Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : CAN_ORGANISE (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : The Francis Crick Institute — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 2500000.0 €

The spatial of organisation of tumours is the cumulative result of a myriad of cell-cell and cell-matrix interactions. These interactions determine the shape and relative positions of cells and the deposition and structure of the extracellular matrix (ECM), which feeds back to guide cell migration. The spatial patterns of tumours indirectly encode information about the likely future course of the disease, which is interpreted by pathologists to provide patient prognosis. To understand and control the spatial organisation of tumours requires not just knowledge of cell position, but of the underlying structural matrix. Furthermore, analysis of fixed tissues fails to capture information about cell movement or the relative sequence and kinetics of events. We will place both structural information about the ECM and dynamic analysis obtained through longitudinal intravital imaging and the centre of our work. We will focus on sequentially describing, understanding, and then re-configuring the spatial organisation of the tumour microenvironment. We will develop spatial metrics to analyse stromal architecture and link spatial features to disease outcomes in patient cohorts and therapy responses in intravital imaging studies. Reductionist co-culture assays and microfabricated tools will be used to study the mechanisms of cell-cell and cell-matrix crosstalk that generate spatial patterns. This analysis will be coupled to an agent-based computational model, parameterised using our experimental models, to explore both emergent pattern formation and possible mechanisms of interconversion between spatial patterns. Both experimental and modelling approaches will be used to identify effective mechanisms to control spatial patterns in breast and skin cancer models. Finally, interventional approaches will be adopted to re-organise the spatial architecture of the tumour stroma into patterns that favour effective therapy and tumour elimination.

Mots-clés : tumour microenvironment,stromal fibroblast
Projet ERC : FUMI (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : Peace Research Institute Oslo — Pays : Norvège — Rôle : PI
Acronyme de l'entité : PRIO
Type d'entité : Recherche
Financement ERC de l'entité : 1999672.0 €

The springboard for this project is a striking statistic: half of all young adults in West Africa wish to leave their own country and settle elsewhere. Yet, the vast majority never depart. This discrep-ancy raises a fundamental question: if migration is desired, but never materializes, what are the consequences? The project breaks with traditional approaches by shifting the object of study from observed migration in the present to imagined migration in the future. Although such future migration might never occur, it materializes in thoughts, feelings, communication, and behaviour at present. Young people’s priorities are informed by the futures they imagine, and their lives can thus be formed by migration that is imagined but never achieved. Framing the issue in this way renews research on the precursors of migration and opens up a new chapter about the links be-tween migration and development. The project is guided by a bold central hypothesis: Migration that is imagined, yet never takes place, decisively shapes the lives of individuals and the devel-opment of societies. This hypothesis is addressed through a research design that weaves together three streams: theory development, ethnographic fieldwork, and sample surveys. Drawing upon the PI’s proven qualifications in all three fields, the project aims for deep mixed-methods integra-tion. The project’s empirical focus is West Africa. Migration desires are particularly widespread in this region, and internal socio-economic variation can be exploited for theoretical purposes. By investing in theoretical and methodological development, attuned to a poorly understood aspect of global migration challenges, the project holds the promise of sustained impacts on migration research. The project is set within interdisciplinary migration studies, anchored in human geogra-phy and supported by related disciplines including anthropology, economics, and sociology.

Mots-clés : international migration,migration and development,interdisciplinary migration research,migration research in human geography,ethnographic fieldwork,survey research,mixed methods
Projet ERC : DEEP PURPLE (Horizon 2020, appel 2019, Synergy grants)
Entité participante : University of Bristol — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 148187.25 €

