Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Understanding insect migration behaviour and pathways using individual tracking and radar (InsectMigration)

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: Environment and Geosciences
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-02-01
End date: 2021-02-28
Duration (months): 24.0
Total project cost (EUR): 159460.8
EU funding (EUR): 159460.8
Participants: 1
Project status: CLOSED

Migration involves the seasonal movement of large numbers of animals, usually due to shifts in resource availability. Migrants connect habitats and populations, and have significant effects on ecosystem processes. Insects are the most diverse and abundant group of terrestrial migrants, but in comparison to vertebrates, insect migration is poorly studied. In particular, we have little knowledge regarding the migratory pathways of insects, and their flight behaviour and orientation in relation to topographic barriers. Using a combination of state-of-the-art techniques, individual tracking and vertically-looking radar, I aim to identify migratory routes of insects in Europe, and investigate migratory behaviour in relation to topography. This action will be the first to track migrating insects in Europe using individual-based tracking. This unique combination of methods will provide insight into the migratory behaviour of insects at landscape and local scale and provide us with an unprecedented level of information regarding the mechanisms underlying insect migration. The objectives of the work packages in this project are: WP 1: To investigate the influence of radio-transmitters on the flight behaviour of hawk moths in the laboratory. To investigate space-use and flight behaviour of hawk moths in the field. WP2: To elucidate migratory pathways of insects across Europe using individual tracking, and to understand migratory flight and orientation behaviour in relation to topography along these routes. We will also investigate which factors influence individual departure decisions and stopovers en route. WP 3: To investigate flight behaviour and orientation of hawk hawk moths in relation to weather and topography using vertically-looking radar, at key migration bottlenecks, high altitude passes in the southern Alps.

Keywords: insect migration,radio tracking,flight behaviour,decision rules,radar
Novel Lifesaving Magnetic Tentacles (NoLiMiTs)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Systems and communication engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2018-COG, 2018)
Start date: 2019-05-01
End date: 2025-04-30
Duration (months): 72.0
Total project cost (EUR): 2698136.0
EU funding (EUR): 2698136.0
Participants: 1
Project status: SIGNED

The aim of this project is to characterize fundamental principles at the intersection of robotics, magnetics, manufacturing and medicine, which will enable intelligent tentacle-like robots to augment the capabilities of surgeons in reaching deep into the human anatomy through complex winding pathways and treat inoperable diseases. Magnetic tentacle robots, proposed here for the first time, have the potential to be thin, extremely soft and scalable, and to conform to curvilinear trajectories by leveraging magnetic control over their entire length. The surgeon needing to access difficult to reach targets such as peripheral nodules in the lungs, small diseased blood vessels and regions deep inside the brain, will be able to design personalised tentacles and fabricate them on demand. My world-leading research team in surgical robotics–to be further consolidated by this grant–will define and explore new robotic architectures, as well as the design and fabrication processes integral to this novel concept. Proprioceptive sensing, combined with mathematical models, will enable intelligent robotic control. Robotic assistance will be context dependent, ranging from joystick-based operation to autonomous control along pre-planned trajectories. An integrated design environment will help systematise and streamline implementation. The research programme consists of four work packages: 1) Robotic architectures and models; 2) Intelligence and control; 3) Rapid design, simulation and synthesis; and 4) Multi-scale experimental evaluation, embracing different scenarios where control over the entire body of the robot is crucial: lung biopsy, cardiovascular interventions and neurosurgery. This interdisciplinary research will strengthen Europe’s position in medical robotics and improve public health by reducing patient recovery times, complication rates, and treatment costs, and ultimately saving the lives of patients suffering diseases that are inoperable—and often terminal—today.

Keywords: surgical robotics,robotic surgery,medical robotics,magnetic manipulation,continuum robots,cyber physical systems
Machine learning prediction for breast cancer therapy (PredAlgoBC)

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: France
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-10-01
End date: 2021-09-30
Duration (months): 24.0
Total project cost (EUR): 184707.84
EU funding (EUR): 184707.84
Participants: 1
Project status: CLOSED

