Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : INTRAHETEROSEQ (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Universidad de Cantabria — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498850.0 €

Cancer is caused by somatically acquired changes in the DNA. Some of these changes fall in “cancer genes”, conferring clonal selective advantage to the cells that carry the mutant alleles. Identifying these genes/pathways is of vital importance for a correct understanding of cancer biology as well as for the diagnosis and treatment of human malignancies. In this respect, the use of genetically modified mice has been extremely useful in the past for characterizing the molecular pathways involved in cancer progression. The remarkable progress made during the last two decades on the genetic modification of mouse genomes offers unique opportunities to investigate different aspects of tumor molecular behavior, impossible to study on human samples. Recently, the advent of next-generation sequencing technologies has provided new strategies for the systematic genome-wide identification of somatic changes in cancer cell genomes. Using these technologies, we and others have characterized the high intra-tumor heterogeneity observed in some human tumors. Although the exact significance of this heterogeneity is uncertain, it seems to be responsible for key aspects in the management of cancer patients such as metastasis predisposition and tissue specificity or treatment resistance. Taking advantage of next-generation sequencing, we propose to finely characterize the intra-tumor heterogeneity evolution during the progression of tumors induced in a mouse model of pancreatic cancer, as well as, for the first time, to purify the different cell populations these primary tumors are composed of. A complete genomic and transcriptomic characterization of these populations followed by posterior functional assays will help us to identify the genes/pathways involved in tumor progression as well as metastatic potential and its tissue specificity. This new knowledge could finally contribute to a better understanding of cancer and to the design of more efficient anti-tumor therapies

Mots-clés : cancer molecular biology,mouse genetics
Projet ERC : NanoPokers (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Lund University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2621251.0 €

Cancer is responsible for 20% of all deaths in Europe. Current cancer research is based on cell ensemble measurements or on snapshot studies of individual cells. However, cancer is a systemic disease, involving many cells that interact and evolve over time in a complex manner, which cell ensemble studies and snapshot studies cannot grasp. It is therefore crucial to investigate cancer at the single cell level and in longitudinal studies (over time). Despite the recent developments in micro- and nanotechnologies, combined with live cell imaging, today, there is no method available that meets the crucial need for global monitoring of individual cell responses to stimuli/perturbation in real-time. This project addresses this crucial need by combining super resolution live-cell imaging and the development of sensors, as well as injection devices based on vertical nanowire arrays. The devices will penetrate multiple single cells in a fully controlled manner, with minimal invasiveness. The objectives of the project are: 1) To develop nanowire based-tools in order to gain controlled and reliable access to the cell interior with minimal invasiveness. 2) Developing mRNA sensing and biomolecule injection capabilities based on nanowires. 3) Performing longitudinal single cell studies in tumours, including monitoring gene expression in real time, under controlled cell perturbation. By enabling global, long term monitoring of individual tumour cells submitted to controlled stimuli, the project will open up new horizons in Biology and in Medical Research. It will enable ground-breaking discoveries in understanding the complexity of molecular events underlying the disease. This cross-disciplinary project will lead to paradigm-shifting research, which will enable the development of optimal treatment strategies. This will be applicable, not only for cancer, but also for a broad range of diseases, such as diabetes and neurodegenerative diseases.

Mots-clés : nanowires,nanotechnology,semiconductor,super resolution microscopy,epitaxy,nanosensors,nanoinjections,microfluidics,tumor,cell heterogeneity
Projet ERC : CANCERSCREEN (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : University of Sussex — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 300317.94 €

Cancer screening and the diagnostics industry: a comparative analysis of the political economy of diagnostic innovation A decade after the Human Genome Project, major public and private investments continue to fuel expectations of a genomic revolution in biomedicine. The freight of expectations surrounding the new “age of diagnostics” is accompanied by much uncertainty about how public policy should steer diagnostic innovation, with much debate about inter alia the harms of creating diagnostic monopolies through gene patenting, and the risks of under- or over-regulation. However, due to the paucity of research on diagnostic innovation, policy deliberation is driven more by anecdote and expert opinion than empirical evidence. With a specific focus on screening/early detection of cancer, this project will map industry dynamics, technological trajectories and regulatory developments in Europe and the USA from 1996 to the present day. Combining quantitative and qualitative methods, the project’s innovative dimensions include a new conceptual model of socio-technical transition in the diagnostics sector, and the first integrative analysis linking scientometric data on the interactions between public and private actors in the diagnostic research domain with comparative transnational analysis of regulatory decision-making. Through a novel integration of conceptual insights from the literature on biomedicalisation and scholarship on socio-technical regime change, this project aims to advance both fields of research by applying a new multi-scale, multi-level model of socio-technical transition. The project will provide unprecedented insight into the factors shaping the development of a new generation of molecular diagnostic tests, and examine how these technologies are reconfiguring disease categories and redrawing the boundaries between health and sickness. We will establish a platform of theory and methods for a broader programme of work on diagnostic innovation.

