Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : GRACE (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Université technique de Munich — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1652883.75 €

The pandemic is stressful for many. In response to stress, glucocorticoids are released. They play essential roles as endogenous hormones and clinically as drugs. High levels are associated with cardiometabolic disorders and with aging. In contrast, diets like caloric restriction ameliorate metabolic dysfunction and prolong lifespan. These diets, however, also increase glucocorticoids. Now the open question is: What are the molecular and physiological effects of increased hormone levels, and are these diets beneficial because or in spite of elevated glucocorticoids? We recently found that nutrition reprograms glucocorticoid responses independently of the hormone level and that diurnal glucocorticoid action controls rhythmic gene expression to regulate circulating glucose and triglycerides during day and night. I hypothesize that the benefits of caloric restriction are due to higher glucocorticoid amplitudes, and that their study will uncover transcriptional features prolonging healthspan. I propose to functionally distinguish between diet-induced positive and stress-induced negative glucocorticoid responses. GRACE will identify diet-specific, ‘rejuvenating’ transcriptional complexes and target genes, versus detrimental pathways triggered by excess glucocorticoids such as stress. Glucocorticoid receptor targets unique to caloric restriction will be determined via ChIP- and RNA-seq in Aim 1. The functional impact of diurnal glucocorticoid release will be dissected with a constitutively active receptor allele in Aim 2. I propose to map active transcriptional regulomes in caloric restriction, in youth and old age, by ChIP-MS in Aim 3. I postulate that enhanced glucocorticoid activity at the right time of day may boost circadian rhythms and promote longevity. Ultimately, applying omics to study the molecular mechanisms of stress hormones will identify pathways and genes amenable to pharmacological or nutritional intervention for longer, healthier lives.

Mots-clés : glucocorticoids,transcription,genomics,nuclear receptors,caloric restriction,aging,liver
Projet ERC : SPECOLA (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Université de Padoue — Pays : Italie — Rôle : PI
Acronyme de l'entité : UniPd
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1979375.0 €

In recent years technological advances have made it possible to quantify the mRNA expression of large numbers of genes while preserving the spatial context of tissues and cells. These techniques, collectively known as spatial transcriptomics, are important because key biological processes depend on the physical proximity of cells and the spatial organization of tissues. Furthermore, several diseases are characterized by abnormal spatial organization within tissues.  Despite its early age, spatial transcriptomics is rapidly becoming a widely used tool, complementing single-cell RNA-seq as the tool of choice to study gene expression in complex tissues, e.g., in cancer research and neurobiology. In addition to the gene expression measurements and the spatial localization of transcripts, available data include images collected from the samples that can be used to learn cell-level and tissue-level morphological features. The main objective of this proposal is to combine transcriptomics, spatial structure, and morphology data to better inform key spatial transcriptomics analytical steps.  Specifically, we will: - Enhance the comprehension of imaging-based spatial transcriptomics data by a characterization of the statistical properties of the data and a mechanistic modeling of the in situ transcriptional measurements. - Combine imaging and tabular data to better define cell types and states through the use of statistical models and artificial intelligence. - Develop an inferential framework to model the localization of transcripts within and across cells and of cells within and across samples.  Overall, this proposal will combine machine learning and artificial intelligence approaches with rigorous statistical modeling of transcriptomics data in a spatial, sub-cellular context. This will ultimately serve the biomedical community and provide a suite of tools that will help pave the way towards personalized medicine and computer-assisted pathology.

Mots-clés : spatial transcriptomics,single cell,rna sequencing,transcriptomics,rna,spatial statistics,machine learning
Projet ERC : GLAM-Map (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Institute for Bioengineering of Catalonia — Pays : Espagne — Rôle : PI
Acronyme de l'entité : IBEC
Type d'entité : Recherche
Financement ERC de l'entité : 1999008.0 €

