Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : NANOREACTOR (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Freiburg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 558437.5 €

The catalysis by metal nanoparticles is one of the fastest growing areas in nanoscience due to our society's exploding need for fuels, drugs, and environmental remediation. However, the optimal control of catalytic activity and selectivity remains one of the grand challenges in the 21st century. Here, I propose to theoretically derive design rules for the optimization of nanoparticle catalysis by means of thermosensitive yolk-shell carrier systems. In the latter, the nanoparticle is stabilized in solution by an encapsulating, thermosensitive hydrogel shell. The physicochemical properties of this polymeric 'nanogate' react to stimuli in the environment and thus permit the reactant transport and the diffusion-controlled part of the catalytic reaction to be switched and tuned, e.g., by the temperature or the pH. The novel hybrid character of these emerging 'nanoreactors' opens up unprecedented ways for the control of nanocatalysis due to new designable degrees of freedom. The complex mechanisms behind stimuli-responsive nanocatalysis call for a concerted, interdisciplinary modelling approach that has converged in my group in the recent years. In particular, it can only be achieved by combining my expertise in multiscale computer simulations of solvated polymers with the statistical and continuum mechanics of soft matter structures and dynamics. The key challenge is to integrate the molecular solvation effects and our growing knowledge of hydrogel mechanics and thermodynamics into advanced reaction-diffusion equations for a quantitative rate prediction. In addition, I envision exciting novel phenomena such as a chemo-mechanical 'self-regulated catalysis' or an amplifying 'resonant catalysis', if hydrogel response and fluctuations couple to the chemical output signal. The expected results and design principles will help our collaborators to synthesize tailor-made, superior nanocatalysts and will advance our understanding of their structure-reactivity relationship.

Mots-clés : diffusion controlled reaction,nanocatalysis,thermosensitive hydrogel,molecular transport and kinetics,solvophilic,phobic solvation,computer simulation,reaction diffusion equation,smart material
Projet ERC : NANOREACTOR (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Helmholtz-Zentrum Berlin für Materialien und Energie — Pays : Allemagne — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 1429062.5 €

The catalysis by metal nanoparticles is one of the fastest growing areas in nanoscience due to our society's exploding need for fuels, drugs, and environmental remediation. However, the optimal control of catalytic activity and selectivity remains one of the grand challenges in the 21st century. Here, I propose to theoretically derive design rules for the optimization of nanoparticle catalysis by means of thermosensitive yolk-shell carrier systems. In the latter, the nanoparticle is stabilized in solution by an encapsulating, thermosensitive hydrogel shell. The physicochemical properties of this polymeric 'nanogate' react to stimuli in the environment and thus permit the reactant transport and the diffusion-controlled part of the catalytic reaction to be switched and tuned, e.g., by the temperature or the pH. The novel hybrid character of these emerging 'nanoreactors' opens up unprecedented ways for the control of nanocatalysis due to new designable degrees of freedom. The complex mechanisms behind stimuli-responsive nanocatalysis call for a concerted, interdisciplinary modelling approach that has converged in my group in the recent years. In particular, it can only be achieved by combining my expertise in multiscale computer simulations of solvated polymers with the statistical and continuum mechanics of soft matter structures and dynamics. The key challenge is to integrate the molecular solvation effects and our growing knowledge of hydrogel mechanics and thermodynamics into advanced reaction-diffusion equations for a quantitative rate prediction. In addition, I envision exciting novel phenomena such as a chemo-mechanical 'self-regulated catalysis' or an amplifying 'resonant catalysis', if hydrogel response and fluctuations couple to the chemical output signal. The expected results and design principles will help our collaborators to synthesize tailor-made, superior nanocatalysts and will advance our understanding of their structure-reactivity relationship.

