Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : COMMUNITY (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Université de Leyde — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3343206.0 €

As Nature's medicine makers, Streptomyces bacteria produce a plethora of natural products, which we harness for clinical, biotechnological and agricultural applications, including 70% of the antibiotics. Streptomycetes still have a vast reservoir of unexplored biosynthetic potential, but many biosynthetic gene clusters (BGCs) are not expressed in the laboratory. To bring the chemical dark matter to the light, we need to discover the keys to unlock the expression of cryptic BGCs. I aim to add an entirely new dimension to genome mining, namely via understanding and exploitation of the regulatory networks that control natural product biosynthesis in Actinobacteria. My team discovered the concept of antibiotic production on demand, showing that plant hormones activate antimicrobials. Predicting when instead of what BGCs produce will allow clustering of BGCs based on their response to ecological signals. This can serve as a beacon for prioritising BGCs, and aid in the discovery of new biosynthetic pathways. I will tackle three major challenges: [1] The systems biology challenge is to elucidate the regulatory circuitry of streptomycetes and to reliably predict how BGCs are controlled [2] The metabolic challenge is to unwire the networks that tie carbon metabolism to antibiotic production, to bridge the gap from the complex polysaccharides in nature to the defined carbon sources of the laboratory. [3] The ecological challenge is to unravel the mechanisms and molecules via which plants invoke the power of Streptomyces' bioactive molecules to obtain protection against infections and pests, aimed at biological disease-suppression. COMMUNITY is an open science project that will help to elucidate whether the yet unexplored BGCs will deliver a paradigm shift in drug discovery, for application in agriculture and human health. Deliverables are innovative systems biology tools and detailed transcription factor networks, elicitors for drug screening and disease-suppressive microbes.
Projet ERC : TURNING VIOLENT (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université de Leyde — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499744.0 €

Although violent police-civilian and civilian-civilian encounters constitute a tiny sliver of the social interactions that take place each day, their consequences can be far-reaching. Images of assailants committing ‘bestial’ violence against vulnerable victims arouse public fear and indignation, while the excessive use of force by police undermines public trust, cooperation and the rule of law in democratic societies. Depicting such violence as ‘senseless’ moreover obscures the fact that violent action has meaning to the assailants. Based on the granular analysis of 126 publicly available phone camera recordings of real-life interpersonal conflicts in Paris, London and Berlin, the research program will advance an empirically grounded theory that explains how non-violent altercations between strangers in public space develop into encounters in which physical violence is the dominant mode of interacting, especially one-sided violence against vulnerable/subdued victims. The program breaks new scientific ground by: (1) showing that episodes of interpersonal conflict can be causally explained by understanding how the antagonists and their audiences (co-present peers, colleague police officers, unknown bystanders) structure their interactions in culturally meaningful ways; (2) analysing how slurs, insults, and provocations pertaining to race, ethnicity, class, gender and age as well as differences in policing practices influenced the trajectories of civilian-civilian and police-civilian conflicts; (3) developing the methods of ethnomethodological/conversation analysis to transcribe and analyse in meticulous detail how sequences of bodily actions and verbal utterances become turning points towards the beginning, transformation, and ending of violence; and (4) advancing the scientific use of now ubiquitous phone camera data.

Mots-clés : ethnomethodology multimodal analysis video analysis violence in public urban space interpersonal conflict
Projet ERC : ACME (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Université de Gand — Pays : Belgique — Rôle : PI
Acronyme de l'entité : UGent
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2445063.0 €

I propose a cutting-edge and transformative paradigm for statistical modelling that is crucial to enhance the quality of data analyses. Leveraging my expertise in causal inference and semiparametric statistics, I will establish the fundamental principles of a comprehensive estimation theory, which maps model parameters onto generic, interpretable, model-free estimands (e.g., association or effect measures) with favourable efficiency bound, and harnesses the power of debiased (statistical/machine) learning techniques to estimate these. My core objective is to develop a flexible and accessible data modelling framework, called ‘assumption-lean modelling’. This framework will deliver minimal bias and maximal interpretability, even in the presence of model misspecification, along with honest confidence bounds that account for model uncertainty.  Debiased learning is at the core of this research. While gaining popularity, a rigorous scientific optimality theory is lacking. I shall draw on my expertise in (bias-reduced) double robust estimation to develop optimal debiased learning estimators. These utilize learners that optimize strategically chosen loss functions to achieve low variance and high stability, along with confidence intervals that are valid under weak conditions on the learners.  I will connect to timely, exciting developments in statistics, such as debiased learning of function-valued parameters and the construction of confidence bounds for such parameters. I will offer novel avenues into these problems by incorporating the assumption-lean modelling principles and connecting to real-world needs.  I will develop assumption-lean modelling strategies to tackle significant challenges in causal modelling, including target trial emulation, causal mediation analysis, and statistical modelling of dependent outcomes. I will deliver methods with potential impact on all empirical sciences, as well as on the foundations of the discipline of statistical modelling.

