Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : IMPLANTaLive (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : University of Twente — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

IMPLANTaLive coating technology provides an exciting business opportunity. IMPLANTaLive offers unique advantages of societal and economic importance such as public health and sick leave. Living, dynamic coatings for medical devices, ie. coatings with proper cell response upon implantation, are attractive for restoring body function. Conventional implant coatings are of inferior quality and therefore the majority, if not all, biocoatings fail in suitably interacting with host tissue. This poor performance of existing biocoating technologies is mostly caused by inherently static properties of surface coating, which disturbs the inherently dynamics between cells and surroundings, disrupting healthy tissue response and eventually causing adverse reactions like infections. Living coatings are produced by an innovative one step pre-conditioning of FDA approved polymeric and metal surfaces. Living non-pathogenic bacteria with GRAS status are suitable for in-vivo use, which provide medical devices with dynamic and responsive characteristics. Dynamic IMPLANTaLive coatings provide bidirectionality, ie. the ability to process biological stimuli by cellular control feedback loops and hence influence cellular and tissue characteristics and responses. This greatly enhances the application potential as the living coating can be easily tailored to the specific needs of a patient. IMPLANTaLive coatings can actively stimulate the reconstruction or injured site by releasing specific growth factors (relevant for ligament and tendon repair) or express membrane bound endothelial cell specific adhesion proteins (relevant for vascular devices). A business case will be developed for IMPLANTaLive covering different markets and routes for market introduction. Results of market analysis and financing needs will be combined with science-based technology comparison and used for discussions with potential industry partners. Several companies have already expressed interest in IMPLANTaLive.

Mots-clés : coatings,medical devices,living,chemistry
Projet ERC : INTERACT (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Universitat Politècnica de Catalunya — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UPC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499375.0 €

INTERACT will develop new Interactive Learning Algorithms (ILA), motivated by applications in Natural Language Understanding (NLU). The main assumptions behind supervised approaches are unrealistic because most NLU applications have unique information needs, and large collections of annotated data are necessary to achieve good performance. INTERACT follows a collaborative machine learning paradigm that breaks the distinction between annotation and training. We focus on compositional latent-state models (CLSMs) because natural language is rich, complex and compositional. To reduce the amount of human feedback necessary for learning CLSMs we must eliminate annotation redundancy. We argue that to achieve this in the context of CLSMs we must combine: (1) An optimal human feedback strategy, with (2) inducing a latent structure of parts in the compositional domain. Annotation effort will be minimized because the method will only request representative feedback from each latent class. INTERACT marries representation learning (i.e. of parts) and active learning for CLSMs. Our approach goes beyond classical active learning where the ILA asks labels for samples chosen from a pool of unlabeled data. We empower the ILA with the ability to ask for labels for any complete or partial structure in the domain, i.e. the ILA will be able to generate samples. We work under the framework of spectral learning of weighted automata and grammars and use ideas from query learning. A key idea is reducing the problem of interactive learning of CLSMs to a form of interactive low-rank matrix completion. Our concrete goals are: (1) Develop ILAs for CLSMs based on spectral learning techniques; and (2) Investigate optimal strategies to leverage human feedback, taking into account what is optimal for the ILA and what is easy for the teacher. We will experiment with NLU tasks of increasing complexity, from sequence and tree classification to parsing problems where the outputs are trees.

Mots-clés : natural language understanding,active learning,query learning,spectral learning,deep learning,human in the loop learning
Projet ERC : Habitat-OASIS (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Freie Universität Berlin — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : FU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1533883.05 €

Icy moons in the outer solar system are prime candidates for harbouring alien life within their sub-surface oceans. Among them Enceladus and Europa are considered to have the largest astrobiological potential. Habitat-OASIS aims to explore the habitability of the ocean worlds of Enceladus, Europa, and other icy satellites using in situ mass spectrometry from on-going and future space missions. At Enceladus (and probably Europa) the ice grains expelled by active plumes carry matter previously dissolved and suspended in the subsurface oceans, allowing constraining their geochemistry. The mass spectrometers aboard the Cassini-Huygens spacecraft currently orbiting Saturn are analysing this material and already delivered spectacular science results. Project 1 of this proposal is the refined data analysis of the Enceladus plume material using novel techniques and is the first ever opportunity to explore in detail a potential ocean habitat outside Earth. Newly developed laser-assisted dispersion experiments will be used to acquire mass spectra on a wide variety of analogue materials, enabling the identification and quantification of inorganic, organic and possibly biogenic compounds embedded in the ice grains. Geochemical aqueous alteration experiments and numerical modelling will support further constraining the habitability of Enceladus and extrapolating the results to other ocean moons. Project 2 will leverage the laboratory capabilities from Project 1 to create a comprehensive library of mass spectra in preparation for the upcoming missions visiting Jupiter’s icy moons: ESA’s JUICE Mission and NASA’s Europa Mission. Even if no plume is present both spacecraft will encounter surface material residing in ejecta clouds around the moons that can be connected to subsurface processes. Having analogue measurements available early in the missions will be critical for exploiting their full potential and will maintain the leading edge of ocean world exploration in Europe.

