Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PenAgeing (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : International Institute for Applied Systems Analysis — Pays : Autriche — Rôle : PI
Acronyme de l'entité : IIASA
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Demographic changes in survival rates and age structures require adaptions in public policies. This grant will produce a social benefit by providing policy makers with two kinds of tools that they will need to make these adaptions, fair normal pension ages and consistently up-to-date measures of population ageing that take the changing characteristics of populations into account. An important area of adaption is national pension policy. Recently changes in pension policies have been driven by financial considerations and have aroused a great deal of dissent. One reason for the unhappiness with proposed pension reforms is that they place the burden of reform inequitably. People generally dislike inequitable policies. In this grant, we will produce a detailed case study of equitable pension ages. In the ReAgeing project we dealt with fairness in a very general framework. In this grant, we present an innovative methodology that produces scenarios of equitable normal pension ages using the details of a specific pension system. This grant shows how fairness can enter public policy discussions of ageing. In the future, new problems with respect to population ageing could arise and new data will certainly become available. In the ReAgeing grant, we produced many new measures of population ageing that took the changing characteristics of populations, such as remaining life expectancy and health into account. Our presentations were based on data that were available at the time of writing. In order for the results of the ReAgeing grant to remain relevant requires a second innovation, a way to keep the new measures of population ageing up-to-date. We do this with two pieces of software that can immediately be updated every time the UN produces a new round of data. We cannot predict exactly how demographic conditions will change. With these pieces of software, we can be sure that we will have the tools to deal with them.

Mots-clés : pensions,pension ages,population ageing,characteristics approach to population ageing,reageing,fair pensions,equitable pension ages,intergenerationally equitable normal pension ages,intragenerationally equitable normal pension ages,world ageing data explorer,reageingss r package,shiny server,cran r package,easily updated software,world population ageing,world population prospects
Projet ERC : DenCity (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Durham University — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1344681.0 €

DenCity offers a new approach for understanding density and its relationship to the city. Density is a defining feature of the city and urban life. Across the world, density is now at the centre of policy and planning agendas to build cities that are environmentally, economically, socially and politically ‘sustainable’. While there is a lively tradition of research on density in the city, we lack an understanding of the different ways in which high densities are lived and perceived by residents. Existing research provides rich resources for how we might define and represent density, how we might arrive at optimum numbers of people in a given area, and how capitalism builds or reduces densities within and between places globally. However, we lack an understanding of how high density – what I call intensity – is understood and experienced by different urban inhabitants, and the implications for how we understand the contemporary city. Developing a ‘density assemblage’ approach, I propose to examine the ways in which residents differently know and relate to intensity, including how it comes to matter, for good or ill. I do so by examining different cases of intensity in the Asian city, from travel and transport hubs, and slums to rooftops. While the 20th century witnessed a general global decrease of urban density in favour of urban sprawl, many Asian cities continue to densify. Asia is the densest and most urbanized part of the planet, and the trend is predicted to continue. I will examine some of the highest densities in the world, including in Hong Kong, Mumbai, Manila, Dhaka, and Tokyo. The different ways in which intensity becomes known and comes to matter for residents will be a vital challenge for understanding life in the urban 21st century, and for how we understand the city.

Mots-clés : assemblage,city,density
Projet ERC : topDFT (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Nottingham — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998649.0 €

Density-functional theory (DFT) is the most widely used method to study the electronic structure of complex molecules, solids, and materials. Its use across chemistry, solid-state physics and materials science is a testament to its black-box nature and low cost. However, many important areas remain inaccessible to DFT simulations, including applications to strongly correlated materials and systems in electromagnetic fields. The topDFT project will deliver new conceptual approaches to design the next generation of density-functional methods. This will be achieved by pursuing three parallel strategies: i) Developing new strategies for the design of functionals ii) Implementing topological DFT, a new computational framework iii) Developing extended density-functional theories. A new approach to the exchange–correlation problem, based on a perspective from the kinetic energy of the electrons, will be developed – leading to new practical density-functional approximations (DFAs). A new framework for computation will be developed by combining techniques from topological electronic structure methods with DFT, allowing for the identification of correlation ‘hotspots’. This idea is chemically intuitive; electrons close together interact in a fundamentally different way to those far apart. Recognising these hotspots, and adapting dynamically to them, will lead to new DFAs with substantially greater accuracy. Extended-DFTs will open the way to study strongly correlated systems (e.g. high-Tc superconductors, transition metal oxides, Mott insulators) of importance in chemistry and materials science and magnetic systems (e.g. molecular magnets, spin glasses, spin frustrated systems) of importance in nano-science, advanced materials and spintronics applications. The topDFT project will have wide impact on areas including chemical synthesis, materials design and nano-science that underpin key areas such as manufacturing and medicine of benefit to all sections of society.

