Project acronym CABUM
Project An investigation of the mechanisms at the interaction between cavitation bubbles and contaminants
Researcher (PI) Matevz DULAR
Host Institution (HI) UNIVERZA V LJUBLJANI
Call Details Consolidator Grant (CoG), PE8, ERC-2017-COG
Summary A sudden decrease in pressure triggers the formation of vapour and gas bubbles inside a liquid medium (also called cavitation). This leads to many (key) engineering problems: material loss, noise and vibration of hydraulic machinery. On the other hand, cavitation is a potentially a useful phenomenon: the extreme conditions are increasingly used for a wide variety of applications such as surface cleaning, enhanced chemistry, and waste water treatment (bacteria eradication and virus inactivation).
Despite this significant progress a large gap persists between the understanding of the mechanisms that contribute to the effects of cavitation and its application. Although engineers are already commercializing devices that employ cavitation, we are still not able to answer the fundamental question: What precisely are the mechanisms how bubbles can clean, disinfect, kill bacteria and enhance chemical activity? The overall objective of the project is to understand and determine the fundamental physics of the interaction of cavitation bubbles with different contaminants. To address this issue, the CABUM project will investigate the physical background of cavitation from physical, biological and engineering perspective on three complexity scales: i) on single bubble level, ii) on organised and iii) on random bubble clusters, producing a progressive multidisciplinary synergetic effect.
The proposed synergetic approach builds on the PI's preliminary research and employs novel experimental and numerical methodologies, some of which have been developed by the PI and his research group, to explore the physics of cavitation behaviour in interaction with bacteria and viruses.
Understanding the fundamental physical background of cavitation in interaction with contaminants will have a ground-breaking implications in various scientific fields (engineering, chemistry and biology) and will, in the future, enable the exploitation of cavitation in water and soil treatment processes.
Summary
A sudden decrease in pressure triggers the formation of vapour and gas bubbles inside a liquid medium (also called cavitation). This leads to many (key) engineering problems: material loss, noise and vibration of hydraulic machinery. On the other hand, cavitation is a potentially a useful phenomenon: the extreme conditions are increasingly used for a wide variety of applications such as surface cleaning, enhanced chemistry, and waste water treatment (bacteria eradication and virus inactivation).
Despite this significant progress a large gap persists between the understanding of the mechanisms that contribute to the effects of cavitation and its application. Although engineers are already commercializing devices that employ cavitation, we are still not able to answer the fundamental question: What precisely are the mechanisms how bubbles can clean, disinfect, kill bacteria and enhance chemical activity? The overall objective of the project is to understand and determine the fundamental physics of the interaction of cavitation bubbles with different contaminants. To address this issue, the CABUM project will investigate the physical background of cavitation from physical, biological and engineering perspective on three complexity scales: i) on single bubble level, ii) on organised and iii) on random bubble clusters, producing a progressive multidisciplinary synergetic effect.
The proposed synergetic approach builds on the PI's preliminary research and employs novel experimental and numerical methodologies, some of which have been developed by the PI and his research group, to explore the physics of cavitation behaviour in interaction with bacteria and viruses.
Understanding the fundamental physical background of cavitation in interaction with contaminants will have a ground-breaking implications in various scientific fields (engineering, chemistry and biology) and will, in the future, enable the exploitation of cavitation in water and soil treatment processes.
Max ERC Funding
1 904 565 €
Duration
Start date: 2018-07-01, End date: 2023-06-30
Project acronym Ctrl-ImpAct
Project Control of impulsive action
Researcher (PI) Frederick Leon Julien VERBRUGGEN
Host Institution (HI) UNIVERSITEIT GENT
Call Details Consolidator Grant (CoG), SH4, ERC-2017-COG
Summary Adaptive behaviour is typically attributed to an executive-control system that allows people to regulate impulsive actions and to fulfil long-term goals instead. Failures to regulate impulsive actions have been associated with a variety of clinical and behavioural disorders. Therefore, establishing a good understanding of impulse-control mechanisms and how to improve them could be hugely beneficial for both individuals and society at large. Yet many fundamental questions remain unanswered. This stems from a narrow focus on reactive inhibitory control and well-practiced actions. To make significant progress, we need to develop new models that integrate different aspects of impulsive action and executive control. The proposed research program aims to answer five fundamental questions. (1) Can novel impulsive actions arise during task-preparation stages?; (2) What is the role of negative emotions in the origin and control of impulsive actions?; (3) How does learning modulate impulsive behaviour?; (4) When are impulsive actions (dys)functional?; and (5) How is variation in state impulsivity associated with trait impulsivity?
