Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DECODE-DKD (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University Hospital Aachen — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : UKA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1783319.0 €

Diabetic kidney disease (DKD) is a rapidly growing worldwide health problem and represents one of the most serious threats in current medicine. DKD is the most common cause of chronic kidney disease (CKD) with 20% of DKD patients progressing to end-stage renal disease, which is associated with tremendously increased morbidity and mortality. The pathophysiology of DKD is complex, incompletely understood and the number of treatment options is low. The vision of DECODE-DKD is to utilize a patient-centric research approach to identify novel pathways and druggable targets in patients suffering from DKD. Concrete objectives are: (1) to establish a spatially resolved multi-omic landscape of human DKD; (2) to dissect and identify therapeutic pathways and signalling networks for novel drug target identification; (3) to incorporate patient-derived in-vitro models for target validation. It is envisaged that novel spatial and single-cell multi-omic technologies will generate a blueprint and predictive model of DKD. This unbiased map will serve to generate testable hypotheses with spatial and temporal coordinates at single-cell resolution. To identify disease-relevant pathways and novel drugable targets in-vitro and in-vivo genome editing approaches will be employed combined with high-throughput screens. In-vitro assays with human-derived kidney organoids will be used to screen potential compounds facilitating the development of novel therapeutics. This highly ambitious interdisciplinary proposal requires the expertise of biomedical engineers, computational biologists, biomedical researchers and physician-scientists. The generated knowledge and outcomes of DECODE-DKD will - alone and especially together - be truly transformative and provide an incremental step forward towards novel drug targets and precision medicine for the treatment of diabetic kidney disease using a systems medicine approach.

Mots-clés : diabetic kidney disease,functional genomics,spatial multi comics,micro fluidic engineering,crispr epigenome editing,organoids
Projet ERC : HEATPULSE (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université libre d'Amsterdam — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

The climate catastrophe urgently calls for greening and intensifying chemical reactors. Most chemical reactors use catalysts to speed up reactions, but their operation at steady-state temperature impairs rate, selectivity, and energy efficiency. To go beyond these limitations, applying short heat pulses theoretically leads to >100× higher reaction yield, lower energy use, and a controlled product distribution. However, pulsed heating has remained out of reach because it is hard to heat catalysts selectively and fast enough.  I break this paradigm and take control of dynamic thermo-catalysis by using light pulses and robust “plasmonic” materials that convert light to heat with nanoscale specificity. HEATPULSE comprises three work packages that tackle three challenges: (1) kinetics: modulate pulse timing for controlling reaction rate and selectivity, (2) localization: confine heat at thermal hotspots to boost energy efficiency, and (3) stability and performance: access high peak reaction rates by developing temperature-stable pulsed photocatalysts. Ground-breaking innovations: (1) Access to a normally unreachable reaction landscape, with dynamic tunability of catalyst activity and selectivity; (2) Thermal hotspots break the limit of nanoscale heating and reach 3× higher peak temperatures with exponentially enhanced rates; (3) Metal nitride nano-arrays integrated with single-atom catalysts grant thermal stability beyond 1000 °C.  HEATPULSE represents a revolution in green reactor technology by shifting from burning fossil fuels to heat-pulsing with light, powered by renewables. The project will lead to the new field of “photocatalysis beyond the steady-state” at the crossroads of catalysis, nanophotonics, and materials science. With an accomplished track record in nanoscale light-driven chemistry, and as a pioneer in the field of pulsed catalysis at both experimental and theoretical level, I am uniquely suited to unlock the full potential of pulsed photothermal catal

Mots-clés : plasmonics,photocatalysis,materials science,alternative plasmonic materials,nanoscale heat transfer,pulsed lasers
Projet ERC : PIRO (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université libre d'Amsterdam — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1937138.0 €