Mots-clés : electronic structure theory,density functional theory
Projet ERC : ENAMULATE (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149728.0 €

Dental enamel has a unique chemical composition and a remarkable well-defined hierarchical structure, which together are responsible for its outstanding properties and critical functionality. Once lost, this tissue cannot be regenerated and is directly involved in a variety of dental problems that affect a large percentage of the world population. This ERC PoC project (ENAMULATE) aims to develop the world’s first human dental enamel regeneration material capable of recreating natural enamel in structure and chemical composition; treating dental defects; and replacing restorative materials currently used in dental clinics. The project builds on findings from the ERC Starting Grant STROFUNSCAFF on the development of an elastin-like protein (ELP) self-assembling process capable of triggering and guiding the hierarchical growth of hydroxyapatite as biocompatible, flexible, and robust coatings in vitro over large uneven areas and directly on human enamel and exposed dentinal tubules. ENAMULATE will optimize the crosslinking mechanism to facilitate its clinical use in the operating room, confirm its efficiency in vitro, and validate its performance in an established animal model. The project will also focus on setting up and moving forward a path towards commercialization by consolidating the intellectual property, investigating the industrial viability, and identifying potential markets.

Mots-clés : tissue engineering,biomineralisation,biomaterials,tissue regeneration,dental implant
Projet ERC : DIVERGE (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2033506.25 €

Depression affects 300 million people and represents one of the biggest challenges to human health to date. Of the burden, 80% pertains to low- and middle-income countries. It is thus imperative to understand the global causes of depression to design effective targeted interventions. DIVERGE will build the first ancestrally diverse data resource for depression, generated from biobanks (N=1.8M) and new studies in Pakistan (N=20K) as well as sub-Saharan Africa (N=13K) with deep phenotyping and genotyping. Differences in depression risk between populations have been shaped by the environment, demography and diverging evolutionary history. Using the novel perspective of evolutionary psychiatry, DIVERGE will comprehensively characterise the genetic architecture of depression and assess how it has been shaped by natural selection. Thereby, I will illuminate how heritability, environmental factors and their interplay affect disease development. I will develop a new method, trans-ethnic colocalization, to address the fundamental question whether genetic risk factors are transferable across populations. This is important to ensure that health benefits of precision medicine can be shared within and across populations. In addition to the big picture approach, I aim to identify specific causes of the disorder. The diversity of the data together with the application of population-matched inheritance models will empower the discovery of novel genetic loci for depression. I will develop and apply cutting-edge methods, including trans-ethnic fine-mapping with functional annotations to uncover biological mechanisms underlying depression loci. Trauma, such as exposure to violence, is a strong risk factor for depression. DIVERGE will investigate the interplay between traumatic life events and genetic susceptibility which could help understand how mental illness differs across groups. These innovations will lead to a step change in our understanding of the aetiology of depression.

Mots-clés : depression,risk factors,diverse populations,transcultural,genome wide association studies,traumatic life events
Projet ERC : WARN-D (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Leiden University — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Depression is common, debilitating, and often chronic. It severely compromises the capacity for independent living, and is the strongest predictor of suicide. Young people are disproportionately affected, and many will spend over 20% of their lives in a state of depression. Further, only 50% of patients improve under initial treatment. Experts agree that prevention is the most effective way to change depression’s global disease burden. The biggest barrier to successful personalized prevention is to identify those at risk for depression in the near future. My proposal aims to solve the challenge who should receive prevention, and when, by developing the personalized early warning system WARN-D. To implement personalized detection, I will follow 2,000 individuals over 2 years, and integrate emerging theoretical, measurement, and modelling approaches from different scientific fields so far unconnected. Regarding theory, I conceptualize depression as a complex dynamical system in which causal relations and vicious cycles between problems can move the system from a healthy to a clinical state, consistent with the Network Approach to Psychopathology that I co-developed. Regarding measurement, I will follow participants in their daily lives, and collect temporal dynamics of bio-psycho-social variables like mood, anxiety, stress, impairment, sleep, and activity via smart-phone based ecological momentary assessment (EMA) and smart-watch based digital phenotype data. I will use dynamical network models to study the relations among problems, and use parameters of these models, combined with baseline, EMA, and digital phenotype data, to construct the prediction model WARN-D via state-of-the-art machine learning models. The interdisciplinary project combines numerous modern tools to develop a tailored personalized early warning system that forecasts depression reliably before it occurs, promising to radically transform the science of depression detection.

