Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ConFluReM (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Leibniz Association — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LG
Type d'entité : Recherche
Financement ERC de l'entité : 2500000.0 €

Today’s materials research in the field of synthetic membranes gives access to highly permeable and extremely selective membranes. However, their potential will remain ineffective as high and selective transport rates always go along with resistances emerging at the membrane fluid interface in the form diffusion limitations in the laminary boundary layers. In order to make full use of the very many new materials, also new means to control and minimize such fluid based resistances need to be developed. Yet another phenomena disturbs the full potential use of membranes: retained solutes, colloids and biological matter accumulates at the membrane interface and causes irreversible fouling and scaling. The proposed research aims to develop a rigorous translational methodology to control and improve mass transport through the fluid/membrane interface. ConFluReM will establish Strategic Tools and New Instruments to: (1) comprehend and quantify the prevalent mass transport resistances in representative membrane separation processes, (2) synthesize and fabricate new nano-, micro- and mesoscale material and device systems as instruments to control and overcome the limitations of concentration polarization and fouling, Strategic Tools are experimental and simulation methods to quantify and engineer the mass transport and hydrodynamical properties of the new membrane systems. These encompass flow imaging (flowMRI, microPIV and microfluidic transport studies) as well as computational fluidic dynamics (CFD and CFDEM). New Instruments are synthetic and fabrication means as well as process condition means to improve mixing at the membrane/fluid interface. These encompass (a) lateral patterning of chemical topology of the membrane surface by printing and stamping, (b) shaping the 3D geometry of channels using additive manufacturing techniques and (c) imposing dynamical gradients to destablize fluid side resistances.
Projet ERC : MARCAN (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Malta — Pays : Malte — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 932612.25 €

Topographically-driven meteoric (TDM) recharge is a key driver of offshore groundwater systems because sea level has been lower than at present for 80% of the last 2.6 million years. Groundwater has been implicated as an important agent in the geomorphic evolution of passive continental margins and the canyons that incise them. However, the geomorphic efficacy of groundwater remains dubious, and a diagnostic link between landscape form and groundwater processes remains poorly quantified, especially for bedrock and cohesive sediments. Obstacles that prevent going beyond the current state-of-knowledge include: (i) a focus on terrestrial contexts and a lack of mechanistic understanding of groundwater erosion/weathering; (ii) limited information on offshore groundwater architecture, history and dynamics. By addressing the role of TDM offshore groundwater in the geomorphic evolution of the most prevalent types of continental margins, MARCAN is expected to open new scientific horizons in continental margin research and bring about a step-change in our understanding of some of the most widespread and significant landforms on Earth. The project’s methodology is rooted in an innovative, multi-scale and multidisciplinary approach that incorporates: (i) the most detailed 3D characterisation of TDM offshore groundwater systems and their evolution during an integral glacial cycle, based on state-of-the-art marine data and hydrogeologic models, and (ii) the development of a comprehensive continental margin geomorphic evolution model, based on realistic laboratory simulations, accurate field measurements and advanced numerical solutions. By placing better constraints on past fluid migration histories, MARCAN will also have strong applied relevance, primarily by improving assessment and exploitation of offshore freshwater as a source of drinking water.

Mots-clés : geomorphology,groundwater,weathering,erosion,canyons,landscape evolution,continental margins
Projet ERC : STATOPINS (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Delft University of Technology — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU Delft
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1355103.0 €

Topological insulators (TI) are a novel class of materials with insulating bulk and conducting surface. The conduction of the surface is protected by the topological properties of the bulk, as long as a fundamental symmetry is present (for instance time-reversal symmetry). My goal is to investigate to what limits does the protection hold in cases where the protecting symmetry is broken, and only present in statistical sense, after averaging over the disordered ensemble. In a pilot study I showed that materials that are protected by such average symmetry, which I have called “statistical topological insulators” (STI) significantly extend the classification of topological phases of matter and promise new methods to robustly control the conducting surface properties. I plan to develop a general theory of STI for physically relevant symmetries, describe the observable properties of their protected surface states, invent ways to predict whether materials are expected to be STI, and explore the generalization of STIs to strongly interacting topological phases of matter. I expect that the outcome of my research will significantly extend our understanding of topological phases of matter, and provide new ways to design materials with robust properties.