To answer these questions, we will use carefully designed behavioural paradigms, cognitive neuroscience techniques (TMS & EEG), physiological measures (e.g. facial EMG), and mathematical modelling of decision-making to specify the origin and control of impulsive actions. Our ultimate goal is to transform the impulsive action field by replacing the currently dominant ‘inhibitory control’ models of impulsive action with detailed multifaceted models that can explain impulsivity and control across time and space. Developing a new behavioural model of impulsive action will also contribute to a better understanding of the causes of individual differences in impulsivity and the many disorders associated with impulse-control deficits.
Summary
Adaptive behaviour is typically attributed to an executive-control system that allows people to regulate impulsive actions and to fulfil long-term goals instead. Failures to regulate impulsive actions have been associated with a variety of clinical and behavioural disorders. Therefore, establishing a good understanding of impulse-control mechanisms and how to improve them could be hugely beneficial for both individuals and society at large. Yet many fundamental questions remain unanswered. This stems from a narrow focus on reactive inhibitory control and well-practiced actions. To make significant progress, we need to develop new models that integrate different aspects of impulsive action and executive control. The proposed research program aims to answer five fundamental questions. (1) Can novel impulsive actions arise during task-preparation stages?; (2) What is the role of negative emotions in the origin and control of impulsive actions?; (3) How does learning modulate impulsive behaviour?; (4) When are impulsive actions (dys)functional?; and (5) How is variation in state impulsivity associated with trait impulsivity?
To answer these questions, we will use carefully designed behavioural paradigms, cognitive neuroscience techniques (TMS & EEG), physiological measures (e.g. facial EMG), and mathematical modelling of decision-making to specify the origin and control of impulsive actions. Our ultimate goal is to transform the impulsive action field by replacing the currently dominant ‘inhibitory control’ models of impulsive action with detailed multifaceted models that can explain impulsivity and control across time and space. Developing a new behavioural model of impulsive action will also contribute to a better understanding of the causes of individual differences in impulsivity and the many disorders associated with impulse-control deficits.
Max ERC Funding
1 998 438 €
Duration
Start date: 2018-06-01, End date: 2023-05-31
Project acronym CUREORCURSE
Project Non-elected politics.Cure or Curse for the Crisis of Representative Democracy?
Researcher (PI) Jean-Benoit PILET
Host Institution (HI) UNIVERSITE LIBRE DE BRUXELLES
Call Details Consolidator Grant (CoG), SH2, ERC-2017-COG
Summary Evidence of a growing disengagement of citizens from politics is multiplying. Electoral turnout reaches historically low levels. Anti-establishment and populist parties are on the rise. Fewer and fewer Europeans trust their representative institutions. In response, we have observed a multiplication of institutional reforms aimed at revitalizing representative democracy. Two in particular stand out: the delegation of some political decision-making powers to (1) selected citizens and to (2) selected experts. But there is a paradox in attempting to cure the crisis of representative democracy by introducing such reforms. In representative democracy, control over political decision-making is vested in elected representatives. Delegating political decision-making to selected experts/citizens is at odds with this definition. It empowers the non-elected. If these reforms show that politics could work without elected officials, could we really expect that citizens’ support for representative democracy would be boosted and that citizens would re-engage with representative politics? In that sense, would it be a cure for the crisis of representative democracy, or rather a curse? Our central hypothesis is that there is no universal and univocal healing (or harming) effect of non-elected politics on support for representative democracy. In order to verify it, I propose to collect data across Europe on three elements: (1) a detailed study of the preferences of Europeans on how democracy should work and on institutional reforms towards non-elected politics, (2) a comprehensive inventory of all actual cases of empowerment of citizens and experts implemented across Europe since 2000, and (3) an analysis of the impact of exposure to non-elected politics on citizens’ attitudes towards representative democracy. An innovative combination of online survey experiments and of panel surveys will be used to answer this topical research question with far-reaching societal implication.
