Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SpaceClones (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Institute for Bioengineering of Catalonia — Pays : Espagne — Rôle : PI
Acronyme de l'entité : IBEC
Type d'entité : Recherche
Financement ERC de l'entité : 2499999.0 €

Clonal evolution in tumours, the process by which cancer cells expand, diversify and are selected, is a major determinant of tumour growth and response to therapy. How the co-existence of diverse cancer cell clones shape tumour development is a fundamental question that remains open, in part because of limitations on existing experimental platforms and analytical frameworks. Our expertise inferring multicellular behaviours within tissue microenvironments, together with recent advances in imaging, assay automation, and cell engineering, timely place us in an excellent position to profile and engineer clonal interactions within tumours from the tissue level down to the molecular scale, which enables targeting this important question with unprecedented throughput and spatial resolution. In SpaceClones, we aim to: (1) characterize clonal interactions in genetically engineered tumours at sub-100 nm resolution, (2) characterize clonal signatures under metabolically defined environmental conditions, and (3) examine the cell state of engineered clonal spatial patterns. To overcome a variety of challenges to understanding molecular and cellular mechanisms of clonal behaviours in tumours, I have designed a ground-breaking approach that combines highly-multiplexed imaging, in vitro and in vivo tumour models, cell engineering, super-resolution microscopy, combinatorial low-volume liquid handling, and algorithms for deconstruction of spatial patterns. Altogether, SpaceClones will exemplify how to imply causality on the emergence of clonal spatial patterns in tumours, having far-reaching implications for the study of any other multicellular system. Ultimately, a deeper understanding of clonal evolution will contribute in the design of more effective cancer therapies and tools to predict clinical outcomes.
Projet ERC : BIOPOLE (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Université Rovira i Virgili — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499998.0 €

The transition to sustainable fuel and chemical production using renewable energy sources is paramount to curb CO2 emissions and decrease reliance on fossil fuels. In this context, artificial photosynthesis (AP) offers a promising approach to mimic natural photosynthesis (NP) to store solar energy into chemical bonds, driving the conversion of water and CO2 into renewable products. However, current photocatalytic AP systems are constrained by low efficiency, limited product selectivity, specially going beyond the 2 electron CO2 reduction, and poor control of cross-reactivity in solution.  BIOPOLE introduces an innovative compartmentalized approach to AP by mimicking the spatial layout of thylakoid membranes -which separate oxidation and reduction reactions to minimize cross-reactivity- arranging catalysts, photosensitizers and mediators across artificial membranes. Using polymeric vesicles (polymersomes) as bioinspired photocatalytic microreactors BIOPOLE will compartmentalize redox chemistry to ultimately drive the electrons from the oxidation of water to reduce CO2, offering an efficient and stable platform for solar fuel and chemical production. This project aspires to address key challenges in AP, developing novel advanced photocatalytic polymersomes with controlled membrane properties and functionalization, achieving precise separation of reaction centres, enhanced charge separation, and efficient solar-to-fuel conversion. Using photocatalytic polymersomes as simplified models of natural thylakoids to produce solar fuels and chemicals harnessing light as driving force, BIOPOLE will contribute to the understanding of reactivity at the aqueous interface of polymeric membranes and electron/proton transfer between compartments. Ultimately, BIOPOLE’s unique bioinspired polymersome-based approach promises to advance the design and conceptual development of artificial photosynthetic systems and provide a transformative platform for sustainable fuel production.

Mots-clés : photocatalysis,artificial photosynthesis,photocatalytic vesicles,confined catalysis,polymersomes
Projet ERC : MultiMENDo (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : Partner
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 421268.5 €

