Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : VeNiss (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : Université Harvard — Pays : Etats-Unis — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 131250.0 €

In the historical tradition, Venice is a city without walls and gates, and hence lacking suburbs. VeNiss reverses this trope by examining the urban, political, and cultural patterns connecting the capital with the chain of over sixty islands forming its lagoon fringes. Investigation of their integral role in Venice's spatial practices establishes a ground-breaking approach for the study of historic cities' margins as connective tissues, a subject seldom tackled by urban scholars. Reframing Venice within its archipelago, this project addresses that gap and explores the impact of urban edges on city planning, economic dependence, social responsiveness, and artistic production. From the 16th century, Venice became critically conscious of the granular nature of its hinterland, constructing a governance that involved the islands. Lagoon sites were systematically included in the network of capillary infrastructures for the city's supply, defence, and healthcare as well as civic rituals. Cultural entanglements sometimes bypassed the city, as novel lagoon architectural solutions permeated the Italian Peninsula through the agency of religious communities. Maps, atlases, and books of islands published on and in Venice helped consolidate the capital's archipelagic thinking into a coherent framework. VeNiss sheds light on this physical and theoretical construct –abruptly interrupted by the fall of the Venetian Republic (1797)– through a holistic project which combines social history, architecture, art and literary studies with advanced digital technologies. Coupling close archival readings with modelling systems, it proposes a pioneering methodology to reconstruct the islands' transformations alongside their interwoven relationships in a geographically- and temporally-based digital environment. VeNiss will constitute a crucial contribution to Venetian history while providing a valuable model for future urban studies seeking to visualise dispersed places through time and space.

Mots-clés : urban history history of venice digital heritage reconstruction digital knowledge representation
Projet ERC : e-Perinatal (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Andalusian Health Service — Pays : Espagne — Rôle : Partner
Acronyme de l'entité : SAS
Type d'entité : Organismes publics (hors enseignement & recherche)
Financement ERC de l'entité : 180000.0 €

Maternal mental disorders are the most common complications during pregnancy and within the first year after childbirth (defined as the perinatal period) and are the leading cause of maternal suicide. Affected mothers cannot function properly, causing a devastating impact on the entire family. Effective primary prevention interventions are urgently needed. However, the current scientific evidence is insufficient to implementing primary preventive programs at the population level.  I aim to establish the effectiveness of universal preventive interventions for maternal perinatal mental disorders and to support their implementation as normalized routine practice in global healthcare services. Integrating classical and emerging methodological frameworks (family systems, self-determination theory, and normalization process theory), as well as the perspective of patient and public involvement in research, I will: (a) Develop a personalized mobile-Health preventive intervention for mothers and their partners, which integrates evidence-based psychological components and personalized health recommendations; (b) Test preventive intervention effectiveness for reducing the incidence of maternal depression and anxiety disorder, reducing father/partner symptoms of depression and anxiety, and promoting child health and development; (c) Apply a causal methodology, to pinpoint the underlying mechanisms for the effectiveness of the preventive intervention; and (d) Understand the implementation process and identify the factors that can promote or inhibit implementation.  With the multidisciplinary team that I lead – and a large-scale hybrid effectiveness-implementation trail in real-world maternal health services – this research programme promises to be the first in its field. The resulting robust scientific evidence and novel explanatory model will create a new research paradigm. A toolkit for implementation research will enhance translation as normalized routine practice.

Mots-clés : prevention perinatal mental disorders postpartum depression women primary health care
Projet ERC : DOUMOTHERCHINA (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Studies of Cultures and Arts
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 : 1499117.0 €