Mots-clés : topological insulators and superconductors
Projet ERC : TOPSIM (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : University of Florence — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1595000.0 €

Topology and symmetry are two fundamental and intertwined concepts driving the behavior of fermionic systems in both condensed-matter and high-energy physics. The goal of the TOPSIM project is to address open problems concerning topological states of fermionic matter from an experimental point of view, by taking advantage of novel possibilities of quantum control on synthetic systems formed by ultracold neutral atoms. We will investigate the behavior of fermionic matter under strong gauge fields in order to study quantum Hall physics and the emergence of topological order in a fully tunable experimental geometry. We will also synthesize fermionic systems exhibiting enlarged interaction symmetries beyond the SU(2) symmetry of electrons, which will allow us to experimentally realize, for the first time, SU(N) models that have no other experimental counterpart in physics, and to use them to study the emergence of long-sought topological states of matter. With these ambitious goals, the TOPSIM project will considerably advance our understanding of topological fermionic matter, paving the way to new methods of investigation of open questions in both high- and low-energy physics, by approaching many-body problems with metrological quantum control.
Projet ERC : SENSATIONAL TETHERS (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Max Delbrück Center for Molecular Medicine — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MDC
Type d'entité : Recherche
Financement ERC de l'entité : 2500000.0 €

Touch sensation is built upon the ability of sensory neurons to detect and transduce nanometer scale mechanical displacements. The underlying process has been termed mechanotransduction: the high sensitivity and speed of which is enabled by direct gating (opening) of ion channels by mechanical force. Force detection is functionally compartmentalized and only takes place at the peripheral endings of sensory neurons in vivo. Two molecules are known to be genetically necessary for touch in many sensory neurons, the force gated ion channel PIEZO2 and its modulator STOML3. However, mechanotransduction complexes in all touch receptors absolutely require tethering to the extracellular matrix for function. Tethering is dependent on large extracellular proteins that are sensitive to site-specific proteases. Here we will not only identify the nature of these tethers, but will develop technology to acutely and reversibly abolish tethers and other mechanotransducer components. We will use genome engineering to tag tether and mechanotranduction components in order to visualize and manipulate these proteins at their in vivo sites of action. By engineering de novo cleavage sites for site-specific proteases we will render tethers and ion channels newly sensitive to normally ineffective proteases in the skin. We will engineer mutations into candidate ion channels that dramatically alter biophysical properties to physiologcally “mark” function in vivo. Finally we will develop new behavioural paradigms in mice that allow us to measure touch perception from the forepaw. Psychometric curves for different vibrotactile tasks can then be precisely compared between humans and mice. Furthermore, the impact of acute and reversible manipulation of mechanotransduction on touch perception can be measured. Understanding how molecules assemble to function in a mechanotransduction complex in the skin will open up avenues to develop therapeutic strategies to modulate touch.

Mots-clés : mechanotransduction,touch,sensory disorders,genome engineering,ion channels
Projet ERC : TOXANOID (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : University Medical Center Utrecht — Pays : Pays-Bas — Rôle : Partner
Acronyme de l'entité : UMC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 10000.0 €

Toxicology and pharmacology assays are crucial pillars of modern drug development. They are essential to understand how tissues such as intestine and liver take up and degrade pharmaceutically active compounds. Due to the lack of suitable in vitro systems, these assays are carried out in experimental animals. This practice increases cost and development time but also creates significant ethical issues. We recently developed a 3D culture system that allows us to expand human tissue stem cells from intestine and liver as organoids and differentiate them to the respective functional adult tissue in vitro. These stem cell-derived tissues show high cytochrome activity and are able to metabolize drugs in a simple and cost-effective in vitro assay. With support from the ERC Proof of concept grant we aim to prove that our technology can outperform current in vitro systems and replace a significant portion of animal-based toxicology studies. This technological advance will lead to substantial reduction of cost in industrial and academic drug development and overcome practical and ethical pitfalls in animal-based testing. To this end we will develop an organoid-based assay to test tissue-drug interactions in three steps: 1) Definition of optimal parameters for human in vitro assays to assess gastro-intestinal and hepatic toxicity 2) Scale-up 3) Technology transfer and commercial distribution

Mots-clés : stem cells,organoids,toxicology
Projet ERC : TOX-ANT (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Austrian Academy of Sciences — Pays : Autriche — Rôle : PI
Acronyme de l'entité : OAW
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 1498428.0 €

