Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : CelluNANo (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
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 : 150000.0 €

Nanomaterials, especially if bio-sourced, have huge promise in a wide range of applications of societal importance to replace inorganic and synthetic counterparts. This is particularly important in the pigment industry, which has long relied on the use of inorganic nanoparticles as scattering enhancers. Now there is a growing demand for natural and sustainable alternatives that avoid the growing concerns over potential long-term health impacts of inorganic materials such as Titanium dioxide (TiO2) nanoparticles. This proposal aims to harvest the design principles offered by natural nanomaterials to fabricate new highly scattering materials using only biopolymers. By exploiting the most abundant biopolymer on the planet, cellulose, and replicating highly scattering architectures observed in nature, this grant aims to scale up a newly developed generation of scattering enhancers that can completely replace the currently used TiO2 nanoparticles. The ability to control the scattering efficiency of cellulosic material will allow us to produce truly sustainable white enhancers that can find use in everyday application such as cosmetics, food, packaging as well as paints and coatings.

Mots-clés : cellulose,optical material,whitener,biopolymers,sustainability
Projet ERC : Q-CEOM (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : University of Copenhagen — Pays : Danemark — Rôle : PI
Acronyme de l'entité : UCPH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1495073.0 €

Nanomechanical oscillators have recently been realised in the quantum regime, by coupling them to a single mode of the electromagnetic field. Platforms using both superconducting microwave circuits and optical cavities have been employed—separately—for this purpose. Based on the PI's extensive contributions to these developments, we propose to explore the intriguing conceptual and experimental prospects of hybrid multimode systems involving microwave, mechanical and optical modes in the quantum regime, thus unifying the fields of quantum cavity optomechanics and electromechanics. To reach this ambitious goal, an optomechanical system involving two optical modes and one mechanical mode will serve as testbed for quantum conversion and tripartite entanglement protocols. Particular attention will be devoted to the evasion of mechanical thermal noise through noise-resilient schemes, relying, for example, on mechanically dark Bogoliubov modes. This will enable the conservation of quantum coherence in spite of the inevitable coupling of the mechanical device to a thermal environment. The protocols, once established, will be transferred to a hybrid multimode system, consisting of a superconducting microwave resonator, a nanomechanical oscillator, and an optical cavity mode. In this system, we will explore unprecedented opportunities to transduce, entangle and amplify microwave and optical modes through a mechanical device. The specific implementation proposed here opens new avenues for the ultralow-noise processing of microwave signals, with potential applications in radio astronomy or magnetic resonance imaging. In the quantum sciences, it bears great promise to overcome the dichotomy between superconducting circuit platforms for information processing, and flying optical photons for its communication. More generally, the schemes studied here can serve as a blueprint for mechanical transducers—coupling to spin, charge, and fields alike—in hybrid quantum systems.

Mots-clés : cavity optomechanics,cavity electromechanics,entanglement
Projet ERC : TROJANANOHORSE (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Polytechnic University of Turin — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1489219.0 €

Nanomedicine tools for cancer treatment comprise many nanosized systems, so far developed with smart functions such as efficient drug delivery and cell targeting abilities. However they remain still undercharacterized in terms of immunogenicity, potential toxicity due to the materials itself or the unwanted release of drugs. To overcome these challenges this project aims to develop a new generation of multifunctional therapeutic and diagnostic (thus theranostics) nanosystems displaying non-immunogenicity, improved cancer treatment, cell imaging, and high safety for the hosting organism. The innovative concept behind this approach relies on a core-shell nanosystem with a therapeutically active core, i.e. a TrojaNanoHorse (TNH), here validated against leukaemia. The injectable TNH have a lipid bilayer shell derived from autologous cancer cell membrane, naturally non-immunogenic. The hemocompatibility, antithrombogenicity, and targeting ability with antibodies toward malignant blood cells will be proved during this project. Studies will show the zinc oxide nanocrystal core activation developing toxic reactive oxygen species (ROS) for cancer killing, and its green fluorescence emission. The whole TNH would go beyond the state-of-the-art due to its nature-derived biomimetic shell, absence of drugs, its safety and biodegrading fate, and green luminescent emissions for diagnosis. This project will also develop novel set-up for non-immunogenic therapy and diagnosis, impacting on future technology, new standardized protocols for nanomaterial safety assessment, and study chemical and biological mechanism of ROS development effects on cancer cell. Achieving the ultimate goal of a multifunctional TNH will require multidisciplinary expertise in chemistry, material science, biology, medicine and engineering, opening new horizons as nanomedicine tools for efficient cancer therapy with strong scientific, technological and socio-economic benefits.

