Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DWELL (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université de Turku — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499855.0 €

Why do some youth suffer debilitating depression or anxiety after being victimized by peers yet others grow hostile? Why do some youth dwell alone on their problems (rumination) yet others dwell with their friends (co-rumination)? When does talking to friends about problems (e.g., victimization) help or hurt? Despite the serious (and potentially long-lasting) consequences of peer victimization, these questions remain unanswered. We lack a detailed understanding on how victimization, (co-)rumination and mental health co-develop, or when and why their associations differ between individuals.  DWELL moves beyond the state-of-the-art to address these questions in three work packages. WP1 examines individual differences in the pathways between victimization, rumination and mental health. In contrast to existing work, WP1 focuses on why some victimized youth, but not others, ruminate about their victimization – even years later as adults. In WP2, I put forth a new conceptualization of co-rumination - as a dynamic process that can vary within a person across their friendships, rather than as a static trait. Towards this aim, I introduce a novel co-rumination measure that captures who co-ruminates with whom. By identifying a network of co-rumination ties, this also allows for ground-breaking insight into how co-rumination spreads in a peer group. WP3 integrates these findings into a holistic framework, accounting for the temporal ordering of victimization, (co-)rumination, and mental health. Through a multi-method design (longitudinal studies, register data, daily diary, observation), and a novel co-rumination measure, DWELL explains individual differences in day-to-day, short-term (~1 year), and longer-term (up to adulthood) effects of victimization and (co-)rumination on mental health. This framework will help prevent suffering of victimized youth, and has far-reaching implications for non-victimized youth who engage in (co-)rumination in response to other stressors.

Mots-clés : peer victimization rumination co rumination mental health
Projet ERC : SmartHyMat (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Université de Turku — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2123241.0 €

Modern technologies increasingly require smart and sustainable materials that adapt to their operating conditions in functional devices, such as those for efficient energy production and nanorobotics. Their development requires controlling complex material functions in response to external stimuli. While molecular machines demonstrated remarkable potential in a wide range of stimuli-responsive functions, this remains a challenge in the solid state, hampering their use in functional devices. Overcoming this necessitates an amphidynamic platform that is ordered yet permits molecular motion without compromising stimuli-responsiveness, while offering the ease of processing for device fabrication. SmartHyMat will address this enduring challenge by relying on the unparalleled capacity of hybrid halide perovskites to act as unique scaffolds for stimuli-responsive systems. These soft yet crystalline materials recently emerged as one of the leading semiconductors for thin-film optoelectronics, featuring mixed ionic-electronic conductivities and extraordinary performances in solution-processable devices. While their operational stability can be enhanced by incorporating organic moieties, their functionality remains limited to electronically inactive off-the-shelf materials. This project will realize the innovative potential of hybrid perovskites in adaptive nanotechnologies through molecular design, synthesis, and characterization of stimuli-responsive systems in hybrid solid-state architectures. Their potential will be demonstrated in unprecedented smart devices for power generation, memory, and actuation relevant for automation and nanorobotics. This will involve optoelectronic, such as smart solar cells, as well as optoionic devices exploiting mixed conductivities, including artificial synapses and neuromuscular junctions. The focus will be on environmentally friendly materials, setting the stage for an entirely new generation of smart and sustainable nanotechnologies.

Mots-clés : supramolecular stimuli responsive materials,hybrid halide perovskites,optoelectronics,optoionics
Projet ERC : PROTEGO (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : École polytechnique de Milan — Pays : Italie — Rôle : PI
Acronyme de l'entité : PoliMi
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1198295.0 €

Aortic valve diseases are degenerative conditions that develop progressively and insidiously. Once symptoms become evident, life expectancy is significantly reduced. While treatments for these pathologies are widely available, there remains a remarkably high rate of procedural complications. These complications have been shown to have a negative impact on cardiac mortality and the likelihood of rehospitalization for heart failure. This underscores the need for further technological advancements. Protego's objective is to determine whether a combination of immunological and biomechanical profiles in patients with aortic valve diseases can effectively predict post-treatment prognosis. My goal is to develop an innovative, validated, and clinically applicable methodology that can identify the best treatment options and predict post-procedural outcomes while minimizing complications. This methodology will serve to determine the timing of treatment for patients with valvular aortic diseases and assess whether the proposed treatment is likely to be beneficial preoperatively, while also minimizing the risk of post-procedural complications. I will achieve this by combining imaging analysis, deep learning algorithms, in silico models, and in vitro tests. My approach involves the following key objectives: (i) creating a multi-physics digital twin of patients with aortic valve diseases, (ii) developing a validated, high-fidelity model for treatment with quantification of post-treatment outcomes and (iii) generating a proof of concept for a clinically applicable predictive model trained using both immunological profiles and biomechanical features of patients. This innovative approach will provide a deeper understanding of how clinical and biomechanical outcomes correlate with the amplification of inflammation, helping us comprehend the interaction between biomarkers and negative post-treatment prognosis in patients with aortic valve diseases.

