Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : AstroDarkLS (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Université de Rome « La Sapienza » — Pays : Italie — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 706250.0 €

The Standard Model (SM) of particle physics is a successful, extremely well-verified theory. Nevertheless, the SMappears far from being complete. There are still many theoretical and experimental open questions: the strong-CP problem, the origin of neutrino masses, the nature of dark energy and dark matter. The need for physics beyond the Standard Model (BSM) is undeniable, but the question The Standard Model (SM) of particle physics is a successful, extremely well-verified theory. Nevertheless, the SM appears far from being complete. There are still many theoretical and experimental open questions: the strong-CP problem, the origin of neutrino masses, the nature of dark energy and dark matter. The need for physics beyond the Standard Model (BSM) is undeniable, but the question is: how and where will we find it? The aim of the AstroDarkLS project is to try to discover or falsify important theoretical models of light particles, such as axions and dark photons, considering their impact in astrophysical and cosmological systems which were never considered in depth by the particle physics community. The project is organised around three main themes, spanning various length scales in the universe: the use of stars and astrophysical objects to look for new physics; the impact of motivated BSM models on star formation; the investigation of electromagnetic signals both from galaxies and the interstellar medium between them. For each theme groundbreaking objectives are identified, such as the first simulation of Supernovae radiative transport including axions, the first public code for star formation in the presence of light physics, the innovative use of line intensity mapping (LIM) to detect dark matter decay or annihilation into photons. All the objectives are located at the interface between particle physics, astrophysics and cosmology, building on the unique experience of the PI in these various disciplines and in perfect alignment with the European Commission vision.

Mots-clés : dark matter,axions,dark photons,stars and new physics,astroparticle physics
Projet ERC : DIGIPRO (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de La Corogne — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499990.0 €

The personalization of oncology needs predictive methods to anticipate major pathological events and optimize clinical care for each patient. To address this critical demand, computational oncology has produced biomechanistic models for patient-specific cancer forecasting. Although these models are based on cancer growth (increase in extension), the main driver of potentially lethal disease and, hence, the basis for clinical decisions is cancer progression (increase in malignancy). However, despite known correlations between cancer progression and growth, the biophysical mechanisms that explain how cancer progression emerges and alters cancer growth remain unknown. DIGIPRO will address this crucial gap in knowledge. I will build a new class of biomechanistic models to describe the multiscale dynamics of cancer progression, enable its early detection at microscopic stage by using macroscopic clinical data, and construct clinically-practical digital twins to optimally adapt cancer monitoring for early detection of progression. To achieve this ambitious goal, I will focus on newly-diagnosed prostate cancer and (i) build novel micro and macroscale models jointly describing cancer growth and progression using a structured formulation over space, time, and malignancy dimensions; (ii) pioneer a multiscale structured model equipped with a mechanistic learning operator that uses macroscale model-based biomarkers of progression to reconstruct the microscale cancer malignancy profile; and (iii) combine adaptive and immersed isogeometric methods, reduced order models, and multi-objective risk-based optimization to construct practical digital twins of cancer progression and explore optimization of cancer monitoring. Thus, DIGIPRO will push the frontiers of cancer modeling, biology, and care, while also opening new horizons in mechanistic modeling of multiscale progressive phenomena in medicine (e.g., Alzheimer’s disease, atherosclerosis) and engineering (e.g., fracture, damage).

Mots-clés : computational oncology,mathematical oncology,tumor forecasting,patient specific,mechanistic models,biomechanics,computational mechanics,isogeometric analysis,digital twins,mechanistic learning,physics informed machine learning,reduced order models,multiscale models,phase field models,advection reaction diffusion partial differential equations
Projet ERC : STERN (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université de l'Essex — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499253.75 €

