Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : CLLCLONE (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Institute of Oncology Research — Pays : Suisse — Rôle : PI
Acronyme de l'entité : IOR
Type d'entité : Recherche
Financement ERC de l'entité : 1940000.0 €

Chronic lymphocytic leukemia (CLL), the most common leukemia in adults, is addicted of interactions with the microenvironment. The B-cell receptor (BCR) is one of the most important surface molecules that CLL cells use to gain oncogenic signals from the microenvironment. The critical role of BCR signaling for the pathogenesis of CLL is supported by the therapeutic success of ibrutinib, a targeted agent that disrupts the BCR pathway. Beside microenvironment-promoted oncogenic signals, the biology of CLL is also driven by molecular lesions and clonal evolution, that mark CLL progression and treatment resistance. The interconnection between microenvironment-promoted oncogenic signals and clonal evolution has been postulated in CLL but never proven because of the lack of suitable ex vivo models. Ibrutinib allows the unprecedented opportunity of assessing the contribution of cell signaling to cancer clonal evolution directly in vivo in patients. The project working hypothesis is that mutation- and selection-driven clonal evolution is promoted by microenvironment-induced signals, including those propagated from the BCR. According to this hypothesis: i) BCR signaling inhibition due to ibrutinib should stop clonal evolution; while ii) acquisition of by-pass mechanisms that keep ongoing signaling should promote mutation and selection despite BCR inhibition, thus favoring CLL clonal evolution and ibrutinib resistance. In this scenario, the combination of ibrutinib with drugs that overcome by-pass mechanisms could prevent clonal evolution, thus improving treatment efficacy and patient outcome. In order to address our working hypothesis, we will take advantage of clinical trial and co-clinical trial samples to monitor signaling and clonal evolution under ibrutinib and ibrutinib-based combination treatments.

Mots-clés : leukemia,targeted therapy,clonal evolution,precision medicine,drug resistance
Projet ERC : EVOCLOCK (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 1499728.0 €

Circalunar clocks are endogenous biological clocks, which allow organisms to time development and reproduction to lunar phase. They are common in marine organisms, but their molecular basis is still entirely unknown. Candidate gene approaches have failed so far. In the marine midge Clunio marinus (Diptera: Chironomidae), I can elegantly overcome this problem by exploiting an array of local genetic adaptations in circalunar timing. Through evolutionary analysis, QTL mapping and genome screens my group currently produces evidence-based circalunar candidate genes without any need for prior knowledge or assumptions. In this ERC proposal, I aim to take this work to the next level and identify the molecular and cellular basis of circalunar clocks. I will establish molecular tools for Clunio and use them to confirm and characterize circalunar clock candidate genes. Specifically, I aim to: (WP1) Establish genome editing and confirm candidate genes via knockout and allelic replacement. (WP2) Study gene expression modules across the lunar cycle and identify the transcriptional regulators that exert circalunar control on development and maturation. (WP3) Describe Clunio’s larval nervous system and trace circalunar clock sensory input pathways to their convergence point. This will identify the cellular substrate of the circalunar clock. (WP4) Settle the on-going debate on the role of circadian clocks in circalunar timing. I will particularly study the role of the famous period gene. In the future, this molecular endeavour will also boost evolutionary work: Clunio will provide insights into fundamental questions, such as the role of genome architecture in local adaptation. But immediately, unravelling the molecular basis of circalunar clocks will be a breakthrough in chronobiology. It will inspire new ideas and experiments. Comparing circalunar to circadian clocks, we will for the first time be able to see basic principles in the molecular design of biological clocks.

Mots-clés : biological clocks,circalunar clocks
Projet ERC : PARTYOPINION (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Aarhus University — Pays : Danemark — Rôle : PI
Acronyme de l'entité : AU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1995831.0 €

