Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : Evidence-VAW (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of Essex — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Violence against women (VAW) is a fundamental cause of gender inequality and a substantial constraint on women’s lives, but it has drawn significantly less intellectual curiosity from economists than aspects of gender inequality such as the pay gap. I propose to redress this by acquiring, generating and analysing unavailable or under-used data using techniques for causal identification with a view to producing a rich tapestry of scientific evidence to guide policy and further scholarship. This is an important time to do this as there is a growing consensus around prioritizing VAW in international policymaking but the evidence base is thin. There are no systematic data on VAW, partly because women are inhibited in reporting. Creative new strategies are being used in many countries to reduce VAW, but without scientific evaluation. This project will investigate institutional designs to encourage women reporting VAW and to deliver justice on VAW (including penalties for firms, feminization of the criminal justice system and the use of mobile phone apps and social media to provide women information and facilitate their coordination); it will implement and evaluate grassroots interventions designed to address VAW by inducing behavioural change among men and women; it will analyse the likely value of policies addressing proximate causes (alcohol ban, unemployment insurance); the potential of women’s political mobilisation; and the role of UN discourse on VAW. Some projects use randomized control trials (RCTs), others leverage natural experimental variation from policy reform or institutional features. Many use longitudinal administrative data providing unparalleled opportunities for research. Within the RCTs, I will gather unique data on social norms, beliefs and social networks. Although focused on women’s rights, it addresses issues on the frontier of economics research, including inequality, productivity, institutional design, political economy, and legislative

Mots-clés : causal evidence,econometric approaches to gender inequality
Projet ERC : D-FENS (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Slovak Medical University — Pays : Slovaquie — Rôle : Partner
Acronyme de l'entité : SMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 413000.0 €

Viral infection or retrotransposon expansion in the genome often result in production of double-stranded RNA (dsRNA). dsRNA can be intercepted by RNase III Dicer acting in the RNA interference (RNAi) pathway, an ancient eukaryotic defense mechanism. Notably, endogenous mammalian RNAi appears dormant while its common and unique physiological roles remain poorly understood. A factor underlying mammalian RNAi dormancy is inefficient processing of dsRNA by the full-length Dicer. Yet, a simple truncation of Dicer leads to hyperactive RNAi, which is naturally present in mouse oocytes. The D-FENS project will use genetic animal models to define common, cell-specific and species-specific roles of mammalian RNAi. D-FENS has three complementary and synergizing objectives: (1) Explore consequences of hyperactive RNAi in vivo. A mouse expressing a truncated Dicer will reveal at the organismal level any negative effect of hyperactive RNAi, the relationship between RNAi and mammalian immune system, and potential of RNAi to suppress viral infections in mammals. (2) Define common and species-specific features of RNAi in the oocyte. Functional and bioinformatics analyses in mouse, bovine, and hamster oocytes will define rules and exceptions concerning endogenous RNAi roles, including RNAi contribution to maternal mRNA degradation and co-existence with the miRNA pathway. (3) Uncover relationship between RNAi and piRNA pathways in suppression of retrotransposons. We hypothesize that hyperactive RNAi in mouse oocytes functionally complements the piRNA pathway, a Dicer-independent pathway suppressing retrotransposons in the germline. Using genetic models, we will explore unique and redundant roles of both pathways in the germline. D-FENS will uncover physiological significance of the N-terminal part of Dicer, fundamentally improve understanding RNAi function in the germline, and provide a critical in vivo assessment of antiviral activity of RNAi with implications for human therapy.

Mots-clés : germline,rna interference,pirna,retrotransposon,antiviral defense
Projet ERC : VIRUSES AND RNA (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
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 : 1500000.0 €

