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Project acronym ABC
Project Targeting Multidrug Resistant Cancer
Researcher (PI) Gergely Szakacs
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA TERMESZETTUDOMANYI KUTATOKOZPONT
Call Details Starting Grant (StG), LS7, ERC-2010-StG_20091118
Summary Despite considerable advances in drug discovery, resistance to anticancer chemotherapy confounds the effective treatment of patients. Cancer cells can acquire broad cross-resistance to mechanistically and structurally unrelated drugs. P-glycoprotein (Pgp) actively extrudes many types of drugs from cancer cells, thereby conferring resistance to those agents. The central tenet of my work is that Pgp, a universally accepted biomarker of drug resistance, should in addition be considered as a molecular target of multidrug-resistant (MDR) cancer cells. Successful targeting of MDR cells would reduce the tumor burden and would also enable the elimination of ABC transporter-overexpressing cancer stem cells that are responsible for the replenishment of tumors. The proposed project is based on the following observations: - First, by using a pharmacogenomic approach, I have revealed the hidden vulnerability of MDRcells (Szakács et al. 2004, Cancer Cell 6, 129-37); - Second, I have identified a series of MDR-selective compounds with increased toxicity toPgp-expressing cells (Turk et al.,Cancer Res, 2009. 69(21)); - Third, I have shown that MDR-selective compounds can be used to prevent theemergence of MDR (Ludwig, Szakács et al. 2006, Cancer Res 66, 4808-15); - Fourth, we have generated initial pharmacophore models for cytotoxicity and MDR-selectivity (Hall et al. 2009, J Med Chem 52, 3191-3204). I propose a comprehensive series of studies that will address thefollowing critical questions: - First, what is the scope of MDR-selective compounds? - Second, what is their mechanism of action? - Third, what is the optimal therapeutic modality? Extensive biological, pharmacological and bioinformatic analyses will be utilized to address four major specific aims. These aims address basic questions concerning the physiology of MDR ABC transporters in determining the mechanism of action of MDR-selective compounds, setting the stage for a fresh therapeutic approach that may eventually translate into improved patient care.
Despite considerable advances in drug discovery, resistance to anticancer chemotherapy confounds the effective treatment of patients. Cancer cells can acquire broad cross-resistance to mechanistically and structurally unrelated drugs. P-glycoprotein (Pgp) actively extrudes many types of drugs from cancer cells, thereby conferring resistance to those agents. The central tenet of my work is that Pgp, a universally accepted biomarker of drug resistance, should in addition be considered as a molecular target of multidrug-resistant (MDR) cancer cells. Successful targeting of MDR cells would reduce the tumor burden and would also enable the elimination of ABC transporter-overexpressing cancer stem cells that are responsible for the replenishment of tumors. The proposed project is based on the following observations: - First, by using a pharmacogenomic approach, I have revealed the hidden vulnerability of MDRcells (Szakács et al. 2004, Cancer Cell 6, 129-37); - Second, I have identified a series of MDR-selective compounds with increased toxicity toPgp-expressing cells (Turk et al.,Cancer Res, 2009. 69(21)); - Third, I have shown that MDR-selective compounds can be used to prevent theemergence of MDR (Ludwig, Szakács et al. 2006, Cancer Res 66, 4808-15); - Fourth, we have generated initial pharmacophore models for cytotoxicity and MDR-selectivity (Hall et al. 2009, J Med Chem 52, 3191-3204). I propose a comprehensive series of studies that will address thefollowing critical questions: - First, what is the scope of MDR-selective compounds? - Second, what is their mechanism of action? - Third, what is the optimal therapeutic modality? Extensive biological, pharmacological and bioinformatic analyses will be utilized to address four major specific aims. These aims address basic questions concerning the physiology of MDR ABC transporters in determining the mechanism of action of MDR-selective compounds, setting the stage for a fresh therapeutic approach that may eventually translate into improved patient care.
