Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SYSAGING (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : Centre for Genomic Regulation — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CRG;CRG-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 1499981.0 €

A central goal of molecular medicine is to understand how genetics, diet, and environment interact to determine health. However, most complex diseases arise from slow, stochastic changes involving large numbers of genes, making it difficult to systematically develop preventative therapies. To study the early and mid-life origins of late-life diseases, we need new methods capable of measuring the high-dimensional dynamics of physiologic change during aging. C. elegans is a small, fast-aging animal and a powerful model for asking fundamental questions about the conserved molecular origins of complex diseases. However, it is not yet feasible to systematically collect molecular and phenotypic time-series at the precision and scale needed to build quantitative dynamic models of aging. Recently, I developed an automated microscopy and image processing technology that allows life-long observation of large populations. In this proposal, we develop this prototype into an integrative platform combining transcriptomic profiling, in vivo biosensors, and new imaging technology. Collecting data at multiple spatial scales—molecules, cells, individuals, and populations—we can map the causal steps through which slow, stochastic molecular changes drive increases in disease risk. We will then apply this method at scale to characterize all known lifespan-altering interventions in C. elegans, including many being explored for clinical application. Combining molecular genetics with theoretic approaches, we will build quantitative models of how complex diseases emerge from slow molecular-level changes, and make methodological progress toward rapid characterization of the determinants of age-associated diseases. This work will help isolate the physiologic changes whose disruption delays aging and reduces disease risk, including new targets for preventative therapies.

Mots-clés : ageing,health,lifespan,age related diseases,interventions in ageing,fundamental mechanisms of ageing,dynamical systems,stochastic processes,causality,statistical inference,complexity theory,microscopy,fluorescent imaging,longitudinal imaging,genetics,molecular genetics,transcriptomics,single cell sequencing,caenorhabditis elegans,nematodes
Projet ERC : REVOLT (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Bristol — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1592522.0 €

A central part of scientific enquiry involves constructing representations of the world. Representations can take many forms, including diagrams, taxonomies, verbal descriptions, physical models, and abstract mathematical models. Thus a diagram of the solar system, a taxonomy of Alpine flora, a ball-and-stick model of a chemical substance, and a mathematical model of the spread of a disease are all examples of representations. Different though they are, each of these scientific constructs aims to represent some system in the world (the “target system”) and can be assessed for how well they achieve this aim. The aim of my project is to examine how biological evolution has been represented – diagrammatically, verbally and mathematically – in the scientific literature, past and present. A further aim is to examine representations of evolution in the context of pedagogy and science communication. “Biological evolution” is taken to include the process of descent with modification that Darwin first described; the mechanisms that drive the evolutionary process such as natural selection; and the products to which the process has given rise, such as adaptation and diversity. Scientists have constructed representations of each of these elements in their quest to understand how evolution works. My project will offer a systematic study of these representations from an overarching philosophical perspective. The importance of the project lies in its integrative ambition. The project will bring together philosophical ideas about the nature of representation and idealization, linguistic ideas about metaphor and analogy, psychological ideas about reasoning and cognitive biases, and educational ideas about science communication. By drawing on such a diverse range of ideas, the project will deepen our understanding of how evolution is, has been, and should be represented. The results will of interest to both philosophers of science and scientific practitioners.
Projet ERC : ACE-OF-SPACE (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 497883.74 €

A central problem in developmental biology is to understand how tissues are patterned in time and space - how do identical cells differentiate to form the adult body plan? Patterns often arise from prior asymmetries in developing embryos, but there is also increasing evidence for self-organizing mechanisms that can break the symmetry of an initially homogeneous cell population. These patterning processes are mediated by a small number of signaling molecules, including the TGF-β superfamily members BMP and Nodal. While we have begun to analyze how biophysical properties such as signal diffusion and stability contribute to axis formation and tissue allocation during vertebrate embryogenesis, three key questions remain. First, how does signaling cross-talk control robust patterning in developing tissues? Opposing sources of Nodal and BMP are sufficient to produce secondary zebrafish axes, but it is unclear how the signals interact to orchestrate this mysterious process. Second, how do signaling systems self-organize to pattern tissues in the absence of prior asymmetries? Recent evidence indicates that axis formation in mammalian embryos is independent of maternal and extra-embryonic tissues, but the mechanism underlying this self-organized patterning is unknown. Third, what are the minimal requirements to engineer synthetic self-organizing systems? Our theoretical analyses suggest that self-organizing reaction-diffusion systems are more common and robust than previously thought, but this has so far not been experimentally demonstrated. We will address these questions in zebrafish embryos, mouse embryonic stem cells, and bacterial colonies using a combination of quantitative imaging, optogenetics, mathematical modeling, and synthetic biology. In addition to providing insights into signaling and development, this high-risk/high-gain approach opens exciting new strategies for tissue engineering by providing asymmetric or temporally regulated signaling in organ precursors.