Toxin-antidote (TA) elements are a class of selfish elements that spread in natural populations by subverting the laws of Mendelian segregation (gene drive activity). For a decade, the only known TA element in animals was a paternal-acting element discovered in the nematode C. elegans. The lack of other examples perpetuated the idea that TA elements were extremely rare in animals. However, I recently challenged this view with two key findings 1) I genetically dissected a second TA element in C. elegans, the element sup-35/pha-1, and 2) I identified five novel TA elements in C. tropicalis, a close relative of C. elegans. Surprisingly, some of these novel TA elements can affect the fitness of adults and can antagonize each other mimicking the effect of balancing selection. Overall, my research strongly suggests that TA elements are much more common in animals than previously anticipated and raises critical questions about their origin, prevalence, mechanism of action, and contribution to speciation, all of which are largely unknown. This proposal has three main objectives: 1. To dissect the molecular mechanisms underlying an animal TA element for the first time. 2. To identify and characterize novel TA elements in diverse nematode species. 3. To screen for TA elements in medaka fish. My team and I will achieve these objectives by leveraging my multidisciplinary expertise in genomics, evo-devo, and biochemistry, as well as a state-of-the-art bulk QTL mapping method that I recently developed. Dissecting the molecular mechanisms used by natural selfish elements will help us design more efficient and specific synthetic drive elements that could target mosquito vectors spreading diseases such as malaria and Zika virus - global health burdens. I predict that we will discover and characterize many novel TA selfish elements in diverse species from nematodes to vertebrates. Our findings will stimulate new research areas in genetics, evolutionary biology, and medicine.

Mots-clés : gene drive,selfish gene,natural variation,speciation
Projet ERC : Glue2Degrade (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Austrian Academy of Sciences — Pays : Autriche — Rôle : PI
Acronyme de l'entité : OAW
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 1331340.0 €

Traditional drug design relies on inhibition of enzymes or receptors with accessible hydrophobic pockets. The concept of proteolysis targeting chimeras (PROTACs) promised to overcome this limitation. Following our discovery of the first PROTAC that induced selective protein degradation in vivo, this technology has seen a boost in academia and industry. Despite global research efforts, advances are so far incremental: (i) most focus is on degrading targets that can be liganded and are druggable with conventional inhibitors; (ii) currently, only 3 out of 600 E3 ligases can be exploited. Glue2Degrade aims to transform the pharmacologically targetable space of the proteome. The project is built on the hypothesis that molecular glues (MGs), non-chimeric small molecules that degrade target proteins by inducing cooperative binding to E3 ligases, are much more prevalent than anticipated. Lenalidomide and related immunomodulatory drugs (IMiDs) are prime examples of the potential of MGs. Without a specific targeting moiety, IMiDs induce cooperative binding of the E3 ligase CRBN to undruggable proteins like IKZF1/3, thereby inducing their degradation. However, no technologies exist to rationally develop MGs that hijack other E3 ligases. ERC-funding would allow us to address this limitation. Based on data generated in my laboratory, we will systematically identify novel MGs and their E3 ligases by innovating (i) phenotypic discovery strategies, and (ii) an orthogonal chemical genetics pipeline. To elucidate the mechanisms of novel MGs, we will (iii) conduct target identification via unbiased proteomics followed by (iv) chemical optimization and initial translational characterization. Glue2Degrade, if successful, will transform the engageable E3 space and identify novel MGs, thereby opening up the potential for therapeutic development of cell-, tissue-, and cancer-type specific chemical degraders for undruggable proteins.

Mots-clés : protein degradation,molecular glues,chemical biology,undruggable proteins,chemical genetics,e3 ligases
Projet ERC : BrainFrame (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : Erasmus MC — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149937.0 €

