Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SeaSym (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université de Vienne — Pays : Autriche — Rôle : PI
Acronyme de l'entité : Uni Wien
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999496.0 €

Sea- and saltmarsh grasses thrive along most of Earth’s coastlines. They form the basis for some of the most ecologically and economically valuable ecosystems on the planet that are also major ‘blue carbon’ sinks. One of the main challenges these marine flowering plants faced during their evolution back into the sea millions of years ago, and one that global change is currently intensifying, is toxic sulfide accumulation around their roots, produced by microorganisms. Like on land, marine plants associate with specific communities of microorganisms, but much less is known about their roles in the health and evolution of their hosts. Intriguingly, one group of microorganisms, Sedimenticolaceae, is virtually ubiquitous in molecular surveys of sea- and saltmarsh grass roots, and is often enriched in root vs rhizosphere or sediment. Their known relatives are beneficial sulfide-oxidizing, nitrogen-fixing symbionts of marine animals, however, their function in sea- and saltmarsh grasses is unknown. SeaSym’s central goal is to reveal the biodiversity and functional roles of widespread symbioses with Sedimenticolaceae, to understand the ecological networks in which they function and evolve, and to understand how global change could shift their future functioning. SeaSym will use established and novel tools to understand symbiont diversity, function and dispersal, in the context of natural yet complex plant-associated microbial communities. My overarching hypothesis is that Sedimenticolaceae is a widespread symbiont of sea- and saltmarsh grasses, directly influencing host health and shaping element cycling in coastal ecosystems. Just as diverse land plants rely on symbioses with Rhizobia for nitrogen, I propose that diverse marine plants rely on Sedimenticolaceae that provide nitrogen whilst removing toxic sulfide. If so, this so far largely overlooked symbiosis could be one of the most important in terms of current ecological and past evolutionary significance.

Mots-clés : symbiosis,host microbe interactions,seagrasses salt marshes,sulfur metabolism
Projet ERC : AI CARE (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Assistance publique - Hôpitaux de Paris — Pays : France — Rôle : Partner
Acronyme de l'entité : AP-HP
Type d'entité : Recherche
Financement ERC de l'entité : 322255.5 €

Despite considerable improvements in short-term allograft and patient survival in kidney transplantation in the past two decades, long-term graft survival remains low, with 20% of transplants failing within five years. Rejection remains a leading cause of graft loss, with immediate consequences for patient morbidity and mortality, posing a major burden on healthcare systems. Increased allograft longevity requires improved patient monitoring and rejection risk stratification using mechanistically informed, non-invasive biomarker strategies and precision diagnostics. The main limitation for such an endeavor is the lack of deeply phenotyped cohorts. Given the complexity and heterogeneity of allograft rejection, patient cohorts with sufficient volume, velocity, variety and validity of data are critical in order to capture disease activity, disease stage, improve risk stratification and optimize treatment. Another limitation is the paucity of multidimensional and integrative research strategies. The goal of the ERC AI-Care project is therefore to go beyond the current state of the art by establishing a transplant precision medicine system to 1) facilitate personalized, non-invasive patient monitoring using cell-free DNA technology (Liquid biopsy) 2) improve rejection diagnosis beyond conventional histology using molecular technologies and digital pathology, and 3) gain further mechanistic insights and improve diagnostic accuracy of transplant organ diseases and apply this knowledge to new research areas.
Projet ERC : RHYTHM IN DEMENTIA (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Assistance publique - Hôpitaux de Paris — Pays : France — Rôle : Partner
Acronyme de l'entité : AP-HP
Type d'entité : Recherche
Financement ERC de l'entité : 389853.75 €