Mots-clés : debiased statistical learning causal inference statistical modelling nonparametric inference
Projet ERC : e-CRACKER (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de Gand — Pays : Belgique — Rôle : PI
Acronyme de l'entité : UGent
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2496000.0 €

Power to heat (P2H) is expected to be the first type of electrification that will drastically transform the chemical industry. This holds in particular for producing its major building blocks: the 300 Mt/yr light olefins via steam cracking at more than 800°C. e-CRACKER will implement P2H by so-called shockwave heating, enabling an increase in temperature to >1000°C in 10 ms, an order of magnitude faster than the current furnace-based technology in a revolutionary High-Mach reactor. When combined with insight in the pressure-dependence of the cracking chemistry this will allow to avoid undesired side reactions and to increase olefin yields of ethane and plastic waste derived naphtha cracking by 10 wt.% compared to yield gains of 0.1 wt.%, at best, when applying alternative P2H such as resistive heating. e-CRACKER will:  1. generate new fundamental understanding of shock wave heating and kinetics under sub- and supersonic conditions;  2. demonstrate the practical applicability of an open-source, high fidelity Multiscale Modeling platform in combination with finite rate chemistry for turbulent reacting and rotating flows;  3. develop a compact, energy-efficient, electrified High-Mach reactor generating shockwaves and minimizing side products by avoiding back-mixing;  4. pave the way to avoid more than 200 Mt CO2/yr emissions with a scalable, flexible, step-by-step implementable technology driven by renewable electricity. Starting from fundamental local and global (non-)reactive data collection (WP1), and a high-fidelity open source Multiscale Modeling framework (WP2) novel 3D reactors will be designed in silico using advanced optimization (WP3). The power of the approach will be demonstrated in a 3D-printed High-Mach reactor, which, by operating under unconventional cracking conditions (lower pressures and faster heating) achieves yield increases of more than 10 wt% (WP4), contributing in a decisive way to the transition of the chemical industry.

Mots-clés : steam cracking,pyrolysis,olefin production,plastic waste,electrification,co2 reduction
Projet ERC : MATRACs (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université de Gand — Pays : Belgique — Rôle : PI
Acronyme de l'entité : UGent
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Cancer immunotherapy represents a groundbreaking advancement in oncology, leveraging the immune system to combat malignancies with enhanced specificity and reduced systemic toxicity compared to traditional therapies. However, despite significant progress, current immunotherapies face limitations, particularly in targCancer immunotherapy represents a groundbreaking advancement in oncology, leveraging the immune system to combat malignancies with enhanced specificity and reduced systemic toxicity compared to traditional therapies. However, despite significant progress, current immunotherapies face limitations, particularly in targeting tumors without identifiable antigenic signatures and avoiding immune-related adverse events. In my ERC project I will explore an innovative approach utilizing Marker-Agnostic TumoR-Anchoring Chimera (MATRAC) technology, designed to harness the universal acidic microenvironment of solid tumors for targeted delivery of immune-modulating therapies. MATRACs are engineered recombinant fusion proteins that combine a therapeutic payload with a pH-responsive anchoring mechanism, ensuring selective activation in acidic tumor sites while minimizing off-target effects. Preliminary studies demonstrate MATRACs' enhanced tumor localization, pH-selective membrane binding, and potent immune-stimulating effects, laying the groundwork for their development as a versatile platform for innate immune-mediated cytotoxicity, cytokine therapy, and T-cell engagement in various cancer models. This research aims to optimize MATRACs' therapeutic efficacy and safety, with comprehensive preclinical evaluations including pharmacokinetics, immunogenicity, and toxicity assessments. By addressing critical gaps in current cancer immunotherapy, MATRAC technology holds the potential to expand treatment options for a broader range of patients, particularly those with antigenically challenging tumors, while improving the precision and effectiveness of immune-based therapies.

