Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : 3DTunneling (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Université Johann Wolfgang Goethe de Francfort-sur-le-Main — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1836780.0 €

Tunneling is a non-resonant, quantum mechanical process without any classical analog. The electric field of a strong laser pulse can bend atomic and molecular potentials such that an electron can be liberated via tunneling. This allows for probing properties of atomic and molecular orbitals with subnanometer and attosecond resolution (like a tunneling microscope’s tip probes properties of the investigated surface). So far, the electric field vector is restricted to a one-dimensional line (1D, e.g. linearly polarized light) or a two-dimensional plane (2D, e.g. circularly polarized light). Since tunneling acts like a filter to the same 1D or 2D subspace in position space, this limits the sensitivity to the 3D structure of the probed orbital. I propose to build an experimental setup that can synthesize 3-dimensional (3D) light fields with peak intensities of up to 1015 W/cm2. 3D light fields will significantly increase the sensitivity of strong field tunneling to the 3D properties of the bound electronic wave function. Further, non-adiabatic dynamics during tunneling and subsequent acceleration, recollision, or recapture of the electronic wave packet will be driven by the time-dependent 3D field as well. This will e.g. allow for the creation of chiral electron distributions in atoms (i.e. chiral atoms), selectively tunnel ionize one enantiomer of a racemic mixture of chiral molecules and enable a new type of pump-probe experiments. The capability to generate 3D light fields will be matched with a 3D detection system, which measures 3D electron momenta in coincidence with ionic fragments. My team and I will use this novel 3D-light-3D-detection-platform to investigate tunnel ionization from atoms, diatomic molecules, and chiral molecules. I anticipate that the proposed experiments will give rise to a new class of experiments on light-matter interaction and provide ground-breaking insight regarding the quantum mechanical process of tunneling itself.

Mots-clés : light matter interaction,strong field tunnel ionization,time dependent three dimensional laser electric fields,femtosecond laser pulses,momentum spectroscopy,coltrims reactions microscopes,chirality
Projet ERC : BAE (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : Université d'Helsinki — Pays : Finlande — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 87100.0 €

Aerosol formation and growth mechanisms need to be better understood to improve air quality and weather prediction models, and reduce uncertainty of radiative forcing in climate change projections. Globally, half of the aerosol population is formed via gas-to-particle conversion and the fraction exceeds 90% in high latitudes. In many locations, the initial molecular cluster forms from sulphuric acid and ammonia or dimethylamine. Growth to an aerosol particle is often explained by the condensation of sulphuric acid, methanesulfonic acid and highly oxygenated organic compounds. While the roles of strong acids and organic compounds and their oxidation channels are quantified in laboratory and field studies, cation detection and neutral atmospheric base measurements are notably under-represented. An important innovation of this project will be the direct measurement of cations and neutral base molecules and clusters based on mass spectrometry. Ammonia, a base predominantly emitted by agriculture, is a key air pollutant in the formation of fine particulate matter (PM2.5). In western Europe, up to half of PM2.5 is attributed to ammonia pollution because of its ability to form aerosols in reactions with common atmospheric acids. Current atmospheric models do not include amines, which can form aerosol particles at a 1000-times faster rate than ammonia. To uncover the composition and level of toxicity of PM2.5, as well as the scattering and absorption of sunlight by aerosol particles, it is critical to understand the atmospheric chemistry and molecular pathways that control their formation and growth. The project will focus on the role of base molecules in the formation of new particles and their fate in the atmosphere and is led by an established PI with a demonstrated history in ground breaking nanoaerosol and precursor studies. It will underpin the modelling of atmospheric aerosol processes, which are subject to major precursor emission changes in Europe and beyond.

Mots-clés : ammonia,mass spectrometry,air pollution,base,new particle formation,aerosol
Projet ERC : SOC-MISC (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Human Mobility, Environment, and Space
Entité participante : Université d'Helsinki — Pays : Finlande — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 86225.0 €