Mots-clés : diffusion controlled reaction,nanocatalysis,thermosensitive hydrogel,molecular transport and kinetics,solvophilic,phobic solvation,computer simulation,reaction diffusion equation,smart material
Projet ERC : SCIPER (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

The cellular and molecular systems that determine drug responses in cancer are complex, highly individual, and incompletely understood. As a result, many cancer patients receive ineffective or even harmful therapies, which endangers lives, burdens healthcare systems, and prevents new therapies from reaching clinical approval. To address this problem, we are developing a platform that measures hundreds of ex vivo drug responses from small patient biopsies by immunofluorescence, automated confocal microscopy, single-cell image analysis, and machine learning. We preserve cellular memory and maximize physiological relevance by not culturing or sorting cells prior to drug exposure. Sub-cellular, single-cell, and cell population-wide image analysis reveals on-target drug responses and disentangles multicellular ones. In a first interventional clinical trial, this phenotypic information alone led to strongly improved treatment of patients with aggressive hematologic malignancies. Enabled by this high-throughput, predictive, and phenotypic information, I here propose to identify the molecular and cellular systems that govern treatment response individuality in cancer. (Aim 1) We will combine drug response profiling with RNA sequencing and proteomic measurements of malignant and healthy cells from the same biopsies. Critically, the patient-internal comparisons in both screening and OMICs allow neutralizing complex confounding factors. (Aim 2) New multiplexed immunofluorescence and convolutional neural network-based analyses will identify multiclass cell-types and -states, and quantify non-cell-autonomous responses. (Aim 3) Computational integration and causal inference will identify the molecular determinants and governing principles of drug response individuality in cancer, amenable to further validation. This proposal will thus improve our mechanistic understanding of cancer individuality and develop powerful new tools for OMICs-based precision medicine.

Mots-clés : image based screening,personalized medicine,machine learning
Projet ERC : iDysChart (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : Ludwig Boltzmann Gesellschaft — Pays : Autriche — Rôle : Partner
Acronyme de l'entité : LBG
Type d'entité : Recherche
Financement ERC de l'entité : 757291.75 €

The central challenge for the immune system is to efficiently recognize and neutralize foreign antigen while protecting self. If the latter fails, autoimmunity and/or autoinflammation may occur, as observed in many human diseases. Though several human genes involved in the process have been identified we still lack: i) a comprehensive appreciation of all contributing molecular pathways, ii) an understanding of the interplay and epistatic relationships among the various elements and iii) a satisfactory strategy to counteract dysregulation based on an understanding of the regulatory logic. I hypothesize that there is only a finite number of pathways involved and that it should be possible to mount a synergistic strategy to create a first chart of the entire “territory”. Key to this endeavor is the identification of sufficient elements by mapping immune dysregulation genes to “anchor” the chart onto signposts of which the human pathophysiological relevance is certain. From these signposts, contextualization and integration is achieved by interaction proteomics and network informatics mining the existing data universe, validated through biochemical and imaging tools to power an established set of immune assays. While it may be preposterous to claim feasibility with one ERC grant, I propose that once such a chart exists, even at initial low resolution, it can help reconcile disconnected observations and coalesce future work while being immensely improved in accuracy and mechanistic understanding by the entire community. iDysChart will work towards these goals by 1) identifying novel monogenic causes of autoimmune/autoinflammatory diseases, enabling elucidation of fundamental mechanisms, 2) creating a network-level understanding of molecular pathways of immune dysregulation and 3) employing chemical and genetic screens to complement human disease gene discovery in predicting the core human immune dysregulome and investigating potential avenues for therapeutic modulation.

Mots-clés : inborn error of immunity,immunodeficiency
Projet ERC : AVS-ISS (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 62500.0 €

The central objective of this project is to investigate key algorithmic verification questions concerning two fundamental mathematical structures used to model and analyse infinite-state systems, namely discrete linear dynamical systems and counter automata, in both ordinary and parametric form. Motivated especially by applications to software model checking (more specifically the termination of linear loops and predicate abstraction computations), as well as parametric real-time reasoning and the verification of Markov chains, we will focus on model-checking, module-checking, and synthesis problems for linear dynamical systems and one-counter automata against various fragments and extensions of Linear Temporal Logic (LTL) specifications. The key deliverables will be novel verification algorithms along with a map of the complexity landscape. A second objective is then to transfer algorithmic insights into practical verification methodologies and tools, in collaboration with colleagues in academia and industrial research laboratories. We will build on a series of recent advances and breakthroughs in these areas (some of which from the PI’s team) to attack a range of specific algorithmic problems. We believe that this line of research will not only result in fundamental theoretical contributions and insights in their own right—potentially answering mathematical questions that have been open for years or even decades—but will also impact the practice of formal verification and lead to new and more powerful methods and tools for the use of engineers and programmers.