Project acronym ATOMKI-PPROCESS
Project Nuclear reaction studies relevant to the astrophysical p-process nucleosynthesis
Researcher (PI) György Gyürky
Host Institution (HI) Magyar Tudomanyos Akademia Atommagkutato Intezete
Call Details Starting Grant (StG), PE2, ERC-2007-StG
Summary The astrophysical p-process, the stellar production mechanism of the heavy, proton rich isotopes (p-isotopes), is one of the least studied processes in nucleosynthesis. The astrophysical site(s) for the p-process could not yet be clearly identified. In order to reproduce the natural abundances of the p-isotopes, the p-process models must take into account a huge nuclear reaction network. A precise knowledge of the rate of the nuclear reactions in this network is essential for a reliable abundance calculation and for a clear assignment of the astrophysical site(s). For lack of experimental data the nuclear physics inputs for the reaction networks are based on statistical model calculations. These calculations are largely untested in the mass and energy range relevant to the p-process and the uncertainties in the reaction rate values result in a correspondingly uncertain prediction of the p-isotope abundances. Therefore, experiments aiming at the determination of reaction rates for the p-process are of great importance. In this project nuclear reaction cross section measurements will be carried out in the mass and energy range of p-process to check the reliability of the statistical model calculations and to put the p-process models on a more reliable base. The accelerators of the Institute of Nuclear Research in Debrecen, Hungary provide the necessary basis for such studies. The p-process model calculations are especially sensitive to the rates of reactions involving alpha particles and heavy nuclei. Because of technical difficulties, so far there are practically no experimental data available on such reactions and the uncertainty in these reaction rates is presently one of the biggest contributions to the uncertainty of p-isotope abundance calculations. With the help of the ERC grant the alpha-induced reaction cross sections can be measured on heavy isotopes for the first time, which could contribute to a better understanding of the astrophysical p-process.
The astrophysical p-process, the stellar production mechanism of the heavy, proton rich isotopes (p-isotopes), is one of the least studied processes in nucleosynthesis. The astrophysical site(s) for the p-process could not yet be clearly identified. In order to reproduce the natural abundances of the p-isotopes, the p-process models must take into account a huge nuclear reaction network. A precise knowledge of the rate of the nuclear reactions in this network is essential for a reliable abundance calculation and for a clear assignment of the astrophysical site(s). For lack of experimental data the nuclear physics inputs for the reaction networks are based on statistical model calculations. These calculations are largely untested in the mass and energy range relevant to the p-process and the uncertainties in the reaction rate values result in a correspondingly uncertain prediction of the p-isotope abundances. Therefore, experiments aiming at the determination of reaction rates for the p-process are of great importance. In this project nuclear reaction cross section measurements will be carried out in the mass and energy range of p-process to check the reliability of the statistical model calculations and to put the p-process models on a more reliable base. The accelerators of the Institute of Nuclear Research in Debrecen, Hungary provide the necessary basis for such studies. The p-process model calculations are especially sensitive to the rates of reactions involving alpha particles and heavy nuclei. Because of technical difficulties, so far there are practically no experimental data available on such reactions and the uncertainty in these reaction rates is presently one of the biggest contributions to the uncertainty of p-isotope abundance calculations. With the help of the ERC grant the alpha-induced reaction cross sections can be measured on heavy isotopes for the first time, which could contribute to a better understanding of the astrophysical p-process.
Project acronym BEHAVIORAL THEORY
Project Behavioral Theory and Economic Applications
Researcher (PI) Botond Koszegi
Host Institution (HI) KOZEP-EUROPAI EGYETEM
Call Details Starting Grant (StG), SH1, ERC-2012-StG_20111124
Summary "This proposal outlines projects to develop robust and portable theories studying the impact of psychological phenomena in economic settings. The proposed work falls in three broad research agendas. My first main agenda is to formally model and economically apply a simple observation: that when people make decisions, they do not focus equally on all attributes of their available options, and overweight the attributes they focus on. I will build a set of portable models of focusing in attribute-based choice and risky choice based on the idea that a person focuses more on attributes in which her options differ more. I will also use the framework to develop novel, focus-based, theories of intertemporal choice and social preferences, as well as analyze the implications of focusing for product design, principal-agent relationships, and other economic questions. My second main agenda is to explore some implications for market outcomes, welfare, and policy of the possibility that consumers misperceive certain aspects of products. I will investigate the circumstances that facilitate the profitable deception of consumers; firms' incentives for ""innovating"" deceptive products, including novel financial products aimed at exploiting investors; how firms' ability to distinguish naive and sophisticated consumers affects the consequences of deception; whether learning on the part of consumers will help them to avoid making mistakes; and how regulators and other observers can detect consumer mistakes from market data. Two further projects apply the model of reference-dependent utility I have developed in earlier work to understand the pricing and advertising behavior of firms. I will also aim to disseminate some of my work, along with other cutting-edge research in psychology and economics, in a Journal of Economic Literature survey on ""Behavioral Contract Theory."""