Breast cancer is the cancer with the highest incidence in women worldwide, and is the leading cause of cancer-related death, mainly due to treatment resistance. Recently, tumor heterogeneity has been described as one of the key driver in treatment failure. Indeed, tumor is not a homogeneous entity to treat, but a complex association of subclonal populations driven by their own genetic alterations, and immune and stromal cells from microenvironment. Breast cancer subtypes and tumor heterogeneity advocate for the development of tailored, personalized treatments, but so far, the discovery of efficient predictive markers has been compromised by the lack of adapted biological models and methodological tools. The recent developments of high-throughput methods for bulk and single-cell analyses has generated large ‘omics’ datasets from patients, stored in open access databases (ArrayExpress, GEO). Combining these numerous datasets will grant a sufficient statistical power to reveal a comprehensive overview of tumor complexity. However, this data mining is currently limited by methodological challenges like cross-platform normalization and the difficulty to analyze complex data structure with high dimension observations. To overcome these issues, I propose to implement a multidisciplinary project at the interface between mathematics, biology, and information technologies. With the support of the mathematicians and bioinformaticians from the Bioinfomics unit of the regional comprehensive cancer center (ICO), I will develop and implement machine-learning algorithms in the search of predictive biomarkers for breast cancer treatment. This innovative strategy will lead to personalized medicine in breast cancer by guiding clinicians in the selection of the optimal therapeutic option. Moreover, this generated pipeline for predictive marker discovery could be further adapted for the treatment of other cancer types.

Keywords: breast cancer mathematical oncology,machine learning,predictive markers predictive algorithm bulk and single cell analysis,transcriptomic
Commercial feasibility of targeting the histone methyltransferase SETD8 in cancer: New chemical entities and biomarkers. (TARGETSET)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Cellular, Developmental and Regenerative Biology
Panel description: Structure and function of the cell, cell-cell communication, embryogenesis, tissue differentiation, organogenesis, growth, development, evolution of development, organoids, stem cells, regeneration, therapeutic approaches
Countries involved: Spain
Call: Call for proposals for ERC Proof of Concept Grant (ERC-2020-PoC, 2020)
Start date: 2021-07-01
End date: 2022-12-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Within our ERC CoG grant, RSHEALTH, our group has contributed to the to the preclinical development of chemical inhibitors of the ATR kinase as anticancer agents, that are now in clinical trials by several companies. During the course of our investigations, we also made important advances in developing inhibitors of SETD8, another interesting cancer-related target. SETD8 is a histone methyltransferase known to play important roles in DNA replication and repair. Evidence indicating that targeting SETD8 could be interesting for cancer therapy has been building up in recent years. For instance, SETD8 is overexpressed in a wide range of cancers, and recent works identified SETD8 as a specific vulnerability in High-Risk Neuroblastoma or MYC-driven Medulloblastomas. Unfortunately, all available SETD8 inhibitors have low potency and poor pharmacological properties, and none has progressed to the clinic. We here propose to capitalize in our strengths in academic drug development, and our experience in transferring our inhibitors to the industry, in order to facilitate the clinical development SETD8 inhibitors. Our proposal includes objectives that will help us improve the quality of our inhibitors, valorise them in preclinical cancer models and develop companion biomarkers that would be used for patient stratification. All of this would be integrated within a business plan that should facilitate a coherent development of this line of work oriented towards the clinical development of SETD8 inhibitors for the benefit of cancer patients.

Keywords: setd8,cancer,drug development,pharmacology,biomarker,preclinical valorisation
Population Codes for Space in the Mammalian Cortex (KiloNeurons)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Synergy grants
Action type: ERC actions
Countries involved: Israel,Norway
Call: ERC Synergy Grant (ERC-2020-SyG, 2020)
Start date: 2021-02-01
End date: 2027-01-31
Duration (months): 72.0
Total project cost (EUR): 9976875.0
EU funding (EUR): 9976875.0
Participants: 2
Project status: SIGNED