Mots-clés : depression onset,depression,prediction,early warning signals,critical slowing down,ecological momentary assessment,wearable technology,digital phenotype,machine learning
Projet ERC : EPI-X4Health (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : University of Ulm — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 95256.0 €

Deregulation of CXCL12 signaling via the CXCR4 chemokine receptor plays a key role in many diseases, including cancer, rheumatoid arthritis, chronic inflammation and cardiovascular disorders. Thus, agents modulating CXCR4 signaling offer many prospects for therapeutic development. CXCR4 is also a major coreceptor for HIV entry. Thus, we used HIV as tool to screen peptide libraries encompassing the entire blood peptidome for novel CXCR4 ligands. This approach allowed the identification of a small fragment of human serum albumin as potent HIV inhibitor. Remarkably, this naturally occurring peptide, named EPI-X4 (Endogenous Peptide Inhibitor of CXCR4), blocks CXCL12/CXCR4 signaling and suppresses cancer cell migration and invasion. Preclinical studies in mice show that EPI-X4 mobilizes hematopoietic stem/progenitor cells and inhibits lung inflammation in an asthma model. Preliminary analyses suggest that EPI-X4 is more specific and better tolerated than Mozobiol® (AMD3100), the only CXCR4 antagonist approved for clinical application. Recently, we developed synthetic derivatives of EPI-X4 showing about three orders of magnitude improved potency against HIV as well as increased plasma stability. Key goals of this project are to determine the therapeutic potential of these improved derivatives against cancers (Aim 1) and inflammatory diseases (Aim 2) using established mouse models of colon carcinoma, osteosarcoma, glioblastoma, airway inflammation and dermatitis. These disorders were selected from the large number of CXCR4-linked diseases because no safe and effective treatment exists and since preclinical mouse models are available to determine whether EPI-X4 derived agents are more efficient and better tolerated than other compounds. In parallel to the experimental assessment of the therapeutic potential of these novel CXCR4 antagonists, we will perform market analyses and develop an IPR strategy to pave the way towards commercialization and future clinical application.

Mots-clés : g protein coupled receptors,chemokines,cxcr4 signaling,antagonist,colon carcinoma,osteosarcoma,glioblastoma,inflammation,allergy,endogenous peptides,peptide optimization,mouse models
Projet ERC : IL7sigNETure (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University of Lisbon — Pays : Portugal — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1988125.0 €

Deregulation of signal transduction is a feature of tumor cells and signaling therapies are gaining importance in the growing arsenal against cancer. However, their full potential can only be achieved once we overcome the limited knowledge on how signaling networks are wired in cancer cells. Interleukin 7 (IL7) and its receptor (IL7R) are essential for normal T-cell development and function. However, they can also promote autoimmunity, chronic inflammation and cancer. We showed that patients with T-cell acute lymphoblastic leukemia (T-ALL), an aggressive hematological cancer, can display IL7R gain-of-function mutations leading to downstream signaling activation and cell transformation. Despite the biological relevance of IL7 and IL7R, the characterization of their signaling effectors remains limited. Here, we propose to move from the single molecule/pathway-centered analysis that has characterized the research on IL7/IL7R signaling, into a ‘holistic’ view of the IL7/IL7R signaling landscape. To do so, we will employ a multidisciplinary strategy, in which data from complementary high throughput analyses, informing on different levels of regulation of the IL7/IL7R signaling network, will be integrated via a systems biology approach, and complemented by cell and molecular biology experimentation and state-of-the-art in vivo models. The knowledge we will generate should have a profound impact on the understanding of the fundamental mechanisms by which IL7/IL7R signaling promotes leukemia and reveal novel targets for fine-tuned therapeutic intervention in T-ALL. Moreover, the scope of insights gained should extend beyond leukemia. Our in-depth, systems-level characterization of IL7/IL7R signaling will constitute a platform with extraordinary potential to illuminate the molecular role of the IL7/IL7R axis in other cancers (e.g. breast and lung) and pathological settings where IL7 has been implicated, such as HIV infection, multiple sclerosis and rheumatoid arthritis.

