Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet KGBVIFEF (Horizon 2020, appel à projets 2014)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Membrane fusion is a basic cell biological process found in diverse pathways ranging from vesicle trafficking and cell division to viral host entry. It is mediated by fusion proteins residing in the membrane. The underlying molecular mechanisms are supposed to follow a common order of events, i.e. fusion through hemifusion. Cell entry of Herpes simplex virus-1 (HSV-1) is enabled by glycoproteins residing on the viral envelope membrane. In contrast to other viruses, this is accomplished by different glycoprotein species, mediating together the attachment and subsequent fusion between the viral and host cell membrane. At least four of these proteins are essential for membrane deformation leading to fusion pore formation. In the here proposed project, I will take advantage of the modularity of the HSV-1 fusion machinery to dissect this process into discrete steps which I will analyse in situ at molecular resolution to determine the molecular details of membrane fusion. To do so, I will employ a multidisciplinary approach combining methods and data from structural biology, biochemistry as well as biophysics and molecular dynamics to solve the mechanistic details of a cell biological question. This includes fluorescence and cryo electron microscopy and tomography full-length membrane glycoprotein purification and biochemical reconstitution methods, biomolecular interaction and structural X-ray analysis, sub-volume averaging and classification as well as single particle imaging. To find the nenecessary triggers for fusion I will reconstitute the complete fusion system and thereby reveal the spatio-temporal changes that catalyse the fusion process. Taken together this structure-functional study will enable insights into hitherto ill-characterised intermediates in the conserved mechanism of membrane fusion. This project is a great opportunity to expand my research competence at the interphase of different fields ranging from cellular and structural biology to biophysics.

Mots clés : protein induced membrane fusion, membrane interaction, herpes simplex virus, cell entry, fusion complex, cryo electron microscopy, tomography, single particle imaging

Participants :
- University of Oxford (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 183454.8 €
Projet BrownianReactivation (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Memories are not stored in a stable manner in the brain. Instead they undergo an almost constant process of transformation and reorganization from the very moment of their formation. This phenomenon, going under the name of memory consolidation is also at the core of fundamental changes in the nature of the information carried by the neural representations. In fact, the switch from hippocampal-based short-term memories to cortex-based long-term memories also coincides with the transitions from episodic to semantic memories. In this proposal, we aim at investigating the role played in memory consolidation by stochasticity and criticality of neural dynamics. We will develop a quantitative approach to this question by combining statistical analysis of newly recorded data, with mathematical modelling of the cortical-hippocampal interaction. Our hypothesis takes the emergence of long-range correlation as the central mechanism characterizing semantic memory formation. We propose that cortical neural circuits poised at criticality can exploit activity avalanches associated with this state to induce the collective activation of large portions of the brain necessary to reconstruct the complete input statistics. Using a hierarchical neural network trained with an input of random samplings of the episodic representations stored in the hippocampus, we will explore the interaction between the performance of the network and its closeness to a critical state. We will complement this work with an analysis of the presence of criticality in the cortical cell assemblies formed after learning a complex behavioural task. We expect these cell assemblies to show maximal contribution to the propagation of neural avalanches and to present consistent coordination with the hippocampal activity. We intend to integrate these results in a coherent theory of long-term memory formation, explaining the ability to generalize starting from event-based experiences.

Mots clés : hippocampus, neocortex, semantic memory, critical systems, machine learning

Participants :
- Radboud University Nijmegen (Pays-Bas) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 175572.48 €
Projet ReWoMeN (Horizon 2020, appel à projets 2020)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : SIGNED