Mots-clés : personalised medicine,digital human twin in healthcare,treatment,validation,verification,treatment selection support,aortic valve diseases,transcatheter aortic valve implantation
Projet ERC : HERMES (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : École polytechnique de Milan — Pays : Italie — Rôle : PI
Acronyme de l'entité : PoliMi
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

The overarching goal of HÈRMES is to establish a new methodology for time-resolved imaging by means of Time-Correlated Single Photon Counting(TCSPC). Since its debut in the literature, the potential of TCSPC as non-invasive, ultra-sensitive and extremely precise imaging tool was manifest. Numerous applications have benefited from it so far, but a key limitation still prevents its wide use in many other crucial applications: the speed of a TCSPC acquisition chain must be kept low(few Mcount/s in the best case) to avoid distortion due to pile-up of events. Up to now researchers in this field have tried to work around this limit mainly by posing multiple channels in parallel, but still facing severe limitations mainly due to efficiency, fill factor, precision, linearity and readout complexity. I propose an innovative methodology for removing all constraints on TCSPC, promising a change in the paradigm of how TCSPC systems are conceived and how time-resolved measurements are carried out. To achieve such an ambitious goal, a radical change is necessary. I expect to develop a comprehensive mathematical model showing that pile-up distortion can be avoided with any combination of single photon detector and laser excitation power if additional picosecond-precision information on the status of system in each time bin is acquired at run-time. I will develop ultrafast electronics for Single Photon Avalanche Diodes to move from theory to the real experimental world. Moreover, I will empower the new constraint-less TCSPC by developing an innovative computational imaging framework, opening the way to the real-time acquisition of 4D images. Next-generation TCSPC systems based on the HÈRMES methodology will allow the exploitation of this powerful tool in crucial applications such as, for example, intraoperative and neuron imaging, where an ultrafast but still linear acquisition is necessary to enable complex operations like image-assisted brain surgery and spike analysis of neurons.

Mots-clés : single photon,time correlated single photon counting,tcspc,time resolved imaging,computational imaging
Projet ERC : ARCHEOROBOTICS (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Université norvégienne de sciences et de technologie — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1949705.0 €

In the waters around Svalbard there are more than a thousand undiscovered shipwrecks from the early whaling period on the seabed. With the environmental changes rapidly happening in the Arctic, this presumably well-preserved underwater cultural heritage may be under threat. ARCHEOROBOTICS aims to develop methods for autonomous robots to find and investigate these wrecks and secure the invaluable human and ecological history they represent before it is too late. ARCHEOROBOTICS is divided into five interdependent work packages to address various challenges related to detection, documentation and interpretation of shipwrecks utilizing cutting edge underwater robotic technologies. Key objectives include compiling a detailed knowledge base of shipwrecks, developing a digital wreck simulator, creating algorithms towards embedded archaeological intelligence in robotic systems, and developing a methodological framework for addressing epistemological issues arising from the ambitions of the project. The PI will lead an interdisciplinary team of two PhD students and one research fellow to achieve the ambitious goals in each work package. Field trials on known wreck sites in Trondheimsfjorden will be conducted frequently for data acquisition, testing and validation of methods and algorithms developed in the simulator. A larger field campaign in Svalbard towards the end of the project will utilize the new robotic capabilities for finding and investigating wrecks from the Arctic whaling. The project’s outcomes will enhance our understanding of Arctic history, provide critical data on long-term environmental changes, and push the boundaries of interdisciplinary research between archaeology, robotics, and marine science. By fostering collaboration between archaeologists and engineers, ARCHEOROBOTICS will establish a new paradigm for the investigation of underwater cultural heritage, with far-reaching implications for both archaeological scholarship and technological advancement.
Projet ERC : SELECTDNA (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Institut Karolinska — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499812.0 €

