the study of health inequalities, offering a comprehensive and innovative approach to understanding and addressing this critical issue. The project’s focus on population-scale data and health measurement, combined with frontier empirical methods, positions it to make a substantial impact on both academic research and health policy.

Mots-clés : inequality,health,healthcare,health insurance,behavioral anomalies,prevention,incidence vs treatment,screening,prediction models,health dynamics,healthcare innovation,measurement,registry data
Projet ERC : TraumaNeuroInsight (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université de Tel Aviv — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499750.0 €

Exposure to a traumatic event can induce psycho-physiological reactions and symptoms that in most people recede over time. A minority of trauma-exposed individuals develop posttraumatic stress disorder (PTSD), characterized by severe functional and emotional impairment. The global burden of PTSD is estimated in the hundreds of billions of Euros and millions of years lived with disability. Individual differences in neurobiological vulnerability to traumatic stress have been studied extensively, yet the impact of neuroscience on clinical application is minimal. The proposed work aims to address this gap using three work packages (WPs). WP1 will establish a detailed open-access database to study the impact of traumatic stress on brain structure/function connectome: 1000 participants with PTSD, 1000 trauma-exposed healthy, 1000 non-exposed. WP2 is a longitudinal study of the effects of trauma exposure. It will delineate long-term trajectories of stress-related symptoms and corresponding connectome dynamics. Building on already collected data from 579 veterans who were followed over four years, starting with a pre-exposure baseline, we will add two new data points, at 7- and 9-year post-exposure, to reveal long-term adaptation patterns. WP3 is a 3-armed randomized controlled trial to test the impact of MRI-guided neurostimulation of cortico-hippocampal networks on brain connectivity patterns and severity of memory symptoms. We target cortico-hippocampal connections with broad impact on cortical circuitry, consistent with our focus on whole-brain connectome correlates. Moving beyond separate analyses of brain structure and function in relation to a heterogeneous definition of PTSD, we will use combined structure/function modeling in relation to specific symptoms. Together the proposed work is expected to redetermine the transaction between neuroscience and clinical research in relation to trauma psychopathology.

Mots-clés : traumatic stress,ptsd,mri
Projet ERC : EACTP (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université de Tel Aviv — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2335000.0 €

This research proposal will address fundamental problems concerning the complexity of computing and manipulating polynomials. For example, consider the following questions:  1. What is the complexity of computing the total weight of perfect matchings of a weighted graph? 2. Is there an efficient deterministic parallel algorithm that determines whether a graph has a perfect matching? 3. Is approximation much easier than exact computation? 4. How many EPR pairs can we distill from a given quantum state?  These seemingly unrelated questions represent some of the most important and challenging open problems in theoretical computer science: the first is the algebraic analog of the famous P vs. NP problem. The second question amounts to asking whether a symbolic matrix associated with the graph has full rank. Parallel randomized algorithms for computing this rank are known, but not deterministic ones. This is an instance of the polynomial identity testing (PIT) problem, the most fundamental algebraic derandomization problem. The third question asks about the relation between a complexity class and its closure, which lies at the heart of the Geometric Complexity Theory (GCT) program. The last question concerns the subrank of a tensor representing the given quantum state. Problems related to rank of tensors are at the heart of both algebraic complexity and quantum information theory.  Recent years have seen tremendous advance in our understanding of algebraic computations with new lower bounds, new PIT algorithms and with increasing connections to other branches of computer science and mathematics discovered. Results proved by the PI play an important role in all of these advances.  This project aims to study these and related problems and to develop new methods for solving them. Making progress on any of these problems will constitute a significant breakthrough.

Mots-clés : algebraic complexity,polynomials,tensors,arithmetic circuits,quantum entanglement,gct,vp,vnp,algebraic branching programs,complexity,sparse polynomials
Projet ERC : Meta2Zyme (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Université de Tel Aviv — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2776000.0 €

While enzymes are highly useful in various applications, their limited operational stability and production costs have led to an extensive search for stable catalytic agents that will retain the efficiency, specificity, and environmental-friendliness of natural enzymes. Despite extensive efforts, there is still an unmet need for improved enzyme mimics and novel concepts to discover and optimize such agents. Inspired by the catalytic activity of amyloids and the formation of amyloid-like assemblies by metabolites, our group pioneered the development of metabolite-metal co-assemblies that mimic the catalytic function of common metalloenzymes with remarkably safe and simple building blocks. Intriguingly, the assemblies exhibit high efficiency and exceptional robustness, even under extreme conditions of temperature, pH, and salinity that are impractical for enzymes. Yet, we had only explored a minute fraction of the chemical space as present in natural enzymes. In this project, we propose the first-ever systematic exploration of a vast combinatorial matrix consisting of metabolites and metal ions that co-assemble into unique supramolecular catalytic active sites, analogous to the organization of covalently bound residues and metal ions in conventional enzymes. The proposed work will involve advanced experimental and computational techniques, including artificial intelligence-driven predictive modelling based on functional, structural, and mechanistic data, to identify, optimize, and test the new nanozymes in various relevant application scenarios. Through this comprehensive study, we will not only identify and characterize highly efficient nanozymes, but also gain fundamental insights into the evolution of natural enzymes and design principles of catalytic nanomaterials. This high-risk/high-gain project has the potential to revolutionize the mimicking of enzymatic catalysis and develop robust, highly efficient, cost-effective, and eco-friendly catalytic assemblies.