Viral infections are responsible for significant morbidity and mortality and frequency and impact of epidemics are expected to increase. Thorough understanding of basic virology is critical for informed development of prevention and control. Most systematic studies of virus-host interactions have focused on proteins, however, with recent methodological advances the intersecting fields of viral infection and RNA biology hold great promise for basic and therapeutic exploration. The goal of this application therefore is to discover and dissect RNA-based virus-host interactions and related regulatory mechanisms of gene expression. Micro-RNAs (miRNAs) fine-tune gene expression by repressing mRNA targets. However, cellular miRNAs increase translation and replication of certain viruses. Thus, hepatitis C virus (HCV) critically depends on the liver specific miR-122, which emerged as a therapeutic target. Further, HCV sequesters enough miR-122 to indirectly regulate cellular gene expression. I hypothesize that this RNA-based mechanism contributes to virus induced liver cancer, and aim to address this using our recently developed rodent model for HCV infection (Aim 1). Better understanding of viral RNA (vRNA) interactions could significantly contribute to basic infection biology and novel therapeutics. I therefore aim to systematically identify vRNA interactions with other cellular RNAs and proteins (Aim 2). I expect to identify interactions of value for functional regulation and therapeutic targeting. I finally hypothesize that translation of certain cellular mRNAs – similarly to viruses – increase upon miRNA binding, and aim to systematically screen for such virus-like alternative regulation, with potential to change understanding of post-transcriptional regulation (Aim 3). In conclusion, this high-risk high-gain project has potential to shape novel dogmas for virus and RNA biology and to identify novel RNA-based therapeutic targets; a promising upcoming field of discovery.

Mots-clés : viruses,mirnas,hepatitis c virus,liver disease,translation,rna interactions
Projet ERC : WRAM (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : University of Edinburgh — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149138.0 €

Virtual acoustics is the complete simulation of the listener’s experience in an acoustic space. The applications are many: building acoustics, concert hall design, and virtual reality, including immersive game audio. Conventional audio rendering approaches are based on geometric or ray-based approximations. Though conceptually simple, such methods neglect many audible features of room acoustics, and in particular are not valid at low audible frequencies, or capable of rendering diffraction or shadowing effects around corners or obstructions. Wave-based methods address the shortcomings of ray-based methods, yielding a complete description of the acoustic field within an enclosure. The NESS project (ERC-2011-StG-279068-NESS) has taken wave-based methods from theory to the practical setting of real-world room acoustics, resulting in many key innovations, including the modelling of arbitrary geometries, variable and frequency-dependent wall conditions, and viscothermal effects in air. Building on these innovations, the aim of the proposed ERC PoC project WRAM (Wave-based Room Acoustics Modeling) is to introduce a new generation of sophisticated virtual acoustics rendering tools to the wide market of architectural acoustics, and immersive and game audio practitioners. The main activities under WRAM will be the development of a prototype system for wave-based high-quality room acoustics renderings, to operate ultimately as an on-demand cloud-based service. The development of the WRAM system will be informed by extensive consultation with a wide variety of industrial sectors, with regard to the design of several benchmarking problems, which will be tested against industry-standard ray-based platforms, and compared against measurement. From our interaction with industrial partners, we will build a business case based on a detailed market analysis and investigate possibilities of further investment by potential commercial partners and the strengthening of our IP position.

Mots-clés : room acoustics,game audio,virtual reality
Projet ERC : ADMIRE (Horizon 2020, appel 2017, Proof of concept grants)
Entité participante : National Research Council — Pays : Italie — Rôle : Partner
Acronyme de l'entité : CNR
Type d'entité : Recherche
Financement ERC de l'entité : 101250.0 €

Virtual reality, augmented reality and mixed reality are beginning to transform the way we explore and acquire information from the macroscopic world around us. At the same time, recent advances in holographic microscopy are providing new tools for the 3D imaging of physical and biological phenomena occurring at the micron scale. Project ADMIRE will combine this two emerging technologies into the first prototype of an AugmenteD MIcro-REality system for the immersive exploration and the quantitative analysis of three-dimensional processes at the micron scale. The core of the proposed system will be the three-axis holographic microscope (3DHM) developed within the ERC Project SMART to investigate fast 3D dynamics of swimming bacteria. ADMIRE project will transform 3DHM from a laboratory technique, targeted to a specific application and operated by highly specialised researchers into a general purpose instrument composed of a compact add-on module for commercial optical microscopes and a virtual reality interface allowing for a direct and intuitive use. Through the ADMIRE Holographic Microscope (ADMIRE-HM) the user will be “shrunk” a million times and virtually sent into a live 3D reconstruction of the real microscopic world contained in the glass slide. There he will find himself surrounded by micro-particles or moving cells that could be inspected from multiple directions and characterized by shape parameters (e.g. size, volume, aspect-ratio) or dynamical features (e.g. flagellar motility, sedimentation velocity, transport in a flow) obtained by means of simple and direct gestures. The expected outcome of the project is to bring to a development stage TRL 6-7 a technology that could change the way we experience the microscopic world in basic research, biomedical applications and education.

