Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SOLID (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Ludwig-Maximilians-Universität München — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498400.0 €

The goal of SOLID is the systematic mapping of genetic suppression for important organelles with impaired fidelity in human disease to uncover new strategies to correct the perturbed state. Functioning of the eukaryotic cell relies on the concerted activity of biological machines, defects in which can cause incurable human disease, including metabolic disorders and neurodegeneration. This is exemplified by malfunctioning mitochondria or lysosomes, for which (alongside environmental triggers) hundreds of causative genes have been identified, but cures are mostly lacking. This is mainly due to the difficulty of drugging loss-of-function mutations, which uniquely alter or entirely remove the gene product. Extensive studies in yeast and initial work in the human system show that cellular modules contain a substantial amount of hidden genetic suppression. Revealing suppressors of disease-defining features of organelle perturbation and targeting those instead of the query mutations, will address the frustrations of drugging an absent factor and etiological diversity. Until now, mutation-based genome-wide suppressor surveys were mostly limited to model organisms and phenotypes yielding growth defects, due to technical hurdles associated with recessive genetics in the human system. However, with the development of a groundbreaking new forward genetics platform that combines genome engineering, ultradeep haploid mutagenesis and direct stratification of fixed mutants, we can now, for the first time, interrogate genetic suppression of human organelle defects independent of cellular fitness. SOLID will also develop new technology to study organelle fidelity in an exhaustive fashion that departs from a gene-centric view point and captures complex phenotypes. Altogether, this will create a new paradigm of 'studying cell biology via genetics' widely applicable to many different biological questions, and reveal urgently needed novel therapeutic possibilities for incurable diseases.

Mots-clés : human haploid mutagenesis,genetic suppression,genetic interactions,facs based profiling,non fitness phenotypes
Projet ERC : SPHERES (Horizon 2020, appel 2019, Synergy grants)
Entité participante : Université Côte d'Azur — Pays : France — Rôle : Partner
Acronyme de l'entité : UCA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 120956.25 €

The goal of SPHERES is to understand the dynamics and consequences of adipocyte hypertrophy (enlargement) through investigation of its large lipid droplet (LD). The adipocyte LD is a unique organelle specialized in storing energy in triglycerides (TGs). Its surface is composed of a phospholipid monolayer and specific LD-associated proteins (such as perilipins, CIDEs and lipases), which jointly regulate LD stability and TG turnover. Adipocyte hypertrophy due to an increase in LD size may, irrespective of body fat mass, cause a wide range of pathological conditions, notably cardiometabolic diseases. SPHERES PIs (Langin, Rydén, Antonny) postulate that disturbances in the interactions between LD proteins and LD lipid composition lead to adipocyte hypertrophy and its deleterious consequences. We have identified three fundamental unanswered questions: what determines the unique structure and dynamics of large LD; why does increased LD size alter the functional phenotype of the adipocyte; which factors cause inter-individual variations in LD size. To address these questions, SPHERES gathers expertise in clinical and cellular studies on human adipocytes, in/ex vivo investigations in mouse models, and biophysical analyses of LDs. At the core of this application is the development of beyond-state-of-the-art models and methods (spheroid cultures, native large LD preparation and reconstitution, proximity labelling of LD proteins, gene editing in cell and mouse models, and advanced LD imaging), only achievable through joint integrated effort of the PIs and co-workers. Spanning from molecular, cellular to the whole-body level, SPHERES will link new knowledge on the formation and maintenance of large adipocyte LDs to the deleterious impact of adipocyte hypertrophy. Altogether, SPHERES has a strong potential to discover novel pathogenic mechanisms, leading to a better understanding of highly prevalent diseases and identification of therapeutic strategies targeting adipocytes.
Projet ERC : SPHERES (Horizon 2020, appel 2019, Synergy grants)
Entité participante : Université de Toulouse — Pays : France — Rôle : CO-PI
Acronyme de l'entité : UT
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3326680.92 €

