Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Beyond genotype to phenotype: how ancestor lifestyle impacts on lifespan variation in descendants (NoisyAgeing)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Integrative Biology: from Genes and Genomes to Systems
Panel description: Genetics, epigenetics, genomics and other ‘omics studies, bioinformatics, systems biology, genetic diseases, gene editing, innovative methods and modelling, ‘omics for personalised medicine
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2015-06-01
End date: 2021-06-30
Duration (months): 73.0
Total project cost (EUR): 1499978.0
EU funding (EUR): 1499978.0
Participants: 1
Project status: CLOSED

There are many examples in nature where inter-individual variability in life-history traits is exploited as an adaptive strategy. I and others have shown that inter-individual variability in the longevity pathways –and in particular, in stress response genes- has consequences for genetic/environmental phenotypic robustness as well as for lifespan in Caenorhabditis elegans. My main interest is to uncover the causes that explain inter-individual variability in lifespan. The variability across individuals must include an important non-genetic component because the laboratory strains of this nematode are genetically homogeneous. I propose that lifespan variation is a by-product of non-genetic sources of variability in the pathways that control longevity. Strikingly, inter-individual differences in stress responses are transgenerationally transmitted. Transgenerational memory is an adaptive strategy that informs the next generation about the likely environmental cues that will be encountered, and sets patterns of gene expression by the incomplete erasure of chromatin marks in the germline. I hypothesise that transgenerational epigenome inheritance introduces transcriptional variability for genes that influence lifespan. Also, I propose that the probabilistic nature of lifespan is caused by inter-individual differences in the inheritance of longevity genes that set the rate of ageing from early development. Understanding the basis of lifespan variability is crucial for personalised medicine, where not the average population but rather the individual is centre stage. It is equally crucial for the identification of new factors that may have been missed by the analysis of population averages that can have an impact for human ageing and health. More generally, I propose the inter-individual variability in the vertical transmission of transcriptional states as a unifying framework underlying a large class of adaptive phenotypes that vary among individuals.

Keywords: ageing,caenorhabditis elegans
Drug CandIdates ScreenINg (DeCISIoN)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Treating and managing disease
Action type: SME instrument
Countries involved: Germany,Netherlands
Call: Supporting innovative SMEs in the healthcare biotechnology sector (H2020-SMEINST-2-2016-2017, 2016)
Start date: 2016-07-01
End date: 2018-12-31
Duration (months): 30.0
Total project cost (EUR): 3228570.0
EU funding (EUR): 3228570.0
Participants: 2
Project status: CLOSED

Pluriomics is an international Dutch/Belgian biotech company specialised in developing stem cell-based assays for cardiac safety pharmacology and drug discovery and development. Pluriomics developed a unique proprietary protocol to differentiate heart muscle cells derived from human induced pluripotent stem cells (hiPSCs). The company provides its customers with reliable cell technology systems to test potential drugs in the preclinical phase with high predictive value. Safety issues remains a key problem in drug development. This is amongst others emphasised by the case of AstraZeneca where 82% of pre-clinical and 62% of phase I project closures where related to safety issues. Out of the safety related failures the cardiovascular system is involved in 17% of the preclinical failures and 24% of the clinical failures. Examples of cardiovascular effects, include arrhythmias, hypertrophy, hypertension and reduced ventricular function, which may lead to increased cardiac risk and possibly death. Additional reasons for the decline in success rates are related to the lack of predictive models for early drug efficacy screening. Pluriomics has developed Pluricyte® Cardiomyocytes and integrated proprietary assay systems to overcome the abovementioned challenges. Enabling market uptake and distribution of cell technology based innovations can be challenging, with large scale production and development of regulatory compliant predictive models as main challenges. DeCISIoN will tackle these challenges and thus accelerate market uptake of their cardiac safety assays. DeCISIoN will take the next steps and deliver 1) an up-scaled and more cost-effective manufacturing process; 2) novel, validated, predictive high-throughput cardiac assays for further improved cardiac toxicity and drug efficacy testing and 3) a fully developed marketing and commercialisation strategy for the cardiac assays. As such, DeCISIoN will take Pluriomics' cardiac assays from TRL6 to TRL9.

