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

DIARIES will enable the experienced researcher, Dr Amy Prendergast (AP) to undertake a 24-month fellowship – Textuality, Place, and the Self: Reimagining Life Writing through Women’s Diaries from Ireland, 1725-1810 – at Queen’s University Belfast, under the supervision of Professor Moyra Haslett, an expert in eighteenth-century Irish and women’s writing. Engaging with overlooked archival diaries by women across Ireland, DIARIES will reconceptualise the diary form and reinvigorate international concepts of the diurnal self, transforming the field of life writing, and contributing to groundbreaking findings for Eighteenth-Century Studies. Incorporating methodologies and approaches from multiple disciplines, the project will allow high-impact dissemination, forming the basis of AP’s second monograph, an international interdisciplinary conference, a peer-reviewed journal article, and a website. Exploring the creative potentials of exchange between university and practitioner organisations, DIARIES will allow for the reimagining of Ireland’s literary and cultural heritage in both Northern Ireland and Republic of Ireland, advancing and enhancing understanding of both the 18c and women’s lives. This period of mobility will see AP learn new research-specific skills; continue her professional development; and gain research-relevant inter-sectoral experience through a prestigious secondment at the National Trust. The pioneering research generated will be innovatively disseminated for diverse audiences within and beyond the academy, embedding knowledge through workshops, an exhibition, teaching and collaboration, and cross-border outreach events. DIARIES will augment and advance AP’s international reputation as a leading scholar of 18c writing and an emerging expert in life writing, enabling her to realise her outstanding potential, and positioning her to secure a permanent lectureship in a prominent European University.

Mots clés : life writing, women s writing, eighteenth century writing, irish literature, paratext, archives

Participants :
- Queen's University Belfast (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 224933.76 €
Projet DNA NANO MAP (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

DNA analysis will become an important clinical tool in identification the composition of microbial species living in the gut. The most dominant technique at the time is based on PCR amplification of the 16s rDNA gene and subsequent sequencing of the variable region in the gene. This method however is limited in the amount of detail it provides and is notoriously susceptible to primer bias. Furthermore, due to the requirement of a PCR machine and sequencer the technique is too expensive and time consuming for a clinical setting. Over the past few years nanopores have been heralded as a cheap alternative for biomolecular analysis. Specifically solid-state nanopores, which consist of a small pore in a solid membrane, have the potential for cost-effective mass-production in cleanroom facilities. Furthermore, since these pores can detect double stranded DNA they can easily be used for analysis of DNA maps. In this proposal I suggest to use DNA mapping with solid state nanopores. The basic idea is to sequence-specifically label DNA molecules using DNA Methyltransferases and synthetic analogues of the natural cofactor S-adenosyl-methionine. The pattern of labels attached to the DNA is unique for the underlying sequence. In my Ph.D. I used this method to transfer fluorescent dyes to the DNA and subsequently extracted the DNA map using super resolution fluorescence microscopy. In this case, the attached label will induce a current-drop when the DNA molecule translocates through the channel. The extracted current-trace will then be converted to a DNA map in basepairs and can be used to match to a real sequence. This proposed method can be used to identify genomic elements and eventually be used to recognize species, for a fraction of the cost of 16s rDNA sequencing.

Mots clés : nanopores, mapping, methyltransferase, microbiome

Participants :
- Board of the Swiss Federal Institutes of Technology (Suisse) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 175419.6 €
Projet ProArc (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : SIGNED

DNA and proteins are now almost routinely being retrieved from sediments and archaeological artefacts. Despite the realization that adsorption of DNA molecules onto the surfaces of minerals can significantly decrease the DNA and protein decay rate, the longevity of mineral bound biomolecules is a still-standing frontier. Recently it was shown that peptide sequences in eggshell proteins persist to 3.8 Ma in Africa, implying that protein sequences will span the whole of human history in all parts of the world. Ancient protein sequences, therefore, persist beyond the lipid or DNA sequence and can be used to identify organisms (ZooMS), identify specific tissues, sex individuals, and identify tissue responses to disease. Understanding the protein-mineral interaction and environmental preservative conditions of adsorbed biomolecules – proteins can thus allow us to a) target such environments for paleoecological and palaeogenetic studies and; b) serve as a quantitative tool for assessing protein sequence migration i.e. ancient microbial communities. To date, we only have a qualitative idea of how solution composition affects the protein-mineral adsorption/desorption at the bulk level, and we have no quantitative insight into the single bond level energetics as well as the nature and fraction of the interacting bonds. With ProArc I will: a) assess the proteins preservation state in archaeological samples like calculus and ceramics and other fossil samples. I will also: (b) quantify the Gibbs free energy (ΔGbu) and kinetic bond parameters of in vitro protein-mineral interactions; and (c) examine the nature, fraction and stability of interacting bonds of in vitro protein-mineral associations at the bulk level. (d) Finally, I will make a conceptual model for addressing the characteristics and longevity of different protein-mineral systems.

