Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ONco-Energetics_OFF (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : TU Dresden — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUD
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499875.0 €

Tumors reprogram their metabolism to fuel rapid growth. Glycolysis and oxidative phosphorylation “OXPHOS” are the main energy-producing pathways. For decades, metabolic reprogramming of tumors was perceived as only increased glycolysis (Warburg effect). This dogma has recently been revised as we started to realize the importance of OXPHOS in tumor metabolism. We are now entering a new era as metabolomics studies show that tumor metabolism is more heterogeneous than initially assumed. In the preparatory phase of this proposal, using an integrated transcriptional and metabolic profiling, a panel of cancer cell lines was first classified according to the bioenergetic pathway they predominantly utilize (glycolysis or OXPHOS). Second, the response of glycolytic and OXPHOS-dependent cells to the inhibition of their wired bioenergetic program was assessed. My findings show that regardless of their dependency at baseline, cancer cells can be collectively categorized according to their adaptability into “bioenergetically-committed” to one of the two pathways or “bioenergetically-plastic” cells which are able to switch from one to the other upon metabolic challenges. This proposal uses an integrated system approach to dissect the molecular signature, regulation and implications of bioenergetic plasticity. We will answer three key questions: 1-Why some cancer cells are bioenergetically-plastic while others are committed? What are the differences in metabolic machineries and oncogenic switches between both? 2-How heterogeneous tumor cell subpopulations are in terms of bioenergetic plasticity? Does metabolic crosstalk contribute to bioenergetic plasticity of tumors? 3-What are the implications of bioenergetic plasticity in drug resistance and metastasis and finally how to design approaches to target this plasticity? Only handful drugs targeting tumor energetics have made it to clinical use. ONco-Energetics_OFF has a realistic and immediate translational potential.

Mots-clés : tumor metabolism,bioenergetics,plasticity,glycolysis,oxidative phosphorylation,mitochondrial respiration,oxphos,mcl 1,mtorc1,pp2a,metformin,fasting,drug resistance,metastasis
Projet ERC : UniTED (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 275625.0 €

Turbulence governs essentially all large-scale flows on our planet, including our atmosphere and oceans. With a vast number of engineering applications in transportation technology, renewable energies, and more, turbulence has a direct impact on our lives. However, developing predictive theories of turbulence, which ultimately all modeling applications rely on, remains one of the outstanding scientific challenges. Moreover, while massive simulations on the largest supercomputers are nowadays an established tool, reaching realistically high Reynolds numbers remains prohibitive. Already today, analyzing the sheer amount of peta-scale simulation data requires new paradigms for making meaningful progress. Fundamentally new approaches are needed to achieve a breakthrough. UniTED will deliver such an approach by a unique, synergistic combination of data-driven theory and large-scale computations. How? Recently, I showed that the complex statistics of turbulence can be disentangled into much simpler sub-ensembles. This significant reduction of complexity points toward exciting new theoretical pathways and novel computational methodologies, which I will explore in this project. In UniTED, we will (A) dissect the multi-scale structure of turbulence through massively parallel computations. This will (B) provide the foundation for a statistical theory of turbulence which is based on a novel ensemble decomposition approach. Combining (A) and (B), we will (C) develop a novel ensemble-based simulation approach, enabling unprecedented insights into turbulence at high Reynolds numbers. We will then use this approach to (D) provide big data for modeling small-scale turbulence using physics-informed machine learning. UniTED will boost our fundamental understanding of turbulence at very high Reynolds numbers and provide new modeling approaches in a breadth of fields such as computational engineering, the Earth sciences, renewable energy, and plasma physics.