Keywords: cardiac toxicity,drug efficacy,drug development,human induced pluripoten stem cells,preclincal predictive models,disease in a dish
Modelling brain aneurysm to elucidate the role of platelets (Damocles)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Physiology in Health, Disease and Ageing
Panel description: Organ and tissue physiology, comparative physiology, physiology of ageing, pathophysiology, interorgan and tissue communication, endocrinology, nutrition, metabolism, interaction with the microbiome, non-communicable diseases including cancer (and except disorders of the nervous system and immunity-related diseases)
Countries involved: France
Call: ERC Starting Grant (ERC-2017-STG, 2017)
Start date: 2018-06-01
End date: 2025-08-31
Duration (months): 87.0
Total project cost (EUR): 1498618.0
EU funding (EUR): 1498618.0
Participants: 1
Project status: SIGNED

In the European Union, 15 million people have an unruptured intracranial aneurysm (IA) that may rupture one day and lead to subarachnoid haemorrhage (SAH). The IA rupture event is ominous and lingers as a clinical quandary. No safe and effective non-invasive therapies have, as of yet, been identified and implemented in clinical practice mainly because of a lack of knowledge of the underlying mechanisms. Increasing evidence points to inflammation as one of the leading factors in the pathogenesis of IA. Intrasaccular clot formation is a common feature of IA occurring unruptured and ruptured IA. In addition to forming clots, activated platelets support leukocyte recruitment. Interestingly, platelets also prevent local hemorrhage in inflammatory situations independently of their ability to form a platelet plug. We hypothesize that the role of platelet may evolve throughout the development of IA: initially playing a protective role of in the maintenance of vascular integrity in response to inflammation and contributing later to intrasaccular thrombus formation. What are the platelet signaling pathways and responses involved and to what extent do they contribute to the disease and the rupture event? To answer these questions, we designed an interdisciplinary proposal, which gathers biophysical, pharmacological, and in-vivo approaches, with the following objectives: I) To investigate platelet functions from patients diagnosed with intracranial aneurysm at the sites of aneurysm sac. II) To delineate platelet mechanisms and responses in a cutting-edge technology of a 3D reconstruction of IA that will take into account the hemodynamic shear stress. III) To test in a preclinical mouse model of IA efficient anti-platelet therapies and define a therapeutic window to intervene on platelet activation. The proposed project will yield new insights in IA disease and in life science, from cell biology to the discovery of potential new targets in cardiovascular medicine.

Keywords: intracranial aneurysm,platelets,inflammation,vascular wall integrity
Advanced manufacturing and the transition of regional economies: institutions, social regulation and development in Apulia and Lower Silesia (REGinTRAN)

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: Social Sciences and Humanities
Countries involved: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-11-01
End date: 2021-04-30
Duration (months): 30.0
Total project cost (EUR): 180277.2
EU funding (EUR): 180277.2
Participants: 1
Project status: CLOSED

At a time of technological transition REGinTRAN aims to understand under which conditions advanced manufacturing might turn out to be a viable driver for sustaining the development of regions suffering from structural disadvantages. On the one hand, the literature on systems of advanced manufacturing has mostly concentrated on a few highly successful regions and established a clear-cut distinction between growing and declining regions. On the other hand, studies on the national models of capitalism have tended to adopt a deterministic account of the process of economic development yet overlooking the role of actors. The main innovative contribution of REGinTRAN will be to embrace a dynamical perspective of the study of regional trajectories by taking into consideration the hitherto unrealized potential of less developed territories. More precisely, the project will investigate the linkages between social actors’ mobilizations, patterns of state intervention and the opportunities and constraints offered by digital technologies for industrial transformation. This will contribute to produce new knowledge on the institutions and mechanisms that can foster (or hinder) a process of socio-economic transition. REGinTRAN will be based on an interdisciplinary approach building on comparative political economy, sociology of public action and regional and economic geography. Apulia and Lower Silesia will be investigated in depth through a systematic comparison using causal process tracing (1999-2016). A quantitative analysis of socio-economic indicators for less developed regions in Europe will complement the case-study analysis. The project will provide policy inputs on how to build a collective capacity of action by mobilizing unused resources and promoting inclusive growth. Different measures (workshops with students and professionals; one policy-brief) will be taken in order to disseminate results and stimulate a wider non-academic debate.