The goal of SPHERES is to understand the dynamics and consequences of adipocyte hypertrophy (enlargement) through investigation of its large lipid droplet (LD). The adipocyte LD is a unique organelle specialized in storing energy in triglycerides (TGs). Its surface is composed of a phospholipid monolayer and specific LD-associated proteins (such as perilipins, CIDEs and lipases), which jointly regulate LD stability and TG turnover. Adipocyte hypertrophy due to an increase in LD size may, irrespective of body fat mass, cause a wide range of pathological conditions, notably cardiometabolic diseases. SPHERES PIs (Langin, Rydén, Antonny) postulate that disturbances in the interactions between LD proteins and LD lipid composition lead to adipocyte hypertrophy and its deleterious consequences. We have identified three fundamental unanswered questions: what determines the unique structure and dynamics of large LD; why does increased LD size alter the functional phenotype of the adipocyte; which factors cause inter-individual variations in LD size. To address these questions, SPHERES gathers expertise in clinical and cellular studies on human adipocytes, in/ex vivo investigations in mouse models, and biophysical analyses of LDs. At the core of this application is the development of beyond-state-of-the-art models and methods (spheroid cultures, native large LD preparation and reconstitution, proximity labelling of LD proteins, gene editing in cell and mouse models, and advanced LD imaging), only achievable through joint integrated effort of the PIs and co-workers. Spanning from molecular, cellular to the whole-body level, SPHERES will link new knowledge on the formation and maintenance of large adipocyte LDs to the deleterious impact of adipocyte hypertrophy. Altogether, SPHERES has a strong potential to discover novel pathogenic mechanisms, leading to a better understanding of highly prevalent diseases and identification of therapeutic strategies targeting adipocytes.
Projet ERC : UFSD (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : University of Eastern Piedmont Amadeo Avogadro — Pays : Italie — Rôle : Partner
Acronyme de l'entité : UNIPMN
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 50000.0 €

The goal of our project is to empower a broad range of research fields with a completely new particle detector, able to concurrently deliver time resolutions of the order of ~10 picoseconds and position resolutions of ~30 microns. In so doing, we will remove the constrains that many applications such as particle tracking, medical PET, mass spectroscopy, and beam monitoring have due to the lack of precise information on all 4 dimensions. Our analysis of state-of-the-art particle detectors has shown a dichotomy: specialized sensors measure very accurately either time or position, but not both: the ambitious goal of UFSD is to create a new family of detectors, based on controlled charge multiplication in silicon, which will remove this limitation. We will have to tackle significant challenges along this research path, but our simulations and prototypes indicate that this approach has the potentiality to radically transform present detectors and to enable many applications to reach their peak performances. Our ultimate goal -- a highly segmented detector with a space resolution of ~30 microns and a time resolution of ~10 picoseconds -- can be achieved only by developing full custom Very Large Scale Integrated chips that, matching the size of the read-out to the area of each pixel sensor, will deliver unprecedented timing resolution at the pixel level. The PI, N. Cartiglia, is well known in the field of particle physics and detector development. He is currently in charge of several projects involving both new directions in physics, among which the LPCC forward physics group and the CT-PPS project at CERN, as well as new developments in instrumentation. He will lead the project leveraging on his past experience in detector development and group/grant management, his knowledge of the silicon research foundries and laboratories, and the expertise available in his home institution (INFN, Torino, Italy).

Mots-clés : ultra fast particle tracking,4dimensional tracking,silicon sensor,quartic gauge coupling
Projet ERC : DIADEPH (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Vrije Universiteit Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : VU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 120000.0 €

The goal of the DIADEPH project is to develop a “Business Proposition Package” that could enable our group to eventually bring a new non-invasive gynaecological device to market. The device holds promise to reduce the number of biopsies that are currently carried out to rule out cervical cancer, thus mitigating the pain, anxiety, and financial costs that the shortcomings of the diagnosis pathway brings today on patients, their families, and our society. Every year, more than half-a-million women are diagnosed with cervical cancer: for half of them, the diagnosis is a death sentence. This terrible disease often affects young lives: in Europe, it represents the 2nd most common form of cancer among women aged 15-44. The diagnostic evaluation starts if, during a periodical screening, the patient is found positive to high-risk Human Papilloma Virus. The patient is then primarily referred to colposcopy to look for possible signs of cervical intraepithelial neoplasia (CIN). Unfortunately, this exam leaves much to be desired: even for high grade leasions (CIN3), colposcopy gives a false negative in almost one case in three. To address the shortcomings of colposcopy, we propose a new transvaginal probe that obtains two independent neoplasia indicators: (1) a high-resolution 3D subsurface image, and (2) a quantitative assessment of its mechanical properties. The data are collected during a procedure that does not generate discomfort and is expected to provide a better diagnosis in a few minutes. We already developed a prototype for dermatological analysis, and tested it on volunteers; with this grant, we will convert the current form factor to enable transvaginal measurements. Supported by a team of physicists, engineers, medical doctors, and business developers, we will analyze the business opportunity and align all the stakeholders that are needed to go from a proof-of-concept to a market-ready product.

