Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SynUbL (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Université de Saint-Jacques-de-Compostelle — Pays : Espagne — Rôle : PI
Acronyme de l'entité : USC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1850374.0 €

Plants are continuously attacked by pathogens and pests, resulting globally in large agricultural losses and food insecurity at high economic cost. To counter infection, plants have developed sophisticated immune responses in which the post-translational modifier, ubiquitin, plays indispensable roles. Ubiquitination is a versatile protein modification that regulates the amplitude and intensity of immune responses, thereby establishing durable resistance. Substrate ubiquitination is performed by E3 ligases that act as matchmakers by recruiting specific substrates. Despite the essential roles of E3 ligases in plant immunity, it remains unclear how they achieve such extraordinary substrate selectivity and how they evolved to adapt to changing threats in their environment, including new pathogens. Conversely, pathogens have evolved effector proteins that hijack ubiquitin signalling to prevent immune activation, but the underpinning molecular mechanisms remain obscure.  The SynUbL project will establish interactions between the major cereal crop, barley, and fungal pathogen, Puccinia hordei, as an economically relevant host-pathogen system for addressing these questions and to bioengineer durable resistance. By functionally tracking immune-induced E3 ligases along the evolutionary tree, we will reveal how these enzymes evolved structural features for specific substrate recognition. Simultaneously, we will expose P. hordei’s hijacking tactics, thereby uncovering the significance of ubiquitin in shaping the evolutionary arms race between host and pathogen. Collective insights are then utilised to synthetically engineer novel E3 ligases to allow on-demand activation of host immune pathways and on-demand destruction of immune-suppressing pathogen effectors. Hence, this project not only provides fundamental discoveries in ubiquitin signalling, it exploits these innovations by generating sustainable strategies for durable crop resistance in the agrifood sector.

Mots-clés : ubiquitin signalling,e3 ligases,posttranslational modifications,plant immunity,disease resistance,barley,crops,effectors
Projet ERC : Decode Relapse (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université de Lund — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

The childhood cancer neuroblastoma (NB) is a major challenge in pediatric oncology, and children with relapse have a very poor prognosis due to treatment-resistance at metastatic sites. There is an urgent need to better understand NB treatment resistance to inform the design of novel therapeutic strategies. However, current models do not mimic relapsed human NB in its most common metastatic niches in the bone and bone marrow. We recently developed advanced patient-derived and humanized NB in vivo models and 3D tumor organoid models which are excellent tools for preclinical drug testing. Here, we aim to further develop and exploit these models, investigate mechanisms of NB metastatic treatment resistance/relapse, and target relapsed NB with combination therapies. First, we will develop patient-derived in vivo and ex vivo models of relapsed NB in the human metastatic bone marrow niche exposed to standard-of-care chemotherapy treatment. These models will be exploited to investigate mechanisms of metastasis and treatment escape upon therapy and at relapse. We will integrate NB and stromal cell lineages, cell states and molecular details with phenotype and drug response, and elucidate NB tumor cell plasticity and clonal evolution. The mechanistic data and our new models will help us to identify novel therapeutic targets and compounds targeting relapsing and resistant NB, which we will validate experimentally. The project will lead to a deeper understanding of NB metastatic treatment resistance and identification of novel cell state-directed treatments to target resistant and metastatic disease.  My combined background in clinical medicine/pathology, in vivo/ex vivo modeling, NB chemoresistance, and preclinical drug testing coupled with development and application of state-of the-art advanced assays will generate the next generation of patient-derived models, mechanistic insight and novel treatment against relapsed NB.

Mots-clés : treatment resistance,relapse,metastasis,neuroblastoma,pediatric cancer,mouse model,pdx model,tumor organoid,tumor cell state,tumor microenvironment,preclinical drug testing
Projet ERC : PIONEER (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Centre norvégien de recherche — Pays : Norvège — Rôle : PI
Acronyme de l'entité : NORCE
Type d'entité : Recherche
Financement ERC de l'entité : 2171640.0 €