Memory and learning are human central cognitive abilities. The importance of understanding human memory functioning is evident from its central role in our cognitive health as well as its role as the main inspiration behind developments in artificial intelligence, in particular artificial deep neural networks (DNN). Despite considerable progress in the recent years in the area of DNNs, robustness of these networks is an important open issue. In particular, noise robustness, i.e., DNNs are fragile in maintaining the correct predictions if their input is perturbed. In contrast, a healthy human’s memory system maintains performance despite perturbed inputs. This motivates us to learn from the biological neuronal networks of human memory for a more robust DNN. The human memory is composed of several modules responsible for processing, learning, and recalling the received information. Among the memory modules is the working memory (WM) which is responsible for holding and processing information in a temporary fashion and in service of higher order cognitive tasks, e.g. decision making. The short-term nature of the WM makes it a great example for designing dynamic DNNs, which are useful in safety critical applications in uncertain environments. The aim of this proposal is to build a combined model-based and data-driven mathematical framework for understanding Recall dynamics of human Working Memory Networks (ReWoMeN) for realization of a robust DNN as well as contributing to the mechanistic understanding of the human WM. ReWoMeN address three main challenges including derivation of a biologically plausible system-level model to account for the measured data of human experience of WM recalling, analysis of such a complex model for explaining and predicting WM behavior, and comparing the robustness of our WM model with a recurrent DNN in an image recognition application.

Mots clés : nonlinear dynamical systems, memory and cognition, deep neural networks, network control systems

Participants :
- Delft University of Technology (Pays-Bas) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 175572.48 €
Projet URBINEX (Horizon 2020, appel à projets 2020)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : SIGNED

Mental health disorders are one of the primary sources of ill health for young people, affecting up to 20% of children and adolescents worldwide. Moreover, stark social inequalities in children’s mental health exist, with those from more disadvantaged backgrounds being up to three times more likely to experience mental health problems than those more privileged. Our understanding of the mechanisms through which childhood socio-economic circumstances (SEC) affect children’s mental health is incomplete. With three quarters of EU citizens now living in cities, attention is turning to the effects of environmental stressors such as ambient air pollution, traffic noise, and natural space on children’s development. In many cities, children from lower socio-economic backgrounds are disproportionately exposed to more harmful aspects of the urban environment. However, we do not know to what extent greater exposure or vulnerability to these stressors contributes to social inequalities in child mental health. URBINEX will undertake epidemiological analysis of data from over 200,000 children across 16 EU cities using the recently established EU Child Cohort Network. Cutting-edge methods in causal inference and life course epidemiology will be applied to decompose the relationship between SEC, exposure to environmental stressors and children’s mental health. The key objectives are to (i) use multi-level models to describe inequalities in mental health trajectories across childhood, (ii) use counterfactual mediation to test whether variation in exposure to urban environmental stressors mediates the relationship between SEC and mental health, and (iii) explore whether SEC and environmental stressors interact to confer additional vulnerability to mental health problems. URBINEX has the potential to inform EU policies to bring structural changes to meet UN Sustainable Development Goals in reducing health inequalities, improving mental health and building sustainable cities.

Mots clés : mental health, epidemiology, urban environmental stressors, exposome, pollution, noise, green spaces, social inequalities, socio economic conditions, socio economic status

Participants :
- University of Copenhagen (Danemark) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 219312.0 €
Projet VOLATILES_MERCURY (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : CLOSED

Mercury has been extensively characterized by the NASA MESSENGER spacecraft that was orbiting the planet from 2011 to 2015. The surface of Mercury is covered by lavas and magmatic processes have structured the planet into an extremely large core, a thin mantle and a relatively thick crust, which is highly reduced, iron-depleted, and rich in volatiles. Some volatiles (sulfur and carbon) have been measured at the surface in relatively high abundances compared to other terrestrial planets butthe speciation, role and their fate under highly reducing conditions are still unclear. In this research program, the understanding of the evolution of volatiles in magma on Mercury will be advanced by combining MESSENGER data and laboratory experiments. Relevant data will be obtained from high-temperature and low- to high-pressure experiments using furnaces, presses and multi-anvil apparatus. We will investigate experimentally compositions corresponding to the possible primitive mantle composition, and to surface compositions provided by X-Ray Spectroscopy data from MESSENGER. These recent data provide a unique opportunity to perform innovative experiments under the extremely reducing conditions characteristic for Mercury on sulfides liquid immiscibility, mantle partial melting, and speciation and solubility of volatiles in magmas. Our objectives are to provide new and firm constraints on (1) the P-T position of the solidus of the mantle of Mercury; (2) the speciation, role and fate of carbon and sulfur volatiles in magmas on Mercury and (3) the partitioning of trace elements between sulphide melts (FeS and (Ca,Mg,Fe)S) and silicate melt in the Mercurian mantle.