Mots-clés : tumor targeting,fusion proteins,tumor acidosis,immunotherapy
Projet ERC : TIME (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université de Gand — Pays : Belgique — Rôle : PI
Acronyme de l'entité : UGent
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2498875.0 €

This proposal aims to get track of time for all events taking place when guest molecules are sent over a crystal particle of a nanoporous material, as is occurring during catalysis, separation, sensing.  The observation: When a feed of molecules is sent over a crystalline nanoporous framework following events take place: first the molecules need to enter the crystal, then travel through the material to find interesting sites where they adsorb/desorb or react and eventually products leave the crystal. All these events are characterized by vastly different time- and length scales varying from the picosecond to the second/hours and the nano- to micrometre. Length and time phenomena are entangled - the dynamics is altered by modifications at the length scale - leading to spatiotemporal phenomena.  The gap of knowledge: We have insufficient knowledge on characteristic time scales of all these events and consequently can not use the time axis as a control parameter to steer the functionality of nanoporous materials.  The hypothesis: By coupling Machine Learning Potentials, reaction path discovery with advanced kinetic theories, it is possible to obtain kinetic and time information for all events taking place at the crystal particle from the nano- to the mesoscale with quantum mechanical accuracy. This contrasts sharply with current practice where only local events at the nanoscale are modelled with interatomic forces having quantum accuracy.  The grand challenge: Building consistent kinetics models for events – reaction, diffusion, adsorption – with disparate time scales, thereby reconciling the dynamics of local and non-local events.  The mission: Setting up integrated reaction diffusion models based on underlying characteristic times/kinetics obtained with quantum accuracy.  The outcome: Spatiotemporal control over nanoporous materials used in catalysis, separation, sorption, sensing.  It’s TIME to obtain a time perspective on functional nanoporous materials.

Mots-clés : heterogeneous catalysis,diffusion,zeolites,machine learning potentials,molecular dynamics,kinetics
Projet ERC : DOPA-Kiss (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University of Córdoba — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UCO
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499995.0 €

Child obesity is a worrying condition, affecting 20% adolescents. Among its comorbidities, early obesity is linked to disturbed puberty, which is more evident in girls, but bound to adverse health outcomes in both sexes. Yet, how our brain decodes nutritional info to finely control puberty remains unsolved. Genetic data suggest obesity is largely an hypothalamic disease. Puberty is also hypothalamic-driven and governed by complex neuronal circuits. Among them, Kiss1 neurons have emerged as key elements in the brain control of puberty and its metabolic regulation, likely in cooperation with other central signaling systems, as POMC/melanocortins. Yet, the mechanisms whereby early obesity impacts on different Kiss1 neuronal populations and pubertal timing are ill-defined. The global aim of DOPA-Kiss is to unveil the brain basis of obesity-induced pubertal alterations in both sexes, with a major focus on Kiss1 neurons. An integral research plan will be implemented based on (i) Multidimensional integration of omics data, including hypothalamic global and spatial metabolomics, as well as transcriptomic and epigenomic profiling of Kiss1 neuronal subpopulations during pubertal maturation in conditions of obesity; (ii) Analysis of the molecular mechanisms for nutrient & metabolic sensing at the hypothalamus, and particularly in Kiss1 neurons; and (iii) Functional genomic dissection of key metabolic pathways in Kiss1 neurons using Cre/LoxP- & CRISPR-based genome editing in vivo. Sex differences in the impact of early obesity on subsets of Kiss1 neurons and puberty, and, when relevant, parallel changes in POMC neurons, will be explored. Putative human correlates of our experimental data will be scrutinized using public databases. DOPA-Kiss will not only surface unsolved aspects of the metabolic control of puberty, but will reveal also groundbreaking info on pathophysiological mechanisms and putative targets of intervention in conditions of altered puberty due to early obesity.

Mots-clés : puberty,child obesity,kisspeptins,kiss1 neurons,hypothalamus,lipid and nutrient sensing
Projet ERC : TARGETNMDs (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
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 : 2495250.0 €

Hematopoietic stem cell (HSC) gene therapy based on self-inactivating integrating vectors has proven unprecedented therapeutic potential in inherited neurometabolic diseases (NMDs). However, phenotypic effects are delayed after treatment likely due to the slow replacement of resident microglia by transplant-derived cells that hampers the broad application of this approach. Moreover, unregulated gene expression driven by the in-use promoters could in the long term cause unwanted effects. Finally, recent events suggest that the treated patients might be at risk of developing side effects related to vector integration. Therefore, novel strategies anticipating therapeutic benefit and reducing these potential safety concerns are desirable to address the still unmet medical need of NMD patients. Our long-term goal is to develop a novel, broadly effective and safe treatment platform for NMDs based on a newly empowered HSC targeted gene addition approach at a newly identified microglia locus. Our central hypothesis is that correcting the gene defect by targeted addition at this locus in HSCs of patients affected by NMDs could generate in a timely manner a microglia-like progeny endowed with unprecedented therapeutic potential. Indeed, based on our recent findings, gene editing and targeted integration at this locus are expected to uniquely favor the timely engraftment and efficient, rapid myeloid/microglia differentiation of transplanted, edited HSCs in the recipients’ brain, and to induce robust and regulated expression of the integrated transcript in transplant-derived microglia-like cells. Based on this hypothesis, we aim at developing a targeted gene addition approach at the newly selected microglia locus for correcting the underlying genetic defect in HSCs and obtaining proof of concept of its therapeutic potential in NMDs animal models. Thus, the proposed work could generate the basis for a novel treatment platform for these devastating conditions.