Mots-clés : oceanology
Projet ERC : INTEGRAL (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : University of Basel — Pays : Suisse — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499500.0 €

Identification of the molecular mechanisms by which gene regulatory landscapes integrate diverse signaling inputs into a robust and dynamic transcriptional output is key to a comprehensive mechanistic understanding of the systems that govern vertebrate organogenesis. We will tackle this by taking advantage of our in-depth knowledge of the self-regulatory signaling systems controlling vertebrate limb development. To capture the dynamics by which the major signaling pathways (BMP, SHH, WNT, FGF) interact to control gene expression, we will profile chromatin architecture, epigenetic marks and the interaction kinetics of transcriptional effectors with cis-regulatory modules (CRMs) during mouse limb bud development. First, we will focus on the Grem1 gene regulatory landscape, as this BMP antagonist is a key node in the system and its spatio-temporal expression is regulated by all four pathways. This analysis will capture the temporal activity of all CRMs in the Grem1 landscape and reveal the ones that are targets of one or several signaling pathways. The functional requirements of single and multiple CRMs with redundant functions will be assessed by gain- and loss-of-function genetics in mice. This analysis together with in silico simulations of the relevant interactions aims to reveal the underlying regulatory logic. Second, the genome-wide datasets will be used to analyse the gene regulatory landscapes of signals involved in epithelial-mesenchymal and auto-regulatory feedbacks. Third, the trans-cis regulatory alterations underlying the evolutionary diversifications that resulted in digit loss and reductions will be functionally studied by comparative analysis of mouse, bovine, pig and chicken limb buds. Finally, as aberrant Grem1 expression predisposes to various diseases and cancers, we will study the trans-cis regulatory alterations that affect the Grem1 landscape in a mouse model of SHH-induced cerebellar medulloblastomas, which depends on aberrant Grem1 expression.

Mots-clés : limb development,gene regulatory networks,signaling systems,evolutionary diversification,disease
Projet ERC : STROMATA (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Lausanne — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UNIL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1060250.0 €

Identifying Archean fossil remains from the Earth’s early biosphere is ambitious and determining the biological origin and the associated metabolic pathways present in these fossils is one outstanding question in the bigger quest of how life evolved on Earth. Stromatolites and Microbially Induced Sedimentary Structures (MISS) are considered as one of the earliest evidence of Life in Earth’s history, and can be found from the Archean to the present time. Stromatolites are “attached laminated, sedimentary growth structure accretionary away from a point of initiation”, and their morphological comparison with actual structure prevail for assessing the microbial origin of ancient stromatolite in the geological record. However, experimental studies have shown that abiotic precipitation can also form structures with a similar morphology. Therefore stable isotope proxies have been used to identify past microbial metabolisms even if abiotic processes can also produce similar isotope composition. Therefore new biogenicity criteria are needed to be determined by studying modern and ancient stromatolites and by comparing them to abiotic experiment. Stromatolites and MISS contain submicrometer sulfides (pyrite) that can have recorded large isotopic variations, interpreted as reflecting the influence of various microbial metabolisms like microbial sulfate reduction and iron respiration. STROMATA proposes to define new criteria based on actual stromatolite and to test the earliest traces of life by studying in situ these nano-pyrites in various emblematic and well-characterized samples from the Archean. STROMATA will be the first far-reaching scientific in situ study of nano-pyrite in ancient (3.4 to 1.9 Ga) and modern microbial mats and stromatolites and will compare the results with experimentally produced abiotic pyrite. Due to the small scale of the pyrite, STROMATA will develop an original in situ approach by combining state of art techniques, SIMS, NanoSIMS, FEG-TEM, XANES.