Social inequalities are reinforced within the education system. Stereotypes may have a major role in this, since they may lead to differential treatment of minority students, resulting in self-fulfilling prophecies that hinder their academic outcomes. Beyond the obvious role of teachers, that of peers is also crucial, as they are important parts of students’ socialisation: how they are perceived by peers could affect their motivation, interests, achievements, and relationships. However, it is not clear how much students apply stereotypes to their peers, given the wealth of individuating information they have about them.  This project introduces the new concept of applied stereotypes: this expresses how an individual perceives another along stereotype-related dimensions, such as warmth and competence. I propose that applied stereotypes develop jointly with peer networks of school communities. For example, the application of stereotypes could be mitigated by friendships (judging one’s friends more positively) or by accepting the established personal reputation of specific peers as warm or competent instead of judging them based on stereotypes. Such peer-based processes of stereotype application, combined with the effect of applied stereotypes on outcomes, are crucial to understand, as students’ educational trajectories emerge gradually in school, surrounded by peers. The project investigates social mechanisms that explain the dynamic interplay between stereotypes, applied stereotypes, and outcomes. As there is no established way to measure applied stereotypes, I develop a novel dyadic measure that captures who perceives whom in what way and collect detailed data in ten English secondary schools. I conduct empirical analyses by using and extending cutting-edge methods of social network analysis. By taking a so-far neglected level of applied stereotypes into account, this project has the potential for a ground-breaking impact on the study of social inequalities.

Mots-clés : stereotypes,social networks,education
Projet ERC : OligoAging (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Institut Weizmann — Pays : Israël — Rôle : PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498665.0 €

Myelin, an oligodendrocyte membrane spirally wrapped around axons, has only recently been appreciated to be a plastic structure, which constantly remodels in response to experience. Myelin plasticity is based on proliferation and maturation of oligodendrocyte precursor cells (OPCs) to form new myelinating oligodendrocytes (oligodendrogenesis), in conjunction with remodelling of myelin that is already established. The cellular and molecular mechanisms governing myelin plasticity and how it contributes to aging-related cognitive decline remain mostly unknown. Whereas cognitive aging is often attributed to neuronal vulnerability, here I propose that early oligodendrocyte dysfunction is a key driver of cognitive decline. I recently found that oligodendrocytes in the aging brain react to rejuvenating cues arising from young cerebrospinal fluid (CSF), with substantial effects on their cellular function and memory consolidation. Mechanistically, I identified the transcription factor serum response factor (SRF) to be necessary in oligodendrocytes for developmental myelination (Iram et al, bioRxiv), and showed that SRF is downregulated with age and induced by young CSF (Iram et al., Nature). Strikingly, oligodendrocytes remain susceptible to microenvironmental cues even at late stages of aging, positioning them as promising targets for therapeutic interventions.  Combining genetic, optogenetic, and transcriptomic tools with cutting-edge whole proteome metabolic labelling, I will pursue three complementary objectives: 1) Uncover the transcriptional regulation of oligodendrocyte plasticity and aging. 2) Elucidate the molecular basis of failed oligodendrogenesis in aged mice. 3) Define mechanisms underlying decline in myelin plasticity with age by nascent proteome tagging. Completion of this work will have a profound impact on our understanding of how oligodendrocytes age and provide novel targets for brain rejuvenation through improving myelin health and integrity.

Mots-clés : oligodendrocyte,myelin,aging,plasticity,memory
Projet ERC : BeyondMapping (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Institut Weizmann — Pays : Israël — Rôle : PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1637981.0 €

Social information pervades every aspect of our lives, and our ability to process it and respond appropriately is essential to our success as individuals and of society as a whole. Despite its critical importance, there are profound individual differences in social processing abilities. The key to understanding this variance may lie beyond isolated cortical regions, in the poorly understood large-scale interactions between different cortical networks which facilitate the integration of information and the execution of complex tasks. We propose a novel framework, designed to introduce new tools to the study of some of the most fundamental questions in social neuroscience: are there dedicated brain mechanisms for the processing of social information? What goes wrong in social information processing disorders, and how does social information processing relate to social anxiety? Do these abilities fluctuate over long time scales (years)? Can we predict their change? We will create new behavioral tasks to tease apart social task elements, and objectively estimate individual social processing abilities using our innovative measure of typicality. We will quantify individual differences in performance on social tasks, and identify the variance in neural activity which predicts them from a wide range of network features at the high resolution of ultra-high field 7 Tesla fMRI. This will yield testable hypotheses about the links between networks and social behavior. Finally and most crucially, to test these hypotheses, we will use covert neurofeedback, a cutting-edge technique which I have been developing, to perturb the networks, establishing their causal contribution to behavior. The combination of novel behavioral, neurocomputational, and above all perturbation tools for testing causality, will provide insights which will profoundly impact our understanding of social information processing in health, and advance the reality of personalized treatment of social disorders.