One in four women experience a miscarriage. Loss of pregnancy may affect fertility intentions and lead to adverse mental and physical health. Yet, we know little about how social inequalities affect the risk of miscarriage; how miscarriages may exacerbate existing social inequalities in population health; or how context shapes these experiences. One reason for this is poor quality of data, as miscarriages are often either underreported in surveys or only included in health registers if they require hospital care. Moreover, to date, sexual and reproductive health has often been ignored in life course epidemiology.  This proposal goes beyond the state-of-the-art by being the first comprehensive study of the patterns of social inequality in miscarriage and its outcomes. It reaches this goal by assessing the patterns of miscarriage underreporting in surveys before obtaining its estimates. It will make ground-breaking contributions by:  1) Analysing underreporting patterns of miscarriage and using this in further analyses to obtain more reliable results than before. 2) Showing how individual and family-level social inequalities affect miscarriage risk over the life course. 3) Establishing how mental and physical health consequences of miscarriage depend on one’s social background and may widen social inequalities in health. 4) Uncovering the role of national and sub-national context in social inequalities in miscarriage.  Unlike many previous studies based on small and outdated samples, I use longitudinal population registers and large representative surveys in Finland, France and the UK that are exceptionally rich in miscarriage, socioeconomic, other reproductive and health data, and can be triangulated to obtain more reliable results.  The project will lead to a significantly better understanding of a common reproductive experience affecting mental and physical wellbeing, and can help policy makers improve reproductive and population health.

Mots-clés : miscarriage,sexual and reproductive health,social demography,sociology,social epidemiology,pregnancy,social inequalities in health
Projet ERC : Seq2Func-NC (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Institut Francis Crick — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : The Crick
Type d'entité : Recherche
Financement ERC de l'entité : 1499511.0 €

Deciphering how genetic variants lead to disease can advance precision diagnostics and mechanistically informed therapies. Yet, our ability to link variants in the human genome’s vast noncoding regions to phenotypic consequences is highly limited. This stems largely from a lack of experimental evidence on individual variants’ functional effects. Here, we propose to develop and deploy a suite of new genome editing methods to generate functional data for noncoding variants at unprecedented scale.  First, we will leverage a prime editing screening platform we have recently established to systematically ask how intronic variants and 5’-untranslated region (5’UTR) variants lead to loss of function (LoF) across dozens of human disease genes. Second, we will interrogate relationships between regulatory sequence variants, transcription factor binding sites (TFBSs), and genomic contexts across diverse cell types using novel methods to link variants to effects on messenger RNA (mRNA) levels. Third, we will uncover new noncoding variants underlying disease by combining variant effect prediction with large-scale functional assessment.  Collectively, this work will establish new technologies to experimentally characterize noncoding variants, delineate sequence-function relationships from 100,000s of variant effect measurements, and substantially advance our ability to predict, identify, and engineer noncoding variants of functional importance.

Mots-clés : functional genomics,human genetics,multiplexed assays of variant effect maves,rare disease,cancer genetics,noncoding variants,splicing,gene regulation,sequence function models,prime editing
Projet ERC : SafetyBounds (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Recent breakthroughs in machine learning (ML) have brought about a transformative impact on decision-making, autonomous systems, medical diagnosis, and creation of new scientific knowledge. However, this progress has a major drawback: modern predictive systems are extremely complex and hard to interpret, a problem known as the ’black-box effect’. The opaque nature of modern ML models, trained on increasingly diverse, incomplete, and noisy data, and later deployed in varying environments, hinders our ability to comprehend what drives inaccurate predictions, biased outcomes, and test time failures. Perhaps the most pressing question of our times is this: can we trust the predictions for future unseen instances obtained by black-box systems? The lack of practical guarantees on the limits of predictive performance poses a significant obstacle to deploying ML in applications that affect people's lives, opportunities, and science.  My overarching goal is to put precise, interpretable, and robust error bounds on ML predictions, communicating rigorously what can be honestly inferred from data. I call for the development of protective ecosystems that can be seamlessly plugged into any ML model to monitor and guarantee its safety.  This proposal introduces a unique interplay between statistics--the grammar of science--and ML--the art of learning from experience. Leveraging my expertise in both domains, I will show how statistical methodologies such as conformal prediction and test-martingales can empower ML, and how recent breakthroughs in ML such as semi-supervised learning and domain adaptation technologies can empower statistics. I will tackle challenges rooted in real-world problems concerning (1) availability and (2) quality of training data, as well as (3) test-time drifting data. A successful outcome would not only lead to a timely and rigorous way toward safe ML, but may also significantly reform the way we develop, deploy, and interact with learning systems.