Mots-clés : embryonic development,signal transduction,zebrafish,systems biology,self organization
Projet ERC : GLOBALPROD (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of Oslo — Pays : Norvège — Rôle : PI
Acronyme de l'entité : UiO
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1476948.0 €

A defining feature of the global economy is the gradual fragmentation of production across firms and borders, a phenomenon that has been termed outsourcing or global value chains. State-of-the-art empirical economic analysis on value chains has mostly been limited to the study of aggregate data because there is limited data on actual firm-to-firm linkages in the global economy. Even less is currently known about which products are typically outsourced, and which workers are affected. This project will change that. I will bring together four unique firm-to-firm datasets on local and global value chains that will push the research frontier forward in two main directions: - Previous research has shown that economic integration encourages growth. Due to data limitations, however, we know little about the origins of growth, and to what extent the emergence of value chains can explain the growth response. New theory is needed, where firm-to-firm connections are endogenously formed in response to economic integration. I will confront theory with data and directly test whether integration facilitates new buyer-supplier relationships and growth. - Previous research has found that economic integration has large negative effects on wages for low-skill workers. But again, due to data limitations, it is unclear to what extent value chains are responsible for this. Simply put, the impact of outsourcing on wages will depend on which workers are displaced by outsourcing. Until now, researchers have not been able to observe which workers, along with their occupations and skills, that are employed in both the supplying and outsourcing firm. For the first time, this information will be available, allowing for a rich analysis of labor market effects for different skill groups. GLOBALPROD will inform policymakers about how wages for different types of skills change in response to globalization, but also how economic integration can promote efficiency and competitiveness.

Mots-clés : outsourcing,value chains,productivity,skill premium
Projet ERC : PIPE (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Aalto University — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1858013.0 €

A fascinating tension exists between computer vision and computer graphics. Decades of research efforts have led to the ability of graphics algorithms to simulate the world to a degree often indistinguishable from reality -- given an accurate enough model of scene geometry and appearance. Similarly, decades of ingenuity have given computer vision techniques the already, at times, superhuman capability of detecting, recognizing, and predicting objects, actions, and identities from pictures or video. Vision and graphics meet at a common point of pain: the model of scene geometry and appearance. To yield photorealistic results, graphics algorithms require an essentially perfect forward model. Yet, the capability of computer vision algorithms to robustly and accurately reason about the 3D shape and appearance of the world, unfortunately, greatly lags behind the capabilities to detect, recognize, segment, and so on. A great discrepancy exists between the semantic and the pixel-perfect, accurate shape and appearance. Bridging this chasm is the goal of this research. This entails solving fundamental, long-standing, unsolved problems in computer vision through the aid of computer graphics and machine learning}. First, we seek to simultaneously capture accurate 3D shape and appearance of complex real-world scenes from photographic inputs; second, we seek to extend these capabilities still further to``zero-shot'' generative modelling. These extremely ambitious goals will be reached by marrying simulation (rendering) and machine learning, building on the PI's three existing strengths: (1) ability to capture photorealistic material appearance models using commodity devices; (2) his leading standing in physically-based image synthesis; and (3) his results on generative modeling of photorealistic images through deep convolutional neural networks.
Projet ERC : PLASTINET (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : University of Cambridge — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 168204.2 €