Mots-clés : automated verification,model checking,synthesis problems,discrete linear dynamical systems,counter automata,parametric systems,probabilistic and real time systems,decidability,complexity
Projet ERC : AVS-ISS (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1772475.0 €

The central objective of this project is to investigate key algorithmic verification questions concerning two fundamental mathematical structures used to model and analyse infinite-state systems, namely discrete linear dynamical systems and counter automata, in both ordinary and parametric form. Motivated especially by applications to software model checking (more specifically the termination of linear loops and predicate abstraction computations), as well as parametric real-time reasoning and the verification of Markov chains, we will focus on model-checking, module-checking, and synthesis problems for linear dynamical systems and one-counter automata against various fragments and extensions of Linear Temporal Logic (LTL) specifications. The key deliverables will be novel verification algorithms along with a map of the complexity landscape. A second objective is then to transfer algorithmic insights into practical verification methodologies and tools, in collaboration with colleagues in academia and industrial research laboratories. We will build on a series of recent advances and breakthroughs in these areas (some of which from the PI’s team) to attack a range of specific algorithmic problems. We believe that this line of research will not only result in fundamental theoretical contributions and insights in their own right—potentially answering mathematical questions that have been open for years or even decades—but will also impact the practice of formal verification and lead to new and more powerful methods and tools for the use of engineers and programmers.

Mots-clés : automated verification,model checking,synthesis problems,discrete linear dynamical systems,counter automata,parametric systems,probabilistic and real time systems,decidability,complexity
Projet ERC : RxmiRcanceR (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Hebrew University of Jerusalem — Pays : Israël — Rôle : PI
Acronyme de l'entité : HUJI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2840729.0 €

The challenge for cancer therapy involves hampering the mechanisms by which the normal gene expression machinery is taken over to allow the aberrant appearance of cancer driving genes. I propose exploiting the therapeutic potential of a special class of tumor microRNAs (miRs) that function as natural post-transcriptional tumor suppressive regulators of many genes in key pathways. These anti-cancer effectors represent an inherent organismal property that I propose to augment and thereby translate into a form of systemic anti-cancer therapy. First, focusing on hepatocellular carcinoma (HCC), I shall perform high throughput screening to identify preferred HCC tumor suppressive miRs. Second, I shall search for small molecules capable of elevating the level of those relevant miRs in tumor cells and tissues. Increasing miR expression will potentially also enhance their secretion into the circulation in exosomes thereby suppressing gene expression at remote tissue sites as well. Third, I shall test the potential of these miRs to better target and inhibit the growth of tumor cells both, in culture and in vivo. This unprecedented conceptual strategy should stimulate the organism’s self-healing potential by enhancing inherent anti-tumor mechanisms. This project is built on robust preliminary findings that show promiscuous anti-cancer effects and predictably fewer side effects due to its completely host-based nature, with the administered miR inducer being the only foreign element. Additionally, due to the fact that each miR simultaneously targets a number of molecular pathways as well as multiple steps within a given pathway, it could help to overcome the major problem of cancer therapy – resistance. This strategy of harnessing these efficient and robust miRs and exosomes for delivery of anti-cancer therapeutics may overcome the high-risk challenge involved and enable high gain value.
Projet ERC : LO-ACT (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of London — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 38108.0 €

The challenge of LO-ACT is to enable low carbon urban development in medium and small cities in rapidly urbanising areas in East, Central and West Africa, South Asia and South East Asia. The majority of emissions in the next century will be emitted by infrastructures that are yet to be built, particularly in rapidly urbanising areas where infrastructure is lacking. Population forecasts suggest that most population growth will take place in small and medium cities. Yet, to date, research on climate action has focused on showcasing strongly branded, successful initiatives in global cities. The low carbon transition depends on myriad of actions in ordinary cities, that is, cities outside global networks of climate innovation and leadership. LO-ACT will address this critical gap by delivering the first multi-dimensional, large scale assessment of low carbon action in ordinary cities. It will contribute a new framework to understand global environmental politics and urban governance. First, LO-ACT will analyse the imaginaries of local action that have shaped global environmental politics over 30 years (Objective 1). The work programme will also analyse the mobility of low carbon urban policies in transport, energy, and housing across different urban contexts (Objective 2). LO-ACT will deliver a comparative analysis of urban trajectories in 113 ordinary cities, and five in-depth ethnographic case studies (Objective 3). Finally, it will provide a critical assessment of governance theory and a revised framework to acknowledge the messy and ordinary contexts of urban action (Objective 4). LO-ACT will bring together an interdisciplinary, international team of researchers, an international network of academic advisors, and four regional hubs that will support context-specific data collection and analysis. The research will contribute to the fields of human geography, urban studies, environmental politics, sustainability transitions and science and technology studies.