Molecules are the fundamental building blocks of life: disease is intrinsically linked to molecular malfunction and, sometimes, a tiny molecular error in a single cell can kill an organism. Drugs, such as antibiotics, are designed to protect us: they rid us of pathogens by disrupting their molecular machinery. If unsuccessful, surviving bacteria might adapt to evade future attacks and a few resistant bacteria can cause great damage. Everything mentioned above relies on specific molecular changes. A technique that could rapidly visualise them holds great promise: it would allow us to specifically target this one deadly cancer cell or adopt antibiotics treatment before resistance emerges. Vibrational imaging, which combines spatial cues with molecular resolution, is the prime-candidate for revealing this molecular stand-off: Spontaneous Raman readily acquires broadband spectra but is too slow to interrogate large samples. Coherent Raman can measure them but lacks spectral resolution. Finally, Fourier transform infrared microscopy combines spectral resolution and speed but its spatial resolution is insufficient. PIRO promises to deliver the necessary tool for the job by combining concepts from nonlinear ultrafast spectroscopy and digital holography. PIRO implements a novel vibrational imaging platform: a phototransient infrared holographic microscope (PIROscope). The PIROscope, inspired by our recently introduced ultrafast holographic microscope, combines femtosecond IR-excitation with visible readout to, ultimately, retrieve spectrally resolved quantitative images with an unprecedented combination of imaging speed, spectral observation window and spatial-resolution. During PIRO we will implement the PIROscope and validate it for biomedical imaging. We will then use our edge over the state-of-the-art to take first steps towards PIRO-based diagnostics by high-resolution visualising breast cancer tissue and the metabolic activity of antibiotics-treated bacteria.

Mots-clés : ultrafast vibrational spectroscopy,digital holography,photothermal imaging,vibrational imaging,quantitative phase imaging,ir spectroscopy
Projet ERC : EUROTYPES (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Université de Leyde — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Cultural stereotypes are often present in the political and media discourse on European Union (EU) governance: e.g., the lazy Greeks, the tax-dodging Italians, the stingy Dutch, and so forth. Especially when stereotypes are negative, they create conflict between national governments, fuel Euroscepticism among voters, and can lead to the discrimination of citizens or Member States. Yet while stereotypes have been studied in political rhetoric and media coverage, we know little about their impact on the behaviour of national and EU officials. To address this gap, EUROTYPES sets out to investigate how cultural stereotypes impact cooperation and effectiveness in contemporary EU governance.  The project is the first of its kind because it studies stereotypes among civil servants as opposed to political elites in the EU, who often use stereotypes strategically for electoral gains. The focus is on multi-level policy enforcement, a new phenomenon in European integration which captures the participation of national and EU civil servants in joint ‘on-the-ground’ operations in border control, law enforcement cooperation, financial supervision, etc. Since they are not socialized in Brussels or running for office, such officials are much more likely to (genuinely) display cultural stereotypes.  EUROTYPES pushes the frontiers of knowledge in several directions. First, it applies an original version of qualitative content analysis to identify stereotypes relevant for multi-level policy enforcement. Second, it uses recent developments in experimental research to capture the role of stereotypes among civil servants. Theoretically, the project constructs an innovative account of stereotypes as habits and positions them vis-à-vis other explanations of political behaviour (interests, norms, ideas). The goal is to show whether and how stereotypes hinder EU cooperation and, in the long run, establish a comprehensive research agenda on cultural stereotypes in transnational bureaucracies.

Mots-clés : cultural stereotypes european union multi level governance eu policy implementation bureaucratic behaviour eu agencies migration police cooperation banking supervision
Projet ERC : HOPE (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
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 : 2498856.0 €