Mots-clés : machine learning,statistical testing,uncertainty quantification,conformal prediction,safe machine learning,reliable machine learning
Projet ERC : ExtractABact (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and I mmunotherapy
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1997500.0 €

Over the past two decades, gut bacteria have emerged as major regulators of human health. The focus in the field thus far has been on bacterial taxonomy, with their spatial organization and functionality largely overlooked. Crohn’s disease (CD) vividly portrays this spatiofunctional dimension, as it features patches of gut inflammation (skip lesions) surrounded by uninflamed regions—in the same host—with a clear demarcation but unknown cause. Our preliminary data demonstrate host-microbe functional feedback loops in which bacterial strains can adapt and modify their immunomodulatory functions in response to the host. Moreover, we find functional alterations in gut bacteria of IBD patients. Thus, we hypothesize that bacterial spatio-functionality can be largely affected by host physiology, and, in turn, modulate the pathophysiological state, creating a functional feedback loop. We propose to study bacterial spatiofunctional plasticity and mechanisms of host-microbe interactions in CD, and their potential causal effects on inflammation, combining microbiology, immunology and systems biology approaches. We intend to focus on three independent yet complementary aims: (1) Characterize host-microbe spatio-functional alterations in skip lesions and assess their potential causal effects on inflammation; (2) Decipher the functional and molecular mechanisms of host-microbe feedback loops in healthy and inflamed intestines; and (3) Develop a toolbox for high-resolution functional analyses of gut bacteria directly in their natural environments. This study will address, for the first time, bacterial functional plasticity in response to host inflammation, unveiling the phenomena, its mechanism of action, and potential causal effects on gut inflammation. Such understanding can shift our perception on microbiota-host interactions, may explain contradictions in the field, point to novel contributing factors to CD and related disorders, and guide future translational studies.

Mots-clés : microbiome,inflamatory bowel disease,crohn s disease,bacterial functional plasticity,feed back loop interaction,phase variation
Projet ERC : AngioArchitects (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Université de Coimbra — Pays : Portugal — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2098617.0 €

Brain capillaries are the lifelines of the brain, supplying essential nutrients and oxygen and safeguarding its delicate environment. Therefore, proper establishment of this hierarchically branched circuitry is crucial for brain growth and function throughout life. Orchestrating the creation of a functional vascular network requires coordinated signalling among endothelial cells, the vessels´ building blocks, with adjacent cells. Despite its importance, the exact spatiotemporal events, and molecular bases of the capillary network construction during postnatal development remain a mystery. Elucidating this dynamic process within the intact developing mammalian brain in both space and time is a challenging but a necessary step to unveil this fascinating biological knowledge gap. Towards this goal, I recently established a longitudinal live imaging approach to capture brain development processes with minimal perturbation. Based on preliminary work, I postulate that endothelial tip cells instruct microglia, the brain resident immune cells, to serve as pathfinders and guide them to their target vessel. To address this original and innovative hypothesis, ANGIOARCHITECTS proposes to employ a powerful multi-disciplinary combination of mouse genetics, two-photon live imaging, omics profiling, high-resolution microscopy mapping, and computational modelling tools to reveal the developmental principles of building the capillary network, focusing on communications between endothelial tip cells and microglia. This pioneering project will be the first to offer unprecedented imaging of vascular-immune interactions during angioarchitecture formation in the neonatal period, when the brain is highly susceptible to insults and injuries. ANGIOARCHITECTS will not only advance the frontiers of vascular research but also holds immense potential for driving future investigations in neonatal healthcare and clinical therapies targeting cerebrovascular disorders.

Mots-clés : two photon microscopy,endothelial microglia crosstalk,brain capillary network,neonatal brain,live imaging,cerebrovascular branching pattern,angioarchitecture
Projet ERC : FIREMOD (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de Londres — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : UoL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1480466.0 €