Mots-clés : cognition,individual differences,plasticity,neural networks
Projet ERC : SynaptoMitophagy (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Université nationale et capodistrienne d'Athènes — Pays : Grèce — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Age-dependent accumulation of damaged mitochondria and synaptic loss represent early pathological hallmarks of brain ageing leading to neuronal death. Mitochondria-selective autophagy (mitophagy) is triggered to eliminate defective organelles promoting cellular and organismal survival. Mitophagy declines with age, while its induction extends lifespan and confers neuroprotection across diverse species. Although the pivotal role of mitophagy in neuronal physiology is steadily emerging, its contribution to synaptic homeostasis remains elusive. Building on our previous pioneering studies, SynaptoMitophagy aims to reveal the molecular underpinnings of age-dependent synaptic impairment, focusing on mitochondrial maintenance and turnover. We will combine the nematode Caenorhabditis elegans, which offers a well-defined nervous system, with cutting-edge technologies, such as super resolution imaging, microfluidics and optogenetics, to manipulate spatiotemporally mitochondrial damage and monitor synaptic mitophagy at nanoscale resolution, in vivo. Mammalian neurons will be used to address the functional conservation of synaptic mitophagy components. The objectives are four-fold: 1) Establish mitophagy reporters for in vivo monitoring of mitochondrial fate at synapses during ageing and under neuroprotective conditions 2) Use optogenetic tools to stimulate synapse-restricted mitochondrial damage and, thereby, to detect mitophagy induction and its contribution to neurotransmission. 3) Characterize the synaptic defects and assess behavioral deficits arising from mitophagy impairment. 4) Conduct forward genetic screen for synaptic mitophagy modulators, towards augmenting mitochondrial quality control and resistance to age-related synaptic failure. The cumulative results of this proposal will decode the molecular mechanisms of neuronal mitophagy compartmentalization at synapses during ageing, providing critical insights with broad relevance to human health and quality of life.

Mots-clés : ageing,autophagy,c elegans,energy metabolism,mitochondria,mitophagy,mitochondrial proteostasis,neurodegeneration,neuronal imaging,synapse
Projet ERC : ECHOES (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Université de Saragosse — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499608.0 €

By contracting our muscles, we move and interact with the world. In turn, the activated muscles act as signal repeaters of the neural inputs they receive. Muscles do not only receive inputs determining how they need to contract (and thereby how we move), but they also receive a rich set of neural information originating in the central nervous system and traveling through nerves and muscles without directly altering motor commands. This 'motor null space' in the muscles may represent a unique opportunity to explore the human central nervous system in an unobtrusive, spatially selective, and robust way, thereby overcoming the most critical inherent limitations of currently available non-invasive neuroimaging technologies. To test this novel concept, fundamental research is needed to develop methods to extract, separate, and interpret the non-motor neural projections to human muscles. ECHOES will capitalize on recent breakthroughs in decoding the spinal outputs to muscles to develop a theoretical and experimental framework to unveil the 'motor null space' in human muscles. The project will then demonstrate the potential benefits of the extracted neural information in three scientific fields with growing societal and clinical impact: human-machine interfaces, targeted brain neuromodulation, and diagnosis of movement disorders. I expect that the project's multidisciplinary research program will further our understanding of the origin and relevance of neural signals generated by the human brain and spinal cord. This will markedly improve future research aimed to understand, use, and modulate human neural activity by providing a first-of-its-kind, minimally invasive, and robust neuroimaging technology with unprecedented spatio-temporal resolution. By achieving these goals, ECHOES technology will enable the development of new applications for the clinical and industry fields.