Earthquakes are spectacular natural disasters, as exemplified by the 2004 Sumatra and 2011 Tohoku-Oki earthquakes. Predicting earthquakes remains one of the biggest societal challenges in natural science. This research project will attempt answering the following question: How predictable are earthquakes? We propose a multidisciplinary approach articulated around three main axes: (i) the deterministic predictability of earthquakes in simple, homogeneous faults, studied by reproducing and understanding earthquake phenomena in the laboratory, (ii) the deterministic predictability of earthquakes in complex, heterogeneous faults, studied by laboratory experiments producing multiple earthquake cycles on faults with controlled heterogeneities and (iii) the statistical predictability of earthquakes, studied by forecasting the spatial distribution of experimental seismicity using machine learning. At the core of this project lies the development of a new dedicated experimental setup to generate multiple earthquake cycles along a fault with prescribed complex geometry and rheology. With this new capability, we will conduct a threefold experimental program to: (i) compute the complete energy budget of laboratory earthquakes, (ii) study the sensitivity of rupture nucleation, propagation and arrest to heterogeneities, and (iii) study the effect of heterogeneities on the relation between fault seismic coupling and seismicity. Our work will provide insights for earthquake hazard mitigation, constrain the physics underlying ubiquitously observed seismological statistical laws (Omori, Gutenberg-Richter) and test seismic slip inversion and dynamic rupture modelling techniques in unprecedented data sets on rock fracture dynamics in experiments that mimic field conditions. The new infrastructure we plan to install will reproduce earthquake rupture processes with a spatio-temporal imaging resolution never achieved before.

Mots-clés : laboratory earthquakes,dynamic rupture,heterogeneous faults,spatial and temporal forecasting
Projet ERC : NEURO-SOCIETY (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
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 : 1396400.0 €

In social species, peers represent a major part of the external environment and adaptation to the environment requires adaptation to peers. One striking example is that not only other species can be deadly predators, but members from our own society can pose a deadly threat to us. On the other hand, not only family members can be our allies but also friends we choose from non-kin related group members. This matter of fact exemplifies the importance of tracking others and their relations, and possessing a structured knowledge about our societies. Primates, including humans and monkeys, spend most of their time watching others. While several neural circuits for social perception have been unraveled in their brains, we don’t know how neural circuits further transform social percepts into a meaningful set of social concepts used spontaneously to represent social networks. This question calls for an investigation at multiple levels. An exploratory approach at the whole brain level, using functional magnetic resonance imaging (fMRI) in monkeys and humans, will enable us to chart the brain territories involved in processing social concepts of increasing levels of abstraction, whereby concepts about individuals are less abstract than concepts about relationships, which are in turn less abstract than concepts about social networks topology. Next, a nailed down approach to the level of neurons, using fMRI-guided neurophysiology, will enable us to understand the neuronal network mechanisms by which the transformation from multi-sensory social percepts to social concepts is implemented. Finally, exploiting real-world social knowledge of semi-free ranging monkeys, will enable us to track the encoding of social network topology by neuronal networks. Understanding how neural circuits and single-neurons within these circuits are encoding social networks will provide fundamental mechanistic insights into the toolkit for smoothly maneuvering our primate societies.

Mots-clés : non human primates monkey fmri neurophysiology faces social interactions social networks multi sensory processing neuroethology
Projet ERC : ORGANDICT (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Institute for Employment Research (IAB) of the Federal Employment Agency (BA) — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : IAB
Type d'entité : Recherche
Financement ERC de l'entité : 106730.0 €

The objective of my proposal is to push the frontier of our understanding of how the adoption of information and communication technologies (ICT) affects the internal organization of firms and thus firm productivity, employees’ careers and wages; how ICT adoption affects the organization of firms’ global value chains (GVC) and thus domestic employee outcomes; and how ICT adoption affects the foreign sourcing of innovation and thus domestic innovation.  Existing research gives only partial answers to these questions as it provides limited insights into the economic mechanisms behind the effects of ICT adoption and the organization of GVC. Research is impeded by lack of data with exhaustive information on ICT, GVC, and firm and employee outcomes.  My proposal will change that. I will assemble novel, comprehensive data sets with specific information on firms’ ICT use, GVC, balance sheets, and patents, as well as all employees’ characteristics, tasks, and wages. I will break new ground by developing theory and conducting theory-based empirical analyses that both identify causal effects and shed light on the economic mechanisms behind them.  My proposal consists of three parts. Part 1 exploits unique features of my data to study how ICT adoption induces firms to reorganize employees. I will analyse changes to task complexity and autonomy, careers and wages within employees over time to explore complementarities between higher availability of information due to ICT and employee knowledge.  Part 2 quantifies the effect of ICT adoption on offshoring, and, for the first time, studies how ICT adoption and offshoring jointly affect the task complexity and autonomy, careers and wages of employees, testing the predictions of task-based models.  Part 3 evaluates the effect of ICT adoption on offshoring of research and development (R&D), a key determinant of growth, and derives and tests novel conditions under which foreign R&D complements or substitutes domestic innovation.