Traditional methods of software modeling and simulation take prohibitive amounts of time to run for the size and complexity of biologically realistic neuron populations (e.g. >1 million). For instance, simulation of a 100 high-detail (Inferior-Olive) neuron-network for 10 minutes of brain time take 42 hours to complete on an modern PC workstation. To tackle this problem - common to the international neuroscience community -, we have turned to hardware-accelerated simulation platforms. We have employed award-winning, FPGA -based, dataflow machines provided by Maxeler Technologies, which offer high-performance computing capabilities and come with programming tools of unprecedented user friendliness. Our current Maxeler setups have offered impressive acceleration rates of more than 4 orders of magnitude (x10000). Despite the achieved speeds, however, we have found the Maxeler programming tools to be cumbersome to learn by neuromodelers with little hardware knowledge. Engineering personnel has, thus, been employed to assist them in (efficiently) translating and deploying their models. To streamline this process and bring a powerful tool directly to the hands of modelers, we propose BrainFrame, a novel system consisting of Maxeler hardware and a comprehensive software toolflow, effectively adding an abstraction level for neuromodelers to work on without specific knowledge of the underlying simulation platform. BrainFrame comprises a “one-stop shop”, integrated solution primarily targeting labs and companies active in the field of brain-modeling research and applications.

Mots-clés : computational neuroscience,neuroinformatics,brain modeling,simulation,hardware acceleration,fpga,dataflow computing,neural controller,brain machine interface
Projet ERC : DyNeRfusion (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Glasgow — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1996043.0 €

Training and experience can lead to long-lasting improvements in our ability to make decisions based on either ambiguous sensory or probabilistic information (e.g. learning to diagnose a noisy x-ray image or betting on the stock market). These two processes are referred to as perceptual and probabilistic/reward learning, respectively. Despite considerable efforts to uncover the neural systems involved in these processes, perceptual and reward learning have largely been studied in separate lines of research using divergent learning mechanisms. The primary aim of this proposal is to develop a unified framework for integrating these lines of research and understand the extent to which they share a common computational and neurobiological basis. Specifically, we will test the proposition that both the perceptual and reward systems could be understood in a common framework of “reward maximization”, whereby a domain-general reinforcement-guided learning mechanism – based on separate prediction error representations – facilitates future actions and adaptive behavior. To offer a comprehensive spatiotemporal characterization of the relevant networks and their computational principles we will adopt a state-of-the-art multimodal neuroimaging approach to fuse simultaneously-acquired EEG and fMRI data, via machine-learning-inspired multivariate single-trial analysis techniques and computational modelling. The project’s ultimate goal is to empower a level of neuronal and mechanistic understanding that extends beyond what could be inferred with each of these modalities in isolation. We will achieve this goal by exploiting endogenous trial-by-trial electrophysiological variability to build parametric fMRI predictors that can offer additional explanatory power than what can already be achieved by stimulus- or behaviorally-derived predictors, allowing us to go over and beyond what has been reported previously in the literature.

Mots-clés : fmri,modelling,learning,decision making
Projet ERC : OSIRIS (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Fribourg — Pays : Suisse — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Transducing information to and from biological environments is essential for bioresearch, neuroscience and healthcare. There has been recent focus on using organic semiconductors to interface the living world, since their structural similarity to bio-macromolecules strongly favours their biological integration. Either water-soluble conjugated polyelectrolytes are dissolved in the biological medium, or solid-state organic thin films are incorporated into bioelectronic devices. Proof-of-concept of versatile applications has been demonstrated – sensing, neural stimulation, transduction of brain activity, and photo-stimulation of cells. However, progress in the organic biosensing and bioelectronics field is limited by poor understanding of the underlying fundamental working principles. Given the complexity of the disordered, hybrid solid-liquid systems of interest, gaining mechanistic knowledge presents a considerable scientific challenge. The objective of OSIRIS is to overcome this challenge with a high-end spectroscopic approach, at present essentially missing from the field. We will address: 1) The nature of the interface at molecular and macroscopic level (assembly of polyelectrolytes with bio-molecules, interfacial properties of immersed organic thin films). 2) How the optoelectronics of organic semiconductors are affected upon exposure to aqueous environments containing electrolytes, biomolecules and cells. 3) How information is transduced across the interface (optical signals, thermal effects, charge transfer, electric fields, interplay of electronic/ionic transport). Via spectroscopy, we will target relevant optoelectronic processes with ultrafast time-resolution, structurally characterize the solid-liquid interface using non-linear sum-frequency generation, exploit Stark shifts related to interfacial fields, determine nanoscale charge mobility using terahertz spectroscopy in attenuated total reflection geometry, and simultaneously measure ionic transport.

Mots-clés : organic bioelectronics and biosensors,conjugated polymers and polyelectrolytes,organic thin films,solid liquid interfaces,ultrafast spectroscopy,terahertz time domain spectroscopy