Mots-clés : zinc oxide nanocrystal,exosome derived lipid shell,sonodynamic therapy,sonoluminescence
Projet ERC : ProFF (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
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 : 2141379.0 €

Natural enzymes are awesome catalysts, in terms of their catalytic efficiency, selectivity, control mechanisms, etc. Revamped as laboratory or industrial tools, they have allowed more than a few breakthroughs, such as PCR, next generation sequencing or green chemistry. The next revolution will be brought by a new generation of extensively modified “enzymatic” catalysts working in non-natural environments, possibly build from non-natural chemistries and targeting an unlimited range of non-natural functions. However, their design is still an arduous process; computational design lacks precision while the combinatorial approach, directed evolution, is limited by labor-intensive or ad hoc selection stages. We will remove the selection bottleneck in directed evolution by introducing biochemical computers able to perform this step autonomously. Based on recent developments in DNA-based molecular programming, these molecular scouts will be co-compartmentalized with genetic libraries into billions of individual compartments in micrometric emulsions. At each generation and in each droplet, after expression of the genotype, these molecular programs will autonomously: i- evaluate the phenotypic signature of a candidate, ii- integrate this information into a predefined scoring function and iii- propagate the relevant genetic information according to this score. The programmability of this approach will make directed evolution versatile, faster, and able to address more challenging problems. The evolution dynamics itself become tunable, offering new perspectives on the fitness landscape of biopolymer catalysts. A quantitative in silico model will be built and integrated in a computer-assisted tool for the fast set-up of in vitro experiments and tuning of the various experimental knobs. Overall, we will close a virtuous circle by evolving the molecular tools enabling the programmable selection of the next generation of catalytic tools.

Mots-clés : directed evolution,molecular programming,droplet microfluidics,dna nanotechnology
Projet ERC : CALCULUS (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Acronyme de l'entité : KUL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2227500.0 €

Natural language understanding (NLU) by the machine is of large scientific, economic and social value. Humans perform the NLU task in an efficient way by relying on their capability to imagine or anticipate situations. They engage commonsense and world knowledge that is often acquired through perceptual experiences to make explicit what is left implicit in language. Inspired by these characteristics CALCULUS will design, implement and evaluate innovative paradigms supporting NLU, where it will combine old but powerful ideas for language understanding from the early days of artificial intelligence with new approaches from machine learning. The project focuses on the effective learning of anticipatory, continuous, non-symbolic representations of event frames and narrative structures of events that are trained on language and visual data. The grammatical structure of language is grounded in the geometric structure of visual data while embodying aspects of commonsense and world knowledge. The reusable representations are evaluated in a selection of NLU tasks requiring efficient real-time retrieval of the representations and parsing of the targeted written texts. Finally, we will evaluate the inference potential of the anticipatory representations in situations not seen in the training data and when inferring spatial and temporal information in metric real world spaces that is not mentioned in the processed language. The machine learning methods focus on learning latent variable models relying on Bayesian probabilistic models and neural networks and focus on settings with limited training data that are manually annotated. The best models will be integrated in a demonstrator that translates the language of stories to events happening in a 3-D virtual world. The PI has interdisciplinary expertise in natural language processing, joint processing of language and visual data, information retrieval and machine learning needed for the successful realization of the project.