Citizens’ opinions about public policy lies at the heart of democracy. A long-standing, but little researched, claim in political science is that political parties provide a vital informational basis that citizens can use to inform their policy opinions. However, current literature shows the opposite: Parties distort citizens’ decision-making and make them dogmatic defenders of their party without caring about policy substance. Therefore, we lack a theory of how – or even if – parties can provide policy information citizens use to inform their opinions. This project advances a new research agenda to examine the informational role of political parties in citizens’ opinion formation. The project is not only pioneering in developing a novel theoretical model of when and how citizens use parties to inform their opinions; it also breaks new ground methodologically by combining experiments with a cross-national design. The project is unique in that it integrates macro-level party characteristics with micro-level opinion formation, helping scholars ask new questions and seek novel answers to how parties affect citizens’ opinions. As key empirical contribution, the project will develop a new survey instrument to offer the first mapping of how citizens view parties’ “policy reputations”; develop and use new measures of citizens’ policy reasoning; conduct a series of innovative survey experiments across party systems to obtain generalizable causal estimates of when and how parties inform opinions across individuals, parties and countries in Western Europe; and implement a panel survey to track how parties inform opinions during a real-world debate. The project will significantly improve our understanding the relationship between citizens and political parties. Timely and innovative, the project will answer how current transformations of party systems affect citizens’ ability to participate meaningfully in democracy, and if parties still play a role in that process.

Mots-clés : public opinion,party cues,political behavior,survey experiments,panel survey,political parties,political,communication,citizen politics
Projet ERC : CALENDARS (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Bergen — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1084021.0 €

Climate change may be undermining the stock of seasonal representations that society draws on to understand and live according to the weather. The CALENDARS project studies how modern society represents seasons, and how these representations shape institutions and help people live with seasonal change. The project opens an important emerging field in climate adaptation research by examining the representations of ‘normal’ seasons underlying key institutions, assesses their quality for successful adaptation to rapid climate change, and analyses facilitators and barriers to adopting representations more flexibly to new climates. It contributes a novel perspective on how to transform our institutions – from schools to farmer cooperatives – from the foundational culture and representations up, to better fit the changing seasonal cycles we are experiencing. CALENDARS empirically explores the relationship between different institutions’ ideas of seasons and their successful adaptation through an in-depth comparative study of a set of institutions in two local communities, in Norway and New Zealand. It is steered by an overall objective to: ‘Advance knowledge and understanding of how seasonal representations shape and are shaped by institutions, and critically appraise the quality of these representations for contributing to successful adaptation to seasonal change’. Conceptually, CALENDARS looks at representations as continuously ‘co-produced’ at the boundary of nature and society, and society and institutions. It tests a novel reconceptualisation of co-production as a prism; with each of the project’s three phases looking at the complex processes by which representations emerge through different ‘lenses’ of co-production. Methodologically, the project tests the feasibility of a novel basket of bespoke methods spanning narrative interviews, calendar boundary objects and collaborative sustainability science.

Mots-clés : climate adaptation,seasonal representations,institutions,co production
Projet ERC : AWACA (Horizon 2020, appel 2020, Synergy grants)
Entité participante : Université de Versailles Saint-Quentin-en-Yvelines — Pays : France — Rôle : Partner
Acronyme de l'entité : UVSQ
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 84600.0 €

Climate models predict that precipitation will increase in Antarctica, which will moderate global sea-level rise. Meanwhile, the isotopic composition of snowfall records climate parameters which can be recovered in ice cores. However, there are still major gaps in our understanding of the atmospheric water cycle over Antarctica. For the first time, the AWACA project will provide a consistent and comprehensive combined observation and modeling framework to understand and predict the fate of atmospheric water all along the tropospheric column. Specifically adapted/designed instruments will be combined to form observation platforms deployed at 5 sites along a 1100 km coast-to-plateau transect aligned with the typical moisture-carrying air mass trajectories. The challenges of working in full autonomy in Antarctica, never addressed to such an extent before, will be tackled by collaborating with experts in polar technology and logistics. The resulting data set will make possible the study of the processes driving the water fluxes and composition to an unprecedented level, and the gained insights will be a strong basis to develop new physics parameterizations for regional and climate models. Once validated along the transect but also in other regions of Antarctica thanks to satellite observations and past campaigns, those models will enable us to decipher the past and future variability of the atmospheric water cycle over Antarctica.