Mots-clés : optical coherence tomography,elastography,cervical cancer,colposcopy,gynecology,technology transfer
Projet ERC : GRAPH-IC (Horizon 2020, appel 2018, Proof of concept grants)
Entité participante : AMO (Germany) — Pays : Allemagne — Rôle : PI
Type d'entité : Autres
Financement ERC de l'entité : 149750.0 €

The goal of the Graph-IC proof of concept proposal is to verify the innovation potential of silicon-technology-integrated graphene photodetectors for high-speed and broadband light conversion. The idea of this PoC is to use such graphene photodetectors as an enabling technology for integrated optoelectronic systems with extremely high data rates. The new technology will be fully integrated and allow the utilization of the entire transmission window of optical fibers. Such systems have the potential to decisively outperform existing systems in terms of data-rate, cost and energy consumption, which are becoming major challenges in large data systems. Within this PoC, we plan to establish the viability and identify technical issues of integrated graphene photodetectors with high electrical bandwidth for optical wavelengths. Graph-IC prepares the PI and his team to embark on a very high-risk, very high-gain endeavor, where the goal is to compete in a multi-billion Euro global market. This proposal is based on the scientific results of the ERC starting grant “InteGraDe – Integrating Graphene Devices (307311)”, where the PI has demonstrated the integration of graphene with silicon technology up to the wafer scale.

Mots-clés : data communication,graphene,silicon photonics
Projet ERC : ULT-MAS-DNP (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Commissariat à l’énergie atomique et aux énergies alternatives — Pays : France — Rôle : PI
Acronyme de l'entité : CEA
Type d'entité : Recherche
Financement ERC de l'entité : 1959805.42 €

The goal of the project is to develop a new hyperpolarization approach called Magic Angle Spinning Dynamic Nuclear Polarization (MAS-DNP) to reach levels of sensitivity and resolution that have never been achieved, in order to tackle highly relevant chemical and biological questions that remain unanswered so far. Firstly this will provide major advances in NMR crystallography (solving 3D structures by NMR) by showing that distance measurements between nuclei (13C, 15N, etc.) as well as 17O quadrupolar parameters can be extracted from NMR measurements without requiring isotopic labeling. This will be applied to systems that cannot be easily isotopically enriched and for which X-ray analysis is often not suitable. Secondly we propose an innovative strategy to hyperpolarize nuclear spins using MAS-DNP: rather than polarizing the entire system uniformly, we will selectively “light up” regions where we wish to gather important structural information. This will be developed to study protein-ligand interactions (with unprecedented resolution) to answer specific structural questions and potentially impact the field of drug engineering. Finally we will show that the unique experimental setup developed in this project will open up NMR to the routine study of “exotic”, yet ubiquitous and highly informative, nuclei such as 43Ca and 67Zn. Specifically, we will show that MAS-DNP can become a choice technique for the study of diamagnetic metal binding sites, complementing EPR for the study of metalloproteins. These goals will be achieved thanks to the development of original methods and advanced instrumentation, allowing sustainable access to low temperatures (down to 10-20 K) and fast pneumatic sample spinning, under microwave irradiation. We expect to improve the current sensitivity to such an extent that 4 orders of magnitude of experimental timesavings are obtained, resulting in completely new research directions and regimes.
Projet ERC : ULT-MAS-DNP (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : Partner
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 40000.0 €

