Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Mechanical Adaptation of Lamellipodial Actin Networks in Migrating Cells (LamelliActin)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Austria
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-03-01
End date: 2019-02-28
Duration (months): 24.0
Total project cost (EUR): 178156.8
EU funding (EUR): 178156.8
Participants: 1
Project status: CLOSED

Cell migration is centrally involved in embryonic development, regeneration and immune surveillance. However, when misguided it also contributes to the pathogenesis of Europe’s socioeconomic most relevant diseases including cancer, cardiovascular diseases and chronic inflammation. Accordingly, better understanding the fundamental mechanisms of cell migration is of direct clinical relevance. In order to migrate within a multicellular context, cells have to negotiate physical constraints, such as other cells and the extracellular matrix and effectively integrate mechanical challenges into directional decision-making. This proposal suggests a combined cell biological and biophysical approach to provide a quantitative understanding of the underlying molecular and mechanical principles. We will focus on the prototypic force-generating structure of migrating cells the lamellipodium - a flat sheet-like protrusion of dendritic actin networks at the leading front of migrating cells. We will decipher the ultrastructural adaptations of lamellipodial actin networks with single filament resolution and characterize how nucleation, elongation, depolymerization and crosslinking of actin filaments coordinate circumnavigation of mechanical obstacles. Technically, these questions will be addressed in a multidisciplinary approach by employing correlative fluorescence and electron tomography in combination with artificial environments engineered using microfluidics and substrate micropatterning, as well as genetic approaches and biological modelling. Importantly, findings will ultimately be challenged in living tissues. The expected results will generate an integrated view of force-adaptations of actin networks in living cells and will not only impact the fields of cell biology and biophysics but also cancer biology, immunology and developmental biology.

Keywords: cell migration,lamellipodium,actin networks,actin regulatory proteins,fish keratocytes,dendritic cells,correlative fluorescence and electron tomography
Speeding up the virtual reality revolution with realistic & real-time animation of hand-to-object interaction (VirtualGrasp)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Sweden
Call: SME instrument (H2020-EIC-SMEInst-2018-2020-3, 2020)
Start date: 2020-07-01
End date: 2021-12-31
Duration (months): 18.0
Total project cost (EUR): 700120.0
EU funding (EUR): 490084.0
Participants: 1
Project status: CLOSED

Gleechi was founded in 2014 by Dan Song (a PhD in biomedical engineering), Kai Hübner (a PhD in computer science & robotics) & Jakob Way (a successful serial entrepreneur), building up on 8+ years of advanced research at Swedish Royal Institute of Technology (KTH) in enabling robots to use their manipulators more efficiently. Gleechi develops VirtualGrasp – the first and only standard software solution that creates realistic real-time hand animation & hand-to-object interaction in virtual environments. With predictive & adaptive machine learning algorithms that analyze the physical properties of a virtual object, decipher the most appropriate and realistic grip formation for the hand model and snap to that position, VirtualGrasp will enable immersion and presence in virtual reality not attainable by current ad-hoc methods, such as pre-animation. The global market for virtual reality software is forecasted to reach €32.8bn by 2025 (with videogames, healthcare and manufacturing being the largest segments). Providing a crucial enabling technology for interaction with objects in virtual space, Gleechi aims to address three lucrative market segments: 3D videogames, training in manufacturing and stroke rehabilitation, and grow to €90m+ in revenues and 200+ employees by 2025. Gleechi has been awarded Super Startup of 2015 by Veckans Affärer and is supported by several Swedish Innovation clusters, including STING, VINNOVA, KTH Innovation, EIT ICT Labs, and ALMI. Gleechi was listed as one of the hottest tech startups in Sweden 2018. In 2016 VirtualGrasp was listed as one of the 5 Swedish innovations that “could change your life”. Gleechi’s customers and partners include HTC, CEA, ABB, Intel, Karolinska Institutet and others. We are currently running a Phase 2 project, and are requesting additional €490,000 of grant to industrialize our solution for robotics & €5.4m of equity to commercialize across 4 segments.