Mots-clés : self assembly,bio inspired materials,nanotechnology,molecular recognition,metabolite metal association,enzyme mimicking,catalysis
Projet ERC : multiCODE (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Vlaams Instituut voor Biotechnologie — Pays : Belgique — Rôle : PI
Acronyme de l'entité : VIB
Type d'entité : Recherche
Financement ERC de l'entité : 2498937.0 €

Multicellular plants control the fine-grained expression of thousands of genes during growth, development, and in response to external stimuli. While gene expression varies strongly between different organs and tissues, how this specificity is encoded in the genome is largely unknown. Although various regulatory DNA sequences and sequence-specific transcription factors controlling diverse transcriptional responses have been described, the combinatorial nature of the regulatory code makes the application of rational approaches to learn and predict context-specific gene expression challenging. This is a major obstacle towards engineering plant promoters with predictable and tuneable expression.  multiCODE’s aim is uniting single-cell genomics, explainable artificial intelligence (xAI), and synthetic promoter engineering, to efficiently learn and validate regulatory sequences controlling gene expression in plants. Based on high-resolution single-cell gene expression profiling in the model Arabidopsis and the crop Brassica rapa, xAI models will be built to predict gene expression in leaves under control and stress conditions while at the same time identifying the underlying regulatory DNA sequences and syntax. The power of these predictive models will be validated by exploiting inter- and intra-species sequence variation, revealing the evolutionary conservation of the regulatory code. Furthermore, a novel multi-tier synthetic promoter engineering approach will be used to experimentally validate, directly in plants, the learned regulatory code in a high-throughput manner. By combining the power of advanced computational and experimental methods, I will identify novel regulatory sequences and design novel synthetic promoters controlling gene expression in complex cellular contexts. This represents a crucial step towards a comprehensive understanding of gene regulation and will significantly contribute to developing stress-resilient crops.

Mots-clés : gene regulation,synthetic promoters,plant biotechnology,deep learning,single cell genomics
Projet ERC : OxyPlanets (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : Université de Versailles Saint-Quentin-en-Yvelines — Pays : France — Rôle : PI
Acronyme de l'entité : UVSQ
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2412601.0 €

Among the thousands of extrasolar planets discovered, Earth-like objects focus our attention to seek new habitable worlds. Eleven Earth-sized planets have already been discovered in the Habitable Zone (HZ) of their host-star, including three in the TRAPPIST-1 planetary system. Deciphering their atmospheres is the challenge of the next decade in exoplanetary science, stressing out urgent needs in fundamental data for these objects.  My aim is to investigate how the atmospheric organic reservoir forms and evolves in the frame of humid exoplanetary atmospheres in Habitable Zone. I will also quantify the impact of theses processes on the climate and on the potential for prebiotic chemistry on these planets. I propose to consider the role of organic aerosols as prebio-signature: those are nanoparticles chemically produced in the atmosphere. I will address the capacity of exo-Earths atmospheres to produce organic aerosols in various oxidative conditions, and their further physical and chemical interactions with atmospheric water. To tackle these questions, I will combine experiments and models to discover the reactivity that occurs in atmospheres within an extensive range of oxidation conditions. I will experimentally determine the physical properties of the aerosols, and then model their radiative impact and their propensity to generate clouds in the atmosphere. I will also experimentally identify the prebiotic molecules composing the aerosols that dissolve into clouds. This transfer from the dry organic reservoir towards liquid water is indeed critical for the emergence of life.  The ERC-AdG Oxyplanets project will contribute to interpret and suggest observations for the future NASA-JWST and ESA-ARIEL space missions. Furthermore, it will reinforce our knowledge of the habitability of Earth-like exo-worlds, potentially reappraising the conditions for life to appear on the early-Earth.
Projet ERC : PREFER (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Human Mobility, Environment, and Space
Entité participante : Université de Versailles Saint-Quentin-en-Yvelines — Pays : France — Rôle : PI
Acronyme de l'entité : UVSQ
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2485314.0 €