The stability of the Greenland Ice Sheet (GrIS) is a threat to coastal communities worldwide. The PIs have changed our understanding of why it darkens during the melt season, becoming increasingly deep purple due to pigmented ice algal blooms in the ice surface, producing more melt and accelerating the GrIS towards its tipping point, and increasing sea level. The next step jump in our understanding of biological darkening will be provided by DEEP PURPLE, which will establish the factors that control ice algal blooms. These factors are essential for modelling of future melting, which require a process-based understanding of blooming. DEEP PURPLE will quantify the synergies between the biology, chemistry and physics of ice algae micro-niches in rotting, melting ice, and examine the combination of factors which stabilise them. State-of-the-science analytical and observational methods will be employed to characterise the complex mosaic of wet ice habitats, dependent on factors such as the hydrology, nutrient status, particulate content and light fields within these continually evolving ice-water-particulate-microbe systems. We will quantitatively assess why and how the fine light mineral dust particulates contained within the melting ice amplify the growth of ice algae. The particulate content and composition of different layers in the GrIS is dependent on age, and so the algae that the melting ice can support may fundamentally change over time. We look back to understand if the ice biome has changed through the Anthropocene via analyse of fjord sediments. The first draft genome of ice algae will show their key adaptations to glacier surface habitats. DEEP PURPLE looks forward by providing the critical field data sets and conceptual models of ice algal growth that will facilitate the next generation of predictive models of sea level rise due to biologically enhanced melting of the GrIS.

Mots-clés : greenland ice sheet,bioalbedo,sea level rise
Projet ERC : CosmicExplorer (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Stockholm University — Pays : Suède — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1201630.0 €

The standard model of cosmology postulates ingredients that are not present in the standard model of particle physics – dark matter, dark energy, and a primordial origin for cosmic structure. Their physical nature remains a mystery. In the past few years, it has become clear that formidable modelling and data analysis challenges stand in the way of establishing how these ingredients fit into fundamental physics. Starting in 2023, we have an opportunity to uncover the physical underpinning of the cosmological model, using a new window on the universe opened by the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST). Just in its first year, LSST will see more of the universe than all previous surveys combined. By repeatedly mapping huge sky areas, it will create the first motion picture of our universe. The resulting catalogues will contain billions of galaxies and other, more exotic objects such as the electromagnetic counterparts of gravitational wave sources. This project aims to turn these catalogues into physical insight by solving three pressing challenges: (1) the formidable computational expense of accurately modelling this complex data; (2) the need to tease out subtle signals from (possibly unknown) systematics; (3) capturing the rich information in the “cosmic web” of galaxies tracing the large-scale structure of the universe, inaccessible by standard analysis methods. I will achieve these aims through a unique approach, combining innovative data emulation techniques to accelerate forward-modelling, a ground-breaking ‘explainable artificial intelligence’ approach to scientific discovery, and advanced hierarchical Bayesian methods to achieve not just precision (small error-bars) but accuracy (unbiased results). The combination of the unique tools I will develop, and LSST’s new view of the universe, opens up a vast discovery space. I will explore this space with the aim of achieving a breakthrough in our understanding of physical cosmology.

Mots-clés : survey cosmology,bayesian methods,machine learning,dark matter,dark energy,early universe
Projet ERC : BAHAMAS (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Liverpool John Moores University — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : LJMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1725982.0 €

The standard model of cosmology, the ɅCDM model, is remarkably successful at explaining a wide range of observations of our Universe. However, it is now being subjected to much more stringent tests than ever before, and recent large-scale structure (LSS) measurements appear to be in tension with its predictions. Is this tension signalling that new physics is required? For example, time-varying dark energy, or perhaps a modified theory of gravity? A contribution from massive neutrinos? Before coming to such bold conclusions we must be certain that all of the important systematic errors in the LSS tests have been accounted for. Presently, the largest source of systematic uncertainty is from the modelling of complicated astrophysical phenomena associated with galaxy formation. In particular, energetic feedback processes associated with star formation and black hole growth can heat and expel gas from collapsed structures and modify the large-scale distribution of matter. Furthermore, the LSS field is presently separated into many sub-fields (each using different models, that usually neglect feedback), preventing a coherent analysis. Cosmological hydrodynamical simulations (are the only method which) can follow all the relevant matter components and self-consistently capture the effects of feedback. I have been leading the development of large-scale simulations with physically-motivated prescriptions for feedback that are unrivalled in their ability to reproduce the observed properties of massive systems. With ERC support, I will build a team to exploit these developments, to produce a suite of simulations designed specifically for LSS cosmology applications with the effects of feedback realistically accounted for and which will allow us to unite the different LSS tests. My team and I will make the first self-consistent comparisons with the full range of LSS cosmology tests, and critically assess the evidence for physics beyond the standard model.
Projet ERC : FASDEM (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Gothenburg — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