Keywords: virtual reality,hand motion,hand interaction
Neural Mechanisms of Action-Selection During Sensory Conflict (CourtEscape)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-09-01
End date: 2024-08-31
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: SIGNED

Prioritising the most urgent goal according to the context and physiological needs is crucial for the success of any organism. Action-selection processes are often disrupted in neuropathologies, such as Parkinson's disease, Alzheimer's disease and addiction; however, the underlying neuronal mechanisms are not well understood. Crucially, how the brain evaluates sensory conflicting options and selects an appropriate action remains unknown. I will tackle this question using a novel assay in which Drosophila fruit fly males are confronted with visual threats during courtship, which creates a conflict between survival and reproduction. Capitalising on refined genetic tools, I aim to unravel neural mechanisms that govern the selection between competing options. I will carry out a behavioural screen to identify neurons that allow the fly to choose between courting a mate and escaping a threat. From an in silico screen of Gal4 fly lines targeting defined cells, I will select lines based on their potential connectivity with courtship-command neurons. Using optogenetic tools, I will identify neurons that, when activated or inhibited, prevent males from blocking courtship in response to the threat. Next, I will ask if these cells respond to the threat in live Ca2+ imaging studies, and test if they are linked with the courtship circuitry using pre and post-synaptic markers and GRASP (to test potential synaptic connections). To probe if candidate neurons are functionally linked, I will manipulate the activity of upstream cells, and test the responses in downstream cells with Ca2+ imaging. This will allow me to build a map of the neural network of action-selection. Finally, I will test how external and internal state variables modulate action-selection. This study will provide insights into fundamental brain processes that may work in other animals, including humans.

Keywords: drosophila,decision making,neural circuits,action selection,optogenetics,calcium imaging,defensive behaviour,courtship behaviour,confocal light microscopy,connectome,neurogenetic dissection
Building a causal regulatory network of mesenchymal cells using targeted programming experiments (DesignerCells)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Switzerland
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-09-01
End date: 2023-08-31
Duration (months): 24.0
Total project cost (EUR): 203149.44
EU funding (EUR): 203149.44
Participants: 1
Project status: SIGNED

Gene regulation is one of the main drivers of a cell's fate and function, but current methods that infer genome-wide regulatory networks have problems with inferring causal and/or combinatorial interactions. Pooled single-cell screening technologies, such as those developed in the host lab, now provide a powerful alternative to regulatory network inference. However, as this technology matures, data analysis is now more and more becoming the rate-limiting step in inferring causal and combinatorial regulatory networks. In this project, I will develop a combined computational and experimental workflow to infer regulatory networks. At the computational side, I will develop an algorithm that models how combinations of transcription factors affect a cell's state. The model will go beyond a ball-stick model, and investigate combinatorial logic, dosage effects, cell proliferation and cellular heterogeneity. The algorithm will also propose new combinations that may move a cell towards a fate of interest. Through multiple rounds of modelling and experimentation, I will iteratively improve our understanding of the causality and combinatorics of a regulatory network. I will validate the workflow on mesenchymal stem cells (MSCs), a cell type for which some (combinations of) transcription factors that drive its differentiation are already known, but for which a combinatorial view across lineages is still missing. I will first start with easier well-studied systems, such as adipocyte differentiation, and later in the project move on to less-studied systems such as adipocyte progenitors. By integrating experimental and computational techniques, the proposed project will provide a causal regulatory network across MSC lineages, and yield a framework to generate such a network in other systems. Moreover, the project will allow me to expand my computational skill set with emerging experimental techniques and management skills which will be invaluable for advancing my scientific career.
How iron and manganese affect the central metabolism in pathogenic mycobacteria (Myco_Metabolism)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-06-15
End date: 2023-06-14
Duration (months): 24.0
Total project cost (EUR): 171473.28
EU funding (EUR): 171473.28
Participants: 1
Project status: SIGNED