The main objective of the PREFER project is to open the scientific debate on existential risk to empirical enquiry. The PREFER team will identify how lay ethics (the ethics of ordinary people) manifest themselves in non-Western communities faced with extreme threat. Local terminal risks due to the collapse of regional ecosystems will serve as proxies for existential risks. Thus, this pioneering project will obtain, for the first time, empirical evidence on how ordinary humans evaluate and cope with real-life terminal situations. Existential risks concern humanity as a whole: it is essential to add to the variety and number of voices heard in scientific deliberations. A broader discourse on existential risk will contribute to better governance and decision-making around existential risks. The PREFER team will conduct field work in two diverse geographical areas whose inhabitants are experiencing the collapse of life-sustaining ecosystems: the Arctic and the Mekong Delta. Three communities in each area will serve as case studies. Preparatory fieldwork has revealed that members are aware of the terminal threat and have expressed fears that they are facing the end of the life they know. Community transdisciplinary research (the co-production of knowledge with and for local communities) will be accompanied by ethnographic work. Data will be collected in the form of narratives which will be analyzed as sources of information on how local communities appraise the multiple dimensions of local terminal risk, including descriptions, the meanings drawn from these and involvement in impact mitigation actions. These results will then be applied to existential risks, all the while analyzing the appositeness of the PREFER proxy-based approach. Finally, although the main focus is on widening the discourse on existential risks, PREFER will also contribute to the urgent empirical analysis of terminality in the face of collapsing regional ecosystems.

Mots-clés : lay ethics,existential risk,local terminal risk,transdiscipinary research
Projet ERC : MIGMOBS (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Institut technologique de Buenos Aires — Pays : Argentine — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 117500.0 €

MIGMOBS investigates how borders and hierarchies are maintained between “the West and the Rest”, even as those who are internationally mobile sometimes succeed in challenging the “birthright lottery” - i.e. that citizenship at birth most determines someone’s chances in life. It asks: How does changing categorisation of subordinate populations worldwide in terms of “migration”, “free movement”, and “minorities” relate to these in- and between- country inequalities? It echoes critical migration, mobilities and borders scholars who argue that late capitalism in liberal democracies continues to advance through an ever more sophisticated differentiation and management of population – at the border as well as internal to states. Such work, though, has not adequately examined variation regionally, or across historical shifts in political economy: from post-war liberalism, through neoliberalism, to the era of COVID and beyond. MIGMOBS thus explores in unprecedented empirical breadth and detail how states reproduce sovereign power in an otherwise porous world: selecting and extracting wanted or recognised movers as “immigrants”, brutally excluding many other “migrants”, while simultaneously rendering fluid and untroubling a vast range of banal “mobilities” such as tourism and business travel. Mapping physical, virtual and non-human mobilities, the project details demographic and social connections over time between 21 states. This quantitative comparative historical work underpins co-productive ethnographic case studies rethinking a range of archetypal “migration systems” in and from Europe, Africa, Asia and South America. These investigate how subordinate populations resist the categories, statuses and borders imposed upon them. With the pandemic’s impact on border crossings and transactions, new modes of classification and accreditation suggest an increasingly precise biometric control of movement and behaviour: a new phase of late capitalism I call “viral liberalism”.

Mots-clés : migration,mobilities,global inequality,inequalities,development,borders,diversity,liberalism,racism,globalisation,governmentality,transnationalism,decolonial thought,political demography,mixed methods
Projet ERC : TriCatApp (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Université de Milan — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1042645.0 €

There are two components to this project. (1) Develop and extend the striking new theory, created by the PI in the last few years, which studies triangulated categories via metrics and approximations. (2) Build on very recent work to better understand which functors are Fourier-Mukai and which aren't. In the case of (1), the novel idea of appropriately using metrics has already allowed the PI to prove several difficult conjectures, the most recent just a few weeks ago. The potential of the new theory is immense, and this project aims to extend the scope of the methods and apply them widely. The project also aims to work out the implications of a surprising theorem proved by the methods, which shows that the derived category of perfect complexes and the bounded derived category of coherent sheaves are constructible from each other, as triangulated categories, by an explicit recipe. This theorem flies in the face of accepted wisdom, which viewed the two categories as totally different. Thus a whole body of work, analysing the many differences between these derived categories, needs to be carefully revisited and reconsidered in the light of the new construction. The Fourier-Mukai transforms of (2) have a long and venerable history, with beautiful work by many authors. But there were novel techniques introduced in a couple of recent articles, and the project plans to deploy them more widely. The aim is for a breakthrough in the area, leading to a better understanding of which exact functors are Fourier-Mukai and which aren't.

Mots-clés : derived categories,triangulated categories,enhancements