"This proposal outlines projects to develop robust and portable theories studying the impact of psychological phenomena in economic settings. The proposed work falls in three broad research agendas. My first main agenda is to formally model and economically apply a simple observation: that when people make decisions, they do not focus equally on all attributes of their available options, and overweight the attributes they focus on. I will build a set of portable models of focusing in attribute-based choice and risky choice based on the idea that a person focuses more on attributes in which her options differ more. I will also use the framework to develop novel, focus-based, theories of intertemporal choice and social preferences, as well as analyze the implications of focusing for product design, principal-agent relationships, and other economic questions. My second main agenda is to explore some implications for market outcomes, welfare, and policy of the possibility that consumers misperceive certain aspects of products. I will investigate the circumstances that facilitate the profitable deception of consumers; firms' incentives for ""innovating"" deceptive products, including novel financial products aimed at exploiting investors; how firms' ability to distinguish naive and sophisticated consumers affects the consequences of deception; whether learning on the part of consumers will help them to avoid making mistakes; and how regulators and other observers can detect consumer mistakes from market data. Two further projects apply the model of reference-dependent utility I have developed in earlier work to understand the pricing and advertising behavior of firms. I will also aim to disseminate some of my work, along with other cutting-edge research in psychology and economics, in a Journal of Economic Literature survey on ""Behavioral Contract Theory."""
Project acronym BRAINCANNABINOIDS
Project Understanding the molecular blueprint and functional complexity of the endocannabinoid metabolome in the brain
Researcher (PI) István Katona
Host Institution (HI) INSTITUTE OF EXPERIMENTAL MEDICINE - HUNGARIAN ACADEMY OF SCIENCES
Call Details Starting Grant (StG), LS5, ERC-2009-StG
Summary We and others have recently delineated the molecular architecture of a new feedback pathway in brain synapses, which operates as a synaptic circuit breaker. This pathway is supposed to use a group of lipid messengers as retrograde synaptic signals, the so-called endocannabinoids. Although heterogeneous in their chemical structures, these molecules along with the psychoactive compound in cannabis are thought to target the same effector in the brain, the CB1 receptor. However, the molecular catalog of these bioactive lipids and their metabolic enzymes has been expanding rapidly by recent advances in lipidomics and proteomics raising the possibility that these lipids may also serve novel, yet unidentified physiological functions. Thus, the overall aim of our research program is to define the molecular and anatomical organization of these endocannabinoid-mediated pathways and to determine their functional significance. In the present proposal, we will focus on understanding how these novel pathways regulate synaptic and extrasynaptic signaling in hippocampal neurons. Using combination of lipidomic, genetic and high-resolution anatomical approaches, we will identify distinct chemical species of endocannabinoids and will show how their metabolic enzymes are segregated into different subcellular compartments in cell type- and synapse-specific manner. Subsequently, we will use genetically encoded gain-of-function, loss-of-function and reporter constructs in imaging experiments and electrophysiological recordings to gain insights into the diverse tasks that these new pathways serve in synaptic transmission and extrasynaptic signal processing. Our proposed experiments will reveal fundamental principles of intercellular and intracellular endocannabinoid signaling in the brain.