Amyloid fibrils form and precipitate in more than 50 incurable human diseases, including Alzheimer’s and Parkinson’s disease. All proteins may be able to form amyloids, at least under certain circumstances. However, aggregation is actually rare as the process of amyloid formation is controlled by a high kinetic barrier: protein sequences have to cross a free energy barrier to nucleate transition states which then seed irreversible fibril formation. Short-lived transition states are extremely challenging to study using biophysical methods. We have recently developed a massively parallel genomics approach to quantify the rate of aggregation of thousands of protein sequences. We also have evidence that, by quantifying the interactions between mutations, we can capture the key interactions between residues in the transition state. Here, we will unleash the potential of this approach by targeting the following aims: 1) Map the impact on amyloid nucleation of all possible mutations in >60 human and functional amyloids - generating reference atlases for clinical variant interpretation 2) Build an energetic and structural model of the transition state of disease-associated amyloids 3) Uncover sequences across the genome that nucleate amyloids in response to environmental stress This project will uncover the rules required to understand, predict and engineer amyloid formation. By identifying the mutations that do and do not lead to amyloid formation, we will reveal which variants accelerate aggregation and cause disease. We will also address one of the most important questions in the field, i.e. identifying the interactions established in the transition states of amyloid nucleation, guiding the development of therapeutic approaches in amyloid diseases, including the worst kinds of dementia. Finally, our results will feed a new generation of models and predictors of protein aggregation to employ for disease variant interpretation and the synthetic design of novel proteins.

Mots-clés : deep mutagenesis,protein aggregation,amyloids,genetic interactions,random sequences,kinetic barrier,dementia,clinical variant interpretation,variants of uncertain significance vus
Projet ERC : INASHI (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Groupe ENSAE-ENSAI — Pays : France — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1746614.0 €

Over the last decades, internet has sped up and increased interactions between employers and workers, but aggregate unemployment does not seem to have been much impacted by this revolution. This could be because information frictions are not a first-order contributor of unemployment, or because current tools and institutions do not enable truthful and effective communication between firms and workers. Employers, who are often on the short side of the market, find it difficult and costly to screen potential employees. INASHI aims to provide theoretical frameworks and new empirical evidence about what the remaining information imperfections on the labour market are, how important they are to aggregate unemployment and unemployment of the most vulnerable segments of the labour market, and what solutions can be put in place to improve the recruiting process. INASHI will combine novel data on how firms search for workers on large online job boards with administrative data on vacancies, and matched employer-employee data. It will also leverage a series of randomised controlled trials to test how the provision of new information to employers, whether about candidates or about features of the market, help them make better hiring decisions, leading ultimately to higher aggregate hiring, and higher-quality matches. Three countries will be studied, Austria, France, and Sweden, so that INASHI will provide evidence valid in a variety of contexts.

Mots-clés : hiring,recruitment,information asymmetries,firms,employers,skills,signals
Projet ERC : ElCapiTex (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : École polytechnique — Pays : France — Rôle : PI
Acronyme de l'entité : X
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1948976.5 €

Fibrous media are ubiquitous in natural and engineered systems, due to their versatility, flexibility and functionality. Nonwovens (i.e. entangled fibrous networks), and especially natural fibre -based materials such as paper or flax mats, are heavily used for a variety of applications, and could be largely developed as a sustainable alternative for plastics. The first limitation of their widespread use is their response to humidity, wetting or drying, which is unavoidable in many applications, and is a key step of their manufacturing processes. The ElCapiTex project aims at characterizing and modelling the specific behaviour and properties of wet non-woven textiles (consolidation, imbibition, mechanical response, deformation) and of their manufacturing processes. In order to characterize the complex interplay between the various physical mechanisms that gives rise to the global properties of textiles (hydrodynamics, capillarity, elasticity, swelling), we will combine different approaches coming from three recent active research areas of fluid-structure interactions: the transport of suspensions of elastic objects, elastocapillarity (i.e. the deformation induced by the capillary forces associated with liquid-air interfaces), and poroelasticity. We will work with a hierarchy of experimental model systems of increasing complexity, in particular by fabricating model nonwoven sheets from gel fibre suspensions. We will further build theoretical models, based on recent statistical approaches used to describe the mechanical properties of dry textiles. Understanding these physical mechanisms is mandatory to develop innovative processes and materials; reconciling fundamental pore-scale mechanisms with network behaviour will allow for the design of tailored fibrous media with specific properties.