Mots clés : dental calculus, ancient ceramic, milk proteins, palaeoproteomics, protein mineral interactions

Participants :
- University of Copenhagen (Danemark) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 207312.0 €
Projet STRUDEL (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Deep learning is an enormously successful recent paradigm with record-breaking performance in numerous applications. Individual autoencoders (AEs) of a multilayer neural network are trained to convert high-dimensional inputs into low-dimensional codes that allow the reconstruction of the input. Although some explanations appear to be solidly grounded, there is no mathematical understanding of the AE learning process. This project is a collaborative endeavor of researchers with strong complementary backgrounds. Its main innovation is the idea to capitalize on powerful and fertile concepts from information theory (expertise of researcher) in order to advance the state of the art in deep learning (expertise of supervisor at TC). The innovative research work is motivated by our recent insight that there is an intimate relationship between AEs, generative adversarial nets and the information bottleneck method. This method is a model-free approach for extracting information from observed variables that are relevant to hidden representations or labels and will serve as basic building block for an information theory of representation learning. The planned objectives are split into 3 workpackages: 1) information-theoretic criteria and statistical tradeoffs for extracting good representations, 2) structured architectures/algorithms for learning, 3) use of stochastic complexity to assess the descriptive power (model selection) of deep neural networks. Accomplishing the challenging goals of this proposal requires a variety of methodologies with a rich potential for transfer of knowledge between the involved fields of information theory, statistics and machine learning. Our new framework is expected to bridge the gap between theory and practice to facilitate a more thorough understanding and hence improved design of deep learning architectures. The fellow researcher is coordinating the LIA Lab of the CNRS (started in 2017) where he is collaborating with the supervisor at TC

Mots clés : machine learning, deep learning, information theory, autoencoder, unsupervised learning, supervised learning, learning algorithms, distributed representations, neural networks

Participants :
- Université de Montréal (Canada) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- CentraleSupélec (France) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 171349.2 €
Projet DNLIBiomed (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Deep neural networks (DNNs) have become a critical tool in natural language processing (NLP) for a wide variety of language technologies, from syntax to semantics to pragmatics. In particular, in the field of natural language inference (NLI), DNNs have become the de-facto model, providing significantly better results than previous paradigms. Their power lies in their ability to embed complex language ambiguities in high dimensional spaces coupled with non-linear compositional transformations learned to directly optimize task-specific objective functions. We propose to adapt Deep NLI techniques to the biomedical domain, specifically investigating question answering, information extraction and synthesis. The biomedical domain presents many key challenges and a critical impact that standard NLI challenges do not posses. First, while standard NLI data sets requires a system to model basic world knowledge (e.g., that ‘soccer’ is a ‘sport’), they do not presume a rich domain knowledge encoded in various and often heterogeneous resources such as scientific articles, textbooks and structured databases. Second, while standard NLI data sets presume that the answer/inference is encoded in a single utterance, the ability to reason and extract information from biomedical domains often requires information synthesis from multiple utterances, paragraphs, and even documents. Finally, whereas standard NLI is a broad challenge aimed at testing whether computers can make general inferences in language, biomedical texts are a grounded and impactful domain where progress in automated reasoning will directly impact the efficacy of researchers, physicians, publishers and policy makers.