A few days after fertilisation mammalian embryos form a blastocyst comprised of three tissues; trophoblast and hypoblast are the forebears of extraembryonic structures, while naive epiblast cell are the pluripotent source of the embryo proper. Classical mouse embryological studies indicate that lineage potencies are determined concomitant with segregation of the three founder tissues. Textbook definitions of pluripotency thus exclude extraembryonic potential. Consistent with this paradigm, mouse embryonic stem cells are generally ineffective in producing trophoblast or hypoblast derivatives. However, we have discovered that human naïve pluripotent cells have high intrinsic competence for trophoblast formation. Furthermore, unlike in mouse, extraembryonic transcription factors are present in human epiblast in vivo. These findings challenge the dogma of early lineage restriction but may be compatible with the ancestral origin of pluripotency. We hypothesise that extraembryonic plasticity underlaid by entwined regulatory networks is the evolutionary template of pluripotency. Consequently, signal modulation to suppress extraembryonic specification may be crucial for capture of stem cells representative of naïve epiblast in most mammals. We will examine human and non-human primates, farm animals in which embryos undergo extended development before implantation, and a marsupial in which pluripotent cells are generated from the trophoblast. In a cross-disciplinary approach we will employ transcriptomics, embryo and stem cell experimentation, and formal computational modelling to uncover the core biological program moulded by evolution into different forms. We aim to establish hitherto elusive chimaera-competent embryonic stem cells from species of importance for research, biomedical applications and livestock improvement. We will obtain fresh insight into the molecular logic governing early development, lineage plasticity, pluripotent identity, and stem cell self-renewal.

Mots-clés : logical modelling,mammalian embryo,lineage specification and commitment,pluripotency,self renewal
Projet ERC : PLASTINET (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : University of Exeter — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2331765.8 €

A few days after fertilisation mammalian embryos form a blastocyst comprised of three tissues; trophoblast and hypoblast are the forebears of extraembryonic structures, while naive epiblast cell are the pluripotent source of the embryo proper. Classical mouse embryological studies indicate that lineage potencies are determined concomitant with segregation of the three founder tissues. Textbook definitions of pluripotency thus exclude extraembryonic potential. Consistent with this paradigm, mouse embryonic stem cells are generally ineffective in producing trophoblast or hypoblast derivatives. However, we have discovered that human naïve pluripotent cells have high intrinsic competence for trophoblast formation. Furthermore, unlike in mouse, extraembryonic transcription factors are present in human epiblast in vivo. These findings challenge the dogma of early lineage restriction but may be compatible with the ancestral origin of pluripotency. We hypothesise that extraembryonic plasticity underlaid by entwined regulatory networks is the evolutionary template of pluripotency. Consequently, signal modulation to suppress extraembryonic specification may be crucial for capture of stem cells representative of naïve epiblast in most mammals. We will examine human and non-human primates, farm animals in which embryos undergo extended development before implantation, and a marsupial in which pluripotent cells are generated from the trophoblast. In a cross-disciplinary approach we will employ transcriptomics, embryo and stem cell experimentation, and formal computational modelling to uncover the core biological program moulded by evolution into different forms. We aim to establish hitherto elusive chimaera-competent embryonic stem cells from species of importance for research, biomedical applications and livestock improvement. We will obtain fresh insight into the molecular logic governing early development, lineage plasticity, pluripotent identity, and stem cell self-renewal.

Mots-clés : logical modelling,mammalian embryo,lineage specification and commitment,pluripotency,self renewal
Projet ERC : HEFT (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Klagenfurt — Pays : Autriche — Rôle : Partner
Acronyme de l'entité : AAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