Mots-clés : remote sensing,paleoclimatology,climate projection,cloud and precipitation observation and microphysics,water vapor,antarctica,surface flux,blowing snow
Projet ERC : CaNANObinoids (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Hebrew University of Jerusalem — Pays : Israël — Rôle : PI
Acronyme de l'entité : HUJI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Clinical experience with globally-acting cannabinoid-1 receptor (CB1R) antagonists revealed the benefits of blocking CB1Rs for the treatment of obesity and diabetes. However, their use is hampered by increased CNS-mediated side effects. Recently, I have demonstrated that peripherally-restricted CB1R antagonists have the potential to treat the metabolic syndrome without eliciting these adverse effects. While these results are promising and are currently being developed into the clinic, our ability to rationally design CB1R blockers that would target a diseased organ is limited. The current proposal aims to develop and test cell- and organelle-specific CB1R antagonists. To establish this paradigm, I will focus our interest on the kidney, since chronic kidney disease (CKD) is the leading cause of increased morbidity and mortality of patients with diabetes. Our first goal will be to characterize the obligatory role of the renal proximal tubular CB1R in the pathogenesis of diabetic renal complications. Next, we will attempt to link renal proximal CB1R with diabetic mitochondrial dysfunction. Finally, we will develop proximal tubular (cell-specific) and mitochondrial (organelle-specific) CB1R blockers and test their effectiveness in treating CKD. To that end, we will encapsulate CB1R blockers into biocompatible polymeric nanoparticles that will serve as targeted drug delivery systems, via their conjugation to targeting ligands. The implications of this work are far reaching as they will (i) point to renal proximal tubule CB1R as a novel target for CKD; (ii) identify mitochondrial CB1R as a new player in the regulation of proximal tubular cell function, and (iii) eventually become the drug-of-choice in treating diabetic CKD and its comorbidities. Moreover, this work will lead to the development of a novel organ-specific drug delivery system for CB1R blockers, which could be then exploited in other tissues affected by obesity, diabetes and the metabolic syndrome.

Mots-clés : endocannabinoids,cb1 receptor,diabetes,obesity,diabetic nephropathy,mitochondrial biogenesis,mineral and bone disorder,nanomedicine,targeted drug delivery
Projet ERC : CloudCT (Horizon 2020, appel 2018, Synergy grants)
Entité participante : Technion – Israel Institute of Technology — Pays : Israël — Rôle : CO-PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2539563.0 €

Clouds play a lead climatic role, controlling energy fluxes and regulating fresh water distribution. There is an acute need for cloud-resolving and global-climate models that accurately describe and parametrize the physics of warm convective and stratiform clouds, and the clouds’ sensitivity to environmental changes. Currently this requirement is not being met due to a gap in observational capabilities. Namely, there is a lack of sufficient sensing tailored to capture the 3D macro and microphysical properties of warm clouds, which are often spatially unresolved. Moreover, current retrievals use a plane-parallel radiative model, which is incompatible with the 3D heterogeneous nature of clouds. These gaps lead to uncertainties in climate models and prediction. We propose an innovative sensing approach: cloud scattering-tomography, relying on an unprecedented large formation of ten cooperating, high performance pico-satellites. They will simultaneously image cloud fields from multiple directions, at 50m resolution. Based on this data, the novel tomography approach will seek the 3D volumetric structure of cloud fields, base-to-top profiles of droplets' size and their variance, volumetric distribution of optical extinction and rain indicators. The required pointing accuracy, data size and coordinated control of a complex 10 pico-satellite formation demands advanced space engineering, beyond existing technologies of traditional single satellites and constellations of satellites. Realizing a large formation requires innovative, distributed, networked, cooperative control, including advanced sensors and actuators for pico-satellites, as well as in-orbit autonomy. On-board hardware and flexible software will be adapted to meet computational needs within the physical limitations of pico-satellites (energy, mass, volume). Using the acquired spaceborne images for tomography-based 3D atmospheric retrievals requires advancements in computer vision and efficient analysis based on three-dimensional radiative transfer. New information gained will improve and validate our cloud resolving models, leading to more realistic simulations of cloud fields. This will enable better understanding of how environmental changes affect warm clouds and help improve their representation in climate models. This multidisciplinary, synergic approach will establish and test critical and currently unconventional aspects of remote sensing and mathematical retrieval based on a pico-satellite formation. It will yield a database of 3D macro and micro structure of warm cloud fields, while setting the stage for next-generation distributed spaceborne global observations.