Mots clés : biomedical information extraction, question answering, natural language inference, deep learning

Participants :
- Athens University of Economics and Business (Grèce) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 82326.6 €
Projet MEMENTO (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Deeply embedded in the medial temporal lobe (MTL) memory system, the entorhinal cortex (EC) is a small yet potentially key region for intact memory. While a series of recent ground-breaking findings in rodents point towards a pivotal role of EC in spatial navigation, thought of as an evolutionary precursor to memory, little is known about its precise contribution to episodic memory in humans. Building on preliminary evidence that EC subregions may be specialised for different stimulus types and/or different memory processes, MEMENTO proposes a systematic investigation of memory function in the human EC. The action combines state-of-the-art high-resolution and ultra-high field functional magnetic resonance imaging (fMRI) with advanced analysis techniques to assess how these EC subregions support material-specific memory processing on four levels of resolution: the laminar level, the subregion level, the system level, and the behavioural level. MEMENTO is highly collaborative: it brings together expertise of the ER (high-resolution fMRI of entorhinal cortex subregions), the host supervisor (functional dynamics of the MTL, advanced fMRI analysis), and the partner organisation (ultra-high field fMRI). Given that the EC is one of the first structures affected in Alzheimer’s disease, the project results have great potential to stimulate important clinical implications. The ER will advance her research profile through highly transferable experience not only with cutting-edge methods, but also with managing and engaging in scientific and public communicative events. This will qualify her to lead her own research group upon returning.

Mots clés : entorhinal cortex, medial temporal lobe, episodic memory, high resolution fmri, ultra high field fmri

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

Deformation zones may localize seismicity not only at upper crustal levels along brittle faults, but also at greater depth along ductile shear zones. The latter is at odds to classic rheological models predicting shear zones to creep and behave aseismically. Cycles of frictional and viscous deformation and brittle precursors to ductile deformation have been proposed as possible explanation. The “SLIP” action will contribute to better constrain seismic localization at mid-crustal depths along ductile shear zones by studying key areas of the Northern Apennines of Italy (NA). SLIP relies on the hypothesis that exhumed brittle-ductile shear zones of the inner NA represent the fossil analogue of the still seismically active deformation zones in the central and external portions of the orogen. SLIP will investigate microstructures in a multidisciplinary action to derive constraints upon the seismic deformation mechanisms steering the orogen seismic activity. The objectives of this proposal are to: 1) Unravel the pressure-temperature-time-deformation histories of exhumed fossil shear zones; 2) Define the role of fluids in triggering metamorphic reactions, enhancing deformation and steering the transient rheology of the shear zones; 3) Determine the provenance of the metamorphic fluids; 4) Reconstruct the tectonic evolution and the conceptual seismotectonic model of the NA. To achieve the above defined specific objectives, a multidisciplinary approach has been designed including fieldwork, optical and scanning electron microscope analyses, Raman spectroscopy, electron probe micro-analyser, laser ablation mass spectrometry, thermodynamic modelling, and age dating of deformation fabrics. SLIP will contribute to our understanding of shallow to mid-crustal earthquakes and its results will remarkably assist in better interpreting current seismic patterns and crustal behaviours. It will also shed new light on the fluid pathways and fluid-rock interaction processes in the crust.

Mots clés : structural geology, petrology, fault geochronology, petrochronology, brittle ductile transition, shear zone rheology, fluid rock interaction, seismotectonic model

Participants :
- University of Bologna (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 183473.28 €
Projet solLED (Horizon 2020, appel à projets 2020)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Physics
Statut du projet : SIGNED

Delivering light deep into tissue is an important open challenge in biomedical engineering, with particular relevance for optogenetics. One feasible solution is the application of miniaturized bio-implantable light-emitting devices. Such devices should be able to adapt to stimulate cells in tissues with different shapes, sizes, stiffness, and mechanical characteristics. OLED is the most successful light application in current display technologies with many advantages but it cannot adapt to the extreme requirement in three-dimensional structures. The limitations come from the multi-layered device architecture and manufacturing process of vacuum evaporation. Here, we propose a radically different device concept, a solution-phase light-emitting device (sol-LED) with a simple structure that can readily adapt various form factors and thus is of particular relevance to novel applications in the biomedical context. The sol-LED consists of electrodes and a solution that adopts the exciplex host-dye guest system. The fabrication is based on the process under liquid-state such as injection and capillary processes to fill the space in pre-formed devices. The proposed sol-LED will take advantage of existing state-of-the-art OLED materials and established OLED device physics and translate them to the liquid state by dissolving solid-state materials in suitable solvents. Apart from developing this entirely novel type of light source, the use of sol-LEDs as light-source for optogenetics will be developed and tested. Sol-LED with a needle-like shape will be produced by injection of the solution into a hollow microneedle. The resulting devices will be implanted into muscles of the posterior thighs of mice. The motor function will then be mimicked by alternating stimulation of the muscle cells responsible for contraction of the left and right legs. With this, we will test if the device can stimulate cells in vivo with constant intensity and frequency despite strong muscle movements.