The emergence of Homo sapiens' behavioural complexity represents a fundamental milestone in the evolution of humankind. Still, the causes of this critical transformation remain debated. For the African Middle Stone Age (MSA, ~300 000–40 000 years) a key question is whether and how climate variability contributed to the increasing behavioural complexity in modern humans. However, behavioural-environmental hypotheses remain untestable because the existing palaeoclimatic datasets are spatially, stratigraphically, and causally disconnected from the archaeological record.  PIONEER will overcome this impediment by developing a new analytical framework that allows testing of previously untestable hypotheses and thereby advances our understanding of human behavioural evolution. To achieve this, cutting-edge analytical (leaf wax isotope analyses) and computational approaches (climate- and agent-based modelling (ABM)) will be combined with African archaeology. Fundamental to my approach are high-resolution climate records from within the archaeology-bearing sediments, thus directly connecting environmental- and archaeological records. PIONEER will test behavioural-environmental hypotheses by interlinking several activities:  1) establish unprecedented high-resolution datasets of past vegetation and palaeohydrology changes from five key cave sites, inhabited by early Homo sapiens, located along the South African coast 2) create a high-resolution spatial representation of the environments experienced by our ancestors from novel climate simulations 3) explore likelihoods for different behavioural-environmental scenarios via ABM  Although PIONEER focuses on the South African MSA, my approach is applicable to most archaeological timeframes and locations. Consequently, PIONEER will transform future studies of climate-human interactions, clarifying key aspects of early human behaviour.

Mots-clés : african middle stone age,south africa,behavioural complexity
Projet ERC : BEAST (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Czech University of Life Sciences Prague — Pays : Rép. Tchèque — Rôle : PI
Acronyme de l'entité : CULS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999363.0 €

We face an unprecedented threat from global alteration of nature and biodiversity, but we still lack rigorous estimates of how fast, where, and at which scales biodiversity changes. Studies report fragmented and seemingly contradictory results, suffer from mismatches in biodiversity metrics, mismatches in temporal and spatial grains, and are constrained by huge data gaps. Moreover, local loss and gain of biodiversity is decoupled from changes in countries or continents, with opposing directions at different scales being plausible. A quantitative synthesis that connects all this, and bridges the gaps, is needed. The objective of BEAST is to map and interpolate temporal biodiversity change in Europe, the US, and the world, across continuous space, time, and their grains, from locations as small as 1 m, to countries and continents, over the last ca 40 years, for birds, plants, and butterflies. To do this we will combine data from local time series with high-quality gridded atlas data from countries and continents. We will use a new cross-scale model to interpolate biodiversity change jointly across space and time, and across the data gaps. We will test if temporal change of diversity, distributions, and turnover can be estimated from: (i) static patterns of diversity and distributions, (ii) from data lacking temporal replication, (iii) from space-for-time substitution of spatial vs temporal species turnover, (iii) from spaceborne remotely sensed spectral diversity and turnover. These methods will enable integration of heterogeneous and messy biodiversity data, and they will improve estimates of change in data-poor regions of the global South. BEAST will deliver the first integrative statistical model revealing, for the first time, how multiple facets of biodiversity change across scales. It will show which regions, habitats, and biomes undergo the most pronounced change, which is critical for informed large-scale conservation policy.

Mots-clés : macroecology,spatial statistics,biogeography,global
Projet ERC : NEUTIME (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Université Friedrich-Alexander d'Erlangen-Nuremberg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999970.0 €

Neurons in the brain must function for a life-time with limited replacement; thus, they need to robustly maintain their identity and function. Understanding the mechanisms underlying the longevity and persistence of neurons will be key for preventing and treating age-related neurological diseases. By focusing on epigenetic mechanisms regulated by nuclear RNAs, the project aims at understanding the fundamental mechanisms underlying the long-term maintenance of neural identity and their biological roles in the development of age-related vulnerability. The successful completion of this proposal will uncover novel roles of RNAs in long-term epigenetic regulation, and key biological links between epigenetic dysregulation and age-related pathological development. We recently discovered that some nuclear RNAs in rodent brains do not turn over for two years. These RNAs are maintained in a neural cell type-specific manner and are mainly localized around heterochromatin. Through a targeted approach, satellite RNA was found to be one of the stable nuclear RNAs and is critical for the maintenance of heterochromatin. Based on this finding, the proposed project aims to test the specific hypothesis that neural cells possess several long-retained nuclear RNAs which interact with chromatin to stabilize cell type-specific epigenetic regulation, but that they deteriorate as a result of aging. To address this question, we will use an interdisciplinary approach. First, the molecular identity of long-retained nuclear RNAs will be probed globally using deep sequencing. In parallel, mechanisms responsible for maintaining RNAs will be investigated Second, the roles of the nuclear RNAs and associated complexes we identify in maintaining cell type-specific epigenetic regulation will be investigated using neurobiological, epigenomic and biochemical approaches. Efforts will be directed toward understanding the roles of nuclear RNAs in pathophysiological brain aging.