Mots-clés : capillarity textiles swelling fibres imbibition drops
Projet ERC : personAlg (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université hébraïque de Jérusalem — Pays : Israël — Rôle : PI
Acronyme de l'entité : HUJI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1741309.0 €

The structure of the current data ecosystem carries grave threats to individuals' privacy and autonomy, facilitates discrimination, promotes social fragmentation, and threatens our ability to govern ourselves. Many of these concerns stem specifically from algorithmic personalization---the practice of providing individuals with personalized opportunities, information, or experiences, on the basis of their personal data and on patterns learned from others' data. Despite the urgency of the algorithmic personalization problem, the mathematical toolkit for studying and auditing for problematic algorithmic personalization remains extremely limited---particularly if we wish to do so in a manner that provides formal privacy guarantees.  The goal of this proposal is to tackle this important problem head-on by establishing the mathematical foundations needed to study algorithmic personalization and to collectively audit personalization systems while guaranteeing privacy to participants. Such tools could transform our collective ability to make the best possible use of our data while ensuring autonomy, privacy, and overall positive social impact.  My vision focuses on three core objectives: (1) building new mathematical concepts and definitions allowing us to articulate, prioritize, and study personalization-based problems, (2) addressing the key algorithmic challenges of privacy-preserving auditing of personalization systems, and (3) integrating deep understanding of the broader legal and ethical context into our approach. For each of these components, the proposal maps out a concrete research strategy, including preliminary steps that indicate the feasibility of this groundbreaking project.

Mots-clés : algorithmic fairness,differential privacy,algorithms and policy
Projet ERC : FiBeGa (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Human Mobility, Environment, and Space
Entité participante : École polytechnique — Pays : France — Rôle : PI
Acronyme de l'entité : X
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998950.0 €

Do only foolish people drown and only compulsive gamblers suffer flood losses? Conventional wisdom is based on flawed underlying assumptions and the EU vision of a disaster- and climate-resilient society cannot be achieved by relying on “behaviour-blind” assessments and policy. Whilst the behaviour of individuals, businesses and public services before, during and after a crisis has a significant impact on damages, recovery and resilience, current assessments fail to include such critical factors because they are hardly understood. Floods and weather hazards are affecting 2bn people and exposure is expected to grow due to climate change. Despite trillions of public funds invested, current flood reduction and planning policies are failing to reduce risks and losses of lives. This is due to a mismatch between the rising application of risk, vulnerability and resilience assessments and the understanding of their empirical validity. The overreaching goal of this proposal is to move from “behaviour-blind” to “behaviour-aware” assessments, indicators and policies to save lives and public money. Lifting the current barriers to predicting and simulating risk perception and behaviour will create forefront knowledge and open new horizons. Social and technological changes have widened the gaps in our knowledge making new empirical research essential to refine or replace existing theories. This project will provide four demonstrators representative of the European and Mediterranean context, graded in size, wealth and exposure to reach general considerations: Paris, Barcelona, Bucharest and Algiers. It is aiming at cross-validation on floods and transferability to other emergencies (technological disasters, epidemics, terrorism, etc). It will launch a new line of research by providing “behaviour-aware” participatory assessments and indicators, spatially-explicit interactive short- and long-term simulation tools enabling decision-makers to refine their strategies and policies.

Mots-clés : perception behaviour resilience policy data science economy geography political science psychology sociology risk management
Projet ERC : PROSPECT (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : École polytechnique — Pays : France — Rôle : PI
Acronyme de l'entité : X
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1644025.0 €

Many important economic decisions are made after individuals have had opportunities to acquire information. For example, investors can do research about the fundamentals of companies to estimate their future stock prices; consumers can read reviews before making purchase decisions; managers can experiment with different organizational structures before settling on one. As information acquisition is costly, decision-makers must evaluate its benefit ex ante by engaging in prospective learning, that is, by trying to predict the amount of information they will receive.  PROSPECT aims to investigate experimentally whether individuals are able to correctly assess the benefits of future information acquisition, and to use this information proactively when making dynamic choices. The main objective is to uncover some potential fundamental biases in dynamic decision-making, such as a tendency to acquire too little information and to under-experiment relative to the rational benchmark. In Part 1, I aim to identify biases in prospective learning. The key question is whether individuals are able to correctly forecast the amount of information that a given real-life event reveals. Part 1a will study finance professionals’ ability to prospectively learn from market prices, and Part 1b will investigate whether the general population is able to extract information from past economic events to better predict future economic events.  Part 2 studies how individuals take prospective considerations into account when solving dynamic decision problems. In Parts 2a and 2b, I will characterize whether they experiment as much as economic models predict they should, and study two candidate micro-foundations for insufficient experimentation. Part 2c revisits an old idea in behavioral economics, according to which prospective thinking is key to achieving self-control.