Using reproductive medicine is not a recent practice in China. While authorized artificial insemination and In Vitro fertilization have become common practice, the commercialization of gametes and surrogacy remains officially prohibited. However, an underground market of agencies and medical establishments has emerged in major cities, responding to the growing demands from the LGBTQ+ community and heterosexual couples who have lost their only child. How do the Assisted Reproductive Technologies (ARTs) and the surrogacy market operate in China? Why do some Chinese intended parents, when pursuing surrogacy abroad, anticipate having mixed-race children? How do these new reproductive practices challenge the traditional system of patrilineality and the conception of parenthood? As China experienced its first demographic decline in 2022 for the past sixty years, policies related to ARTs have gradually relaxing in recent years. How does this demographic challenge influence the political and legal development related to reproductive technologies? What kinds of ethical, legal, kinship, and gender issues are associated with surrogacy and ARTs in China, and how do they differ from those in European and American societies? This project delves into the realm of ARTs and surrogacy in China, an unexplored area within the anthropology of contemporary kinship, primarily founded on European and American societies. Employing an interdisciplinary approach that combines anthropology, law, history and literature, this endeavor aims to enhance our understanding of Chinese modernity, contribute to a shift in anthropological knowledge about contemporary kinship, and shed light on the construction of bioethics and reproductive medicine laws in China. These insights may offer valuable reference points for other regions and countries, particularly in Europe, where ARTs remain contentious topics in public and political discussions.

Mots-clés : kinship,surrogacy,gender,assisted reproductive technologies,parenthood,lgbtq,demographic policies,polygyny,race,sexuality,conjugality,intergenerational relationships,china
Projet ERC : FiRes (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Wageningen University & Research — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : WUR
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499926.0 €

The challenge. Despite a global decline in burned area, total CO2 emissions from fires have increased due to more fires in previously largely fire-free and therefore fire-sensitive forests. Existing knowledge of fire impacts comes from fire-adapted ecosystems and cannot be easily translated to fire-sensitive forests. Particularly the Amazon has seen recent increase in fire frequency and intensity, with devastating local effects on the forest, regional-scale air pollution, and global CO2 rise. Aim. I aim to understand fire resilience – i.e. resistance to fire and post-fire recovery – of fire-sensitive ecosystems by studying the Amazon. I will assess fire resilience at multiple temporal scales: 1) the past to understand long-term recovery and full disturbance-recovery cycles, 2) the present to experimentally understand mechanisms underlying fire damage and mortality, and 3) the future to Amazon resilience to future fire regimes. Approach. I will integrate across temporal scales and their different disciplines. For past fire resilience (last 10,000 y), I will use paleo pollen and charcoal records. For present fire resilience, I will build a monitoring network in burned forests and perform a unique fire experiment. For future resilience, I will use the previous steps to adapt a dynamic forest model and simulate future fire resilience. I will quantify fire regime as fire frequency and intensity, which are fundamentally different aspects of fire regime but rarely tested simultaneously. To assess how climate drives fire resilience, I will study seasonally dry and wet evergreen tropical forests. To understand mechanisms underlying tree mortality and recovery, I will use physiological measurements and plant functional traits to understand species and community resilience in the past, present and future. Impact. This project will advance our understanding of resilience of fire-sensitive ecosystems, and provide the knowledge needed for future safeguarding of these ecosystems

Mots-clés : functional traits,tropical forests,fire,ecosystem resilience
Projet ERC : MORPHOFBD (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
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 : 1491461.0 €

The fossil record provides crucial evidence to inform our study of evolution and past diversification processes. Recent methodological developments have allowed to integrate fossil species directly into the reconstruction of phylogenetic trees, providing more accurate estimates of the age of evolutionary events as well as speciation and extinction through time. However, the current methods fail to account for many of the specific characteristics of fossil samples compared to extant species. Genetic sequences are usually unavailable for fossils, so phylogenetic inferences including fossils rely on morphological characters. This morphological information interacts with other components of the analysis, such as the genetic sequence alignment, or the sorting of fossil samples into a taxonomy itself informed by morphological traits. These interactions are not accounted for by current models and could lead to strong biases in the estimates of the phylogeny, its ages and its underlying diversification process. To address these issues, the proposed project will build a new methodological framework for integrating the complex interplay between morphological evolution, diversification, and fossil sampling. We will develop new models adapted to fossil data, which will be carefully validated using realistic simulations, and then applied to several empirical datasets. Some of these datasets will serve as a comparison of our new approach to existing methods. Other datasets have never been studied under a combined phylogenetic framework with fossil evidence before, so our analyses will form a new understanding of their diversification, and build a high-quality phylogeny for future work on these groups. In conclusion, this project will pave the way for efficiently combining information on past and present species into a highly accurate and nuanced representation of the evolution of biodiversity through time.
Projet ERC : hCerebEvol (Horizon Europe, appel 2024, 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 : 1499958.0 €