A major goal in neuroscience is to understand neural computation in the mammalian cortex. Since the 1950s, we have learnt how cells respond to changes in the environment but the cells have largely been observed one at a time. However, single-cell recording cannot access the complexity of distributed processing and coding in the large, intermixed cell populations of the cortex. To understand this complexity, we need population-wide activity measurements, at single-cell resolution, as well as theoretical models to interpret the data. In this project, we shall combine experiments and theory to enable a paradigmatic shift from single-cell to population analysis for a prototypical high-level cortical system, the navigation system of the mammalian medial entorhinal-hippocampal region. In this system, spatial firing correlates of individual cells are so evident that they have been given simple, descriptive names – such as place cells, grid cells, and head direction cells. The wealth of information on the phenomenology of these cells, and the existence of theoretical frameworks that offer strong predictions on their population-wide activity patterns, renders the system perfect for population-level analyses of cortical computation. We shall introduce experimental tools to obtain the amount and specificity of multi-neuron data required to decipher neural population codes in freely navigating rodents. Guided initially by theory on attractor network dynamics, we shall identify regularities in firing and connectivity patterns of thousands of simultaneously monitored neurons and use the data to test, refine and develop theoretical models. This exercise will be extended to less-understood high-end systems such as lateral entorhinal cortex, where computational operations have remained elusive due to the lack of similar single-cell correlates. The project is transformative in that it will uncover fundamental and general mechanisms of high-end cortical population coding in mammals.

Keywords: computational neuroscience,entorhinal cortex,hippocampus,attractor networks,continuous attractors,grid cells,head direction cells,cortex,neural networks,spatial computation
a Theoretical chemistry Approach to tiME-resolved molecular Plasmonics (TAME-Plasmons)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Physical and analytical chemical sciences
Panel description: Analytical chemistry, chemical theory, physical chemistry/chemical physics
Countries involved: Italy,Italy
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-04-01
End date: 2021-09-30
Duration (months): 66.0
Total project cost (EUR): 1432890.0
EU funding (EUR): 916621.53
Participants: 2
Project status: CLOSED

Ultrafast spectroscopy is a powerful tool able to disclose the atomistic real-time motion picture of the basic chemical events behind technology and Life, such as catalytic reactions or photosynthetic light harvesting. Nowadays, by cleverly harnessing the interaction of the studied molecules with plasmons (collective electron excitations supported, e.g., by metal nanoparticles) it is becoming possible to focus these investigations on specific nanoscopic regions, such as a portion of a catalytic surface or of a photosynthetic membrane. This coupling can also produce new quantum effects such as molecule-plasmon hybrid excitations. On the other hand, it makes the real-time molecular evolution and its perturbation by light more complex, and thus calls for new theoretical treatments. The available ones are unable to tackle this complexity, because they consist of phenomenological models focused on field enhancements or on generic features of the various plasmon-molecule coupling regimes. The goal of TAME-Plasmons is to develop a theoretical chemistry approach to directly simulate the real time evolution of molecules interacting with plasmons and light. Our approach lifts the current theoretical limitations by coupling a real-time quantum chemical description of the molecules with a time-dependent electromagnetic description of plasmons, rooted in our previous work on steady-state molecular plasmonics. We will implement this approach in an open-source software, accessible also to non-specialists. We will address current open issues such as the controversial nature of plasmon-aided frequency up-conversion by noble gases and the interpretation of sub-molecularly resolved photoemission induced by scanning tunneling microscopy. We will also anticipate questions that may arise along with progress in the field, for example how to engineer energy transfer paths in photosynthetic light harvesting proteins by exploiting the coupling to plasmons.

Keywords: time dependent density functional theory,ultrafast spectroscopy,molecular plasmonics,implicit solvation models
Bioinformatic approaches to identify and detect both disease- and drug-related genomic alterations in breast cancer patients (BRIDGES)

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: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-06-01
End date: 2017-05-31
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

Breast cancer is the most common cancer among European women showing high clinical and molecular heterogeneity. Current clinical management causes patients overtreatment with implications on both patients’ quality of life and healthcare costs. Moreover, intrinsic or acquired tumor resistance to treatment leads to incurable metastatic progression in a significant proportion of patients. Advances in cancer genomics highlighted a high inter- and intra-tumor genetic heterogeneity, reinforcing the need for a mutation-based personalized treatment and a way to non-invasively monitor evolving disease. This project will significantly contribute in addressing such unmet challenge aiming 1) to identify altered breast cancer driver pathways, 2) to study their association with drug response and 3) to develop tools for a non-invasive assessment of such alterations. By integrating multi-dimensional molecular data from more than 3000 cases, driver pathways will be identified and their association with previous breast cancer classifications as well as their prognostic significance will be studied. Their predictive power will be investigated in a matchless bio-bank of Patient Derived Xenografts, a much more reliable pre-clinical model, able to recapitulate inter- and intra-tumor heterogeneity observed in patients. Multi-dimensional molecular data and high throughput drug screenings are available and will be integrated to identify novel pharmacogenomics associations. Mining of such amount of data will allow defining a portfolio of relevant breast cancer alterations that will be sought in plasma of patients from the DETECT trial, towards a non-invasive monitoring able to guide therapeutic strategy. Development and application of cutting-edge computational approaches is fundamental to reach above aims and it will constitute a major part of the efforts, considerably expanding Experienced Researcher's know-how in the field of cancer genomics and translational medicine.