Summary
Evidence of a growing disengagement of citizens from politics is multiplying. Electoral turnout reaches historically low levels. Anti-establishment and populist parties are on the rise. Fewer and fewer Europeans trust their representative institutions. In response, we have observed a multiplication of institutional reforms aimed at revitalizing representative democracy. Two in particular stand out: the delegation of some political decision-making powers to (1) selected citizens and to (2) selected experts. But there is a paradox in attempting to cure the crisis of representative democracy by introducing such reforms. In representative democracy, control over political decision-making is vested in elected representatives. Delegating political decision-making to selected experts/citizens is at odds with this definition. It empowers the non-elected. If these reforms show that politics could work without elected officials, could we really expect that citizens’ support for representative democracy would be boosted and that citizens would re-engage with representative politics? In that sense, would it be a cure for the crisis of representative democracy, or rather a curse? Our central hypothesis is that there is no universal and univocal healing (or harming) effect of non-elected politics on support for representative democracy. In order to verify it, I propose to collect data across Europe on three elements: (1) a detailed study of the preferences of Europeans on how democracy should work and on institutional reforms towards non-elected politics, (2) a comprehensive inventory of all actual cases of empowerment of citizens and experts implemented across Europe since 2000, and (3) an analysis of the impact of exposure to non-elected politics on citizens’ attitudes towards representative democracy. An innovative combination of online survey experiments and of panel surveys will be used to answer this topical research question with far-reaching societal implication.
Max ERC Funding
1 981 589 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym ELECNANO
Project Electrically Tunable Functional Lanthanide Nanoarchitectures on Surfaces
Researcher (PI) DAVID ECIJA FERNANDEZ
Host Institution (HI) FUNDACION IMDEA NANOCIENCIA
Call Details Consolidator Grant (CoG), PE4, ERC-2017-COG
Summary Lanthanide metals are ubiquitous nowadays, finding use in luminescent materials, optical amplifiers and waveguides, lasers, photovoltaics, rechargeable batteries, catalysts, alloys, magnets, bio-probes, and therapeutic agents. In addition, they bear potential for high temperature superconductivity, magnetic refrigeration, molecular magnetic storage, spintronics and quantum information.
Surprisingly, the study of lanthanide physico-chemical properties on surfaces is at its infancy, particularly at the nanoscale. To address this extraordinary scientific opportunity, I will research the foundations and prospects of lanthanide elements to design functional nanoarchitectures on surfaces and I will study their inherent physico-chemical phenomena in distinct coordination environments, targeting novel approaches for sensing, nanomagnetism and electroluminescence. Importantly, our studies will encompass both metal substrates and decoupling surfaces including ultra-thin film insulators and graphene. Nurturing from these studies and in parallel, we will focus on graphene voltage back-gated supports, thus surpassing the seminal knowledge on electrically-inert substrates and enhancing the scope of our research to address the overarching objective of the proposal, i.e., the design of electrically tunable functional lanthanide nanomaterials.
The culmination of ELECNANO project will provide strategies for:
1.-Design of functional nanomaterials on high-technological supports.
2.-Development of advanced coordination chemistry on surfaces.
3.-Rationale of the physico-chemical properties of lanthanide-coordination environments.
4.-Engineering of lanthanide nanoarchitectures for ultimate sensing, nanomagnetism and electroluminescence.
5.-In-situ atomistic views of electrically tunable materials and unprecedented fundamental studies of charge-molecule/metal physics on devices.
Summary
Lanthanide metals are ubiquitous nowadays, finding use in luminescent materials, optical amplifiers and waveguides, lasers, photovoltaics, rechargeable batteries, catalysts, alloys, magnets, bio-probes, and therapeutic agents. In addition, they bear potential for high temperature superconductivity, magnetic refrigeration, molecular magnetic storage, spintronics and quantum information.