Mots-clés : origin of life,biogenicity,in situ approache,early earth,fe and s stable isotope proxies
Projet ERC : STROMATA (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Université Jean Monnet — Pays : France — Rôle : Partner
Acronyme de l'entité : UJM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Identifying Archean fossil remains from the Earth’s early biosphere is ambitious and determining the biological origin and the associated metabolic pathways present in these fossils is one outstanding question in the bigger quest of how life evolved on Earth. Stromatolites and Microbially Induced Sedimentary Structures (MISS) are considered as one of the earliest evidence of Life in Earth’s history, and can be found from the Archean to the present time. Stromatolites are “attached laminated, sedimentary growth structure accretionary away from a point of initiation”, and their morphological comparison with actual structure prevail for assessing the microbial origin of ancient stromatolite in the geological record. However, experimental studies have shown that abiotic precipitation can also form structures with a similar morphology. Therefore stable isotope proxies have been used to identify past microbial metabolisms even if abiotic processes can also produce similar isotope composition. Therefore new biogenicity criteria are needed to be determined by studying modern and ancient stromatolites and by comparing them to abiotic experiment. Stromatolites and MISS contain submicrometer sulfides (pyrite) that can have recorded large isotopic variations, interpreted as reflecting the influence of various microbial metabolisms like microbial sulfate reduction and iron respiration. STROMATA proposes to define new criteria based on actual stromatolite and to test the earliest traces of life by studying in situ these nano-pyrites in various emblematic and well-characterized samples from the Archean. STROMATA will be the first far-reaching scientific in situ study of nano-pyrite in ancient (3.4 to 1.9 Ga) and modern microbial mats and stromatolites and will compare the results with experimentally produced abiotic pyrite. Due to the small scale of the pyrite, STROMATA will develop an original in situ approach by combining state of art techniques, SIMS, NanoSIMS, FEG-TEM, XANES.

Mots-clés : origin of life,biogenicity,in situ approache,early earth,fe and s stable isotope proxies
Projet ERC : InterAccent (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
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 : 2499333.0 €

If a group of people were stranded on a desert island with limited contact to outside communities for a period of time, then the group would develop its own characteristic way of speaking or spoken accent. A lack of suitable data as input to an evolutionary computational model has meant that we have but a poor understanding of how spoken accent emerges out of human interaction. Yet a breakthrough in this area is critical for explaining the various forces - including contact between individuals through increased migration - that shape spoken accent development ultimately leading to language diversification and change. The project remedies this deficiency by developing a model of how random, local interactions between individuals leading to group-specific spoken accents can push the sound patterns of languages between stable and changing states. The methodological innovation is that the model's predictions of how spoken accent evolves will be constrained by longitudinal observations about how it actually develops within a group of speakers over time. We seek to generalise from diverse types of data: from children growing up in remote rural communities as opposed to high-contact urban settings; from languages that differ markedly in their sound structure; and from groups of adults isolated together for several months during an Antarctic winter. The project's scientific impact is on developing a computational framework for unifying historical sound change with the cognitive mechanisms by which speech is communicated and adapted to different social settings. The further impact is on understanding how migration and exposure to other accents change the sounds of language. The long-term significance of the project is to build a computationally predictive model of the way that microscopic idiosyncrasies in how humans process speech in everyday conversations accumulate into group-level macroscopic spoken accent change leading to language diversification.

Mots-clés : spoken accent change  agent based modeling  language evolution
Projet ERC : POST-IT (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : University of Groningen — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : RUG
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

ImImmune clearance of infectious diseases requires correct T cell activation by macrophages and dendritic cells (DCs) that present peptides derived from ingested pathogens on major histocompatibility complexes (MHC). Yet, macrophages and DCs also ingest self-antigens present in healthy cells and their presentation might trigger autoimmune disease. Presentation of the minority of ingested pathogens is promoted by so-called phagosome-autonomous trafficking. Here, pathogen binding to Toll-like receptors in phagosomes triggers recruitment of proteases and transporters to these phagosomes, but not to other phagosomes present in the same cell, promoting specific presentation of pathogen-derived peptides. However, a molecular understanding of this pathogen-oriented phagosome-autonomous trafficking is lacking. The goal of this project is to determine how phagosome-autonomous pathogen recognition promotes presentation of pathogen-derived over harmless self-antigens. Based on my preliminary data and literature, I hypothesize that Toll-like receptor signaling triggers phosphorylation of multiple SNARE proteins at the phagosomal membrane. As SNARE phosphorylation can promote or prevent membrane fusion, this alters delivery of proteases and transporters to these phagosomes, which in turn promotes presentation of pathogen-derived peptides. Objective 1 is to determine how SNARE function is altered upon pathogen-recognition in phagosomes using my novel quantitative Förster resonance energy transfer-fluorescence lifetime imaging microscopy (FRET-FLIM)-based technique. Objective 2 is to address how Toll-like receptor-mediated SNARE phosphorylation affects phagosome-autonomous trafficking. Objective 3 is to resolve the functional roles of SNAREs in antigen presentation using a novel bio-orthogonal chemistry-based method. This study will explain the high sensitivity of the adaptive immune system for pathogens and could lead to better vaccinations and therapies for infectious diseases.