Mots-clés : interleukin 7,signaling,t cell acute lymphoblastic leukemia,cancer,animal models,targeted therapeutics,high throughput multi level analyses  phosphoproteomics,transcriptomics,chemical screens
Projet ERC : EVI1inCancer (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : German Cancer Research Center — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : DKFZ
Type d'entité : Recherche
Financement ERC de l'entité : 1499094.0 €

Deregulation of the EVI1 oncogene is a key transforming event in the development of many malignancies, most prominently very high-risk acute myeloid leukemia (AML), ovarian, colon, breast, non-small cell lung cancer, and soft-tissue sarcoma. For decades, both EVI1 function and the mechanism underlying its deregulation have been poorly understood. The consequent lack of a targeted therapy against EVI1 establishes a pressing medical need. In a recent study investigating a distinct category of EVI1-driven AML with inv(3) or t(3;3), we characterized the regulatory domain of EVI1 and identified a master regulatory element of the stemness factor GATA2 to be rearranged to EVI1, thereby deregulating both genes. Applying functional genomics and genome-editing, we found that the rearranged enhancer element adopted novel features, such as superloading of the epigenetic reader and chromatin regulator BRD4, allowing its inhibition with BET/bromodomain inhibitors with relative EVI1 specificity. Interference with EVI1-regulatory mechanisms thus has potential therapeutic value in EVI1-transformed tumors. To pave the way for epigenetic targeting of other EVI1-expressing malignancies, we aim to identify genomic enhancer sequences and protein components of the EVI1 regulatory domain by systematic epigenetic and proteomic profiling. Specifically, we seek to achieve the following experimental goals: (1) Identification of the mechanism underlying EVI1 deregulation in non-3q-rearranged AML and solid tumors; (2) Addressing the role of breakpoint-associated transpos-able retroelements; (3) Characterization of the transcription factor complex regulating EVI1; (4) Identification of epigenetic resistance mechanisms in EVI1+ AML by using an in vivo model and a genome-editing approach. The proposed experiments will provide insight into the epigenetic landscape of EVI1+ malignancies and help reveal new targets and genetic interactions amenable to future therapies in these high-risk malignancies.

Mots-clés : evi1,leukemia,crispr,cas9,chromosome conformation capture sequencing
Projet ERC : FIDELIO (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Anglia Ruskin University — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : ARU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 139962.81 €

Designating Protected Areas (PAs) is the most important policy tool for biodiversity conservation. Over 100 new PAs have been established in the past 36 months in European Union territory. However, effective management of PAs is often obstructed by conflicts mainly associated with the social impacts (SIs) imposed on local communities by their establishment. Despite the importance of these SIs there are certain aspects in this field that remain significantly under-researched. There is now an increasing need to incorporate SI assessments in decision making processes by providing a clear framework explaining how perceptions of these impacts are created and predicting their change in the future. This will support the achievement of international goals for biodiversity conservation and adaptation to climate change as well as better accounting for social justice issues for communities dependent on protected natural resources. The aim of FIDELIO is to develop for the first time a new paradigm in order to understand how perceptions of SIs are formulated taking into consideration the dimensions of space and time. FIDELIO will assist in increasing public engagement and the incorporation of local opinions in decision-making. It will also facilitate the process of policy development and a reduction in conflicts between different stakeholders in PAs. FIDELIO will last 5 years and its research objectives will be explored through the application of a mixed-methods approach including the implementation of two rounds of social surveys in 4 PAs across Europe and the testing of the framework in 15 additional PAs. This is an extremely timely project considering the steady increase of new PAs and the re-designation of current ones. FIDELIO will contribute to the better understanding of SIs and facilitate predictions for their change in the future, while assisting in maximizing social benefits for local communities arising from the designation of a PA.

Mots-clés : protected areas,social impacts,europe