Speciation involves the emergence of new behavioural features that rely on the evolution of neural circuits. The human species displays higher cognitive features which have been linked in part to the evolution of the cerebral cortex, but the involvement of the other brain regions, such as the cerebellum, remains largely unexplored. The human cerebellum displays divergent features at the anatomical, functional, and behavioural levels. It is associated with both higher cognitive functions and cognitive disorders. However, the properties of human cerebellar cells & circuits have not been compared with those of other species, including non-human primates. This knowledge gap hinders our understanding of human brain evolution. Here, I aim to identify and functionally study the impact of human genomic novelties on cerebellum development and function, focusing on neuronal and & circuit levels. I will first investigate the role of a novel human molecular pathway in the cerebellum, based on the hominid transmembrane receptor family LRRC37, which I have recently identified. I will identify the cellular distribution, molecular partners, and function of LRRC37 receptors in cerebellar neurons using three approaches: cross-species tissue comparison, gain-of-function in vivo in the mouse cerebellum, and human models based on pluripotent stem cells. In parallel, I will identify new molecular novelties acting in human cerebellar cells, focusing on human gene duplicates and differentially expressed genes, and link them to divergent cerebellar properties. I will define the spatio-temporal expression patterns of these genes, followed by gain/loss-of-function in the mouse cerebellum and in human cerebellar neurons to study their function. Together, hCerebEvol will uncover entirely new aspects of human cerebellar evolution that will improve our understanding of brain development and function, and may lead to the identification of human-specific sensitivity to brain disorders.

Mots-clés : human brain evolution,cerebellum,duplicated genes,neuronal evolution,lrrc37
Projet ERC : MALAGA (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
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 : 1479643.0 €

In many scientic domains, graphs are the objects of choice to represent structured data: from molecules to social networks, power grids, the internet, and so on. The exploitation of graph data represents a major scientic and industrial challenge. Graph Machine Learning (GML) is thus a fast-growing eld, with so-called Graph Neural Networks (GNN) at the forefront. However, in sharp contrast with traditional ML, the eld of GML has somewhat jumped from early methods to deep learning, without the decades-long development of well- established notions to compare, analyze and improve algorithms. As a result, 1) GNNs, all based on the so-called message-passing paradigm, have signicant limitations both practical and theoretical, and it is not clear how to address them, and 2) GNNs do not take into account the specicities of graphs coming from domains as dierent as biology or the social sciences. Thus, practical results may vary wildly from one case to the other, with no guidelines on how to design reliable GNNs in each case. Overall, these are the symptoms of an overlooked major issue: GML is hitting a glass ceiling due to its severe lack of a grand, foundational theory. The ambition of project MALAGA is to develop such a theory. Solving the crucial limitations of the current theory is highly challenging: current mathematical tools cannot analyze the learning capabilities of GML methods in a unied way, existing statistical graph models do not faithfully represent the many characteristics of modern graph data, computational complexity becomes problematic on large graphs. MALAGA will develop a radically new understanding of GML problems, and of the strengths and limitations of a large panel of algorithms. Our goal is to signicantly boost the performance, reliability and adaptivity of GNNs, with a signicant impact on three types of graph data that exhibit very dierent but representative behaviors: biological networks, social networks, and online recommender systems.

Mots-clés : graph machine learning graph neural networks random graphs theory
Projet ERC : MicroBBB (Horizon Europe, appel 2024, 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 : 1499964.0 €

Brain functioning can be influenced by body ecosystem signals conveyed through the vasculature and regulated by the blood-brain barrier (BBB), a selective and modulable barrier that controls which substances and cells enter the brain. Structural or functional BBB deficits are found in many brain diseases, from neurodevelopment to neurodegeneration, thus understanding how the BBB develops holds critical significance for both biologists and clinicians. Yet, we still lack fundamental knowledge on how interactions between different cellular populations in coordination with environmental signals contribute to BBB construction during early development. To tackle this issue, we will focus on the core components of the BBB -pericytes and endothelial cells- and microglia, the brain resident macrophages. Microglia play key roles in circuit assembly and we have shown that prenatal microglia, which are in close apposition to the vasculature, respond in a sex-specific manner to signals derived from the maternal microbiota. Here, we will study the developmental crosstalk between microglia and BBB in both male and female embryos by investigating (i) how pericytes influence prenatal microglia; (ii) the spatiotemporal heterogeneity of BBB closure and implication of microglia; and (iii) the impact of maternal microbiota on BBB formation and crosstalk with microglia. Our approach leverages multidisciplinary and state-of-the-art techniques in newly developed murine models of microglia depletion and in utero antibiotic treatment, including two-photon live imaging, single-cell and spatial transcriptomics, in vitro BBB model and comparison to human embryos. Ultimately, we will establish an integrated framework of BBB formation and BBB-microglia interplay, shedding light on how signals from maternal microbiota shape brain development. Our findings will provide key insights into normal and pathological brain wiring, paving the way for the identification of potential therapeutic targets.