A forest transition, i.e. forest expansion after a long period of deforestation, has occurred in many, mostly industrialized countries. Forest transitions have recently resulted in declining rates of global net deforestation and contributed to carbon (C) sinks in terrestrial ecosystems. Studies have shown the concurrence of forest transitions and industrialization processes, but the systemic links between forest transitions, their underlying socio-metabolic processes and associated greenhouse gas (GHG) emissions have been neither systematically explored nor quantified. HEFT introduces the idea of “hidden emissions of forest transitions”, i.e. the GHG emissions from socio-metabolic processes reducing pressures on forests. Hidden emissions may stem from processes such as substitution of fuelwood by modern energy sources, intensification of agriculture, and externalization of biomass production to remote regions. Building on the concept of socio-ecological metabolism, HEFT develops a consistent methodological framework to quantify the full GHG emissions and sinks from socio-metabolic and ecological processes in the course of forest transitions, within which their hidden emissions are identified. Forest transitions in multiple contexts are analyzed at local, national and supranational scales: in Europe since c. 1850, North America since c. 1880, and South East Asia since 1980. A coarse global-scale assessment complements the regional case studies. We will integrate sources and analytical methods from environmental and social sciences as well as the humanities to analyze context-specific trajectories and general features of socio-ecological GHG budgets and their respective socio-political contexts since the onset of forest transitions. The sound understanding of hidden emissions will be used to identify the least GHG-intensive trajectories and to draw lessons for future climate-friendly forest transitions.

Mots-clés : forest transition,socio ecological metabolism,land use change,full carbon accounting,long term socio ecological research
Projet ERC : MeSoMat (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
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 : 1899333.0 €

A fundamental difference between man-made and living matter is metabolism: the ability to dissipate chemical energy to drive many different chemical processes out of equilibrium. Metabolism endows chemical systems within living organisms with properties that are standard in biology but odd in chemistry: the capability to process information, to move and to react to the external world. My goal is to endow soft materials with dynamic life-like properties. I have chosen four: molecular computation, movement, self-construction and the capacity to entertain complex chemical conversations with living cells. To do so I will embed stimuli-responsive materials with a biocompatible synthetic metabolism capable of sustaining autonomous chemical feedback loops that process information and perform autonomous macroscopic actions. My approach combines concepts from systems chemistry, synthetic biology and DNA molecular programming with soft materials and uses a biochemical system that I have contributed to pioneer: DNA/enzyme active solutions that remain out of equilibrium by consuming a chemical fuel with non-trivial reaction kinetics. This system has three unique properties: programmability, biocompatibility and a long-term metabolic autonomy. Metabolic matter will be assembled in two stages: i) enabling metabolic materials with dynamic chemical, biological and mechanical responses, and ii) creating metabolic materials with unprecedented properties, in particular, the capacity of self-construction, which I will seek by emulating embryogenesis, and the ability to autonomously pattern a community of living cells. By doing this I will create for the first time chemical matter that is both dynamically and structurally complex, thus bringing into the realm of synthetic chemistry behaviors that so far only existed in biological systems. In the long term, metabolic matter could provide revolutionary solutions for soft robotics and tissue engineering

Mots-clés : dna nanotechnology,molecular programming,reaction diffusion,morphogenesis,non linear chemistry
Projet ERC : uEcologies (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Cambridge — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1210513.81 €

A fundamental dimension of planetary urbanization is its radical transformation of nature. Domestic animals now make up more than twice the biomass of humans on the planet. They are vital to livelihoods of the urban poor in the global south, providing economic opportunities, yet posing zoonotic risks. In contrast, cities of the north are marked by the paucity of animals and concomitant health concerns. Yet, urban ecologies – relations between people and animals, and their interactions with the built environment – have received scant systematic attention in the social sciences. The objective of this project is to lay bare how regulating nonhuman life is fundamental to governing global cities. How are human-animal dynamics differentially composed in cities of the global south and north? What social, economic and spatial forces structure these dynamics? Most global cities regulate animal presence, albeit with varying degrees of success. How then might an expanded notion of urban governance incorporating ecology reorient urban studies? And finally, how might such an analysis help promote resilient and sustainable cities? The project tackles these questions through a comparative analysis focused on New Delhi, Guwahati and London. Using a combination of conventional ethnographic research methods and innovative ecological perspectives, it will generate novel explanatory concepts for understanding urban ecologies and their implications for governing global cities. This research is ground-breaking in four ways: 1) by addressing an uncharted but critical field of human action, it sheds new light on urban governance; 2) by integrating adjacent disciplines that seldom interact, it pushes the frontiers of urban studies; 3) by combining social and ecological perspectives, it adds to methodological innovation in the social sciences; 4) by accounting for how ecology shapes marginalized lives, it contributes to new agendas of making cities resilient for the urban poor.

Mots-clés : political ecology,urban,governance,animals,comparison,ethnography