Fire has long been a ubiquitous and essential part of the global environment, as many ecosystems and societal life fundamentally depend on fire. Despite this, we still lack a fundamental theory of fire spread, which becomes crucial in a changing world if we want to understand and predict the occurrence of uncontrolled fires. Uncontrolled fires are a global phenomena that are becoming commonplace as changes in moisture and local temperature driven by climate change affect local fuel properties and ecosystems. As we construct more housing and industry in areas that were previously wildlands, the Wildland-Urban Interface becomes more critical as wildfires now affect infrastructure and urban systems.  The societal, scientific, and engineering problem of uncontrolled fires is a complex one: it requires the harmonisation of both engineering and environmental science methods, including combustion engineering, real time modelling, data assimilation and management, and the development of techniques that can adequately support the needs of fire management. The aim of this proposal is ambitious, but essential to understand and predict the occurrence of uncontrolled fires: We need a fundamental physical model to understand the process of fire spread. It needs to be validated, and it needs to work for all conditions and fuel types. We will develop this physical model focusing on three different methods, in parallel: i) Study fire across temporal and spatial scales to understand changing fire regimes, including vegetation dynamics. ii) Understanding of fire on multiple scales will help with scaling up from small-scale fine mesh models to much larger grid sizes. iii) Integrate the effect of smouldering combustion into modelling of fire spread. The scientific outcomes of our work will ensure that there is a fundamental step-change in the approach of modelling wildfire ignition and spread, with the proposed methodology and tools then widely available for scientists to adapt.

Mots-clés : fire dynamics,multiphysics modelling,wildland urban interface
Projet ERC : MicroMetSCAN (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université de Londres — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : UoL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998456.0 €

Over 90% of cancer-related deaths are caused by metastases. A major obstacle for accurate patient stratification, development of new treatments against metastases and thorough biological understanding is our inability to detect early-stage micrometastases (µMets). The liver is one of the first and most common sites for metastases, particularly in gastrointestinal tract tumours. Thus, early detection of liver metastases is an urgent need in cancer diagnosis for many patients. Present image-based diagnostic methods, including state-of-the-art Magnetic Resonance Imaging (MRI), cannot detect µMets due to major limitations in current image contrast and resolution, as well as a lack of understanding of liver tissue changes during the metastatic process.  MicroMetSCAN proposes a paradigm-shifting MRI approach based on highly promising preliminary results that leverages recent progress in MRI acquisition, denoising and contrast generation, to reach the breakthrough of exquisite sensitivity and specificity required to detect and characterise μMets in the liver and provide new insights about metastases-related tissue microenvironment dynamics. To achieve its overarching goal, my proposal consists of four objectives: 1) developing new ultra-high resolution MRI methods targeting robust µMets detection, 2) tailoring the specificity of contrasts towards μMet environments, 3) unravelling the transformations from µMets to full metastases in animal models, yielding critical insights into tumour growth patterns, and 4) translating the new MRI approach to the clinic in a prospective clinical study. MicroMetSCAN will significantly advance the state-of-the-art in cancer imaging, to enable precision diagnosis and treatment planning, with wide-reaching applicability, especially benefitting small lesion detection. Furthermore, it will unveil important biological insights on the progression of metastasis, guiding future therapeutic strategies for better prognosis and outcomes.

Mots-clés : cancer imaging,liver metastases,magnetic resonance imaging,mouse models of liver metastases,tissue microstructure,quantitative mri,colorectal cancer,pancreatic cancer
Projet ERC : PGTI (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université de Rome « Tor Vergata » — Pays : Italie — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 50000.0 €

Particle Therapy (PT) is potentially the most conformal and selective form of radiotherapy, but its clinical outcome is still limited, mainly because of the numerous sources of uncertainties affecting both treatment planning and delivery. The objective technical complexity of predicting and verifying the ion path in the patient has led to conservative treatments that, in order to increase safety, sacrifice efficacy. Having the full control of the dose gradient within the patient in real time would allow to fully exploit the ballistic advantage of PT. The healthy-tissue sparing effect can be enormous, further encouraging the use of PT for paediatric malignancies. Alternatively, the target dose could be increased to achieve better tumour control, and dose escalation procedures could be envisaged to treat radio-resistant tumours. With the aim of increasing both safety and efficacy, I propose a new medical-imaging modality to monitor PT treatments in real-time. It exploits the signal of secondary prompt gamma-rays emitted from nuclear interactions in the patients to recover information on ion range, tissue density and dose. I refer to this technique as Prompt Gamma Time Imaging (PGTI). An original reconstruction algorithm and a dedicated detector will be developed to prove the clinical advantages of PGTI, and bring this technique at the doorsteps of its clinical application. I will develop models to correlate the images provided by PGTI to real-time dose distributions, in order to enable the use of this technique for adaptive dosimetry. PGTI will be also explored as a potential approach to proton tomography. For the first time, it would be possible to control the uncertainties affecting both treatment planning and treatment delivery with a unique device. PGTI may be the missing step towards the birth of image-guided particle therapy.

Mots-clés : gamma ray detection