Mots-clés : biomedicalisation,socio technical transitions,responsible research and innovation,regulation,political economy
Projet ERC : MEMCARB (Horizon 2020, appel 2017, Proof of concept grants)
Entité participante : Institut Català d'Investigació Química — Pays : Espagne — Rôle : PI
Acronyme de l'entité : ICIQ;ICIQ-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Carbon dioxide separation, capture and utilization is expected to become a major business opportunity in the near future. Beyond current industrial needs for natural gas or biogas purification, regulatory issues imposing emission control will also contribute to a fast growth in this market. At the industrial level, CO2 separation is still an expensive process, typically based in alkaline amine solutions or cryogenic distillation, and low-cost alternatives are needed. Membrane-based technologies are the most preferred for gas purification processes due to their easy implementation and very low operational costs. However, CO2 separation through membrane systems is not competitive nowadays, due to the low selectivity and poor stability of the available materials. This weakness precludes fully exploitation of the intrinsic benefits (functional and economic) of membrane technologies. We have discovered a porous metal organic framework (MOF) able to separate CO2 from a gas stream (including methane, nitrogen, oxygen, hydrogen, olefins, etc.) that confers organic polymer membranes unique separation capabilities. Composite membranes containing this MOF exhibit unique CO2/CH4 selectivities, at least one order of magnitude higher when compared with current state-of-the-art models. This opens unique possibilities to develop an efficient, robust and affordable membrane system for CO2 separation. Our MEMCARB technology, based on inexpensive starting materials, and obtained via industrially scalable processes, could have excellent market penetration for multiple applications (from gas purification of methane feeds, to treatment of exhaust gas). Through this project we will design, build and validate a membrane-based module for gas purification. The results will be analyzed and compared to current CO2 separation processes to further assess its viability and to identify its competitive advantages. If results are positive, a business plan and road to market will be established.

Mots-clés : metal organic frameworks,carbon dioxide,gas separation,membranes
Projet ERC : UCARE (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University Medical Center Utrecht — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UMC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999979.0 €

Cardiovascular disease causes 51% of deaths in women and 42% of deaths in men in Europe. Women are contributing mostly to the worrying trend of increases in hospitalizations for coronary artery disease (CAD) at younger ages. Missed and delayed diagnoses in women are more common than in men, as the pathophysiology of CAD in women is different than in men. Men often have atherosclerotic plaque rupture as underlying mechanism for CAD whereas women more often suffer from plaque erosion. Plaque erosion refers to thrombus formation on top of an intact non-ruptured plaque in the coronary artery. Early recognition of plaque erosion will, therefore, specifically aid in the diagnosis of CAD in women. However, knowledge on CAD and plaque erosion in women is lagging behind. This is due to the underrepresentation of women in clinical trials for CAD and biobank studies. This gap is now only gradually being recognized in research, but not yet fully addressed as pooling of data from both sexes is still common practice. My research efforts have convincingly contributed to the awareness that sex differences in human diseased vascular tissue are relevant. With my group I have shown that sex differences are specifically evident in regulatory gene networks and key player genes for CAD. This also corresponds with sex-specific epigenetic signatures of atherosclerotic plaques, and human endothelial gene expression patterns. In UCARE, I propose to utilize vascular tissues and plaque samples from well-powered studies to analyze these by sex to a single-cell level. This approach will identify female-specific key player genes in individual cells of plaques and unravel clinically relevant female-specific biology of CAD and plaque erosion. These findings will be translated to systemically expressed DNA methylation profiles in cell free DNA in plasma to move towards early diagnostics. This is a necessary and challenging step towards closing the diagnostic gap between men and women.