We and others have recently delineated the molecular architecture of a new feedback pathway in brain synapses, which operates as a synaptic circuit breaker. This pathway is supposed to use a group of lipid messengers as retrograde synaptic signals, the so-called endocannabinoids. Although heterogeneous in their chemical structures, these molecules along with the psychoactive compound in cannabis are thought to target the same effector in the brain, the CB1 receptor. However, the molecular catalog of these bioactive lipids and their metabolic enzymes has been expanding rapidly by recent advances in lipidomics and proteomics raising the possibility that these lipids may also serve novel, yet unidentified physiological functions. Thus, the overall aim of our research program is to define the molecular and anatomical organization of these endocannabinoid-mediated pathways and to determine their functional significance. In the present proposal, we will focus on understanding how these novel pathways regulate synaptic and extrasynaptic signaling in hippocampal neurons. Using combination of lipidomic, genetic and high-resolution anatomical approaches, we will identify distinct chemical species of endocannabinoids and will show how their metabolic enzymes are segregated into different subcellular compartments in cell type- and synapse-specific manner. Subsequently, we will use genetically encoded gain-of-function, loss-of-function and reporter constructs in imaging experiments and electrophysiological recordings to gain insights into the diverse tasks that these new pathways serve in synaptic transmission and extrasynaptic signal processing. Our proposed experiments will reveal fundamental principles of intercellular and intracellular endocannabinoid signaling in the brain.
Project acronym CholAminCo
Project Synergy and antagonism of cholinergic and dopaminergic systems in associative learning
Researcher (PI) Balazs Gyoergy HANGYA
Summary Neuromodulators such as acetylcholine and dopamine are able to rapidly reprogram neuronal information processing and dynamically change brain states. Degeneration or dysfunction of cholinergic and dopaminergic neurons can lead to neuropsychiatric conditions like schizophrenia and addiction or cognitive diseases such as Alzheimer's. Neuromodulatory systems control overlapping cognitive processes and often have similar modes of action; therefore it is important to reveal cooperation and competition between different systems to understand their unique contributions to cognitive functions like learning, memory and attention. This is only possible by direct comparison, which necessitates monitoring multiple neuromodulatory systems under identical experimental conditions. Moreover, simultaneous recording of different neuromodulatory cell types goes beyond phenomenological description of similarities and differences by revealing the underlying correlation structure at the level of action potential timing. However, such data allowing direct comparison of neuromodulatory actions are still sparse. As a first step to bridge this gap, I propose to elucidate the unique versus complementary roles of two "classical" neuromodulatory systems, the cholinergic and dopaminergic projection system implicated in various cognitive functions including associative learning and plasticity. First, we will record optogenetically identified cholinergic and dopaminergic neurons simultaneously using chronic extracellular recording in mice undergoing classical and operant conditioning. Second, we will determine the postsynaptic impact of cholinergic and dopaminergic neurons by manipulating them both separately and simultaneously while recording consequential changes in cortical neuronal activity and learning behaviour. These experiments will reveal how major neuromodulatory systems interact to mediate similar or different aspects of the same cognitive functions.
Neuromodulators such as acetylcholine and dopamine are able to rapidly reprogram neuronal information processing and dynamically change brain states. Degeneration or dysfunction of cholinergic and dopaminergic neurons can lead to neuropsychiatric conditions like schizophrenia and addiction or cognitive diseases such as Alzheimer's. Neuromodulatory systems control overlapping cognitive processes and often have similar modes of action; therefore it is important to reveal cooperation and competition between different systems to understand their unique contributions to cognitive functions like learning, memory and attention. This is only possible by direct comparison, which necessitates monitoring multiple neuromodulatory systems under identical experimental conditions. Moreover, simultaneous recording of different neuromodulatory cell types goes beyond phenomenological description of similarities and differences by revealing the underlying correlation structure at the level of action potential timing. However, such data allowing direct comparison of neuromodulatory actions are still sparse. As a first step to bridge this gap, I propose to elucidate the unique versus complementary roles of two "classical" neuromodulatory systems, the cholinergic and dopaminergic projection system implicated in various cognitive functions including associative learning and plasticity. First, we will record optogenetically identified cholinergic and dopaminergic neurons simultaneously using chronic extracellular recording in mice undergoing classical and operant conditioning. Second, we will determine the postsynaptic impact of cholinergic and dopaminergic neurons by manipulating them both separately and simultaneously while recording consequential changes in cortical neuronal activity and learning behaviour. These experiments will reveal how major neuromodulatory systems interact to mediate similar or different aspects of the same cognitive functions.