Surprisingly, the study of lanthanide physico-chemical properties on surfaces is at its infancy, particularly at the nanoscale. To address this extraordinary scientific opportunity, I will research the foundations and prospects of lanthanide elements to design functional nanoarchitectures on surfaces and I will study their inherent physico-chemical phenomena in distinct coordination environments, targeting novel approaches for sensing, nanomagnetism and electroluminescence. Importantly, our studies will encompass both metal substrates and decoupling surfaces including ultra-thin film insulators and graphene. Nurturing from these studies and in parallel, we will focus on graphene voltage back-gated supports, thus surpassing the seminal knowledge on electrically-inert substrates and enhancing the scope of our research to address the overarching objective of the proposal, i.e., the design of electrically tunable functional lanthanide nanomaterials.
The culmination of ELECNANO project will provide strategies for:
1.-Design of functional nanomaterials on high-technological supports.
2.-Development of advanced coordination chemistry on surfaces.
3.-Rationale of the physico-chemical properties of lanthanide-coordination environments.
4.-Engineering of lanthanide nanoarchitectures for ultimate sensing, nanomagnetism and electroluminescence.
5.-In-situ atomistic views of electrically tunable materials and unprecedented fundamental studies of charge-molecule/metal physics on devices.
Max ERC Funding
1 994 713 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym ELECTRIC CHALLENGES
Project Current Tools and Policy Challenges in Electricity Markets
Researcher (PI) Natalia FABRA PORTELA
Host Institution (HI) UNIVERSIDAD CARLOS III DE MADRID
Call Details Consolidator Grant (CoG), SH1, ERC-2017-COG
Summary The fight against climate change is among Europe’s top policy priorities. In this research agenda, I propose to push out the frontier in the area of Energy and Environmental Economics by carrying out policy-relevant research on a pressing issue: how to design optimal regulatory and market-based solutions to achieve a least cost transition towards a low-carbon economy.
The European experience provides unique natural experiments with which to test some of the most contentious issues that arise in the context of electricity markets, including the potential to change households’ demand patterns through dynamic pricing, the scope of renewables to mitigate market power and depress wholesale market prices, and the design and performance of the auctions for renewable support. While there is a body of policy work on these issues, it generally does not meet the required research standards.
In this research, I will rely on cutting-edge theoretical, empirical, and simulation tools to disentangle these topics, while providing key economic insights that are relevant beyond electricity markets. On the theory front, I propose to develop new models that incorporate the intermittency of renewables to characterize optimal bidding as a key, broadly omitted ingredient in previous analysis. In turn, these models will provide a rigorous structure for the empirical and simulation analysis, which will rely both on traditional econometrics for casual inference as well as on state-of-the-art machine learning methods to construct counterfactual scenarios for policy analysis.
While my focus is on energy and environmental issues, my research will also provide methodological contributions for other areas - particularly those related to policy design and policy evaluation. The conclusions of this research should prove valuable for academics, as well as to policy makers to assess the impact of environmental and energy policies and redefine them where necessary.
Summary
The fight against climate change is among Europe’s top policy priorities. In this research agenda, I propose to push out the frontier in the area of Energy and Environmental Economics by carrying out policy-relevant research on a pressing issue: how to design optimal regulatory and market-based solutions to achieve a least cost transition towards a low-carbon economy.
The European experience provides unique natural experiments with which to test some of the most contentious issues that arise in the context of electricity markets, including the potential to change households’ demand patterns through dynamic pricing, the scope of renewables to mitigate market power and depress wholesale market prices, and the design and performance of the auctions for renewable support. While there is a body of policy work on these issues, it generally does not meet the required research standards.
In this research, I will rely on cutting-edge theoretical, empirical, and simulation tools to disentangle these topics, while providing key economic insights that are relevant beyond electricity markets. On the theory front, I propose to develop new models that incorporate the intermittency of renewables to characterize optimal bidding as a key, broadly omitted ingredient in previous analysis. In turn, these models will provide a rigorous structure for the empirical and simulation analysis, which will rely both on traditional econometrics for casual inference as well as on state-of-the-art machine learning methods to construct counterfactual scenarios for policy analysis.
While my focus is on energy and environmental issues, my research will also provide methodological contributions for other areas - particularly those related to policy design and policy evaluation. The conclusions of this research should prove valuable for academics, as well as to policy makers to assess the impact of environmental and energy policies and redefine them where necessary.