Mots-clés : joint processing of language and visual data,language understanding
Projet ERC : SYNPEP (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : Goethe University Frankfurt — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3165788.0 €

Natural products (NPs) generated by microbial non-ribosomal peptide synthetases (NRPS) represent several very important and valuable clinical antibiotics, immune-suppressive and anti-cancer drugs. NPs have gone on to inspire several synthetic peptides that are used clinically, but contain amino acids (AAs) or other building blocks that are not found in nature. However, with >500 identified AAs and additional peptide modifications like glycosylation or cyclization, the chemical diversity in NRPS-derived peptides is far larger than proteins and has not yet been fully explored. The modular nature of NRPS suggests the possibility to manipulate them, subsequently leading to the production of non-natural NPs. With an eXchange Unit (XU) concept, developed in Photorhabdus, Xenorhabdus and Bacillus, we have recently identified efficient ways for NRPS manipulation enabling the de novo assembly of novel NRPS for the production of new-to-nature NPs in excellent production yields of >250 mg/L. Within SYNPEP we will expand this approach to other bacterial genera producing peptide NPs. We will identify unusual NRPS systems, analyse them bioinformatically, validate the function of novel NRPS units experimentally and combine high-throughput molecular biology, microfluidics for bioactivity screening, rapid NP identification and structure elucidation to produce potentially any peptide or a peptide library of 2-15 amino acids in <4 weeks, in a semi-automated manner. In contrast to chemical peptide synthesis this production pipeline is more economical, sustainable and scalable. The NPs are produced by bacterial cells in aqueous media using cheap energy sources and the bacterial cultures can be easily scaled up when larger NP amounts are needed. We will also develop NRPS units that accept synthetic building blocks currently not found in natural NRPS. These ‘synthetic’ NRPS units will enable the simplified chemical derivatization of the produced NPs for further compound diversification.

Mots-clés : bioactive natural products,peptides,bioactivity screening,drug development,in vitro peptide production
Projet ERC : EXPLORE (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : University of Glasgow — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 399625.0 €

Natural sources have been highly important for the discovery of new drugs, offering compounds that possess exciting and potent bioactivities. The development of many promising natural products is significantly hampered by the difficulties associated with the synthesis of novel analogs. The family of ribosomally synthesized and post-translationally modified peptide (RiPP) natural products offers a plethora of different, promising bioactivities and highly diverse scaffolds. I propose to develop two new complementary routes to generate modified, bespoke RiPPs in vitro and in vivo: Interchangeable leader peptide (ILP) technology, which is a novel approach tailored to RiPPs. Every RiPP is produced from a precursor peptide that consists of a core peptide (the eventual natural product) and a pathway-specific recognition sequence that is recognized by parts of the biosynthetic machinery. ILP technology will allow me to swap out recognition sequences and thus combine the biosynthetic machineries from diverse RiPP pathways in a mix-and-match approach to generate new-to-nature, hybrid RiPPs using two routes: (1) We will develop this technology in vitro to take full advantage of non-natural amino acids and other building blocks. (2) We will transfer an optimized, streamlined version to an in vivo setting using peptide ligation in the cytoplasm of E. coli. This will allow us to use the power of genetics to create large libraries of compounds. I will harvest the novel enzymatic modifications enabled by ILPs to generate diverse RiPP scaffolds that contain amino acids, non-natural amino acids, enzymatically modified amino acids and non-a-amino acid building blocks. We will then use ILP technology to identify novel pathoblockers for Pseudomonas aeruginosa. The successful completion of this project will revolutionize the design of RiPPs-inspired next generation libraries with diverse scaffolds for application in tool compound development, target identification and drug discovery.

Mots-clés : natural products,ripps,engineering
Projet ERC : ABLASE (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : University of St Andrews — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1436062.5 €

Naturally occurring optical phenomena attract great attention and transform our ability to study biological processes, with “the discovery and development of the green fluorescent protein (GFP)” (Nobel Prize in Chemistry 2008) being a particularly successful example. Although found only in very few species in nature, most organisms can be genetically programmed to produce the brightly fluorescent GFP molecules. Combined with modern fluorescence detection schemes, this has led to entirely new ways of monitoring biological processes. The applicant now demonstrated a biological laser – a completely novel, living source of coherent light based on a single biological cell bioengineered to produce GFP. Such a laser is intrinsically biocompatible, thus offering unique properties not shared by any existing laser. However, the physical processes involved in lasing from GFP remain poorly understood and so far biological lasers rely on bulky, impractical external resonators for optical feedback. Within this project, the applicant and his team will develop for the first time an understanding of stimulated emission in GFP and related proteins and create an unprecedented stand-alone single-cell biolaser based on intracellular optical feedback. These lasers will be deployed as microscopic and biocompatible imaging probes, thus opening in vivo microscopy to dense wavelength-multiplexing and enabling unmatched sensing of biomolecules and mechanical pressure. The evolutionarily evolved nano-structure of GFP will also enable novel ways of studying strong light-matter coupling and will bio-inspire advances of synthetic emitters. The proposed project is inter-disciplinary by its very nature, bridging photonics, genetic engineering and material science. The applicant’s previous pioneering work and synergies with work on other lasers developed at the applicant’s host institution provide an exclusive competitive edge. ERC support would transform this into a truly novel field of research.