Mots-clés : microglia,blood brain barrier,blood vessels,pericytes,microbiota,embryogenesis
Projet ERC : UNREST (Horizon Europe, appel 2024, 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 : 1771915.0 €

Floods and landslides are an intensifying hazard in the context of climate change that affected over 2 billion people worldwide between 1998-2017. In mountainous catchments, these processes play a significant role in rapid erosion contributing to landscape evolution. Yet, multiple barriers limit our current understanding of rapid erosion dynamics, such as the applicability of theoretical transport laws to complex real-world systems, poor understanding of the mechanism behind the initiation of rapid erosion processes, and sparsely distributed observations in time and space.  The UNREST project will cut this Gordian knot by pioneering an interdisciplinary observational framework that integrates several state-of-the-art seismic techniques (spatially dense arrays, seismic interferometry, and machine learning) with physical and numerical models on a previously unexplored spatiotemporal scale. This will be done through three main objectives: (1) identify precursors and magnitude indicators of impending landslides, (2) link seismic signals to complex landslide dynamics, and (3) develop new tools to track unstable flood flow across multiple scales. The project will be conducted in four active Alpine catchments in France and Switzerland, with the developed methods tested in an entirely different geomorphic, geologic, and climatic setting of New Caledonia, a South Pacific island. UNREST will unveil critical thresholds in damage development on unstable slopes and previously unobserved patterns and behaviors in complex flow dynamics. These findings, augmented by the development of near-real time data processing workflows, will have a transformative impact on the understanding of rapid erosion dynamics, paving the way to enhanced warning systems in mountainous catchments.

Mots-clés : environmental seismology,erosion,mountainous catchments,landslides,floods,sediment transport,granular flow dynamics,advanced seismic methods,distributed acoustic sensing,dense seismic arrays
Projet ERC : QGuide (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Organisation européenne pour la recherche nucléaire — Pays : Suisse — Rôle : PI
Acronyme de l'entité : CERN
Type d'entité : Recherche
Financement ERC de l'entité : 780750.0 €

What are the constraints that a low energy Effective Field Theory must satisfy to be consistent with a Quantum Gravity description at higher energies? Can we determine these constraints in a precise way and use them as new guiding principles to progress in High Energy Physics? Recently, novel quantum gravity criteria have been proposed that imply non-trivial constraints on models of Particle Physics and Cosmology and can provide the missing piece to solve the long-standing naturalness issues observed in our universe. However, none of these so-called Swampland constraints have been completely proven yet; and often, they even lack a precise formulation. The goal of my proposal is to determine the constraints that Quantum Gravity imposes at low energies by uncovering the fundamental principles underlying the Swampland conjectures and looking for new universal constraints in the context of string theory. To achieve this goal, I propose a novel approach based on cutting-edge mathematical techniques of algebraic geometry and the topological cobordism groups that extend the notion of symmetry. Each conjecture will be subject to scrutiny such that it gets either disproven or promoted to a sharp statement in the realm of well-established string compactifications. Specific goals include an in-depth analysis of the mechanisms by which string theory avoids new classes of generalised global symmetries, a complete classification of the field spectra emerging at the large field limits of flat space string compactifications, developing new methods to study the scalar potential at the large field limits and determining whether supersymmetry is a necessary condition to ensure vacuum stability. These new quantum gravity constraints will trigger a revolution in our understanding of the Quantum Gravity imprint at low energies, addressing questions about axions, neutrino masses, inflation, hierarchy problems, weakly coupled charged matter and the accelerated expansion of the universe.

Mots-clés : string theory,quantum gravity,string compactifications,swampland,weak gravity conjecture