Circadian rhythm (CR) regulates body functions over the 24-hour day/night period; sleep/wake cycle is its most visible manifestation. CR disruptions have long been observed in patients with dementia and emerging evidence points to their presence in the preclinical period of dementia. This suggests that certain aspects of CR could be useful in identification of high-risk individuals and could serve as potential targets for interventions to delay dementia onset and progression. This requires an in-depth understanding of the role of CR in dementia pathogenesis. As population ageing increases dementia burden, it is critical to find strategies to identify patients at risk of dementia with precision, prevent, and slow its progression. Building on recent advances in accelerometery (to assess CR features comprehensively) and dementia biomarkers (deep-phenotyping of dementia pathogenesis), RHYTHM IN DEMENTIA will make a decisive step-change in knowledge by determining CR features involved in dementia processes along the course of the disease. The aims are: 1) identify core CR features that shape 10-year risk of dementia in a community-dwelling cohort of 4000 older adults; 2) uncover specific CR disruptions that characterise major dementia subtypes and stages of Alzheimer’s disease (determined by biomarkers) in a new cohort of 1500 patients recruited from two memory clinics in Paris; and 3) ascertain how CR affects dementia prognosis in the patient cohort by examining cognitive and functional decline, hospitalisation, institutionalisation, and mortality. This project will yield new insight into the nature of the association between CR and dementia progression. These findings will ultimately inform the potential for a cost-effective and easy to use tool to assess CR features to facilitate both identification of patients at risk of dementia and tailored secondary prevention interventions that address CR disruptions in dementia patients and slow progression of dementia.

Mots-clés : circadian rhythm,dementia,alzheimer s disease,accelerometer
Projet ERC : EPIAROUSAL (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Hospices civils de Lyon — Pays : France — Rôle : Partner
Acronyme de l'entité : HCL
Type d'entité : Organismes publics (hors enseignement & recherche)
Financement ERC de l'entité : 864315.0 €

Both seizures and their complications are modulated by patients’ vigilance states. Several epilepsy complications are associated with sleep, including Sudden and Unexpected Death in Epilepsy (SUDEP). SUDEP primarily results from a fatal postictal central apnea after a nocturnal generalized convulsive seizures. While transient seizure-related respiratory dysfunction is frequent in patients, current hypotheses suggest that in some of them, repetition of seizures may induce a chronic alteration of respiratory regulation, increasing the risk of fatal apnea. Reducing the severity of postictal respiratory dysfunction has thus appeared as one of the most promising way to prevent SUDEP. However, no encouraging result has been reported yet, suggesting that epilepsy-related respiratory dysfunction may only be the tip of the iceberg. Given the numerous interconnections between the network that regulates arousal and sleep and the respiratory network, I make the hypothesis that some patients with drug-resistant epilepsy might combine this well-known seizure-related respiratory dysfunction with a chronic alteration of arousal regulation, resulting in abnormal asphyxia-induced arousal. Adenosine system is deeply implicated in the regulation of sleep and central respiratory control and is modulated by seizures. Epilepsy-related alteration of the brainstem adenosine pathway may play a key role in the development of arousal and respiratory co-dysfunction. Using both experimental and clinical studies, EPIAROUSAL will investigate the exact interplay between epilepsy-related respiratory dysfunction and arousal regulation on the one hand, and the relation between long-term repetition of seizures, brainstem adenosine pathway and the respiratory and arousal co-dysfunction on the other hand. The final objective is to validate that adenosine-targeted therapy can restore normal asphyxia-induced arousal in drug-resistant epilepsy, paving the way for a first a clinical trial of SUDEP prevention

Mots-clés : epilepsy,sudep,adenosine
Projet ERC : IronHeart (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999224.0 €

Mercury is a metal-rich planet from which Earth-based and spacecraft data were collected. Our understanding of its interior structure and thermochemical evolution is however still relatively poor. This is due to: (1) large uncertainties on its polar moment of inertia and surface composition; this will be largely improved by the BepiColombo mission; (2) an unknown bulk-planet composition; and (3) a poor knowledge of some key thermophysical properties (e.g. phase stability, temperature, density) of solid/liquid metals and silicates inside Mercury. This is because under Mercury’s reducing conditions, elements behave differently than on other planets. Currently available phase diagrams for the Moon and Mars are thus irrelevant for calculating the compositions and physical properties of Mercury’s core, mantle and crust. Improving such constraints is critical but requires new experiments under hitherto unexplored conditions; they will be done in IronHeart. So far, it was largely neglected that many compositional features of Mercury are inconsistent with its direct accretion as a small, metal-rich planet. IronHeart’s working hypothesis is that Mercury is merely the remnant of a larger, Martian-sized, chondritic planet (which we call proto-Mercury) involved in collisions having stripped away much of its mantle. This process did eventually set the final composition of modern Mercury. For the first time, IronHeart will evaluate experimentally how proto-Mercury controlled the core and mantle compositions of modern Mercury. Further experiments on these compositions will provide phase equilibria of Mercury’s internal layers allowing us to calculate their thermophysical properties. By combining those with BepiColombo data into thermal and geophysical models, we will provide a clearer than ever picture of Mercury’s structure and evolution. IronHeart will also be critical to understanding dense exoplanets and the Earth, which accreted from similar building blocks as Mercury.