Mots-clés : holographic microscopy,virtual reality,3d imaging
Projet ERC : HeteroDynamic (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Uppsala University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Virtually all terrestrial plants depend on symbiotic interactions with fungi. Arbuscular mycorrhizal (AM) fungi evolved over 450 million years ago, are obligate biotrophs and cannot complete their lifecycle without obtaining carbon from host roots. Mediating nutrient uptake and sequestering carbon in soil this symbiosis lie at the core of all terrestrial ecosystems. Plants on the other hand are facultative mycotrophs but under natural conditions all host roots are colonized as a result of multiple beneficial effects of AM fungi. In the symbiosis, both plants and fungi are promiscuous, forming interactions across individuals and species. In the absence of host-symbiont specificity and given their inability to discriminate among partners prior to interaction, evolutionary theory predicts that “free riders” would evolve and spread. Yet AM fungi remain evolutionary and ecologically successful. I propose that this is thanks to their unique genomic organization, a temporally dynamic heterokaryosis. Unlike other eukaryotes, AM fungi have no single nucleate stage in their life cycle, instead they reproduce asexually by forming large multinucleate spores. Genetic variation is high and nuclei can migrate and mix within extensive mycelial networks. My group has recently established a single nucleus genomics method to study genetic variation among nuclei within AM fungi. With this method I can resolve the extent of heterokaryosis in AM fungi and its temporal dynamics. I will study the emergence of “free riders” upon intra organismal segregation of genetically distinct nuclei during AM fungal adaptation to host. Further I will study how hyphal fusion and nuclear mixing counteract segregation to stabilize the symbiosis. The research program has great potential for novel discoveries of fundamental importance to evolutionary and environmental biology and will also contribute to agricultural practice and management of terrestrial ecosystems.

Mots-clés : symbiosis
Projet ERC : ENVISION (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : Aarhus University — Pays : Danemark — Rôle : PI
Acronyme de l'entité : AU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2480338.0 €

Virus-induced type I interferons (IFN) have classically been considered to constitute the first line of defense against virus infections However, recent work by us and others has identified early antiviral actions that occur independently of inducible type I and III IFN expression and sometimes even prior to IFN action (e.g. Iversen,...., Paludan. Nature Immunology, 2016; Paludan. Trends in Immunology, 2016). These discoveries challenge the current thinking in the field that IFNs constitute the first line of defense. Hence, there is an urgent need for more detailed understanding of the immediate antiviral defense mechanisms. Most importantly, we remain to identify key players in IFN-independent antiviral responses, we completely lack insight into the mechanisms that govern these responses, and we also lack information on the importance of this layer of defense in mice and humans. In accord with this, my proposal follows four aims: (i) Identification of mechanisms of virus detection at epithelial surfaces, (ii) elucidation of the role of tonic IFN signaling in antiviral defense, (iii) identification and characterization of novel restriction factors, and (iv) deciphering the mechanisms that govern induction of the first wave of IFNs at epithelial surfaces. In addition, I will also explore the interactions between the early antiviral actions. To achieve the goals, I will combine unbiased genome-wide screens with hypothesis-driven approaches, and will integrate molecular biology/genetics/biochemistry with advanced cell culture systems, animal science and analysis of patient material. Strong preliminary data have been generated for all four aims, and world-leading collaborations are in place, hence minimizing the risks, and allowing fast progress. Our findings will (i) change the thinking in innate immunology by uncovering a novel layer of antiviral defense and (ii) provide new avenues for therapeutic modulation of immune responses.

Mots-clés : innate immunology,virus infections,pathogen recognition,type i ifn,muscosal immunology
Projet ERC : CATA-LUX (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Italian Institute of Technology — Pays : Italie — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 104592.75 €