The study of democratization lies at the center of political science and is increasingly important in economics, sociology, and history, and has become a central foreign policy objective. Yet, there is little conclusive evidence about in particular endogenous sequences of democratization critical to our ability to provide sound policy advise. FASDEM promises to revolutionize our understanding of the trajectories that fail to lead to democracy, and the pathways that are successful, by addressing two key questions: Which are the failing versus successful sequences of democratization? What are the determining causal relationships in these sequences? Critical is the just finalized Varieties of Democracy (V-Dem) dataset including some 350 indicators, 34 component-indices, and five main indices of varieties of democracy from 1900 to the present for 173countries – about 15 million data points on democracy. FASDEM, if funded, will use this data capitalizing on a set of novel analytical approaches, tools, and adaptations of modeling from evolutionary biology developed by a research team in a related, project, that together can establish sequences between sets of hundreds of ordinal variables. Under the second objective, FASDEM will take a step further developing upon the latest statistical methodologies of establishing causal identification in observational data, and use these to test each step of such manifest sequences. FASDEM will make a radical departure from the crude and “correlational” paradigm in democratization studies to detail and explain failing and successful sequences of democratization for the first time.
Projet ERC : COREX (Horizon 2020, appel 2020, Synergy grants)
Entité participante : University of Copenhagen — Pays : Danemark — Rôle : PI
Acronyme de l'entité : UCPH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2904917.0 €

The study of the past is undergoing a dramatic transformation: researchers in the fields of archaeology, genetics, linguistics, history and archaeometry are blurring the lines delimiting their respective fields, and working in increasingly collaborative efforts to understand how history and prehistory unfolded. Recent debates stress the need for new explanatory models which integrate both micro- and macro-level historical processes, and diverse types of datasets. We approach this challenge by applying novel modelling approaches allowing us to move from correlations to explanations of how changes have been shaped by the dynamic interaction of cultural innovation, migration, admixture, population growth and collapse, landscape transformation, dietary change, biological adaptation, social structure, and the emergence of new diseases. To achieve this overall goal the project is built upon four specific aims, which translates into four work packages: WP1: Database for C14, cultural and subsistence (including isotope) data, ancient genomes, eDNA sites, fossil pollen datasets and strontium samples WP2: Environmental DNA and high- resolution local environments,WP3 Exploratory analyses and discriminative models, WP4 Generative models and explanations. Our findings will serve to determine what the impact of the movement of people was on the European landscape, simultaneously on multiple scales: continental, regional and local, providing a research program defying the boundaries of archaeology, genetics and mathematical modelling.Thus, by identifying prehistoric regularities in the interactions of human biology, social and economic organisation, and demography we will be able to compare them to anthropological and historical models of such processes in recent times, to form a more comprehensive understanding of the nature of migration, integration and cultural change, then and now.

Mots-clés : environmental dna,generative models,discriminative models,archeological databases
Projet ERC : COREX (Horizon 2020, appel 2020, Synergy grants)
Entité participante : National Museum of Denmark — Pays : Danemark — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 456990.0 €