Max ERC Funding
1 422 375 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym FRAGMENT
Project FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe
Researcher (PI) Carlos Perez Garcia-Pando
Host Institution (HI) BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION
Call Details Consolidator Grant (CoG), PE10, ERC-2017-COG
Summary Soil dust aerosols are mixtures of different minerals, whose relative abundances, particle size distribution (PSD), shape, surface topography and mixing state influence their effect upon climate. However, Earth System Models typically assume that dust aerosols have a globally uniform composition, neglecting the known regional variations in the mineralogy of the sources. The goal of FRAGMENT is to understand and constrain the global mineralogical composition of dust along with its effects upon climate. The representation of the global dust mineralogy is hindered by our limited knowledge of the global soil mineral content and our incomplete understanding of the emitted dust PSD in terms of its constituent minerals that results from the fragmentation of soil aggregates during wind erosion. The emitted PSD affects the duration of particle transport and thus each mineral’s global distribution, along with its specific effect upon climate. Coincident observations of the emitted dust and soil PSD are scarce and do not characterize the mineralogy. In addition, the existing theoretical paradigms disagree fundamentally on multiple aspects. We will contribute new fundamental understanding of the size-resolved mineralogy of dust at emission and its relationship with the parent soil, based on an unprecedented ensemble of measurement campaigns that have been designed to thoroughly test our theoretical hypotheses. To improve knowledge of the global soil mineral content, we will evaluate and use available remote hyperspectral imaging, which is unprecedented in the context of dust modelling. Our new methods will anticipate the coming innovation of retrieving soil mineralogy through high-quality spaceborne hyperspectral measurements. Finally, we will generate integrated and quantitative knowledge of the role of dust mineralogy in dust-radiation, dust-chemistry and dust-cloud interactions based on modeling experiments constrained with our theoretical innovations and field measurements.
Summary
Soil dust aerosols are mixtures of different minerals, whose relative abundances, particle size distribution (PSD), shape, surface topography and mixing state influence their effect upon climate. However, Earth System Models typically assume that dust aerosols have a globally uniform composition, neglecting the known regional variations in the mineralogy of the sources. The goal of FRAGMENT is to understand and constrain the global mineralogical composition of dust along with its effects upon climate. The representation of the global dust mineralogy is hindered by our limited knowledge of the global soil mineral content and our incomplete understanding of the emitted dust PSD in terms of its constituent minerals that results from the fragmentation of soil aggregates during wind erosion. The emitted PSD affects the duration of particle transport and thus each mineral’s global distribution, along with its specific effect upon climate. Coincident observations of the emitted dust and soil PSD are scarce and do not characterize the mineralogy. In addition, the existing theoretical paradigms disagree fundamentally on multiple aspects. We will contribute new fundamental understanding of the size-resolved mineralogy of dust at emission and its relationship with the parent soil, based on an unprecedented ensemble of measurement campaigns that have been designed to thoroughly test our theoretical hypotheses. To improve knowledge of the global soil mineral content, we will evaluate and use available remote hyperspectral imaging, which is unprecedented in the context of dust modelling. Our new methods will anticipate the coming innovation of retrieving soil mineralogy through high-quality spaceborne hyperspectral measurements. Finally, we will generate integrated and quantitative knowledge of the role of dust mineralogy in dust-radiation, dust-chemistry and dust-cloud interactions based on modeling experiments constrained with our theoretical innovations and field measurements.
Max ERC Funding
2 000 000 €
Duration
Start date: 2018-10-01, End date: 2023-09-30
Project acronym GENOMIA
Project Genomic Modifiers of Inherited Aortapathy
Researcher (PI) Bart Leo LOEYS
Host Institution (HI) UNIVERSITEIT ANTWERPEN
Call Details Consolidator Grant (CoG), LS4, ERC-2017-COG
Summary Thoracic aortic aneurysm and dissection (TAAD) is an important cause of morbidity and mortality in the western world. As 20% of all affected individuals have a positive family history, the genetic contribution to the development of TAAD is significant. Over the last decade dozens of genes were identified underlying syndromic and non-syndromic forms of TAAD. Although mutations in these disease culprits do not yet explain all cases, their identification and functional characterization were essential in deciphering three key aortic aneurysm/dissection patho-mechanisms: disturbed extracellular matrix homeostasis, dysregulated TGFbeta signaling and altered aortic smooth muscle cell contractility. Owing to the recent advent of next-generation sequencing technologies, I anticipate that the identification of additional genetic TAAD causes will remain quite straightforward in the coming years. Importantly, in many syndromic and non-syndromic families, significant non-penetrance and both inter- and intra-familial clinical variation are observed. So, although the primary genetic underlying mutation is identical in all these family members, the clinical spectrum varies widely from completely asymptomatic to sudden death due to aortic dissection at young age. The precise mechanisms underlying this variability remain largely elusive. Consequently, a better understanding of the functional effects of the primary mutation is highly needed and the identification of genetic variation that modifies these effects is becoming increasingly important. In this project, I carefully selected four different innovative strategies to discover mother nature’s own modifying capabilities in human and mouse aortopathy. The identification of these genetic modifiers will advance the knowledge significantly beyond the current understanding, individualize current treatment protocols to deliver true precision medicine and offer promising new leads to novel therapeutic strategies.