In nanomedicine, patterns, shapes and mechanics are tuned to improve performance in applications such as drug delivery and pattern matching binders. A fundamental bottleneck is that structures need to be individually assembled and tested limiting the number that can be screened and likely missing structures with optimal performance. In this proposal we describe a new class of DNA nanostructures, assembled as diverse libraries of branched DNA wireframes with complex 3D shapes that fold from single stranded genomes. The structure genomes can be amplified and sequenced allowing us to test vast pools of structures in a single pot and amplify those with the best performance transforming nanomedicine from a design to a selection problem. This proposal has three objectives: First, we will refine the tools to assemble DNA structure libraries, perform selection and analyse the sequencing data to identify structures with optimal performance. Secondly, we aim to develop DNA based multivalent antibody alternatives by selecting DNA structures that can pattern multiple aptamers with respect to the epitope distribution on targets. We will target pathogenic proteins of both bacterial and viral origin to create a new route to rapid to develop / deploy binders for diagnostics. We also aim to construct multivalent binders that are specific for nucleosomes with multiple histone modifications. The interaction between DNA nanostructures and cells are controlled by geometry, mechanics and patterns of moieties. In our third objective we will use cell-type specific uptake a selection pressure to produce patterned DNA nanostructures that can deliver gene silencing RNA with specificity to diverse cell types, including cancer cells. By moving nanomedicine from single-pot rational design to an evolutionary approach inspired by how nature produces protein and RNA structures we hope to improve current applications and unlock new applications that can’t be approached with current methods.

Mots-clés : dna nanotechnology,selection,avidity,drug delivery,nanopore sequencing
Projet ERC : ExMilk (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université norvégienne de sciences et de technologie — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1891529.0 €

Innovative preventive strategies are urgently required to halt the rising prevalence of childhood obesity given the inefficacy of current interventions. Mother-to-child transmission of obesity accounts for a large proportion of childhood obesity, more than what can be explained by genes. Nutrition during the first 3 months of life is crucial, with rapid weight gain in this period associated with subsequent obesity. Breastmilk is considered optimal for infant nutrition, but its composition depends on the mother’s metabolic health: the concentrations of some breastmilk compounds linked to infant obesity are associated with maternal body mass index. Maternal lifestyle factors, such as diet, can alter breastmilk composition. Little is, however, known about the effect of exercise during lactation. Exercise is a major regulator of systemic metabolism affecting multiple tissues and organs. In this ambitious, inter-disciplinary project, I will determine how exercise during lactation influences breastmilk composition in women with overweight/obesity and whether exercise-induced changes in breastmilk will influence infant obesity risk. My preliminary data show acute effects of exercise on breastmilk concentrations of adiponectin and lipid metabolites relevant for energy metabolism. In ExMilk, I will determine both acute effects and adaptations after regular exercise on a complex matrix of breastmilk compounds. By linking breastmilk data to comprehensive data for the infants, I will investigate the potential mechanisms underlying the effects of maternal exercise on infant obesity risk, mediated by changes in breastmilk composition. To reach my goals, I will perform gold-standard randomised trials and analyse biological samples from mothers and infants on multi-omics platforms. My experience in metabolomics and exercise intervention trials in reproductive-aged women will enable me to break new ground in understanding how exercise during lactation modifies infant obesity risk.

Mots-clés : childhood obesity,breastmilk,exercise,epigenetic modifications,randomised controlled trial,metabolomics,lipidomics,bioinformatics,inflammation,energy balance
Projet ERC : EnvIronchannel (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Université norvégienne de sciences et de technologie — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Corals form the basis for some of the most diverse marine ecosystems on the planet. Yet these unique ecosystems have suffered tremendous harm due to anthropogenic influences and are predicted to be among the most adversely affected habitats under the foreseen changes in climate. Among these changing conditions are the occurrence and composition of microorganisms in the coral’s habitat, which are affected by changes in temperature and pH. Corals associate with several specific microorganisms, that govern central aspects of their complex lifecycle, such as the recruitment of larvae, a process that ensures health and resilience of coral reefs. While the central role of biofilms is established in tropical coral species, the vast deep-sea cold-water coral species are less well studied. Lophelia Pertusa is a framework-forming cold-water coral with a global distribution and important ecosystem function -however whether larval recruitment depends on biofilm abundance and composition is unknown. It is therefore urgently required to study this fundamental process in cold-water species to assess and mitigate environmental threats to this unique ecosystem. The proposed study will pioneer investigations into the mechanistic basis of cellular and molecular signal recognition in cold-water coral larvae, taking advantage of the specialized settlement behavior and recent advances in sequencing technology. Here, I will use an interdisciplinary approach, at the border of bacterial recognition, development and sensory biology. I will combine the power of single cell patch clamp electrophysiology, behavioral- and molecular analysis to address central questions about sensory biology in cold-water corals and thereby, the project will produce fundamental knowledge about coral habitat selection that are urgently required to understand which impact environmental changes have on this central process.