Mots-clés : turbulence,computational fluid dynamics,statistical field theory,reduced order models
Projet ERC : UltimateRB (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : University of Twente — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499375.0 €

Turbulent thermal convection plays an important role in a wide range of natural and industrial settings, from astrophysical and geophysical flows to process engineering. The paradigmatic representation of thermal convection is Rayleigh-Bénard (RB) flow in which a layer of fluid is heated from below and cooled from above. A major challenge is to determine the scaling relation of the Nusselt number (Nu), i.e. the dimensionless heat transport, with the Rayleigh number (Ra), which is the dimensionless temperature difference between the two plates, expressed as Nu∼Ra^γ. Theory predicts that the scaling exponent γ increases for extremely strong driving when the boundary layers transition from laminar to turbulent. Understanding the transition to this so-called ‘ultimate’ regime is crucial since an extrapolation of results from lab-scale experiments and simulations to astro- and geophysical phenomena becomes meaningless when the transition to this ‘ultimate’ state is not understood. So far, there is no consensus among experimental efforts for obtaining the ‘ultimate’ regime. We propose using direct numerical simulations (DNS) to gain a better understanding of the transition towards the ‘ultimate’ regime. While obtaining ‘ultimate’ thermal convection in simulations has been elusive, new developments make this feasible now. The benefit of simulations is that they allow full access to the flow and temperature fields, while all boundary conditions are set exactly and independently. This allows us to test various physical effects at full dynamic similarity. To trigger the excitation of the ‘ultimate’ regime at lower Ra than in standard small aspect ratio cells, we want to study the effect of roughness, additional shear, and large domains in which a stronger flow can develop than in confined small aspect ratio cells that are traditionally considered. The addition of rotation will be studied to disentangle the complicated effect of rotation on high Ra number thermal convection.

Mots-clés : rayleigh benard convection,turbulence,fluid dynamics,heat transfer,direct numerical simulations,high performance computing
Projet ERC : CompDB (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1918750.0 €

Two major hardware trends have a significant impact on the architecture of database management systems (DBMSs): First, main memory sizes continue to grow significantly. Machines with 1TB of main memory and more are readily available at a relatively low price. Second, the number of cores in a system continues to grow, from currently 64 and more to hundreds in the near future. This trend offers radically new opportunities for both business and science. It promises to allow for information-at-your-fingertips, i.e., large volumes of data can be analyzed and deeply explored online, in parallel to regular transaction processing. Currently, deep data exploration is performed outside of the database system which necessitates huge data transfers. This impedes the processing such that real-time interactive exploration is impossible. These new hardware capabilities now allow to build a true computational database system that integrates deep exploration functionality at the source of the data. This will lead to a drastic shift in how users interact with data, as for the first time interactive data exploration becomes possible at a massive scale. Unfortunately, traditional DBMSs are simply not capable to tackle these new challenges. Traditional techniques like interpreted code execution for query processing become a severe bottleneck in the presence of such massive parallelism, causing poor utilization of the hardware. I pursue a radically different approach: Instead of adapting the traditional, disk-based approaches, I am integrating a new just-in-time compilation framework into the in-memory database that directly exploits the abundant, parallel hardware for large-scale data processing and exploration. By explicitly utilizing cores, I will be able to build a powerful computational database engine that scales the entire spectrum of data processing - from transactional to analytical to exploration workflows - far beyond traditional architectures.

Mots-clés : database management systems,query processing,query optimization
Projet ERC : RLeap (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Pompeu Fabra University — Pays : Espagne — Rôle : Partner
Acronyme de l'entité : UPF
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 671299.85 €

Two of the main research threads in AI revolve around the development of data-based learners capable of inferring behavior and functions from experience and data, and model-based solvers capable of tackling well-defined but intractable models like SAT, classical planning, and Bayesian networks. Learners, and in particular deep learners, have achieved considerable success but result in black boxes that do not have the flexibility, transparency, and generality of their model-based counterparts. Solvers, on the other hand, require models which are hard to build by hand. RLeap is aimed at achieving an integration of learners and solvers in the context of planning by addressing and solving the problem of learning first-order planning representations from raw perceptions alone without using any prior symbolic knowledge. The ability to construct first-order symbolic representations and using them for expressing, communicating, achieving, and recognizing goals is a main component of human intelligence and a fundamental, open research problem in AI. The success of RLeap requires the development of radically new ideas and methods that will build on those of a number of related areas that include planning, learning, knowledge representation, combinatorial optimization and SAT. The approach to be pursued is based on a clear separation between learning the symbolic representations themselves, that is cast as a combinatorial problem, and learning the interpretations of those representations, that is cast as a supervised learning problem from targets obtained from the first part. RLeap will address both problems, not just in the planning setting but in the generalized planning setting as well where plans are general strategies. The project can make a significant difference in how general, explainable, and trustworthy AI can be understood and achieved. The PI has made key contribution to the main themes of the project that make him uniquely qualified to carry it forward.