Mots-clés : mercury,bepicolombo,magma ocean,core,experimental petrology
Projet ERC : AMEN (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1940875.0 €

Our understanding of amenable C*-algebras has drastically improved over the past decade due to substantial advances in the Elliott classification program. The proposed research is intended to spearhead the classification and structure theory for C*-dynamics, which encompasses groups acting continuously on C*-algebras and the question to which extent their detailed structure is encoded at the level of computable invariants. The objectives involve the following lines of investigation: - The case of discrete groups acting on simple amenable C*-algebras, the latter of which have become accessible due to recent methodological breakthroughs within Elliott's program. The task is to develop a dynamical version of Elliott's program, i.e., to consider natural categories of such group actions, identify functorial invariants such as K-theory and traces, and show that these invariants completely classify a naturally occuring category up to a suitable notion of isomorphism. - The theory of invariants for noncommutative C*-dynamics. This field is faced with numerous open problems requiring solutions before a fully general classification theory can be developed. This part of the project addresses the need for effective computational methods for equivariant Kasparov classes, or systematic techniques to exploit equivariant Ext-theory for the purpose of classification. - The case of noncommutative time evolutions, which includes new rigidity phenomena for the passage of time in simple C*-algebras, both with and without the presence of equilibrium states. A deeply rooted theme within all these objectives is the presence of amenability for the actions and the C*-algebras, which gives rise to radically new phenomena in the context of non-amenable acting groups. Drawing ideas from diverse areas such as the Elliott program, equivariant Kasparov theory, classical and noncommutative ergodic theory, novel methods are proposed to achieve groundbreaking results in the area of C*-dynamics.

Mots-clés : c dynamical systems cocycle conjugacy classification of c algebras elliott program amenability
Projet ERC : KISSIES (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2480500.0 €

Detecting and monitoring volatile organic compounds (VOCs) is an important task with applications ranging from disease diagnosis via breath analysis to monitoring exposure to toxic chemicals. However, in all such applications, selectively measuring specific VOCs is challenging due to their low concentrations and the presence of a multitude of interfering compounds. Since current miniature sensors cannot efficiently distinguish between VOCs, there is a need for a novel technology capable of distinguishing a VOC of interest from a complex background.  KISSIES will address this challenge by bridging the worlds of porous crystalline materials and sensor technology. For the first time, kinetic selectivity in the tailored nanopores of metal-organic frameworks will be leveraged to mimic nature’s approach to olfaction and enable selective sensing. This way, KISSIES will not only enable cross-fertilization between research fields that have thus far been separated by traditional subject boundaries but also open up perspectives on solving unaddressed real-world challenges. Moreover, the novel methodology that will be developed will have an impact beyond the scope of the project, in domains such as separation technology and adsorption measurements.

Mots-clés : metal organic frameworks,chemical sensors,adsorption,diffusion
Projet ERC : SUPERSTARS-3D (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1995750.0 €

Stars with masses many times that of our Sun are the direct progenitors to cosmic phenomena such as supernova explosions, black holes, and gravitational wave (GW) sources. Through electromagnetic observations we obtain empirical information of such massive stars, however decoding the radiation reaching us through our telescopes is a highly non-trivial exercise. To constrain fundamental properties like temperatures, radii, chemical abundances, and mass loss, the observed radiation is fit by means of model stellar atmospheres. Observations and theory show that the radiation-dominated atmospheres of massive stars are highly complex, multi-dimensional systems. However, although 3D model atmospheres of sun-like stars have already been on the market for a while, for hot, massive stars we still rely solely on results derived from inadequate 1D simulations. This severely limits our knowledge of the basic physics of massive stars and our capacity to correctly interpret observations, thereby preventing progress also in the large number of astronomical fields (e.g., black hole and GW progenitor models) that rely on a firm understanding of the massive-star life-cycle. The time is now ripe to change this.  Building on the unique expertise of the PI and his team, in a groundbreaking effort we will here develop the very first 3D model atmospheres for hot, massive stars with winds. SUPERSTARS-3D will fundamentally improve our physical understanding of massive stars, and revolutionize analysis and interpretation of their observed radiation. By further confronting our pioneering simulations directly to state-of-the-art observations, we will derive unprecedented constraints on evolution and end-of-life models. We will develop all new models in an open-source fashion and make them easily accessible for a broad community; as such, SUPERSTARS-3D will also provide the critical cornerstone from which a large number of future scientific programs undoubtedly will be built.