Mots-clés : ict adoption firm organization global value chains multinational firms employment wages tasks corporate innovation productivity
Projet ERC : CHORAL (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Organisation des Nations unies pour l'éducation, la science et la culture — Pays : France — Rôle : PI
Acronyme de l'entité : Unesco
Type d'entité : Recherche
Financement ERC de l'entité : 1280750.0 €

Rich internal representations of complex data are crucial to the predictive power of neural networks. Unfortunately, current statistical analyses are restricted to over-simplified networks, whose representations (i.e., weight matrices) are either random, and/or project the data in comparatively very large or very low dimensional spaces; in many applications the situation is very different. The modelisation of realistic data is another issue. There is an urgent need to reconcile theory and practice.  Based on a synergy of the mathematical physics of spin glasses, matrix-models from physics, and information and random matrix theory, CHORAL’s statistical framework will delimit computational gaps in the learning, from structured data, of much more realistic models of neural networks. These gaps will quantify the discrepancy between:  (i) the statistical cost of learning good representations, i.e., the minimal amount of training data required to reach a satisfactory predictive performance; (ii) the cost of efficiency, i.e., the amount of data needed when learning using tractable algorithms, such as approximate message-passing and noisy gradient descents. Comparing these costs will quantify when learning is computationally hard or not.  To achieve this, CHORAL will first focus on dictionary learning, another essential task of representation learning, and then move on to multi-layer neural networks, which can be thought of as concatenated dictionary learning problems.  CHORAL’s ambitious program, by defining benchmarks for algorithms used in virtually all fields of science and technology will have a direct practical impact. Equally important will be its conceptual impact: the study of information processing systems has become a major source of inspiration for mathematics.

Mots-clés : high dimensional inference theory of neural networks spin glasses disordered systems random matrix theory matrix models information theory approximate message passing algorithm noisy gradient descents signal processing computational gaps
Projet ERC : MarmOTChat (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
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 : 1398750.0 €

Primate social interactions rely heavily on visual and acoustic signalling. Yet little remains known about how social context affects how vocalisations are perceived and produced, and the neural mechanisms that support this this process. Given the complex dynamics that typify primate societies, addressing such questions remains of critical importance to elucidating the mysteries of the primate social brain. I hypothesize that oxytocin (OT), a neurohormone that regulates social behaviour and a promising therapeutic target for psychiatric disorders, influences context-dependent effects on primate vocal communication, notably by acting in higher order brain regions involved in vocalisations and encoding social information. I propose to explore the neural basis of socially adapted acoustic communication. To do so, I will record vocalisations from marmoset monkeys, a highly vocal primate and promising model for neuroscience, in different social contexts designed to elicit positively or negatively valenced calls between differently affiliated monkeys. Importantly, these experiments will happen in semi-natural conditions, focusing on freely moving animals expressing their normal behaviours within the colony. This is a highly novel approach that starkly contrasts with classical task-based experiments. Additionally, using modern tools including high throughput neurophysiology, chemogenetics and intravenous viruses, I will manipulate OT neurons activity while recording from hundreds of neurons. This will enable analyses focusing on neural populations instead of single units, all wireless and without interfering with the animals’ behaviours. This multidisciplinary approach will allow me to uncover some fundamental aspects of how the primate brain encodes natural conversations and adapts its response accordingly to the social context. Moreover, I will for the first time study how endogenous OT controls social behaviours in primates.

Mots-clés : oxytocin,marmoset,neurophysiology,acoustic communication,social behaviour