Mots-clés : neural engineering biomedical engineering biosignal processing neuroprosthetics neural control of movement neural population activity brain machine interface human machine interaction
Projet ERC : HERDPATH (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : University College Dublin — Pays : Irlande — Rôle : PI
Acronyme de l'entité : UCD
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1460000.0 €

Palaeogenomics has transformed our understanding of the genetic consequences of domestication, particularly for livestock species, first brought into the anthropological sphere ~10,000 years ago in Southwest Asia. However, we know little of how domestication shaped the evolution and frequency of pathogens affecting livestock. Moreover, the evolution and occurrence of zoonoses - pathogens infecting both animals and humans - in Neolithic and later societies has been debated, but studies have focused on human remains to obtain ancient pathogen genomes, neglecting animal sources.  HERDPATH will address this deficit through large-scale palaeogenomic screening of faunal remains from Eurasia across 10,000 years. Focusing on sheep and goats, two of our oldest domesticates and which share a high number of common diseases with humans, HERDPATH will analyse both pathogen and ruminant genomes to reveal the dynamic between ancestry, husbandry-induced inbreeding, immune gene variation, and pathogen occurrence through time. Bioinformatic screening will produce a temporal, multi-species archive of pathogen-positive livestock, providing the first molecular baseline of infectious disease presence in domestic herds. Time-stamped pathogen genomes will permit the timing of key evolutionary events such as host adaptation and the origin of lineages circulating today. Using data derived from multiple livestock species, HERDPATH will explore the co-evolutionary trajectory of pathogens and immune genes since domestication.  Exploiting temporal genomes from underexplored sources will reveal how domestication shaped pathogen evolution towards increasing host adaptation, helping us to model the evolutionary dynamics of future livestock disease, zoonosis outbreaks, and food security. HERDPATH will be a step-change in our understanding of the consequences of domestication; how it drove pathogen evolution and the genetic makeup of our herds, shaped animal health, and our own health in return.

Mots-clés : goat genomics,sheep genomics,livestock pathogens,pathogen palaeogenomics,domestication palaeogenomics
Projet ERC : SEVEN (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Université de Saragosse — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1843500.0 €

Metastasis research is one of the greatest challenges in the medical field. The nanoengineering of inorganic/organic nanoparticles (NPs) with natural signaling carriers such as extracellular vesicles (EVs) is a promising tool to address the lack of treatment efficiency of currently available therapies, blamed on the insufficient accumulation of the antitumoral molecules in the metastasis tissues. Despite several years of intense efforts, therapeutic EVs are still far away from clinical practice. Recent studies have evidenced that this failure is due to the lack of knowledge on how EVs behave in biological environments and how their therapeutic cargo affects the metastasis targeting moieties present on their membranes. Seven believes that the lack of attention on the unknown biomolecular corona (BC) and on its role governing the EVs’ biological identity may well be behind such uncertainties. Understanding EVs’ BC formation will improve the rational EV-inspired nano-therapy design. SEVEN has been designed to generate substantial understating of the NPs-loaded therapeutic EVs behavior, the BC identity and its surface topography to generate new vectors with a much improved accumulation in metastasis target tissues. SEVEN will validate BC’s influence in the EVs metastasis targeting properties in a conceptually and operational ground-breaking experimental design to modify the BC’s surfactome composition for tailoring their therapeutic action. In addition, SEVEN will use supercritical fluid technology as a new scalable and reproducible strategy to create high yield loading of therapeutic NPs-loaded EVs-inspired therapies, maintaining their natural metastasis signaling properties and overcoming the main limitations that have prevented their successful translation to the clinic. All this will allow SEVEN to screen most promising metastasis targeting tailored EVs (loaded with therapeutic NPs) in patient-derived orthotropic xenograft (PDOXs) models.

Mots-clés : biomolecular corona,extracellular vesicles