Mots clés : organic electronics, optoelectronics, bio implantable device, solution phase device, device fabrication, optogenetics, peripheral nervous systems, neuroscience

Participants :
- University of Cologne (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 162806.4 €
Projet ViSionRF (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Dementia is a syndrome in which there is cognitive function deterioration and memory loss. Alzheimer's disease consists or contributes to 60–70% of dementia cases. At present, worldwide around 50 million people have dementia, but nearly 10 million new cases are added every year. The total number of people suffering from dementia is projected to reach 82 million in 2030 and 152 million by 2050 – a 3-fold increase. This puts tremendous pressure on the healthcare system and society as a whole. Equally important, dementia is overwhelming for patients' families and their carers, as they require full-time care and watch. For all these reasons it timely and imperative to develop a low-cost and efficient full-time health monitoring solution. The goal of this research is to develop an unobtrusive system Suite (ViSionRF) that will be able to capture the vital physiological signals of users (breathing, heart rate, heart beat shape, body position), remotely by using low-power radar, Wi-Fi and RFID signal technologies. Envision a home with a single remote and unobtrusive device that acts as a stethoscope, heart monitor, irregular breath detector, and posture sensor. Such a home would have the ability to monitor your breathing, your heart (rate and pulse shape), and your position and alert your doctor when an emergency occurs. Such a home would help tremendously impaired citizens (e.g. dementia patients) and their carers. Unlike traditional patient monitoring systems that require users to ‘wear’ devices and sensors, the proposed system does not require wearing any wearable electronic or on-body sensor. This maximizes mobility and makes the system completely transparent to the user. This is important as dementia sufferers repeatedly forget or decline to ‘wear’ their sensors. The goal will be achieved by developing a hybrid technology that merges Wi-Fi, radar and RFID responses with advanced signal processing algorithms that are further trained using powerful machine learning.

Mots clés : radar, wireless, sensing, health care, monitoring, dementia, machine learning

Participants :
- Heriot-Watt University (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 224933.76 €
Projet DIVE into AD (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Dementia represents a major challenge for our ageing societies. The number of citizens suffering from dementia in the EU is expected to reach 19 millions by 2050. Alzheimer’s disease (AD) is responsible for the vast majority of dementia cases. However there is still not a single available treatment that modifies the course of disease. Therefore, the development of innovative approaches to better understand the pathophysiology and ultimately treat patients must be a priority. This project aims to understand the determinants of the diversity of AD clinical phenotypes through the deep analysis of pathological variants of the tau protein. As the accumulation of Aβ peptide has long been considered a causative event in AD, most therapeutic approaches have targeted Aβ metabolism, but unsuccessfully. Modern biomarkers, have confirmed that the brain deposition of tau pathology, the other hallmark of AD, correlates much better with human cognition and neurodegeneration. Recently, it was shown that tau behaves like a prion and can spread from one neuron to another. Moreover, tau strains or conformers seem to template native tau and propagate the pathological conformation with high fidelity. Discrete tau strains generate distinct aggregates morphology or patterns of neuronal vulnerability. I postulate that different strains of tau are responsible for the variability of AD and may determine the progression rate, gender differences or clinical expression. Therefore, my objective is to develop the technologies to identify tau strains signatures in distinct AD phenotypes. In particular, I plan to develop and optimize biosensor cell lines that sensitively detect tau strains from human brain samples and cerebrospinal fluid, and characterize respective repertoire of tau strains. Understanding AD heterogeneity would potentially increase our ability to take care of every individual patient. In addition, this work could lead to the development of biomarkers and novel targeted therapies.

Mots clés : alzheimer s disease, prion, propagation, strains, conformers, personalized medicine

Participants :
- University of Geneva (Suisse) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 190207.68 €
- The general hospital corporation (Etats-Unis) — Partner, organization partner, Autres, subvention : 0.0 €