Summary
Thoracic aortic aneurysm and dissection (TAAD) is an important cause of morbidity and mortality in the western world. As 20% of all affected individuals have a positive family history, the genetic contribution to the development of TAAD is significant. Over the last decade dozens of genes were identified underlying syndromic and non-syndromic forms of TAAD. Although mutations in these disease culprits do not yet explain all cases, their identification and functional characterization were essential in deciphering three key aortic aneurysm/dissection patho-mechanisms: disturbed extracellular matrix homeostasis, dysregulated TGFbeta signaling and altered aortic smooth muscle cell contractility. Owing to the recent advent of next-generation sequencing technologies, I anticipate that the identification of additional genetic TAAD causes will remain quite straightforward in the coming years. Importantly, in many syndromic and non-syndromic families, significant non-penetrance and both inter- and intra-familial clinical variation are observed. So, although the primary genetic underlying mutation is identical in all these family members, the clinical spectrum varies widely from completely asymptomatic to sudden death due to aortic dissection at young age. The precise mechanisms underlying this variability remain largely elusive. Consequently, a better understanding of the functional effects of the primary mutation is highly needed and the identification of genetic variation that modifies these effects is becoming increasingly important. In this project, I carefully selected four different innovative strategies to discover mother nature’s own modifying capabilities in human and mouse aortopathy. The identification of these genetic modifiers will advance the knowledge significantly beyond the current understanding, individualize current treatment protocols to deliver true precision medicine and offer promising new leads to novel therapeutic strategies.
Max ERC Funding
1 987 860 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym ICON-BIO
Project Integrated Connectedness for a New Representation of Biology
Researcher (PI) Natasa PRZULJ
Host Institution (HI) BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION
Call Details Consolidator Grant (CoG), PE6, ERC-2017-COG
Summary The aim of the project is to develop a comprehensive framework for generalizing network analytics and fusion paradigms of non-negative matrix factorization to medical data. Heterogeneous, interconnected, systems-level omics data are becoming increasingly available and important in precision medicine. We are seeking to better stratify and subtype patients into risk groups, discover new biomarkers for complex and rare diseases, personalize medical treatment based on genomics and exposures of an individual, and repurpose known drugs to different patient groups. Existing methodologies for dealing with these big data are limited and a paradigm shift is needed to achieve quantitatively and qualitatively better results.
The project is motivated by the recent success of non-negative matrix tri-factorization (NMTF) based methods for fusion of heterogeneous data in biomedicine. Though these methods have been known for some time, the availability of large datasets, coupled with modern computational power and efficient optimization methods, allowed for creation and efficient training of complex models that can make a qualitative breakthrough. For example, NMTF has recently achieved unprecedented performance on exceptionally hard problems of simultaneously utilizing the wealth of diverse molecular and clinical data in precision medicine. However, research thus far has been limited to special variants of this problem and used only fixed point methods to address these exciting examples of hard non-convex high-dimensional non-linear optimization problems.
The ambition of the project is to develop general data fusion methods, from mathematical models to efficient and scalable software implementation, and apply them to the domain of biomedical informatics. The project will lead to a paradigm shift in biomedical and computational understanding of data and diseases that will open up ways to solving some of the major bottlenecks in precision medicine and other domains.