Mots-clés : brain aging,longevity,epigenetics
Projet ERC : PEROVAP (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Leibniz-Gemeinschaft — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : WLG
Type d'entité : Recherche
Financement ERC de l'entité : 1999843.75 €

Metal halide perovskites (MHPs) have been in the spotlight of scientific research for over a decade due to their remarkable properties and performance in solar cells. Their future relies on a deeper understanding of their fundamental properties, better control of their structure, and implementation by scalable deposition methods. While most research efforts are dedicated to the solution processing of MHPs, vapour deposition holds many benefits. It is a solvent-free, scalable method of high industrial relevance offering high throughput, homogeneity, material economy, safety, yield and controllability. Despite these clear advantages, the development of engineering approaches to precisely control the properties of MHPs by vapour deposition remains in its infancy. In PEROVAP, I will develop novel routes for engineering MHPs by vapour deposition and the fundamental understanding of their growth and crystallisation, thus enabling new material structures with tailor-made properties. I will establish structural control over the phase, orientation and microstructure of MHPs by additive engineering, and develop a new class of perovskite-organic hybrid semiconducting composites. I will also demonstrate efficient, controllable n- and p- electrical doping of vapour deposited MHPs and create graded MHP layers with tailored optoelectronic properties and energetic landscape. To realise this, I propose a unique combinatorial fabrication-characterisation methodology for their in-situ spectroscopic characterisation. This approach will allow to efficiently explore the multi-dimensional parameter space required to engineer the MHP properties, and enable the development of the fundamental understanding of the film formation processes. Finally, to reveal the structure-property relations, the engineered MHPs will be integrated in novel solar cell architectures. The approaches developed in PEROVAP will open a new path for MHP electronics and optoelectronics far beyond state-of-the-art.

Mots-clés : metal halide perovskites vapour deposition engineering composites doping spectroscopy electronics optoelectronics photovoltaics
Projet ERC : SLEEPAWAY (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université de York — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999769.0 €

What we remember and forget lies at the core of who we are. But how do our brains shape our memories of the past? Sleep promotes the flexible use of memory by reactivating and thereby strengthening information that is most relevant to our future needs. Whether memory reactivation in sleep also weakens unwanted components of prior experience is unknown, but represents a major gap in our understanding of memory and how sleep influences our autobiographical identities. SLEEPAWAY combines an innovative technique for manipulating lab-based and real-world memories with an unprecedented array of neuroimaging methodologies to test the novel hypothesis that memory reactivation during sleep weakens unwanted memories in service of adaptive forgetting. Using magnetoencephalography with optically pumped magnetometers (OPM-MEG), I will first determine whether reactivating a target memory in slow-wave sleep weakens unwanted memories from the same experience, making them less accessible. Second, I will bring together OPM-MEG, fMRI and immersive virtual reality to obtain the first anatomically localised evidence of emotional memory reactivation in human rapid eye movement sleep, closing an important translational gap with extant animal models. Third, I will employ fMRI and EEG to examine the intriguing possibility that memory reactivation in sleep facilitates emotion regulation by weakening negative interpretations of real-world events, fostering a concrete pathway towards clinical intervention. Finally, to advance understanding of the symbiotic relationship between endogenous memory operations in the waking and sleeping brain, I will use OPM-MEG to test the prediction that active forgetting during wakefulness inhibits spontaneous memory reactivation in later sleep. In sum, SLEEPAWAY will make a substantial novel theoretical contribution by delineating the basic mechanisms through which our brains eradicate unwanted details of the past to support our cognitive and emotional goals.