Mots-clés : laser,micro laser,biophotonics,fluorescent protein,f rster transfer,biocompatibility,strong coupling,biologically inspired photonics,biologically produced photonics,biolaser,bionic
Projet ERC : DYNAPOL (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Polytechnic University of Turin — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999623.0 €

Nature uses self-assembly to build fascinating supramolecular materials, such as microtubules and protein filaments, that can self-heal, reconfigure, adapt or respond to specific stimuli in dynamic way. Building synthetic (polymeric) supramolecular materials possessing similar bioinspired properties via the same self-assembly principles is interesting for many applications. But their rational design requires a detailed comprehension of the molecular determinants controlling the assembly (structure, dynamics and properties) that is typically very difficult to reach experimentally. The aim of this project is to obtain structure-dynamics-property relationships to learn how to control the dynamic bioinspired properties of supramolecular polymers. I propose to unravel the molecular origin of the bioinspired behavior through massive multiscale modeling, advanced simulations and machine learning. First, we will develop ad hoc molecular models to study monomer assembly and the supramolecular structure of various types of self-assembled materials on multiple scales. Second, using advanced simulation approaches we will characterize the supramolecular dynamics of these materials (dynamic exchange of monomers) at high (submolecular) resolution. We will then study bioinspired properties such as the ability of various supramolecular materials to self-heal, adapt or reconfigure dynamically in response to specific stimuli. Our models will be systematically validated by comparison with the experimental evidence from our collaborators. Finally, we will use machine learning approaches to analyze our high-resolution simulations and to identify the key monomer features that control and determine the structure, dynamics and dynamic properties of a supramolecular material (i.e., structure-dynamics-property relationships). This research will produce unprecedented insight and fundamental models for the rational design of artificial dynamic materials with controllable bioinspired properties.

Mots-clés : molecular simulation,multiscale modeling,self assembly,bioinspired,dynamic materials,supramolecular polymer,coarse graining,structure property relationships,responsive,adaptive materials
Projet ERC : REPCOR (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Einaudi Institute for Economics and Finance — Pays : Italie — Rôle : Partner
Acronyme de l'entité : EIEF
Type d'entité : Recherche
Financement ERC de l'entité : 394900.0 €

Nearly all activities in which the public sector is involved, from defense to transportation, from education to healthcare, require the public sector to procure works or goods from private contractors. Thus, it is crucial that the procedures through which procurement occurs be designed to avoid waste and enhance social welfare. Preventing corruption and ensuring contractor compliance with their obligations constitute primary design goals. Nevertheless, very limited evidence exists as to how different awarding methods are susceptible to corruption, and how contractors’ past reputation should be used to award new tenders. This research proposal describes three empirical projects that will advance the frontier of our understanding of the roles of corruption and reputation in procurement. Component 1 focuses on the use of reputation in contract procurement. It analyzes the evidence produced by the introduction of a vendor rating system to: i) determine whether the new system induced contractors to improve their performance, ii) determine whether performance improvements caused higher procurement costs, and iii) evaluate concerns on corruption and entry of new bidders. Component 2 focuses on corruption in public procurement. It analyzes evidence on the presence of networks of firms engaged in criminal activities in public procurement to determine: i) the extent of the phenomenon, (ii) the functioning of different awarding rules against corruption, and iii) the use of tests to detect corruption. Component 3 focuses on healthcare procurement regulations. It analyzes evidence on the public procurement of medical devices to accomplish: i) a descriptive analysis of the procurement practices across the EU, ii) an assessment of whether discretionary awarding rules are used to foster corruption or to reward contractors with better reputation, and iii) an evaluation of these procurement practices in terms of patients’ welfare.