Keywords: institutionalism,state society relationships,collective action,public policies,social mechanisms,industrial transformation,local and regional development,models of capitalism
Exchanges for SPEech ReseArch aNd TechnOlogies (ESPERANTO)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Spain,Argentina,Cuba,Malaysia,Tunisia,Greece,France,France,France,France,Czechia,United States,United Kingdom,Chile,Cameroon,Canada
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2020, 2020)
Start date: 2021-01-01
End date: 2025-12-31
Duration (months): 60.0
Total project cost (EUR): 1191400.0
EU funding (EUR): 1191400.0
Participants: 19
Project status: SIGNED

The ESPERANTO project aims at pushing speech processing technologies to their next step in order to enable the diffusion of these technologies in European SMEs and to maximize and securize their use in the civil society for forensic, health or education. The ESPERANTO consortium forsees that the next generation of artificial intelligence algorithms for speech processing should : 1. be more accessible : via a larger number of spoken languages, and for applications where resources are strongly limited (health, education, robotics…); 2. integrate a human in the loop to guaranty a higher usability and ease of deployment and maintenance; 3. be explainable in order to enable sensitive applications related to forensic or health and contribute to personal data preservation by detecting and characterizing existing biases due to the data-driven nature of current speech technologies. ESPERANTO intends to lead the scientific community by releasing evaluation metrics, protocols and standards that will boost the development and evaluation of this new generation of algorithms. To achieve this ambitious goal, the ESPERANTO project gathers a large and trans-sectorial community of experts in speech related applications such as speech transcription, separation, enhancement, translation, understanding and speaker recognition and diarization to transfer knowledge, organize, produce and standardize resources with the aim of catalyzing and cross-pollenizing this area. The main goals of the ESPERANTO project are: - support the development of open-source tools that will encourage fast developement, exchanges and reproducibility; - produce tutorials and competitive baselines on various topics of speech processing in order to boost the fostering of new speech-AI students, researchers and engineers; - facilitate the collection and sharing of linguistic and speech resources through standards; - organize workshops to progress on the speech technologies and favor tranfer of knowledge.

Keywords: speech processing,neural networks,explainability,human assisted learning,low resources,natural language processing,standardization,evaluation
Smart and CO2 neutral Olefin Production by arTificial Intelligence and MAchine Learning (OPTIMAL)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Norway,Belgium,China,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2020, 2020)
Start date: 2021-08-01
End date: 2026-12-31
Duration (months): 65.0
Total project cost (EUR): 1205200.0
EU funding (EUR): 772800.0
Participants: 13
Project status: SIGNED

The proposed project is to develop and maintain long term collaborations between Europe and China towards CO2 neutral Olefin production. We will realize this objective by carrying out joint research in big data and artificial intelligence (AI) for ethylene plants integrated with carbon capture and CO2 utilisation. Specifically this requires a universal set of skills such as pilot scale experimental study, process modelling and analysis, optimisation, catalysis and reaction kinetics that will be strengthened by the individual mobility of researchers between Europe and China. There are 12 partners involved in OPTIMAL with 3 industrial partners. These partners are world leading in their respective research areas. OPTIMAL is planned to start from Aug. 2021 and will continue for 65 months. There will be 28 experienced and 35 early stage researchers participating in OPTIMAL with exchange visits of 262 person months. The funding of €772,800 will be requested from European Commission to support these planned secondments. The European beneficiaries are experts at catalysis, CO2 utilisation, intensified carbon capture, reaction mechanism and kinetics & CFD studies, hybrid modelling, molecular simulation and dynamic optimisation, whilst the Chinese partners are experts at exergy analysis, process control and optimisation, solvent-based carbon capture & data-driven model development, deep reinforced learning based model free control, intelligent predictive control, physics-based reduced order model development, soft exergy sensor development and optimisation under uncertainty. Transfer of knowledge will take place through these exchange visits. We will generate at least 25 Journal publications and 25 Conference papers. 2 Special Issues will be established in leading journals such as Applied Energy. 2 Workshops and 2 Special Sessions in major international conferences will also be organised to disseminate project results.