Mots-clés : climate change governance,urban transitions
Projet ERC : PANTROP (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Wageningen University & Research — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : WUR
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499895.0 €

The challenge- Tropical forests are global hotspots of biodiversity, play key roles in the global carbon and water cycle and deliver crucial ecosystem services but are threatened by human-induced climate change, deforestation and biodiversity loss. I focus on forests that regrow after complete forest removal for agriculture (secondary forests), because they cover large areas, have great potential to recover biodiversity and carbon, and are the basis for ecosystem restoration. The key challenge is to understand and predict forest resilience: when, and under what conditions are regrowing forests able to recover and have the same quality and functioning as old-growth forests? Aims- This study aims to understand and predict the resilience of tropical forests to human-driven disturbance by analyzing the effects of (1) continent and biogeography, (2) climate, (3) landscape, and (4) biodiversity on forest recovery rate. Approach- I will use a pantropical approach by synthesizing current data and doing controlled experiments on three continents (Neotropics, Africa, and Australia) in climatically contrasting forest types (dry and wet forest). I will (1) assess long-term multidimensional resilience by expanding a unique Neotropical network of 60 sites to the pantropics, (2) analyse the role of the landscape on forest recovery by doing a natural experiment along forest cover gradients, (3) understand how different kinds of diversity affect succession and ecosystem functioning through a biodiversity removal experiment. Impact- This study addresses key questions in ecology and advances our understanding how human-driven climate change, landscape degradation, and biodiversity loss affect forest resilience and succession. The insights can be applied to (1) reduce human impacts on tropical forests, (2) design resilient and multifunctional tropical landscapes, and (3) design effective forest restoration strategies.

Mots-clés : secondary forest,tropical forest,resilience,secondary succession,community assembly,functional traits,biodiversity ecosystem functioning,biogeography,climate,landscape,remote sensing,carbon,water,restoration
Projet ERC : CQWLED (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498515.0 €

The colloidal quantum dots (CQDs) are an emerging class of light-emitting compounds for solution-processed optoelectronics such as the light-emitting diodes (LEDs). Compared to the state-of-the-art compound semiconductors and organic light emitting diodes (OLED), the CQD-based LEDs possess extremely high color purity and low materials cost, representing the only feasible materials solution towards realization of the newly-defined Rec. 2020 standard for the next-generation displays. However, the theoretical upper limit of the device external quantum efficiency (EQE) is only ~20%, considerably lower than those in OLEDs and InGaN LEDs. The fundamental bottleneck is that it is not yet possible to control the emission directionality perpendicular to the substrate plane in the CQD superlattices, without compromising the photoluminescence quantum yield (PLQY). As a result, a lot of photons are wasted due to the total internal reflection (TIR) at the air/glass interface, as well as exciton quenching during interparticle energy transfer. In order to overcome the efficiency limitation, my research group pioneers synthesis, physics, and LED device of layer-controlled colloidal quantum wells (CQWs) of organic-inorganic hybrid lead halide perovskites (OIHPs), the two-dimensional nanocrystals of OIHP in colloidal solution. Our results have suggested that the materials system might be the ultimate solution for the quantum-dot based LEDs. We found that the CQWs possess: (i) the aggregation-induced emission (AIE) characteristics, boosting the film PLQY up to 97%, and (ii) the emission directionality (ED) perpendicular to the substrate plane in their self-assembled superlattices. Based on the new photophysical properties that have never been found in any other CQD systems, in this proposal, we aim to optimally utilize the characteristics of the AIE and ED, in order to realize high-efficiency and long-lifetime LED technology that can fulfill 100% Rec. 2020 color gamut.

Mots-clés : quantum dots,light emitting diodes