Visible light photocatalysis and metal-free organocatalytic processes are powerful strategies of modern chemical research with extraordinary potential for the sustainable preparation of organic molecules. However, these environmentally respectful approaches have to date remained largely unrelated. The proposed research seeks to merge these fields of molecule activation to redefine their synthetic potential. Light-driven processes considerably enrich the modern synthetic repertoire, offering a potent way to build complex organic frameworks. In contrast, it is extremely challenging to develop asymmetric catalytic photoreactions that can create chiral molecules with a well-defined three-dimensional arrangement. By developing innovative methodologies to effectively address this issue, I will provide a novel reactivity framework for conceiving light-driven enantioselective organocatalytic processes. I will translate the effective tools governing the success of ground state asymmetric organocatalysis into the realm of photochemical reactivity, exploiting the potential of key organocatalytic intermediates to directly participate in the photoexcitation of substrates. At the same time, the chiral organocatalyst will ensure effective stereochemical control. This single catalyst system, where stereoinduction and photoactivation merge in a sole organocatalyst, will serve for developing novel enantioselective photoreactions. In a complementary dual catalytic approach, the synergistic activities of an organocatalyst and a metal-free photosensitiser will combine to realise asymmetric variants of venerable photochemical processes, which have never before succumbed to a stereocontrolled approach. This proposal challenges the current perception that photochemistry is too unselective to parallel the impressive levels of efficiency reached by the asymmetric catalysis of thermal reactions, expanding the way chemists think about making chiral molecules

Mots-clés : asymmetric organocatalysis,photocatalysis,asymmetric catalysis,radical reactivity
Projet ERC : CosmicAntiNuclei (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 215101.05 €

Visible matter constitutes only 5% of the matter-energy content of the Universe, whereas the remaining 95% is constituted by unknown forms of matter (20%) and energy (75%) that appear as ``dark'' to us. In the landscape of Dark Matter searches, antinuclei are a promising, almost background-free smoking gun signal for WIMPs and are a target of indirect dark matter searches. This project attacks in a systematic and comprehensive way the modelling of light antimatter cluster formation, necessary to predict the expected signal and background rates for dark matter antinuclei searches in space-borne experiments. The programme is based on precision measurements of rare antihelium production in proton-proton, proton-nucleus and nucleus-nucleus collisions with the ALICE detector at the CERN LHC. An innovative approach based on the measurement of two-particle correlations will be applied for the first time to investigate experimentally antinuclei formation via coalescence in relation to the nucleus wavefunction and interaction potential. The results of the analysis of the ALICE data will be input for the modelling of antinuclei formation and propagation in the Galaxy. The final goal of the project is to obtain a prediction for the expected cosmic ray antihelium background rate for AMS-02, further enhancing the scientific value of the proposed research programme. The outcome of this project will shed light on the production mechanisms of light nuclei and antinuclei in high-energy interactions. In addition, it will extend the ALICE and LHC physics programme to the astrophysical domain, with a deep innovative impact in a well-established field of research. It will have direct fundamental applications to indirect dark matter searches with existing (AMS-02) and future (GAPS, AMS-100) experiments, providing relevant input to frontier research in this sector.

Mots-clés : antimatter,light nuclei formation,coalescence models,phenomenology,indirect searches for dark matter
Projet ERC : EVA (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499562.0 €

Visual artificial intelligence automatically interprets what happens in visual data like videos. Today’s research strives with queries like: “Is this person playing basketball?”; “Find the location of the brain stroke”; or “Track the glacier fractures in satellite footage”. All these queries are about visual observations already taken place. Today’s algorithms focus on explaining past visual observations. Naturally, not all queries are about the past: “Will this person draw something in or out of their pocket?”; “Where will the tumour be in 5 seconds given breathing patterns and moving organs?”; or “How will the glacier fracture given the current motion and melting patterns?”. For these queries and all others, the next generation of visual algorithms must expect what happens next given past visual observations. Visual artificial intelligence must also be able to prevent before the fact, rather than explain only after it. I propose an ambitious 5-year project to design algorithms that learn to expect the possible futures from visual sequences. The main challenge for expecting possible futures is having visual algorithms that learn temporality in visual sequences. Today’s algorithms cannot do this convincingly. First, they are time-deterministic and ignore uncertainty, part of any expected future. I propose time-stochastic visual algorithms. Second, today’s algorithms are time-extrinsic and treat time as an external input or output variable. I propose time-intrinsic visual algorithms that integrate time within their latent representations. Third, visual algorithms must account for all innumerable spatiotemporal dynamics, despite their finite nature. I propose time-geometric visual algorithms that constrain temporal latent spaces to known geometries. EVA addresses fundamental research issues in the automatic interpretation of future visual sequences. Its results will serve as a basis for ground-breaking technological advances in practical vision applications.

Mots-clés : video understanding