I aim to define how Mycobacterium tuberculosis (Mtb) and Mycobacterium abscessus (Mabs) have adapted their central metabolism (CM) to variation of metals availability. Bacterial nutrition is a fundamental aspect of pathogenesis. While the host environment is in principle nutrient-rich, hosts have evolved strategies to interfere with nutrient-acquisition by pathogens. Pathogens, in turn, have developed mechanisms to circumvent these restrictions. The ability to adapt to nutrient availability drives the fitness of pathogen, influencing the outcome of infection. One of the strategies adopted by innate immune cells such as macrophages and neutrophils to limit bacterial replication is varying the availability of metals, starving or intoxicating the unwelcome guest. The expression and the activity of some central metabolism enzymes are regulated by metal availability in pathogenic bacteria, and it is unknown how this regulation affects the assimilation of carbon sources. Preliminary data shows that Fe and Mn affect the carbon sources metabolism in these pathogens. I aim to identify potential Fe or Mn-regulated metabolic routes utilising proteomics (LC-MS/MS) and metabolomics (LC-MS). These investigations will help to elucidate a neglected aspect of mycobacterial physiology, the interaction between metal homeostasis and central metabolism, disclosing more mechanisms underlying the mycobacteria physiology. Through this EF, I will bring the knowledge acquired during my five-year appointment at the Francis Crick Institute (UK) (mycobacterial metabolism and metabolomics) to my origin country (Italy) implementing my research line at the University of Padua. Through this EF, I will undertake training to re-enforce my independence, increase my expertise in proteomics (at the UNIPD) and metabolomics (at the secondment, Francis Crick).

Keywords: mycobacteria,metal homeostasis,central metabolism,metabolomics,proteomics
FLow Induced Phase Transitions, A new low energy paradigm for polymer processing (FLIPT)

Framework: Horizon 2020 — Excellent Science
Programme: Future and Emerging Technologies (FET)
Theme: EIC Pathfinder
Destination: Novel ideas for radically new technologies
Action type: Research and Innovation actions
Countries involved: Germany,Finland,Finland,Denmark,United Kingdom,Portugal,United Kingdom
Call: FET-Open research projects (H2020-FETOPEN-2014-2015-RIA, 2015)
Start date: 2016-09-01
End date: 2019-12-31
Duration (months): 40.0
Total project cost (EUR): 3741871.25
EU funding (EUR): 3741870.25
Participants: 9
Project status: CLOSED

Currently there is no truly sustainable pathway for the production of plastics, an industry which in the EU employs 1.45M people, has a turnover of €89B but consumes ~778GWh of energy per annum. This is an opportunity for industry with pressure increasing to develop low energy, high-quality, wet-processing techniques for consumer products. Here Nature may provide us with inspiration, as over hundreds of millions of years, it has evolved numerous strategies for efficient processing of its materials. One such solution has been recently hypothesised in natural silk spinning: FLIPT: FLow Induced Phase Transitions, a disruptive process which we believe could hold the key to a new low energy paradigm for polymer processing. Our research is promising, as it has already shown that silk is at least 1000 times more efficient at processing than a standard polymer (HDPE). To address these challenges our consortia will combine the expertise of world-leading groups in natural materials, polymer synthesis and material processing alongside practical input from 2 SME partners and larger European companies. Taking inspiration from the spider and silkworm, novel functionalised polymers (‘aquamelts’) will be created that utilise FLIPT; enabling controlled solidification with minimal energy input. We firmly believe that there is huge potential in uncovering silks hidden functionality and applying it to enhance the processing of a range of polymeric materials. It is our goal to develop a platform technology to generate novel, bespoke, naturally derived, low embodied-energy materials, which would be competitive with current petroleum-based polymers in terms of performance and economics while well exceeding such materials in terms of sustainability.

Keywords: biopolymers,silk,cellulose,suberin,cutin,natural materials,sustainability,life cycle assessment,rheology,spectroscopy
Multi-cloud Execution-ware for Large-scale Optimized Data-Intensive Computing (MELODIC)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Norway,Greece,Poland,Norway,Czechia
Call: Cloud Computing (H2020-ICT-2016-1, 2016)
Start date: 2016-12-01
End date: 2020-01-31
Duration (months): 38.0
Total project cost (EUR): 4890223.75
EU funding (EUR): 4890223.75
Participants: 7
Project status: CLOSED