Summary
The aim of the project is to develop a comprehensive framework for generalizing network analytics and fusion paradigms of non-negative matrix factorization to medical data. Heterogeneous, interconnected, systems-level omics data are becoming increasingly available and important in precision medicine. We are seeking to better stratify and subtype patients into risk groups, discover new biomarkers for complex and rare diseases, personalize medical treatment based on genomics and exposures of an individual, and repurpose known drugs to different patient groups. Existing methodologies for dealing with these big data are limited and a paradigm shift is needed to achieve quantitatively and qualitatively better results.
The project is motivated by the recent success of non-negative matrix tri-factorization (NMTF) based methods for fusion of heterogeneous data in biomedicine. Though these methods have been known for some time, the availability of large datasets, coupled with modern computational power and efficient optimization methods, allowed for creation and efficient training of complex models that can make a qualitative breakthrough. For example, NMTF has recently achieved unprecedented performance on exceptionally hard problems of simultaneously utilizing the wealth of diverse molecular and clinical data in precision medicine. However, research thus far has been limited to special variants of this problem and used only fixed point methods to address these exciting examples of hard non-convex high-dimensional non-linear optimization problems.
The ambition of the project is to develop general data fusion methods, from mathematical models to efficient and scalable software implementation, and apply them to the domain of biomedical informatics. The project will lead to a paradigm shift in biomedical and computational understanding of data and diseases that will open up ways to solving some of the major bottlenecks in precision medicine and other domains.
Max ERC Funding
2 000 000 €
Duration
Start date: 2018-04-01, End date: 2023-03-31
Project acronym ImmunoFit
Project Harnessing tumor metabolism to overcome immunosupression
Researcher (PI) Massimiliano MAZZONE
Host Institution (HI) VIB
Call Details Consolidator Grant (CoG), LS4, ERC-2017-COG
Summary Anti-cancer immunotherapy has provided patients with a promising treatment. Yet, it has also unveiled that the immunosuppressive tumor microenvironment (TME) hampers the efficiency of this therapeutic option and limits its success. The concept that metabolism is able to shape the immune response has gained general acceptance. Nonetheless, little is known on how the metabolic crosstalk between different tumor compartments contributes to the harsh TME and ultimately impairs T cell fitness within the tumor.
This proposal aims to decipher which metabolic changes in the TME impede proper anti-tumor immunity. Starting from the meta-analysis of public human datasets, corroborated by metabolomics and transcriptomics data from several mouse tumors, we ranked clinically relevant and altered metabolic pathways that correlate with resistance to immunotherapy. Using a CRISPR/Cas9 platform for their functional in vivo selection, we want to identify cancer cell intrinsic metabolic mediators and, indirectly, distinguish those belonging specifically to the stroma. By means of genetic tools and small molecules, we will modify promising metabolic pathways in cancer cells and stromal cells (particularly in tumor-associated macrophages) to harness tumor immunosuppression. In a mirroring approach, we will apply a similar screening tool on cytotoxic T cells to identify metabolic targets that enhance their fitness under adverse growth conditions. This will allow us to manipulate T cells ex vivo and to therapeutically intervene via adoptive T cell transfer. By analyzing the metabolic network and crosstalk within the tumor, this project will shed light on how metabolism contributes to the immunosuppressive TME and T cell maladaptation. The overall goal is to identify druggable metabolic targets that i) reinforce the intrinsic anti-tumor immune response by breaking immunosuppression and ii) promote T cell function in immunotherapeutic settings by rewiring either the TME or the T cell itself.
Summary
Anti-cancer immunotherapy has provided patients with a promising treatment. Yet, it has also unveiled that the immunosuppressive tumor microenvironment (TME) hampers the efficiency of this therapeutic option and limits its success. The concept that metabolism is able to shape the immune response has gained general acceptance. Nonetheless, little is known on how the metabolic crosstalk between different tumor compartments contributes to the harsh TME and ultimately impairs T cell fitness within the tumor.