The MensEndoDiag project aims at finding diagnostic biomarkers and prognostic biomarker candidates, as well as investigating new therapeutic approaches for endometriosis using menstrual fluid, an easily accessible yet overlooked biological fluid. Endometriosis is a common gynecological disorder affecting 6-10% of women of childbearing age. It is associated with pelvic pain and infertility. It leads to a reduced quality of life and is an economic burden. It is defined by the presence of endometrial tissue outside the uterus. Endometriotic lesion form from retrograde menstruation (menstrual fluid reflux through the fallopian tubes) but the precise pathogenesis remains unclear. There are no noninvasive biomarkers currently used in clinical care but they are essential to improve the diagnosis delay, currently estimated at 8 years. There is no specific treatment and pharmacological options are contraceptive. Here, I propose to use menstrual fluid as a relevant biological fluid for endometriosis. In Aim 1, single-cell transcriptomics and soluble protein multiplex assays on 64 menstrual fluid samples will be used to identify candidate diagnostic biomarkers that differentiate endometriosis affected women from healthy controls. Validation of these biomarkers will be carried out in menstrual fluid samples from 250 women. In Aim 2, menstrual fluid derived organoids cultured with or without immune cells will be used to assess endometriosis associated functional changes and to test new immunomodulatory treatments. In Aim 3, longitudinal cohorts will be established to identify prognostic candidate biomarkers for response to surgery and in vitro fertilization. Diagnostic and prognostic biomarkers are essential to assess disease establishment, evolution and to choose the most appropriate treatment. This project will enhance our understanding of endometriosis pathophysiology as well as allow the study of a new biological fluid, relevant to gynecologic and reproductive disorders.

Mots-clés : endometriosis,gynecology,fertility
Projet ERC : STEMGUARD (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and I mmunotherapy
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : Partner
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 270000.0 €

Stem cells guard tissue integrity by renewing the pool of differentiated cells, and must therefore be shielded from threats such as transposable elements or viruses. In that line, stem cells can largely resist viral infections, but they do so without deploying the antiviral pathways at play in differentiated cells. So, what guards the guardians? I recently discovered a stem cell-specific immune pathway, driven by a protein termed aviD (antiviral Dicer), which mounts an antiviral RNA interference (RNAi) response and thwarts RNA virus infection. This illustrates that stem cells implement specific defence mechanisms that are poorly understood, or unknown. My proposal aims at bridging the current knowledge gap in stem cell immunity. We will do so by investigating the role of the aviD pathway in vivo using an aviD knock-out mouse, as well as by unravelling the molecular regulation of the pathway (Aim 1). Stem cell’s demise can additionally be provoked by the expression of transposable elements (TEs). Converging evidence suggests that aviD and the RNAi pathway may play a second defensive role in shielding uninfected stem cells from TE expression, which we will explore in Aim 2. Because cancer is characterised by a stemness transcriptional program, aviD may similarly control TEs in tumour cells. We will study aviD expression in various tumour models and assess its role in controlling TEs. This is of special interest because awakening TE expression in cancer is being leveraged by new therapeutic approaches in multiple malignancies. Similarly, we will explore if inhibiting aviD and the RNAi pathway could have an antitumour effect (Aim 2). Finally, I hypothesize that stem cells are protected by additional, unknown antiviral pathways, which we aim to identify and characterise using new genome-scale approaches (Aim 3). Overall, this proposal aims at unveiling new biology in stem cell immunity as well as developing clinical applications in the field of antitumour therapy.

Mots-clés : stem cells,avid,antiviral immunity,transposable elements,tumour immunity
Projet ERC : StateNeuromod (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : PI
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 1297063.0 €

Being sleepy, hungry, afraid, or happy impacts our daily experience and defines our behavior and actions. Such internal states are characterized by unique signatures of activity across neural circuits and are actively shaped by neuromodulators, such as dopamine, serotonin, acetylcholine, and norepinephrine, that are released widely throughout the brain to alter the function of target neural circuits. At any moment, distinct combinations of neuromodulators are being released in each brain region. Changes in the neuromodulator balance have a powerful impact on the brain-wide configurations that underlie internal and behavioral states, while most mood disorders are associated with neuromodulator imbalance, and most therapeutic strategies attempt to restore this balance. However, how combinations of neuromodulators define distinct brain configurations and shape internal states remains unknown. The prefrontal cortex and the hippocampus are two interconnected regions, which are essential for cognitive processing and memory. They receive converging neuromodulatory inputs, and synaptic alterations in these regions are critical for learning, while dysfunction of this pathway is involved in most mood disorders. Despite the vital role of these circuits for brain function, little is known about how combinatorial neuromodulation regulates circuit configuration and coordinates information flow between these regions. In this project, we will combine neuromodulator monitoring with large-scale in vivo electrophysiology, optogenetics, and in vivo genome editing to answer the following questions and resolve the contribution of neuromodulators to the organization of neuronal ensembles and information gating in the hippocampus-prefrontal circuit in behaving mice.  1. What is the neuromodulatory landscape across behavioral states? 2. How does state-specific neuromodulation sculpt neuronal dynamics? 3. What are the circuit elements underlying combinatorial neuromodulatory action?