Mots-clés : phagocytosis,pathogen recognition,snare protein,macrophage,dendritic cell,phosphorylation
Projet ERC : 3DScavengers (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Spanish National Research Council — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CSIC
Type d'entité : Recherche
Financement ERC de l'entité : 1498414.0 €

Imagine a technology for powering your smart devices by recovering energy from lights in your office, the random movements of your body while reading these lines or from small changes in temperature when you breathe or go out for a walk. This very technology will provide energy for wireless sensor networks monitoring the air in your city or the structural stability of buildings and large constructions remotely and sustainably, avoiding battery recharging or even replacing them. These are the challenges in micro energy harvesting from (local) ambient sources. Kinetic, thermal and solar energies are ubiquitous at our surroundings under diverse forms, but their relatively low intensity and intermittent availability limit their potential recovery by microscale devices. These restrictions call for multi-source energy harvesters working under two principles: 1) combining different single-source harvesters in one device, or 2) using multifunctional materials capable of simultaneously converting various energy sources into electricity. In 1), efficiency per unit volume can decrease compared to the individual counterparts; in 2), materials as semiconductors, polymeric and oxide ferroelectrics and hybrid perovskites may act as multisource harvesters but huge advances are required to optimize their functionalities and sustainable fabrication at large scale. I propose to fill the gap between these approaches offering an all-in-one solution to multisource energy scavenging, based on the nanoscale design of multifunctional three-dimensional materials. The demonstration of an industrially scalable one-reactor plasma/vacuum method will be crucial to integrate hybrid-scavenging components and to provide 3DScavengers materials with tailored microstructure-enhanced performance. My ultimate goal is to build nanoarchitectures for simultaneous and enhanced individual scavenging applying photovoltaic, piezo- and pyro-electric effects, minimizing the environmental cost of their synthesis

Mots-clés : nanowires,nanoarchitectures,energy harvesting,energy scavenging,nanogenerator,solar cells,plasma assisted deposition,vacuum deposition
Projet ERC : ULTRAIMAGE (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Groningen — Pays : Pays-Bas — Rôle : Partner
Acronyme de l'entité : RUG
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Imaging charge, spin, and energy flow in functional materials when hit by a light pulse, is a current grand challenge in nanotechnology relevant to a host of systems including photovoltaics, optoelectronic and spin devices. The design of such materials relies critically on the availability of accurate characterisation tools of how light-induced function and performance are related to nano-to-mesoscale electronic and lattice structural properties. To address this challenge, ULTRAIMAGE will introduce ground-breaking capabilities in microscopy of nanomaterials, providing access to their far-from-equilibrium states, with resolution on nanometer-to-Ångstrom length and femtosecond time scales. Key to this advance is the combination of extreme ultraviolet (EUV) to soft X-ray tabletop coherent light sources with a technique for coherent diffractive imaging called ptychography, in which multiple diffraction patterns from overlapping fields of view are processed by iterative algorithms to recover amplitude and phase images of sample and beam, separately. Nanoscale movies of the sample’s impulsive response, irradiated by ultrafast laser pulses, will be obtained with extremely high fidelity and in a non-destructive approach, with sub-20nm transverse resolution, 0.5Å axial precision, and ≈10fs temporal resolution. Each movie frame will be characterized by amplitude and phase images of the sample, with exquisite quantitative contrast to material composition, and to its topography. ULTRAIMAGE will introduce a world-class tabletop facility for ultrafast ptychography with coherent short-wavelength EUV light, which will enable the understanding with unprecedented detail of fundamental nanoscale behaviour, vital to a better design of energy-efficient next generation devices.

Mots-clés : characterisation,nanoparticle,superlattice,femtosecond,coherent diffractive imaging,ultrafast ptychography,euv and soft x ray light,structure property relations,collective modes