This proposal aims to decipher which metabolic changes in the TME impede proper anti-tumor immunity. Starting from the meta-analysis of public human datasets, corroborated by metabolomics and transcriptomics data from several mouse tumors, we ranked clinically relevant and altered metabolic pathways that correlate with resistance to immunotherapy. Using a CRISPR/Cas9 platform for their functional in vivo selection, we want to identify cancer cell intrinsic metabolic mediators and, indirectly, distinguish those belonging specifically to the stroma. By means of genetic tools and small molecules, we will modify promising metabolic pathways in cancer cells and stromal cells (particularly in tumor-associated macrophages) to harness tumor immunosuppression. In a mirroring approach, we will apply a similar screening tool on cytotoxic T cells to identify metabolic targets that enhance their fitness under adverse growth conditions. This will allow us to manipulate T cells ex vivo and to therapeutically intervene via adoptive T cell transfer. By analyzing the metabolic network and crosstalk within the tumor, this project will shed light on how metabolism contributes to the immunosuppressive TME and T cell maladaptation. The overall goal is to identify druggable metabolic targets that i) reinforce the intrinsic anti-tumor immune response by breaking immunosuppression and ii) promote T cell function in immunotherapeutic settings by rewiring either the TME or the T cell itself.
Max ERC Funding
1 999 721 €
Duration
Start date: 2018-07-01, End date: 2023-06-30
Project acronym InfoSampCollectJgmt
Project The Implications of Selective Information Sampling for Individual and Collective Judgments
Researcher (PI) Gael Georges Marcel LE MENS
Host Institution (HI) UNIVERSIDAD POMPEU FABRA
Call Details Consolidator Grant (CoG), SH3, ERC-2017-COG
Summary Much research has shown that judgments are the products of imperfect information processing heuristics. Recently, an alternative theoretical perspective has been proposed. It emphasizes that people form judgments by observing information samples about the alternatives. Sampling-based theories can explain numerous judgment patterns such as risk aversion, overconfidence, illusory correlations, the in-group out-group bias, or social influence.
The sampling approach has illustrated how these and other important patterns of human judgments can be parsimoniously explained by assuming a common source of bias. But at least two important questions remain:
1. How do sampling explanations for judgment biases can be integrated with explanations that focus on information-processing biases in order to explain judgment patterns in naturally occurring environments?
2. What are the implications of selective information sampling for collective judgments and the distribution of beliefs and attitudes over social networks?
I set to answer these pressing questions by (1) developing integrative belief formation models that incorporate both sampling-based mechanisms and information processing-based mechanisms; (2) collecting and analyzing experimental and field data to test these integrative models and uncover how the two classes of mechanisms interact; (3) building on these insights to develop models that lead to testable predictions about collective judgments and test these predictions with field and experimental data; (4) running experiments to measure the extent to which social network driven information sampling can contribute to opinion polarization.
The project will carry novel prescriptions to limit judgment biases such as the prevalence of negative stereotypes about socially distant others or the resistance to institutional change. It will also carry prescriptions to limit the emergence of collective illusions, and contain the polarization of opinions across social groups.
Summary
Much research has shown that judgments are the products of imperfect information processing heuristics. Recently, an alternative theoretical perspective has been proposed. It emphasizes that people form judgments by observing information samples about the alternatives. Sampling-based theories can explain numerous judgment patterns such as risk aversion, overconfidence, illusory correlations, the in-group out-group bias, or social influence.
The sampling approach has illustrated how these and other important patterns of human judgments can be parsimoniously explained by assuming a common source of bias. But at least two important questions remain:
1. How do sampling explanations for judgment biases can be integrated with explanations that focus on information-processing biases in order to explain judgment patterns in naturally occurring environments?
2. What are the implications of selective information sampling for collective judgments and the distribution of beliefs and attitudes over social networks?
I set to answer these pressing questions by (1) developing integrative belief formation models that incorporate both sampling-based mechanisms and information processing-based mechanisms; (2) collecting and analyzing experimental and field data to test these integrative models and uncover how the two classes of mechanisms interact; (3) building on these insights to develop models that lead to testable predictions about collective judgments and test these predictions with field and experimental data; (4) running experiments to measure the extent to which social network driven information sampling can contribute to opinion polarization.
The project will carry novel prescriptions to limit judgment biases such as the prevalence of negative stereotypes about socially distant others or the resistance to institutional change. It will also carry prescriptions to limit the emergence of collective illusions, and contain the polarization of opinions across social groups.
Max ERC Funding
1 158 625 €
Duration
Start date: 2018-05-01, End date: 2023-04-30