Mots-clés : neuromodulators,prefrontal cortex,hippocampus,sleep,memory consolidation,learning and memory,behavior,dopamine,serotonin,norepinephrine,acetylcholine
Projet ERC : DeCodeGels (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : PI
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 1499999.0 €

Despite recent advances there is still a clear need for injectable and regenerative biomaterials that can spatiotemporally modulate the inflammation and, in parallel, induce the desired regenerative pathways. Usually, biopolymeric hydrogels need a narrow and somewhat opposite set of physical and biological properties which allow for their degradation, adhesion as well as immune cell invasion to allow complete tissue regeneration. To resolve this issue, following my unique interdisciplinary expertise, I plan to develop new injectable self-assembling peptides (SAPs) biomaterials that simultaneously: i) possess improved adhesion to local tissues in vivo, ii) exhibit controlled degradation matching the desired regeneration outcome, and iii) allow tissue regeneration by enabling controlled immune cells invasion and progression of inflammation from neighbouring tissues. The basic rules for decoupling these properties will have broad implications to the biomedical community. Following injury, inflammation is the trigger of tissue repair, however, chronic inflammation is detrimental. The persistent inflammatory nature of tendinopathy contributes to localized tissue damage, often developing to a low-grade chronic inflammation with recurring tears. Unlike conventional anti-inflammatory therapies that merely address symptoms, DeCodeGels introduces an innovative therapeutic strategy utilizing temporally modulating SAPs biomaterials. This groundbreaking approach aims to i) initially induce a controlled, localized pro-inflammatory state, then ii) gradually transition this state to an anti-inflammatory environment over time to ultimately achieve a dual-purpose therapy that reverses chronic inflammation and promotes therapeutically driven healthy tissue regeneration. This single, multifaceted treatment has the potential to revolutionize our approach to chronic inflammatory conditions, offering a path to true healing rather than just symptomatic relief.

Mots-clés : self assembling peptides hydrogels immunomodulation biomaterial degradation biomaterial adhesion tendinopathy inflammation macrophages tendon regeneration
Projet ERC : NeuroQuality (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: B iological  Mechanisms , Structures  and Functions
Entité participante : Eurac Research — Pays : Italie — Rôle : Partner
Acronyme de l'entité : EURAC
Type d'entité : Recherche
Financement ERC de l'entité : 100000.0 €

Ribosome-associated quality control (RQC) is crucial for degrading truncated nascent proteins produced on aberrant mRNAs. This is done by elongation of the nascent chain on the large ribosomal subunit in the absence of mRNA and the small ribosomal subunit (CAT tailing) and by marking the nascent chain for degradation. Mutations in RQC components cause neurodegeneration both in animal models and human patients. Moreover, RQC insufficiency and subsequent protein aggregation critically contribute to proteostasis impairment and systemic decline during ageing. Strikingly, we lack mechanistic understanding of this crucial process in humans. This project stems from my post-doctoral research, in which I have solved the structure of the yeast RQC complex and discovered a novel RQC factor, the eIF5A. This conserved protein is critical in yeast RQC and was recently implicated in brain development and Huntington's disease. Moreover, I have developed a human cell-free translation extract, which enables structural studies of co-translational processes in the human system. In the proposed research, we will provide mechanistic understanding of CAT tailing and nascent chain degradation in human RQC using cryo-EM. We will define working principles of RQC components and the mechanisms by which their disease-causing mutations specifically affect neurons in vivo using the C. elegans as a model organism. Our approach utilizes a multidisciplinary approach to provide detailed mechanistic understanding of the critical RQC system in combination with an in vivo study to reveal processes leading to RQC-driven pathological changes in neural tissue. Since the RQC pathway is conserved in all kingdoms of life and serves a pivotal role in protein homeostasis with critical implications for neurodegenerative disorders and ageing, our findings will have important implications for human health and the potential to reveal novel drug targets.