Mots-clés : forgetting sleep
Projet ERC : dynaBBO (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1999975.0 €

Black-box optimization algorithms are among the most widely applied optimization techniques in practice, used to solve numerous problems across a broad range of industrial branches and academic disciplines every day. Given this importance, it is not surprising that a plethora of different black-box optimization algorithms exist, complementing each other in strengths and weaknesses. In the dynaBBO project, we set out to obtain more efficient black-box optimization techniques by leveraging this complementarity, both with respect to different problem instances and with respect to different stages of the optimization process. To this end, we will develop approaches that select and dynamically switch between different black-box optimization algorithms "on the fly". The two key research questions that guide our project are (1) when to switch from one algorithm to another, and (2) how to warm-start the selected solver so that it can continue the search as effectively as possible. Both questions are largely under-explored and are handled rather naively in practice. To obtain our dynamic approaches, we intertwine insights about black-box optimization algorithms, obtained through rigorous theoretical analyses, with automated machine learning techniques. In particular, we will design trajectory-based algorithm selection and configuration techniques that combine exploratory landscape analysis with newly designed algorithm features that capture information about the solver-instance interaction. We compare the efficiency of these feature-based approaches with deep learning techniques, reinforcement learning, and approaches based on hyperparameter optimization. We will further increase our project's impact by validating its results on applications in bio-medicine and in computational mechanics.

Mots-clés : black box optimization,randomized search heuristics,evolutionary computation,automated machine learning,algorithm selection,algorithm configuration,local search,discrete optimization,algorithm analysis,randomized algorithms,parameter control
Projet ERC : ATCOM (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université de Trente — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999358.0 €

Declarative memory is fundamentally relational. We not only remember things or events, but also whether and how they are related to each other. Cracking the mental code that supports relational memory is one of the greatest challenges of cognitive neuroscience. Here I suggest that memories are relationally encoded through an attentional repertoire, such that different types of conceptual relationships (before/after, bigger than, part of, caused by, etc.) correspond to different dynamic attentional patterns. Such an attentional code is largely decodable from eye-movement and embodies the structure of our relational knowledge. I provide preliminary data showing that spontaneous eye movements encode conceptual similarity, as well as conceptual relationships, in abstract semantic spaces and cognitive maps; and that the eye movements of different people synchronize while listening to the same narrative even if their eyes are closed. On this basis I hypothesize that: (i) structural knowledge in the form of low-dimensional schemas is encoded in attentional templates that support relational thinking and cross-domain generalization; (ii) in principle all conceptual relationships encoded in memory can be represented through an attentional code that can be decoded from eye movements; (iii) the construction of this code through sequential movements of attention is supported by hippocampal/parietal mechanisms for sequence generation and memory consolidation; (iv) this attentional code allows us to understand each other via inter-subject synchronization of attentional schemas. I will test these hypotheses using cutting-edge eye-tracking technology, multimodal neuroimaging (fMRI, MEG, iEEG) and deep neural networks. ATCOM is a high-risk/high-gain investigation of a novel groundbreaking hypothesis that, if correct, will have a long-lasting impact in cognitive neuroscience, artificial intelligence, and related fields, reshaping the way we think about memory.

Mots-clés : memory,eye movements,attention,relational knowledge,cognitive maps,hippocampus
Projet ERC : volta (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1992959.0 €

Consciousness entails the phenomenal experience we have of the world and ourselves. Although it is at the heart of major philosophical, scientific and ethical issues, our understanding of the neural mechanisms of consciousness remains limited. The study of consciousness is compartmentalised, with researchers focusing on isolated sub-aspects of the problem, via restrictive paradigms that ignore the temporal dynamics of conscious experience, its metacognitive component, or its dependence on levels of consciousness. Moreover, we know virtually nothing about the single-neuron and neurochemical basis for consciousness in humans.  VOLTA will advance beyond these empirical and theoretical limitations by conducting a multidimensional and multiscale study of consciousness. The project builds on a computational framework I recently developed linking consciousness to evidence accumulation. It will utilise the clinical context of pharmaco-resistant epilepsy to collect unprecedented behavioural and neural data. Individuals with epilepsy will participate in novel behavioural paradigms quantifying multiple dimensions of conscious experience, including its temporal dynamics, metacognitive components, and existence under sleep and anaesthesia. These experiments will be combined with triple neural recordings that simultaneously characterise #1 the global activity of neural populations, #2 spiking activity of individual neurons, and #3 electrochemical activity by measuring neuromodulator release with voltammetry. These unprecedented recordings will provide a multiscale map of the neurobiological basis of consciousness. My team and I, assisted by international experts, will interpret this rich dataset in light of seven preregistered hypotheses derived from my computational framework. In summary, VOLTA will carry out a first-of-a-kind within-subject study to reveal the electrophysiological and electrochemical mechanisms of the multiple dimensions of consciousness.

Mots-clés : electrophysiology,metacognition,computational modelling