Mots-clés : planning,learning symbolic representations from data
Projet ERC : FLATLAND (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 2640632.89 €

Two-dimensional crystalline materials exhibit exceptional physical properties and offer fascinating potential as fundamental building blocks for future two-dimensional electronic and optoelectronic devices. Transition metal dichalcogenides (TMDCs) are of particular interest as they show a variety of many-body phenomena and correlation effects. Key properties are: i) additional internal degrees of freedom of the electrons, described as valley pseudospin and layer pseudospin, ii) electronic many-body effects like strongly-bound excitons and trions, and iii) electron-lattice correlations like polarons. While these phenomena represent intriguing fundamental solid state physics problems, they are of great practical importance in view of the envisioned nanoscopic devices based on two-dimensional materials. The experimental research project FLATLAND will address the exotic spin-valley-layer correlations in few-layer thick TMDC crystals and TMDC-based heterostructures. The latter comprise other 2D materials, organic crystals, metals and phase change materials as second constituent. Microscopic coupling and correlation effects, both within pure materials as well as across the interface of heterostructures, will be accessed by time- and angle-resolved extreme ultraviolet-photoelectron spectroscopy, femtosecond electron diffraction, and time-resolved optical spectroscopies. The project promises unprecedented insight into the microscopic coupling mechanisms governing the performance of van der Waals-bonded devices.

Mots-clés : two dimensional materials,ultrafast photoelectron spectroscopy,time resolved diffraction,van der waals bonded heterostructures
Projet ERC : FOCUS (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Université de Brest — Pays : France — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 51750.0 €

Two-thirds of the Earth’s surface is covered by water and thus largely inaccessible to modern networks of seismological instruments. The FOCUS project is poised to revolutionize seismic monitoring of the seafloor through a novel use of fiber optic cables to improve hazard assessment and increase early warning capability. Laser reflectometry using BOTDR, commonly used for structural health monitoring of large-scale engineering structures (e.g. - bridges, dams, pipelines, etc.), can measure very small strains (< 1 mm) at very large distances (10 - 200 km). It has never been used to monitor deformation caused by active faults on the seafloor. The objective of the FOCUS project is to demonstrate that this technique can measure small (1 - 2 cm) displacements on a primary test site offshore Sicily where the 28 km long EMSO Catania cable crosses the recently mapped North Alfeo Fault. BOTDR observations must be calibrated by other independent measurements. Therefore, targeted marine geophysical surveys of the seafloor along the trace of the cable and faults are planned, with micro-bathymetry, high-resolution seismics, seafloor seismic stations and use of seafloor geodetic instruments to quantify fault displacement. Once the BOTDR fault-monitoring technique has been tested and calibrated offshore Sicily, the goal is to expand it to other fiber optic cable networks, either existing research networks in earthquake hazard zones (Japan, Cascadia) or to the Mediterranean region through access to retired telecommunication cables, or through the development of dual-use cables with industry partners, (two of the anticipated outcomes of the FOCUS project). The novel secondary use of fiber optic cables as described by FOCUS represents a potentially tremendous breakthrough in seismology, tectonics and natural hazard early warning capability, one that could turn Earth’s future undersea communication infrastructure into a seismological monitoring network of unprecedented scale.

Mots-clés : earthquake hazard,active faults,seafloor deformation,montitoring,fiber optic cables,laser reflectometry,botdr,strain measurements,mediterranean,sicily,ionian sea
Projet ERC : Reg-Seq (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
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 : 1500000.0 €