Mots-clés : gender,coronary artery disease,diagnosis,pathophysiology,plaque erosion
Projet ERC : HEART.FM (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : Partner
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 85459.06 €

Cardiovascular disease is the world’s leading cause of death, and hypertension is its foremost medical risk factor. Reducing blood pressure in hypertensive patients has positive cardiovascular effects, and music listening offers non-pharmacological ways to regulate heart rate and blood pressure. Presently, the most effective way to administer music inventions with long-lasting effects is labor-intensive and relies on professional therapists’ intuitions, making it non-scalable to large cohorts. HEART.FM is an app-creation initiative to democratize access to personalized music medicine interventions, informed by physiological feedback. Current music therapy apps fail to address the subjectivity and specificity inherent in individual music response; a gap further exists between music therapy apps and physiological feedback. By leveraging advances in wearable ECG monitors and portable blood pressure sensors, HEART.FM will offer music therapy based on individual users’ physiological feedback around musical change points and transitions, which correspond to emotionally salient moments in music listening. HEART.FM exploits the music structure knowledge and cross-modal music-physiology analysis methods developed and trialed in the ERC project COSMOS to advance the state of the art by linking physiological feedback with computational music structure analysis to provide personalized music listening therapy to achieve targeted autonomic nervous system responses. A development goal will be to make HEART.FM ready for large-scale deployment in randomized, controlled research trials that can establish music-hypertension cause-effect relationships for healthy individuals as well as hypertensive patients. HEART.FM will benefit the research community by offering a crowdsourced portal for collecting research data in cardiovascular disease and music-based preventative therapies. The PoC will explore commercialization and market solutions in both music and medical sectors.

Mots-clés : personalized music medicine,computational music structure analysis,software system,hypertensive heart disease
Projet ERC : VASCUGRAFT (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Heidelberg University — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Cardiovascular diseases are one of the major causes of death in the EU and appropriate treatment remains challenging and expensive. Often, the only treatment option is the replacement of a native blood vessel, for example if a coronary artery bypass is needed. Although patient-derived vascular grafts remain the gold standard as a replacement of the original vessel, alternatives have to be found, as donor material is limited. Currently available synthetic grafts have several drawbacks in comparison to native blood vessels. The major drawback is the mismatch between the mechanical properties of the native vessel and the synthetic graft, thus causing major complications like intima hyperplasia. While the stress-strain-curve in synthetic grafts is linear and the grafts are relatively stiff, native blood vessels are soft and have a non-linear, strain-stiffening mechanical behavior. In our ERC Starting Grant CELLINSPIRED we have developed a material structure that allows us to mimic the strain-stiffening of blood vessels. We will employ our strain-stiffening materials in synthetic vascular grafts with broad applicability in the field of vascular surgery. Within the proposed project VASCUGRAFT we will fabricate demonstrators of such biomimetic vascular grafts and strive to find a company that licenses our invention and brings it on the national and international market.

Mots-clés : vascular graft,implant,soft material,mechanical compliance
Projet ERC : BigData4Cat (Horizon 2020, appel 2015, Proof of concept grants)
Entité participante : Institut Català d'Investigació Química — Pays : Espagne — Rôle : PI
Acronyme de l'entité : ICIQ;ICIQ-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 149875.0 €

Catalysis is one of the scientific areas in which Europe has a leading position. The radical change in the use of raw materials from oil towards gas or biomass might compromise this position. Computational techniques have been identified as the third pillar in catalysis research and provide a great amount of data that can speed up the generation of new catalytic systems through rational design. Industries are now starting to focus on the large amount of data published in the open literature regarding mechanistic studies so that they can accelerate their discovering of new catalysts. However, the unstructured and unlinked nature of this information hinders a fast transference of published knowledge to the chemical industry. Our BigData4Cat proof of concept would generate a simple, unified platform: ioChem-BD, where all the data regarding atomistic theoretical simulations in catalysis could be stored and retrieved in a structured manner. The platform will highlight the links, establish the relationships between data from different sources, provide error bars, and allow inferring data from missing steps in complex reaction networks. Moreover, it will provide problem-targeted structured databases with data-mining options. The final goal to the project is to transfer the mature computational Chemistry methodology and data into growing research strategies through the ioChem-BD platform. The goal of the proof-of-concept will be to store, structure and search the Catalysis Big Data resources in a sustainable manner that can be adapted to different problems at academic, editorial and industrial levels.