Mots-clés : chemotactile sensation,receptor proteins,development,signal integration,environment
Projet ERC : MeltingWell (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de Ljubljana — Pays : Slovénie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498750.0 €

Laser-powder bed fusion of metals (PBF-LB/M), also known as selective laser melting (SLM), enables the production of geometrically complex and high-performance metal parts, such as medical implants, nature-inspired structures, and aircraft structural elements. In PBF-LB/M, the laser beam melts metal powder layer after layer, resulting in a solidified metal bulk piece and/or lattice structure. PBF-LB/M supports sustainability through light-weighting, easing supply chain constraints, and enables a high level of product customization. However, the PBF-LB/M process is limited by process condition variations, which often cause defects and quality variations in the printed parts. For example, due to the heat accumulation effect and specific laser toolpath pattern, the depth of melting will vary despite using constant process input parameters such as laser power and scan speed. The inability to predict and control melting process condition variations leads to qualification and certification challenges, hence hindering the wide adoption of this process in industry. The discovery of feasible and effective control methods that can reduce melting process condition variations is critical for the adoption and further advancement of the PBF-LB/M process. The goal of this project is to develop and validate the first solution for controlling the PBF-LB/M process, which takes into account all common sources of process condition variations. The control solution will be based on the PI's recent breakthrough results in predicting process condition variations in PBF-LB/M. The proposed solution is in i) improved coaxial measuring of meltpool depth variations, ii) combining two state-of-the-art data-driven process condition prediction models, and iii) generating predetermined dynamic adjustments of the laser power along the scan path. The proposed control method's validation will determine the next de facto standard control method for PBF-LB/M.

Mots-clés : additive manufacturing control coaxial measurements meltpool depth artificial intelligence
Projet ERC : LIVING_FLUCTUATIONS (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed Matter Physics
Entité participante : Université de Barcelone — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1350259.0 €

Living matter is active: It is driven far from thermodynamic equilibrium by irreversible microscopic processes, such as the action of molecular motors and cell division. This microscopic activity generates nonequilibrium fluctuations, which overwhelm thermal noise and impact biological processes across scales, from intracellular transport to tumour formation. However, unlike in the case of thermal fluctuations, we have no theoretical framework like the fluctuation-dissipation theorem to predict the statistical properties of active fluctuations. Here, I propose to address this knowledge gap by means of theoretical research combined with experimental collaborations organized in two aims. In the first aim, at the subcellular scale, we will predict the spectrum of active noise based on the nonequilibrium binding kinetics of cytoskeletal proteins. To this end, we will coarse-grain a cytoskeletal network model in which detailed balance is explicitly broken at the molecular scale. We will then use the predictions to analyse experimental data and infer features of molecular activity in living cells and in the mitotic spindle. In the second aim, at the tissue scale, we will predict the statistical properties of active pressure fluctuations due to stochastic cell proliferation, which is itself regulated by pressure. We will establish how this mechanical feedback affects the spectrum of the pressure field in a growing tissue. To this end, we will generalize tools from the renormalization group that were originally developed to study nonequilibrium critical phenomena through the Kardar-Parisi-Zhang equation. We will then collaborate with experimentalists to test our predictions by measuring the spectrum of pressure fluctuations in living tissues for the first time. Overall, this research will lay the basis of a stochastic hydrodynamics of living materials and, at the same time, reveal how active fluctuations promote biological functions in cells and tissues.

Mots-clés : active matter,nonequilibrium statistical mechanics,biological physics,active fluctuations,noise,cytoskeleton,tissues