Mots-clés : satellite formations,distributed satellite systems,networked control,adaptive control,pico satellites,navigation sensors
Projet ERC : CloudCT (Horizon 2020, appel 2018, Synergy grants)
Entité participante : Zentrum für Telematik — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : ZFT
Type d'entité : Autres
Financement ERC de l'entité : 9105636.0 €

Clouds play a lead climatic role, controlling energy fluxes and regulating fresh water distribution. There is an acute need for cloud-resolving and global-climate models that accurately describe and parametrize the physics of warm convective and stratiform clouds, and the clouds’ sensitivity to environmental changes. Currently this requirement is not being met due to a gap in observational capabilities. Namely, there is a lack of sufficient sensing tailored to capture the 3D macro and microphysical properties of warm clouds, which are often spatially unresolved. Moreover, current retrievals use a plane-parallel radiative model, which is incompatible with the 3D heterogeneous nature of clouds. These gaps lead to uncertainties in climate models and prediction. We propose an innovative sensing approach: cloud scattering-tomography, relying on an unprecedented large formation of ten cooperating, high performance pico-satellites. They will simultaneously image cloud fields from multiple directions, at 50m resolution. Based on this data, the novel tomography approach will seek the 3D volumetric structure of cloud fields, base-to-top profiles of droplets' size and their variance, volumetric distribution of optical extinction and rain indicators. The required pointing accuracy, data size and coordinated control of a complex 10 pico-satellite formation demands advanced space engineering, beyond existing technologies of traditional single satellites and constellations of satellites. Realizing a large formation requires innovative, distributed, networked, cooperative control, including advanced sensors and actuators for pico-satellites, as well as in-orbit autonomy. On-board hardware and flexible software will be adapted to meet computational needs within the physical limitations of pico-satellites (energy, mass, volume). Using the acquired spaceborne images for tomography-based 3D atmospheric retrievals requires advancements in computer vision and efficient analysis based on three-dimensional radiative transfer. New information gained will improve and validate our cloud resolving models, leading to more realistic simulations of cloud fields. This will enable better understanding of how environmental changes affect warm clouds and help improve their representation in climate models. This multidisciplinary, synergic approach will establish and test critical and currently unconventional aspects of remote sensing and mathematical retrieval based on a pico-satellite formation. It will yield a database of 3D macro and micro structure of warm cloud fields, while setting the stage for next-generation distributed spaceborne global observations.

Mots-clés : satellite formations,distributed satellite systems,networked control,adaptive control,pico satellites,navigation sensors
Projet ERC : ISIFit (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Acronyme de l'entité : KUL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1734360.0 €

Cochlear implants (CIs) are successful auditory prostheses that enable people with deafness to hear through electrical stimulation of the auditory nerve. In a CI sound processor, a sound signal is converted into a sequence of electrical pulses. This conversion entails many parameters that should ideally be fine-tuned (fitted) for every individual patient, to account for various anatomical and physiological differences. In current clinical practice, devices are fitted during the initial rehabilitation and yearly thereafter. As fitting is very time consuming, only the bare minimum number of parameters is fitted individually. However, for many other parameters, for which currently the same default values are used for all patients, better speech understanding can be achieved with individual fitting. Apart from the fitting, CIs do not take into account the neural or perceptual effects of stimulation. The objective of this project is to provide better fitting to individual patients by developing a closed-loop CI that automatically adjusts its fitting and sound processing based on the neural response to speech. To achieve this, we will (1) objectively measure speech understanding, by recording the electroencephalogram (EEG) in response to ecological speech signals, (2) automatically fit a wide array of sound processing parameters accordingly using a genetic algorithm, and (3) develop a wearable closed-loop CI that continuously records the EEG and adjusts the fitting in real-life situations. This will lead to a better understanding of speech perception of people with a hearing impairment, an objective measure of speech intelligibility with many applications in diagnostics, a method to automatically fit CIs, and a novel closed-loop CI. For the patient this means improved speech intelligibility in noise and therefore better communication and quality of life. For the clinic this means improved efficiency and the ability to better fit devices.

Mots-clés : cochlear implant,evoked potentials,speech intelligibility,automatic fitting,objective measures,genetic algorithm,closed loop