Mots clés : terrestrial planets, magmatic differentiation, magmas, phase equilibria, experimental petrology

Participants :
- University of Liège (Belgique) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 178320.0 €
Projet Glycoli (Horizon 2020, appel à projets 2015)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Metabolic engineering of E. coli has been highly successful in producing diverse free oligosaccharides for research and commercial applications. Currently, we are poised to address the next major challenge: the site-specific synthesis of oligosaccharides directly onto proteins in the E. coli cytosol. In this project we aim at the metabolic engineering of an N-glycosylation pathway in the E. coli cytosol using heterologous glycosyltransferases (GTs) to produce defined glycoprotein structures. Starting point is the newly discovered family of cytosolic N-glycosyltransferases (NGT), which transfer a single glucose residue onto proteins at asparagine (N) residues in the N-X-S/T sequon. Co-expression of an NGT with a galactosyltransferase has been shown to yield N-linked lactose in the E. coli cytosol. This N-linked lactose is an ideal starting point for the design of cytosolic N-glycosylation pathways to synthesize important glycans on proteins. Two goals are delineated. 1) Bacterial GTs will be screened, and potentially engineered, for their ability to extend the N-lactose with defined sugars, thereby generating a diverse repertoire of glycans directly synthesized on proteins. The focus will be on screening of fucosyltransferases and efficient production of fucosylated oligosaccharides, as these are central glycan epitopes in diverse physiological processes. 2) The newly developed glycosylation pathways will be applied to a range of protein substrates in order to explore and address possible limitations of the glycosylation system. The result will be a well-characterized glycoengineering toolbox enabling the bottom-up production of defined glycoprotein structures in E. coli.

Mots clés : metabolic engineering, glycoengineering

Participants :
- Board of the Swiss Federal Institutes of Technology (Suisse) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 187419.6 €
Projet OPEDGP (Horizon 2020, appel à projets 2014)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Metabolomics is a relatively new technology that provides information about levels of human metabolites, the low molecule products at the end (downstream) of the metabolic pathways of human physiology. In theory, metabolite profiles may more closely reflect the clinical phenotype and thus potentially improve risk prediction. Another advantage is that that they can be performed on non-invasive biofluids like urine. Several metabolomics studies have suggested that the metabolite profile of an individual can be used as a predictor of type 2 diabetes. However, evidence from large-scale population-based studies with comprehensive phenotypes of diabetes and thyroid disease is limited. The aim of the project is to identify urine metabolite profiles associated with risk of diabetes and thyroid disease and to investigate pathogenetic pathways by identifying genetic determinants of these metabolites. The project takes advantage of the long tradition of population-based and registry-based epidemiological research in Denmark. The experienced researcher will complete a training program supervised by two recognised Danish research institutions with complementary expertise in the fields of epidemiology and genetics, respectively. Hereby the experienced researcher will achieve competences in the field of statistical modelling of epidemiological data with repeated measures and use of the unique Danish registries for research. Furthermore, during the secondment at the partner institution the experienced researcher will receive training in genetic epidemiology. In return, knowledge of metabolomics will be translated to the beneficiary and partner organizations. It is expected that the results will provide novel insights into the pathophysiology of diabetes and thyroid disease and identify novel biomarkers to improve risk prediction in individuals.

Mots clés : diabetes, thyroid diseases

Participants :
- Capital Region of Denmark (Danemark) — Coordinator, beneficiary, Organismes publics (hors enseignement & recherche), subvention : 200194.8 €
Projet APPEL (Horizon 2020, appel à projets 2015)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Physics
Statut du projet : CLOSED