Mots-clés : radiation hydrodynamics,radiative transfer,massive stars,stellar atmospheres,winds and outflows,quantitative spectroscopy
Projet ERC : C2C-PV (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Forschungszentrum Jülich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : FZJ
Type d'entité : Recherche
Financement ERC de l'entité : 1962404.0 €

The project cradle-to-cradle design of photovoltaic modules (C2C-PV) will design and build the first photovoltaic module with full cradle-to-cradle (C2C) recyclability. Achieving this goal requires a radically new design framework. Today’s photovoltaic modules were not designed for recycling, resulting in a recycling process that is slow and delivers materials of inferior quality. In contrast, C2C-PV will apply the principles of green engineering and techno-economics to create a photovoltaic module with minimal environmental impact over multiple generations and economic viability. Unique to this project is the design of a complex opto-electronic device from scratch according to these principles. The scientific challenge of this proposal is to reconcile durability and separability. Current photovoltaic modules follow a “design for immortality” approach, monolithically integrating solar cells in a module to minimize exposure to the environment. This approach pits durability against separability and is the root cause of all challenges in current photovoltaic module recycling. Highly adhesive interfaces make a clean separation of components slow and challenging at best, and often infeasible. Yet, high throughput and retention of material quality are essential for the economic viability of recycling. The key to resolving this challenge lies in the choice of materials and the design of interfaces. Following the design principles of C2C, the project C2C-PV will only use materials that can be produced and processed in a close-loop manner, avoid toxicity and scarcity, and are material- energy- and capital efficient. Interface design will focus on eliminating unnecessary adhesion and equip all necessary sealing with a mechanism for separation. Perovskite solar cells and photovoltaic modules will serve as a vehicle for demonstrating multigenerational close-loop recyclability. Tracking material-, energy- and capital flow over multiple generations will allow quantifying and op

Mots-clés : recycling,photovoltaic energy,cradle to cralde
Projet ERC : CompSURG (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université de Strasbourg — Pays : France — Rôle : PI
Acronyme de l'entité : UNISTRA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1951931.0 €

The operating room is the most frequent location for hospital-related errors. However, intra-operative adverse events (IAEs) are underreported, which impedes their large-scale analysis, the definition of appropriate safety measures and the development of intra-operative support systems to reduce their occurrence. Recent manual video-based assessments of surgical procedures have shown that not only are IAEs frequent, but also that near miss intra-operative events, previously thought to be inconsequential, are in fact predictors of major errors and correlate with complications and poor surgical outcomes.  We leverage these recent findings to propose a radically new, computational approach to improve intra-operative surgical safety. We propose to focus on automatically detecting and analyzing IAEs in endoscopic videos via novel computer vision methods that model the detailed semantics of tool-tissue interactions, as needed to study the activity patterns leading to these critical events. We will first generate a multi-centric, multi-procedure dataset annotated with tool-tissue interaction semantics and IAEs. We will then develop a new fully differentiable neural network model of surgical videos relying on an intermediate graph representation to disentangle the surgical semantics. Finally, we will introduce new training methods for scaling these approaches to different types of surgeries and centers using a limited set of annotations.  These computational methods will allow the automated reporting and analysis of IAEs at a scale unfeasible with manual methods. We will use them to analyze patterns of IAEs and to identify the activities and phases of the surgical procedures that would benefit from new safety measures. We will also design a prototype for intra-operative support. We believe that this project will help to improve surgical safety and hence greatly benefit patient care.

Mots-clés : surgical video analysis deep learning semi supervised learning laparoscopic surgery intra operative adverse events safety in surgery