The goal of the project is to develop a new hyperpolarization approach called Magic Angle Spinning Dynamic Nuclear Polarization (MAS-DNP) to reach levels of sensitivity and resolution that have never been achieved, in order to tackle highly relevant chemical and biological questions that remain unanswered so far. Firstly this will provide major advances in NMR crystallography (solving 3D structures by NMR) by showing that distance measurements between nuclei (13C, 15N, etc.) as well as 17O quadrupolar parameters can be extracted from NMR measurements without requiring isotopic labeling. This will be applied to systems that cannot be easily isotopically enriched and for which X-ray analysis is often not suitable. Secondly we propose an innovative strategy to hyperpolarize nuclear spins using MAS-DNP: rather than polarizing the entire system uniformly, we will selectively “light up” regions where we wish to gather important structural information. This will be developed to study protein-ligand interactions (with unprecedented resolution) to answer specific structural questions and potentially impact the field of drug engineering. Finally we will show that the unique experimental setup developed in this project will open up NMR to the routine study of “exotic”, yet ubiquitous and highly informative, nuclei such as 43Ca and 67Zn. Specifically, we will show that MAS-DNP can become a choice technique for the study of diamagnetic metal binding sites, complementing EPR for the study of metalloproteins. These goals will be achieved thanks to the development of original methods and advanced instrumentation, allowing sustainable access to low temperatures (down to 10-20 K) and fast pneumatic sample spinning, under microwave irradiation. We expect to improve the current sensitivity to such an extent that 4 orders of magnitude of experimental timesavings are obtained, resulting in completely new research directions and regimes.
Projet ERC : GRAPHCPX (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1162500.0 €

The goal of the proposed project is to create a universal (AKSZ type) topological field theory with values in graph complexes, capturing the rational homotopy types of manifolds, configuration and embedding spaces. If successful, such a theory will unite certain areas of mathematical physics, topology, homological algebra and algebraic geometry. More concretely, from the physical viewpoint it would give a precise topological interpretation of a class of well studied topological field theories, as opposed to the current state of the art, in which these theories are defined by giving formulae without guarantees on the non-triviality of the produced invariants. From the topological viewpoint such a theory will provide new tools to study much sought after objects like configuration and embedding spaces, and tentatively also diffeomorphism groups, through small combinatorial models given by Feynman diagrams. In particular, this will unite and extend existing graphical models of configuration and embedding spaces due to Kontsevich, Lambrechts, Volic, Arone, Turchin and others. From the homological algebra viewpoint a field theory as above provides a wealth of additional algebraic structures on the graph complexes, which are some of the most central and most mysterious objects in the field. Such algebraic structures are expected to yield constraints on the graph cohomology, as well as ways to construct series of previously unknown classes.

Mots-clés : graph complexes
Projet ERC : QUBE (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : CNRS Innovation — Pays : France — Rôle : Partner
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 7203.92 €

The goal of the “Quantum technology with carbon nanotUBEs”, QUBE, project is to provide a commercial solution enabling an easy manipulation of single wall carbon nanotubes, structurally characterized for quantum technologies. This solution will be fully adapted for being integrated into quantum devices. The project will aim to rationalize the production of high quality, “ready to use”, single wall carbon nanotubes and to create of a start-up company whithin the emerging quantum industry sector in Europe.

Mots-clés : carbon nanotubes,quantum technology,nanoassembly techniques
Projet ERC : Cont4Med (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Leibniz University Hannover — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1497965.0 €

The goal of this project is to develop estimation and control strategies for systems where only a (very) limited amount of information (measurements and models) is available. The main motivation to consider these problems are biomedical applications, where such a small amount of available information is often inherent. Examples include hormone concentration measurements when considering thyroidal diseases (which are typically only taken every few days or even weeks) or monitoring the size of a tumor. Estimating the current state of the system and devising appropriate control actions is very challenging in such applications. This is not covered by existing approaches in the literature, necessitating the development of novel methods and tools. Within this project, I will in particular focus on the following aspects. First, observability of nonlinear systems subject to few (sampled) measurements will be studied and sampling strategies together with suitable nonlinear state estimators will be derived. Second, state estimation and control strategies will be developed for situations with only partial or no model knowledge. Again, this is of intrinsic importance in biomedical applications where often the underlying physical principles are only partially understood or too complex. This necessitates the design of data- and learning-based methods, for which desired guarantees can be given, even in case of few measurements. Third, the developed tools will be extended to large-scale systems, where estimation and control has to be achieved in a distributed fashion. The successful achievement of the project goals will (i) enable estimation and control in systems with very few, sampled measurements, (ii) constitute a big step towards a holistic data-based systems and control theory, (iii) result in a new, data-driven, paradigm for the control of large-scale systems, and (iv) enable the design of systematic, personalized, and optimal control strategies in biomedical applications.

Mots-clés : nonlinear control and estimation,data based control and estimation,learning based control and estimation,model predictive control,moving horizon estimation,distributed control,biomedical applications