Metal halide perovskites are currently viewed as a new “wonder materials” due to the combination of their outstanding optical and electronic properties with the ease of processing as compared to similar direct bandgap semiconductor such as GaAs. Despite the meteoric rise of the power conversion efficiency of perovskite solar cells (up to 20% in less than 5 years) they is still a substantial potential of improvement towards the theoretical efficiency limits. During the first research phase, most of the effort has been devoted to the development of deposition processes to produce the best crystalline thin films. APPEL has the ambition to initiate the second phase, in which fundamental understanding of the recombination losses in the perovskite and at heterojunctions with charge extraction layers will make possible to generate devices with efficiencies approaching the full potential of these semiconductors. A perfect solar cell should also be an excellent emitter, since 100% of the absorbed photons must recombine radiatively. Therefore the original approach APPEL is to target primarily light emission (photoluminescence and electroluminescence) to understand the factors governing the recombination losses in solar cells. From the understanding of the fundamental recombination mechanisms at the heterojunctions, I will demonstrate highly efficient devices with >23% power conversion efficiency. Moreover, efficient light-emitting diodes (LED) will be produce alongside photovoltaic devices. This work will set the foundation of the future rational optimisation of metal halide perovskite devices in the same way that optimisation of light emission in GaAs led to the advent of devices approaching the theoretical limits.

Mots clés : photovoltaics, light emitting diodes, electroluminescence

Participants :
- University of Oxford (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 195454.8 €
Projet Pro-Oxides (Horizon 2020, appel à projets 2014)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : CLOSED

Metal oxides are a versatile group of semiconductors that are employed in a broad range of applications including micro/nano-electronics, photocatalysis and thin-film devices. The strength of metal oxides for these contemporary applications resides in the diversity of the electronic and optical properties which determine energy-level alignment and consequently dictate device performance. Furthermore, metal oxides exhibit a sensitivity to stoichiometry, unique among semiconductors, that permits fine-tuning of these properties. This feature offers an elegant yet simple method for additional performance optimisation. However, it requires a deep understanding of the relationship between the stoichiometry of metal oxide compounds and the aforementioned properties that is currently lacking. In this proposal we will fabricate metal oxides with a spatial gradient in chemical composition and characterise the optical, electrical and chemical properties with high-throughput scanner, at an unparalleled rate. From these results we will establish the correlation between these properties and the exact chemical composition for a multitude of compounds. In addition, a model to describe the alignment of energy-levels across metal oxide/metal oxides interfaces will be developed. The present proposal will address the disparity of reported information for metal oxide properties arising from poor chemical analysis and greatly advance the engineering capabilities of thin-film technologies. The research described here is designed to integrate seamlessly and strongly support the All Metal-Oxide Photovoltaic project under the Seven Framework Programme.


Participants :
- Bar-Ilan University (Israël) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 170509.2 €
Projet CADORS (Horizon 2020, appel à projets 2014)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Metallic alloys are used in many industrial applications, needing the constant development of new materials with tailored properties. However, the relations between composition, processing and properties are so complex that alloy development cannot be made anymore by a traditional trial-and-test procedure, and there is a growing need for models able to predict the behaviour of alloys as a function of composition, and for computer-aided optimisation tools for alloy design. The aim of the project is to develop new predictive models, and to include them in computing tools for the design of new nickel-base superalloys for aeronautical, energy and chemical engineering applications, through an automatic optimisation of composition by multi-objective genetic algorithms. Alloy design tools already exist and rely on a number of predictive models; we intend to extend the range of predictive tools by developing, in the case of multi-phase Ni alloys, on the one hand a model for dynamic recrystallisation (DRX) and on the other hand a model for the resistance to hydrogen embrittlement (RHE). First, computational thermodynamics will allow calculating the compositional dependence of microstructure, through the prediction of the nature and fractions of secondary phases, as well as of the driving force for nucleation, which will be used to evaluate the precipitate size and density. Then, the new models will describe the roles of precipitates on DRX (by acting as nucleation sites for the formation of new grains, or at the opposite by acting as pinning centres for grain boundaries, limiting their mobility and hence retarding or inhibiting DRX), and on RHE (by influencing, among others, the distribution of hydrogen between the matrix, the precipitates, the grain boundaries and the precipitate-matrix interfaces). Once developed and assessed, these models will be integrated as new criteria in an automatic optimisation tool for superalloy design, using multi-objective genetic algorithms.

Mots clés : metallurgy, superalloys, dynamic recrystallisation, hydrogen embrittlement, modelling, alloy design, optimisation

Participants :
- University of Cambridge (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 97727.4 €