Keywords: breast cancer,next generation sequencing,cancer genomics,cancer biomarkers,precision medicine,circulating tumor dna,drug resistance
Single-Use paPER-based fuel CELLs (SUPERCELL)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Spain
Call: ERC Consolidator Grant (ERC-2014-CoG, 2014)
Start date: 2015-07-01
End date: 2021-06-30
Duration (months): 72.0
Total project cost (EUR): 1920738.0
EU funding (EUR): 1920738.0
Participants: 1
Project status: CLOSED

The advances in paper microfluidics taking place in recent years show that the new generation of paper-based devices will be able to overcome the limitations of traditional lateral flow tests and offer more accurate and specific information. However, the quantification of paper devices signals by colorimetry, electrochemistry or fluorescence entails the use of sensors and electronic components that require energy to function. Up to now, this has been solved by the use of battery-powered bulky readers, but this is only cost-effective when the reader is meant to be used thousands of times (hospital, care rooms, etc). It is becoming clear that the proliferation of paper-based sensors and their enormous potential impact when applied to personalized healthcare ask for innovative solutions that provide affordable readout. Despite dedicated on-chip solutions that integrate all the required components within a disposable test seem to be the most promising approach, available examples of realization are still scarce. The SUPERCELL project aims to develop a new generation of disposable and low environmental impact fuel cells. The approach presented in this proposal will be a major breakthrough in the fuel cell field, as these devices are conceived for the first time as single-use and disposable power sources. It will also have an enormous impact in the point-of-care diagnostics domain, as it will provide simple, reliable and clean power sources to an upcoming generation of smart paper-based sensors and allow them to be energetically autonomous. Fuel will be harvested from the biological sample to be analyzed – in case of urine and blood – or taken from hydrogen produced in situ upon the addition of any liquid in the paper platform. The proposal is very innovative in conception as well as in technology as these devices will be developed by means of a smart integration of paper microfluidics, printed electronics and electrocatalysis technologies.

Keywords: microfuel cells,paper microfluidics,organic electronics
Strongly Correlated Physics and Materials for Energy Technology (StrongCoPhy4Energy)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Condensed matter physics
Panel description: Structure, electronic properties, fluids, nanosciences, biological physics
Countries involved: France
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-04-01
End date: 2022-12-31
Duration (months): 69.0
Total project cost (EUR): 1656250.0
EU funding (EUR): 1656250.0
Participants: 1
Project status: SIGNED

Materials where conduction electrons experience strong correlation in their dynamics, are both a challenge to the current quantum theories of matter and a mine for possible technological applications. High-temperature copper- and iron-based superconductors and heavy-fermions with large thermoelectric responses are examples of materials with high potential impact on energy transmission and storage technologies or high-magnetic field applications. Recently, the discovery that the well known atomic "Hund's rules" have a surprisingly great and diversified influence on the conduction electrons in d-electron materials changed the traditional view of electronic correlation as a competition between kinetic energy and Coulomb repulsion, adding Hund's exchange energy as a third axis. This project, by using state-of-the-art computational techniques for correlated materials, aims at clarifying the influence of the new Hund's driven mechanisms as possible enhancers of high-Tc superconductivity and of thermoelectric and thermomagnetic properties. In particular Hund's coupling can induce the coexistence of weakly and strongly correlated conduction electrons, culminating in orbital-selective Mott insulating states or in heavy-fermionic physics. We then aim at the creation of a new class of transition-metal (d-electron) compounds reproducing the properties of the more exotic rare-earth (f-electron) heavy-fermion materials, in a tunable way. Iron-based superconductors exhibit some of these properties and will be used as a starting point for the search and exploration of new and enhanced high-temperature superconductors and thermoelectric/thermomagnetic d-electron materials. An exciting application is also proposed, motivating a possible resurgence of technological attention towards thermomagnetic materials: the coating of high-power cables in thermomagnetic materials for self-cooling, and potentially room-temperature superconduction.