The study of the past is undergoing a dramatic transformation: researchers in the fields of archaeology, genetics, linguistics, history and archaeometry are blurring the lines delimiting their respective fields, and working in increasingly collaborative efforts to understand how history and prehistory unfolded. Recent debates stress the need for new explanatory models which integrate both micro- and macro-level historical processes, and diverse types of datasets. We approach this challenge by applying novel modelling approaches allowing us to move from correlations to explanations of how changes have been shaped by the dynamic interaction of cultural innovation, migration, admixture, population growth and collapse, landscape transformation, dietary change, biological adaptation, social structure, and the emergence of new diseases. To achieve this overall goal the project is built upon four specific aims, which translates into four work packages: WP1: Database for C14, cultural and subsistence (including isotope) data, ancient genomes, eDNA sites, fossil pollen datasets and strontium samples WP2: Environmental DNA and high- resolution local environments,WP3 Exploratory analyses and discriminative models, WP4 Generative models and explanations. Our findings will serve to determine what the impact of the movement of people was on the European landscape, simultaneously on multiple scales: continental, regional and local, providing a research program defying the boundaries of archaeology, genetics and mathematical modelling.Thus, by identifying prehistoric regularities in the interactions of human biology, social and economic organisation, and demography we will be able to compare them to anthropological and historical models of such processes in recent times, to form a more comprehensive understanding of the nature of migration, integration and cultural change, then and now.

Mots-clés : environmental dna,generative models,discriminative models,archeological databases
Projet ERC : HelpUS (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Royal Netherlands Academy of Arts and Sciences — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : KNAW
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

The success of humans depends on their ability to cooperate. Cooperation requires learning to avoid actions that harm others and select those that balance benefits for self and others. Reinforcement leaning captures how individuals learn to optimize benefits for themselves, by associating actions and outcomes for the self. The social context requires to incorporate outcomes for others into that equation by transforming them into the currency used to value our own outcomes. Research on empathy, by suggesting that we transform the emotions of others into neural representation of how we would feel in their stead, provides testable mechanistic hypotheses of how we do that. The painful facial expression of our friend after we kick him would be transformed into the pain we would feel when kicked, associating kicking with negative value, thereby motivating us to stop kicking. Testing this hypothesis would require altering brain activity in the anterior insula and cingulate involved in this process, and showing that these changes alter decision making. Because current tools in humans cannot selectively modulate activity in these deeper regions we however remain frustratingly powerless to do so. Here we will develop a brand new method using ultrasounds to modulate brain activity at any depth to brake down this barrier. Using fmri, we will measure vicarious activity and compare it with computational models. This will push our understanding of our social nature to a new computational level, and pave the way to a more causal understanding of prosociality that can inform successful interventions for so far untreatable antisocial disorders. More generally deep brain stimulation via US, and the understanding of how US modulate brain activity, will unleash affective neuroscience to noninvasively explore what had remained beyond our reach: the causal relationship between deeper (limbic) structures and behavior and cognition.

Mots-clés : empathy,vicarious activity,ultrasound,brain stimulation,moral decision making,prosocial behaviour
Projet ERC : MIGPACT (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Lund University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

The successful integration of the high numbers of refugees is one of the most critical issues facing the EU today. We propose to identify factors at the neighbourhood-, family-, peer-, and individual-levels that may protect immigrant children, adolescents and adults from psychiatric disorders, substance use disorders, and crime. We have access to highly accurate and almost complete nationwide sociodemographic data from 1960-2015 including, but not limited to, country of birth, education, income, employment, and social welfare, school grades, and reason for immigration linked to nationwide inpatient- and outpatient health care data, family relations, neighbourhood socioeconomic factors and indices of 250,000 neighbourhood goods and services. These timely data are available for more than 3 million 1st and 2nd generation immigrants, including over half a million more recent immigrants from the Middle East and Africa. We will apply different causal models and our novel designs (e.g., identification of deprived immigrant enclaves, deviant peer contexts, and natural experiments) to examine our aims. We are in a unique position to carry out the entire sequence of the proposed research from direct clinical observations, formulation of novel hypotheses and use of innovative analytic methods to interpretation of findings tailored to subgroups of immigrant populations. Findings from Sweden are highly relevant to the EU as around 25% of the entire population are 1st or 2nd generation immigrants. Our findings will delineate meaningful subgroups of immigrants, including refugees, similar to those in other EU countries. Based on our results, we will develop recommendations at the neighbourhood-, family-, peer-, and individual-levels that, when tailored appropriately, will help guide EU policies and strategies, thus leading to decreased strain on health and social services, improved psychiatric health and successful integration of immigrant populations.

Mots-clés : migration