Type 2 diabetes (T2D) is a complex systemic metabolic disorder which has developed into a global major health problem responsible for early morbidities and mortality. T2D is a multifactorial disease, resulting from progressive alteration of insulin secretion from beta cells in pancreatic islets, on a background of resistance to insulin action in various organs and tissues, including liver, skeletal muscle and adipose tissue. T2D heritability is estimated around 40-70%. Genome-wide association studies identified more than 90 T2D-associated common variants, but altogether they explain less than 15% of T2D inheritance. Rare loss-of-function coding variants may contribute to T2D risk. Moreover, recent studies suggested the putative impact on T2D risk of functional non-coding variants within active enhancers of pancreatic islets; but tissue-specific regulatory regions have remained largely unexplored by genetic epidemiology studies. I intend to make progress in T2D genetic epidemiology and physiology by extending genetic investigation to frequent and rare mutations in non-coding regulatory regions on a whole-genome basis. In the Reg-Seq project, I propose the next-generation sequencing (NGS) of most relevant DNA regulatory sequences of four key metabolic tissues for T2D (pancreatic islets, liver, muscle and adipose tissue) in large well-phenotyped prospective populations (N=10,000 samples), followed by a replication in additional cohorts and by comprehensive functional experiments when genetic associations are identified. This project should lead to the identification of new functional genetic markers and pathways involved in T2D risk and development, and should help to stratify the T2D population for precision medicine, which is one of the major goals of the EU-Horizon 2020 programme. Further elucidation of the missing heritability should enable a major advance in the prediction of T2D risk, which is still very poor for a genuine clinical translation.

Mots-clés : type 2 diabetes,genetics
Projet ERC : OptoBETA (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University of Birmingham — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1681468.0 €

Type 2 diabetes mellitus, one of the major healthcare challenges of our time, is characterized by failure of beta cells to functionally adapt to increased peripheral insulin resistance. The resulting chronic elevations in blood glucose concentration are associated with heart, kidney, liver, nerve and retinal disease, as well as cancer. Here, by combining novel optogenetic, photopharmacological and innovative imaging approaches, we aim to unravel the complexity underlying the multicellular regulation of insulin secretion from islets of Langerhans during health and disease. In particular, we will examine a role for privileged pacemakers/hubs in orchestrating population responses to stimuli, identify what makes these specialized cells unique at the RNA/protein level, and understand how they contribute to islet development and failure. Furthermore, we will address whether the intraislet regulation of insulin secretion operates in vivo to determine glucose homeostasis, focusing on the neural-endocrine interface. Lastly, the mechanisms underlying islet cross-talk will be investigated directly in situ within the pancreas of living mice, paying close attention to the roles of the vasculature and secreted factors. As such, these studies should unveil a new route for restoration of insulin secretion in man, as well as provide the foundation for the de novo construction of islets for transplantation.

Mots-clés : type 2 diabetes,beta cell,islet
Projet ERC : UNIVERSAL HEALTH (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
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 : 1484797.0 €

UNIVERSAL HEALTH is an anthropological study that follows how a new global policy, Universal Health Coverage (UHC), travels and is engaged by policy-makers, bureaucrats and citizens in three African countries. Defined by the WHO as ensuring that all people can use the health services they need without financial hardship, UHC is a powerful concept that approaches public health as a matter of justice and obligation and is included in the Sustainable Development Goals. UHC is particularly important in Africa, where structural-adjustment policies undermined state capacity, promoted privatization and pushed the burden of payment onto the poor. Recent global health initiatives have done little to address the neglect of national health-care systems and citizens’ lack of trust in them. In these contexts UHC is interesting because it reinserts questions of state responsibility and the public good into health-care. Historically however, African states have only partially pursued the public good, while in practice UHC is surrounding by conflicting interests. UHC is thus not a universal model but a contested field, making it an intriguing site for anthropological research. With a focus on actors and institutions at global, national and local levels in each country, the project will explore how moves towards UHC engage relations between states and citizens and universal concepts such as the public good; how UHC intersects with formal systems of social protection; and how it influences informal social networks that support health, thus situating UHC in national histories and social practices. Tracking the frictions surrounding UHC at the levels of policy-making, implementation, among beneficiaries, and in public debate, the project will use ethnographic methodology in innovative ways through fieldwork that is multi-sited and multi-level. The project’s focus on a global policy and the public good opens new research directions and will produce knowledge of relevance beyond Africa.

Mots-clés : social anthropology,african studies,medical anthropology,critical global health,anthropology of the state,development studies,postcolonial studies,ethnography of policy,welfare