Mots-clés : catalysis,chemistry,atomistic simulations,density functional theory,big data,homogeneous,heterogeneous,materials science,storage,computational chemistry,sustainability,database,datamining
Projet ERC : CoopCat (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Spanish National Research Council — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CSIC
Type d'entité : Recherche
Financement ERC de l'entité : 1445000.0 €

Catalysis, a multidisciplinary science at the heart of many industrial processes, is crucial to deliver future growth and minimize anthropogenic environmental impact, thus being critical to our quality of life. Thus, the development and fundamental understanding of innovative new catalyst systems has clear, direct and long-term benefits to the chemical manufacturing sector and to the broader knowledge-based economy. In this ERC project I will develop novel innovative cooperative catalysts using interdisciplinary chemical systems based on main group elements, transition metals and molecular clusters to achieve better efficiency and improve chemical scope and sustainability of key chemical transformations. This will be achieved through 3 complementary and original strategies based on catalytic cooperation: (i) Transition-Metal Frustrated Lewis Pairs (TM-FLPs); (ii) hybrid systems combining low-valent heavier main group elements with transition metals (Hybrid TM/MGs); and (iii) intercluster compounds (ICCs) as versatile heterogeneized materials for Green Catalysis. These systems, of high synthetic feasibility, combine fundamental concepts from independent areas, e.g. FLPs and low-valent heavier main group elements with transition metal chemistry, and homogeneous with heterogeneous catalysis. The overall approach will be pivotal in discovering novel reactions that rely on the activation of otherwise unreactive substrates. The experience and knowledge gained from (i)-(iii) will be used to inform the design of a second generation of ICC materials in which at least one of the nanoscale bricks is based on polymetallic TM-FLPs or Hybrid TM/MG systems. Delivering ground-breaking new fundamental science, this pioneering project will lay the foundation for future broad ranging benefits to a number of EU priority areas dependant on innovations in catalysis: innovative and sustainable future energy systems, solar technologies, sustainable chemistry, manufacturing, and healthcare.

Mots-clés : organometallic chemistry,main group chemistry,molecular clusters
Projet ERC : EYECAS (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Koç University — Pays : Turquie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Cataract is the most prevalent visual disorder and blinding disease in the world. Cataracts cannot be corrected with eyeglasses or contact lenses. Surgery is the only option for improved vision, however, vision simulators for different types of cataracts are limited and vision simulator for different types of intra-ocular lens options do not exist. In this project, computational holographic display technology, which was developed during PI's ERC-AdG project, will be exploited for medical applications. A vision simulator instrument based on head-worn computational holographic display and software modules for vision simulation will be developed. Finally pilot studies with cataract patients will be performed in the ophthalmology clinic.

Mots-clés : computational holography,computer generated holography,intra ocular lens,vision simulator,ophthalmology
Projet ERC : CausalEarth (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : German Aerospace Center — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : DLR
Type d'entité : Recherche
Financement ERC de l'entité : 387037.39 €

CausalEarth is an interdisciplinary project, aiming to improve our understanding of the interdependencies between major drivers (modes) of climate variability by developing novel statistical causal inference methods for both observations and model data. Disentangling the interdependencies of the major modes, such as El Nino Southern Oscillation and the North Atlantic Oscillation, is key to understand regional climate, and essential for process-based climate model evaluation. The modes' interdependencies are characterized by common drivers, indirect effects, nonlinearities, regime-dependence, and heterogeneous spatio-temporal causal relations. Currently, observational analyses are mostly based on the correlation of scalar (one-dimensional) time series derived from regional averaging or principal component analysis, restricted to supposed causal regimes, e.g., the winter season or phases of multi-decadal climate indices, where dependencies are expected to be stationary. Such scalar correlation approaches fall short in capturing the modes' complex regime-dependent spatio-temporal causal interdependencies. CausalEarth will develop innovative methods to move (1) from representing complex phenomena as scalar indices to learning spatio-temporal features, (2) from supposing causal regimes to learning them from data, and (3) from correlation to causal dependencies. To this end, CausalEarth will combine recent developments in machine learning with causal inference algorithms. These methods will be used to infer the causal interdependencies and drivers of major climate modes from observations and to construct the next generation of causal metrics for climate model evaluation. CausalEarth will push the limits of what can be learned from observational data about causal relations and drive model development towards breakthroughs in projecting our future climate.

Mots-clés : causal inference,machine learning,modes of variability,climate model evaluation,gaussian processes,kernel methods