MELODIC will enable data-intensive applications to run within defined security, cost, and performance boundaries seamlessly on geographically distributed and federated cloud infrastructures. Serving the user’s needs and constraints, MELODIC will realise the potential of Cloud computing for big data and data-intensive applications by transparently taking advantage of distinct characteristics of available private and public clouds, dynamically optimise resource utilisation, consider data locality, conform to the user’s privacy needs and service requirements, and counter vendor lock-in. These benefits are achieved by integrating and extending the results and the open source platforms available from three major European Cloud projects with the Hadoop and Spark big data frameworks: The PaaSage platform will be used for intelligent and autonomic cross-cloud deployment and is extended with data aware modelling and deployment configuration reasoning; the CACTOS platform is extended with support for Hadoop and Spark in cross-Cloud application deployment and management; and the PaaSword platform will ensure unified data security and cross-Cloud privacy. MELODIC will integrate with the existing open source development teams for these platforms and the contributions will be released back to the used platforms as open source. The integrated MELODIC platform will be maintained and exploited by a professional software house, and tested in several demanding real world applications: scalable Customer Relationship Management, real-time optimised traffic routing, and fast and scalable processing of genomic data.

Keywords: multi cloud,federated cloud,data intensive cloud computing
Multimodal characterization of the visual word form area: An integrative computational model (ReCiModel)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Spain,United States
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-09-01
End date: 2021-08-31
Duration (months): 36.0
Total project cost (EUR): 257191.2
EU funding (EUR): 257191.2
Participants: 2
Project status: CLOSED

The ventral occipito-temporal (vOT) association cortex contributes significantly to recognize different types of visual patterns. It is widely accepted that a subset of this circuitry, including the visual word form area (VWFA), becomes trained to identify word forms. Nevertheless, due to heterogeneous experimental procedures across studies and intrinsic limitations of functional and structural MRI tools, the exact cortical location of what it is referred as the VWFA typically differs between studies. Additionally, it should be expected that different adjacent brain tissue within the vOT to perform different specific computations. In fact, previous functional, structural, and cytoarchitectonic evidence has highlighted the possibility that distinct VWFAs are involved in different aspects of the visual word recognition process. Here, I propose to conduct the first systematic investigation combining functional and structural MRI data to further characterize spatially segregated VWFAs. Analogously, the functional and structural connectivity between these VWFAs and other relevant visual and language brain regions will be examined as well. These data will be incorporated into a detailed statistical model intended to predict reading behaviour, as the ultimate goal of the project is to create a highly detailed characterization of the early stages of reading and to establish a baseline model and parameter range that will serve to clarify differences between typical and atypical readers.

Keywords: neuroscience,reading,dyslexia,vwfa,neurocomputational model
Artificial Intelligence for Recruitment Europe (AIRE)

Framework: Horizon 2020 — Societal Challenges
Programme: Europe in a changing world - inclusive, innovative and reflective societies
Action type: SME instrument
Countries involved: Ireland
Call: New business models for inclusive, innovative and reflective societies (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-08-01
End date: 2018-01-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The SME has developed significant market intelligence to create a successful proof of concept over the past 36 months. We now possess a tangible working prototype and a world first concept in reshaping the hiring and skills domain. Our rationale is to get market validation, build and scale, seek investment and integrate into the market. We are committed to making a step change in the future of activating people into jobs Not having a job limits people from participating in the economic and social life of a modern society. The EU flagship initiative "European platform against poverty" seeks to ensure social and territorial cohesion such that the benefits of growth and jobs are widely shared and people experiencing poverty and social exclusion are enabled to live in dignity and take an active part in society. During previous waves of automation, workers could switch from one kind of routine work to another; but this time many workers will have to switch from routine, unskilled jobs to non-routine, skilled jobs to stay ahead of automation. That makes it more important than ever to help workers acquire new skills quickly. In this increasingly dynamic market, EU Citizens face two key challenges: 1. Unemployed citizens need to make sure their skills match those required by prospective employers 2. Employed citizens need to ensure their skills are being kept up to date with changing requirements for the job AIRE – Artificial Intelligence for Recruiting Europe will introduce a world 1st personal robot (AIREbot) to help every European apply for jobs, update their skills, register for courses and arrange interviews. This technology will disrupt the market empowering recruitment across the EU in 25 languages. We will create a return of 183% on Phase II investment of 2.4m, grow the company sustainably and hire 70+ staff .Most importantly lower current and future unemployment by filling vacancies faster and ensuring every European is aware of their current skills gap

Keywords: artificial intelligence,machine learning,european standard for classification of occupations,hiring,upskilling,employment,unemployed,robotic,process automation,matching,natural language proc