Mots-clés : beliefs experimentation information acquisition dynamic choice
Projet ERC : GBM_Cellular_States (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Institut Weizmann — Pays : Israël — Rôle : PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1962500.0 €

Cellular heterogeneity is a fundamental property of glioblastoma (GBM) tumors and presents a major barrier for therapeutics. During the past six years we characterized this heterogeneity in glioblastoma, and in other types of glioma, using single cell RNA-seq (scRNA-seq). We found consistent patterns of heterogeneity across patients, such that each tumor harbors multiple subpopulations of cells that resemble neurodevelopmental cell types. The consistency of these cellular states across patients highlights their potential clinical significance. Yet, our understanding of how these common states are regulated and of how distinct states respond, individually or in combinations, to potential treatments, remain poorly understood. Furthermore, it is unclear if additional states of clinical significance remain to be uncovered. To address these challenges, we will perform extensive studies of GBM patient samples, animal models and gliomasphere culture models. First, we will dissect the regulation of the common cellular states (Aim 1). Single cell ATAC-seq of patient samples will be used to infer transcriptional regulators, Spatial Transcriptomics will be used to infer environmental interactions, and resulting predictions will be tested further in established model systems. Second, we will search for novel cellular states, including rare states or those specifically associated with invasion to the brain parenchyma (Aim 2). Third, we will examine strategies for treatment of heterogenous tumors that are composed of multiple states (Aim 3). We will screen for state-specific drug sensitivities, as well as for drugs that induce state transitions, and develop rational combinations to eliminate multiple co-existing states, while considering interactions among states. Taken together, these studies will considerably expand our understanding of cancer heterogeneity and develop strategies to target heterogeneous tumors.

Mots-clés : glioma single cell rna seq
Projet ERC : HAND (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université technique de Vienne — Pays : Autriche — Rôle : PI
Acronyme de l'entité : TU Wien
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1993224.0 €

Chirality plays a major role in several areas due to the different behavior of each enantiomeric form of a compound, critical in the pharmaceutical industry. Obtaining pure enantiomers is one of the most difficult challenges, in which homogeneous asymmetric catalysis has achieved significant steps. Now it is time to undertake the challenge by heterogeneous enantioselective catalysis, implying great advantages in terms of sustainability, and offers further opportunities for in-depth understanding of mechanisms at the molecular level, relevant in multidisciplinary fields. However, successful design of such processes requires understanding and control of all relevant steps, which requires well-defined catalysts designed at atomic level. A new class of atomically precise nanomaterials that offers ample opportunities to explore chirality at the fundamental level, are the monolayer protected metal nanoclusters, which exhibit unexpected catalytic and intrinsically chiral properties. The HAND project aims to tackle actual challenges in heterogeneous asymmetric catalysis and achieve enantioselectivity with chiral nanoclusters on surfaces designed at atomic level. After creating chiral clusters active in homogeneous asymmetric reactions, we will control their immobilization on the support surface and their chiral properties. Such atomically precise chiral surfaces will allow us to overcome sensitivity barriers of available chiral spectroscopic techniques, improving studies of chirality at surfaces. Finally, having a well-defined chiral surface, asymmetric/enantioselective model reactions will be explored, aiming to obtain pure enantiomers. Each process step by itself represents a novel pioneering work in the field of nanoclusters and asymmetric catalysis, so far mostly unexplored. The fabrication and understanding of such a new class of chiral surfaces at the atomic level represent a breakthrough in knowledge relevant for materials science, nanotechnology and medicine.

Mots-clés : chirality,gold nanoclusters,ligand exchange,spectroscopy,asymmetric hydrogenation reaction