Mots-clés : translation,quality control,rqc
Projet ERC : FORESEEING (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : Istituto Nazionale di Geofisica e Vulcanologia — Pays : Italie — Rôle : Partner
Acronyme de l'entité : INGV
Type d'entité : Recherche
Financement ERC de l'entité : 87500.0 €

FORESEEING means “FrOm RupturE procesS to Earthquake Early warnING” and is a groundbreaking research project halfway between the investigation of the earthquake generation processes and the implementation of methods for real-time risk mitigation actions. Incredible progress in earthquake source characterization and modelling has been achieved in the last decades. However, the mechanism of nucleation, radiation and arrest of seismic fractures is still poorly understood and with that, the fundamental issue of seismology is still unsolved: “How do earthquakes begin and what does control their final size?” Within FORESEEING, I want to get to the bottom of the earthquake nucleation with all possible means. I want to solve the unsolved issue of how earthquakes start and understand the physical processes of their generation. Once this issue is understood, I want my research outcomes to become a concrete support for the community and be implemented into Earthquake Early Warning systems, for the prompt activation of emergency actions that can save lives, reduce damage, improve resilience. This will be achieved through an interdisciplinary research approach looking at the rupture process from different points of view. Real earthquake data will be used to find out evidence of the nucleation phase of seismic ruptures and to understand the relationship between the observed features of the initial recorded signals and the following evolution of the seismic ruptures. Laboratory experiments will allow to deeply understand which parameters may influence the rupture development and how they are involved in the process. Digital twins will give the chance to explore in great details the fracture processes during crustal earthquakes and investigate faulting mechanism in realistic conditions. The implementation of real-time algorithms for EEW will move the fundamental knowledge beyond the scientific research, becoming a tool to reduce the risk during major earthquakes.

Mots-clés : earthquake nucleation earthquake rupture seismic source rupture modelling laboratory earthquakes digital twins earthquake early warning
Projet ERC : 10000 DIGITS (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
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 : 1393312.5 €

Polynomial equations and inequalities raises fundamental theoretical issues, many of which have been answered by algebraic geometry. As of applications, nonlinearity is also a formidable computational challenge. Based on recent proof-of-concept works, I propose new foundational methods in computational nonlinear algebra, motivated by the need for reliability and applicability. The joint development of theoretical aspects, algorithms and software implementations will turn these proof-of-concepts into breakthroughs.  Concretely, I will develop a theory of transcendental continuation for the numerical computation of a wide range of multiple integrals, based on a striking combination of algebraic geometry, symbolic algorithms and numerical ODE solvers. This would enable the computation of many integrals (e.g. volume of semialgebraic sets, or periods of complex varieties) with rigorous error bounds and high precision, more than thousands of digits. Building upon transcendental continuation, I propose to design algorithms to compute certain algebraic invariants of complex varieties related to algebraic cycles and Hodge classes, far beyond the current reach of symbolic methods. This surprising application is backed by a recent success on Picard group computation.  Applications include algebraic geometry, with the development of computational tools to experiment on concrete examples and build databases that document the largest possible range of behavior. Besides, I propose applications to Diophantine approximations, Feynman integrals, and optimization.

Mots-clés : computer algebra,experimental mathematics,applications
Projet ERC : NG-NLG (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université Charles de Prague — Pays : Rép. Tchèque — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1420375.0 €

This project aims to overcome the major hurdles that prevent current state-of-the-art models for natural language generation (NLG) from real-world deployment.  While deep learning and neural networks brought considerable progress in many areas of natural language processing, neural approaches to NLG remain confined to experimental use and production NLG systems are handcrafted. The reason for this is that despite the very natural and fluent outputs of recent neural systems, neural NLG still has major drawbacks: (1) the behavior of the systems is not transparent and hard to control (the internal representation is implicit), which leads to incorrect or even harmful outputs, (2) the models require a lot of training data and processing power do not generalize well, and are mostly English-only. On the other hand, handcrafted models are safe, transparent and fast, but produce less fluent outputs and are expensive to adapt to new languages and domains (topics). As a result, usefulness of NLG models in general is limited. In addition, current methods for automatic evaluation of NLG outputs are unreliable, hampering system development.  The main aims of this project, directly addressing the above drawbacks, are: 1) Develop new approaches for NLG that combine neural approaches with explicit symbolic semantic representations, thus allowing greater control over the outputs and explicit logical inferences over the data. 2) Introduce approaches to model compression and adaptation to make models easily portable across domains and languages. 3) Develop reliable neural-symbolic approaches for evaluation of NLG systems.  We will test our approaches on multiple NLG applications—data-to-text generation (e.g., weather or sports reports), summarization, and dialogue response generation. For example, our approach will make it possible to deploy a new data reporting system for a given domain based on a few dozen example input-output pairs, compared to thousands needed by current methods.

Mots-clés : natural language generation,natural language processing