Keywords: process systems engineering,computer aided process design,ethylene manufacturing,carbon capture,co2 utilisation,smart manufacturing,artificial intelligence,machine learning,process control
Multicentric Language Markers of NeuroDegeneration (MULTI-LAND)

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: Argentina,Spain
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-09-01
End date: 2024-08-31
Duration (months): 36.0
Total project cost (EUR): 224496.96
EU funding (EUR): 224496.96
Participants: 2
Project status: SIGNED

By 2030, people aged 65 and over are expected to account for more than 25% of the European population. This fact foreshadows a dramatic growth of aging-related neurodegenerative disorders (NDs), including Alzheimer's and Parkinson's disease. Critically, this scenario will place a severe strain on healthcare systems as NDs incapacitate patients, burden their families, and entail major costs of diagnostics evaluation, including time-consuming neuropsychological batteries and expensive brain scans. Though currently irreplaceable, this approach is often unaffordable and non-viable for remote application -a key requisite during pandemic lockdowns. Thus, these procedures must be complemented with urgent innovations that boost diagnosis and symptom severity detection using low-cost tools applicable to large sections of the population remotely. A promising interdisciplinary framework rooted in natural language markers (NLMs) can offer key solutions to this crisis. This novel framework is based on linguistic features derived from patient's natural speech and analysed via machine learning algorithms. NLMs are characterized by high ecological validity, minimal stress, low costs and adaptability for remote and massive screening. Despite the increasing application of NLMs in the field of mental health, their use in NDs evaluation is still scarce. Building on a unique synergy of international expertise, we will perform the first cross-methodological (behavioural, f/MRI, EEG) and cross-centre (Latin-America and Europe) validation of NLMs in patients with NDs. Specifically, we aim to: (1) establish NLMs diagnostic sensitivity, (2) unveil potential links between NLMs and brain network disruptions, (3) estimate their robustness and generalisation power. The ultimate translational goal of this project is to identify the best-performing set of NLMs to develop a frontline mobile-phone app with clinical value, capable of capturing natural speech features for remote patient evaluation.

Keywords: neurodegenerative diseases,language markers,cognition,neuroimaging,machine learning,healthy aging
Predictive Vision Saving lives in dangerous working environments with Predictive Risk Management software (Predictive Vision)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Netherlands
Call: Open Disruptive Innovation Scheme (implemented through the SME instrument) (H2020-SMEINST-2-2014, 2014)
Start date: 2015-07-01
End date: 2016-12-31
Duration (months): 18.0
Total project cost (EUR): 3418391.25
EU funding (EUR): 2392873.0
Participants: 1
Project status: CLOSED

eVision has the ambition to become market leader in the control of work software market for all hazardous industries. eVision’ s core market is the control of work software market with a 3 billion euros market size, with a CAGR of approximately 25%. At the end of this project eVision will have the proven software, commercial strategy and operational power to fulfill this ambition. The main intent and ultimate goal of the solution is to create a unique real-time and predictive risk management system for usage at the frontline, ensuring entire hazardous industries (e.g. Oil & Gas, Utilities, Chemical, Pharmaceutical, etc.). will be transformed to operate safely. eVision will demonstrate its innovation in a relevant operational environment of present eVision clients in the Oil & Gas industry (Shell, BP and Total), by demonstrating and validating a very intelligent system that can forecast all kinds of possible risks in any operational hazardous enterprise environment (e.g. Refinery plants, Oil drilling plants etc.). The innovation project is expected to combine information from over 25 different software systems, not only giving a real-time overview of risk levels but also giving early warning of any increased risk level (based on predictive analysis). It’s responsive, real-time software that also reports actual views of the emerging situations, advises the employee on how to (re)act and gives worldwide feedback to the management. The technology being created by eVision will revolutionize the way industries are working today. Not only will the system be designed to prevent large incidents with global impact, but the system also allows personal safety to be planned and managed more effectively, decreasing global industry fatality levels. Predictive Vision will: - Lower the risk levels at clients by more than 60% within the first 12 months of usage. - Decrease the expected likelihood of large scale incidents by at least 50%.1 - Drop the likelihood of severe personal inci

Keywords: the intent and goal of the solution is to create a unique real time and predictive risk management system for usage at the frontline,ensuring hazardous industries transformed to operate safely