Mots-clés : hematopoietic stem and progenitor cells,transplantation,microglia,gene therapy,inherited neurometabolic diseases of childhood,lysosomal storage disorders
Projet ERC : ReprOids (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
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 : 1664792.5 €

Understanding the neurodevelopmental causes and mechanisms of the brain disease is challenging due to the limited access to the human brain tissues, the complexity of brain anatomy and the lack of accurate models to recapitulate human brain development. The convergence between induced pluripotent stem cell and organoid technology enable to recapitulate key features of early human neurodevelopment disease in vitro. However, the low efficiency, high cost and technical variability of generating induced pluripotent stem cells (hiPSC) and organoids make an impossible challenge to design a powered study for associating patient genotype to organoids’ in vitro phenotypes. I will generate technology to produce human brain organoids from a selected patient in a robust, timely and seamless process and to capture - so far undetected - neurodevelopmental phenotypes. This will be obtained by combining reprogramming to nascent states of pluripotency with neurodevelopmental morphogenesis in three-dimension. Starting from a single nascent naive hiPSC, we will develop a process to form an epiblast cyst, then neuroepithelial cyst and forebrain organoid in continuous three-dimension process. I will use this technology to investigate genetic and epigenetic modifications in the early phase of neural development of Fragile X Syndrome (FXS). We will generate brain organoids from large cohorts of FXS patients for: i) profiling the whole spectrum of in vitro phonotypes associated with the variety of patient’ genetic and epigenetic modifications; ii) revealing unexplored developmentally regulated mechanisms; iii) design a powered study to assess targeted therapeutic options in FXS. ReprOids will allow the generation of human brain organoids from large cohorts of patients capturing in vitro the whole spectrum of disease manifestations. This will have huge impact in patient clinical management at the diagnostic, prognostic or therapeutic level.

Mots-clés : pluripotent stem cell,reprogramming,organoid
Projet ERC : PLANET (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : National Centre of Scientific Research "Demokritos" — Pays : Grèce — Rôle : PI
Acronyme de l'entité : NCSR-D
Type d'entité : Recherche
Financement ERC de l'entité : 3498333.0 €

In gas-phase manufacture of materials as well as in the atmosphere, the interaction between gas molecules and tiny nanoparticles (TNPs, i.e. particles having sizes from ca. 0.5 to 5 nm) determines their characteristics. These are crucial for the environment impact (climate, air quality and visibility) of TNPs and their performance in engineering and life science applications. Will two molecules collide and go their ways or stick to form a TNP that will grow to a nanoparticle (NP; i.e., a particle from 5 to 100 nm in size) of desired crystallinity? Today manufacturing of NPs is well understood, even at tons/hour (i.e. fumed oxides). However, for TNPs that hold most of the promises of nanotechnology, there is much uncertainty that hinders quantitative understanding of their formation, growth and transport and subsequently the systematic process design for their manufacturing. This project aims at advancing the fundamentals of aerosols from the sub-nano to the few nm scale through methodical experiments and comparison to state-of-the-art molecular dynamics simulations. It will capitalize on a 2023 discovery regarding the exact nature of gas collisions (from ballistic to orbiting and multi-body ones) that nearly halves the well-established value of the gas mean free path that defines aerosol dynamics in the free molecule or the continuum regime. This understanding will be reduced to easy-to-use expressions for process design at the lowest and most potent nanosize range. Project objectives are to: a) explore the interactions of gas molecules with TNPs by fully accounting for the precise structure and force fields of both entities, b) generate TNPs by spark ablation and measure their transport properties, c) develop a nucleation rate of TNPs accounting for the above interactions and d) place on a firm scientific basis the dynamics of aerosol TNPs bridging the gap between molecules and larger (> 5 nm) particles for material synthesis and even atmospheric airshed modeling.

Mots-clés : aerosol nanoparticles,molecular dynamics,particle technology,aerosol diffusion,aerosol nucleation,aerosol coagulation,aerosol engineering