Project acronym COOPAIRENT
Project Cooper pairs as a source of entanglement
Researcher (PI) Szabolcs Csonka
Host Institution (HI) BUDAPESTI MUSZAKI ES GAZDASAGTUDOMANYI EGYETEM
Call Details Starting Grant (StG), PE3, ERC-2010-StG_20091028
Summary Entanglement and non-locality are spectacular fundamentals of quantum mechanics and basic resources of future quantum computation algorithms. Electronic entanglement has attracted increasing attention during the last years. The electron spin as a purely quantum mechanical two level system has been put forward as a promising candidate for storing quantum information in solid state. Recently, great progress has been achieved in manipulation and read-out of quantum dot based spin Qubits. However, electron spin is also suitable to transfer quantum information, since mobile electrons can be coherently transmitted in a solid state device preserving the spin information. Thus, electron spin could provide a general platform for on-chip quantum computation and information processing. Although several theoretical concepts have been worked out to address spin entangled mobile electrons, the absence of an entangler device has not allowed their realization so far. The aim of the present proposal is to overcome this experimental challenge and explore the entanglement of spatially separated electron pairs. Superconductors provide a natural source of entanglement, because their ground-state is composed of Cooper pairs in a spin-singlet state. However, the splitting of the Cooper pairs into separate electrons has to be enforced, which has been very recently realized by the applicant in two quantum dot Y-junction. This Y-junction will be used as a central building block to split Cooper pairs in a controlled fashion and the non-local nature of spin and charge correlations will be addressed in various device configurations. Our research project will lead to a fundamental understanding of the production, manipulation and detection of spin entangled mobile electron pairs, thus it will significantly extend the frontiers of quantum coherence and opens a new horizon in the field of on-chip quantum information technologies.
Entanglement and non-locality are spectacular fundamentals of quantum mechanics and basic resources of future quantum computation algorithms. Electronic entanglement has attracted increasing attention during the last years. The electron spin as a purely quantum mechanical two level system has been put forward as a promising candidate for storing quantum information in solid state. Recently, great progress has been achieved in manipulation and read-out of quantum dot based spin Qubits. However, electron spin is also suitable to transfer quantum information, since mobile electrons can be coherently transmitted in a solid state device preserving the spin information. Thus, electron spin could provide a general platform for on-chip quantum computation and information processing. Although several theoretical concepts have been worked out to address spin entangled mobile electrons, the absence of an entangler device has not allowed their realization so far. The aim of the present proposal is to overcome this experimental challenge and explore the entanglement of spatially separated electron pairs. Superconductors provide a natural source of entanglement, because their ground-state is composed of Cooper pairs in a spin-singlet state. However, the splitting of the Cooper pairs into separate electrons has to be enforced, which has been very recently realized by the applicant in two quantum dot Y-junction. This Y-junction will be used as a central building block to split Cooper pairs in a controlled fashion and the non-local nature of spin and charge correlations will be addressed in various device configurations. Our research project will lead to a fundamental understanding of the production, manipulation and detection of spin entangled mobile electron pairs, thus it will significantly extend the frontiers of quantum coherence and opens a new horizon in the field of on-chip quantum information technologies.
Project acronym EPIDELAY
Project Delay differential models and transmission dynamics of infectious diseases
Researcher (PI) Gergely Röst
Host Institution (HI) SZEGEDI TUDOMANYEGYETEM
Summary The aim of this project is to develop and analyse infinite dimensional dynamical models for the transmission dynamics and propagation of infectious diseases. We use an integrated approach which spans from the abstract theory of functional differential equations to the practical problems of epidemiology, with serious implications to public health policy, prevention, control and mitigation strategies in cases such as the ongoing battle against the nascent H1N1 pandemic. Delay differential equations are one of the most powerful mathematical modeling tools and they arise naturally in various applications from life sciences to engineering and physics, whenever temporal delays are important. In abstract terms, functional differential equations describe dynamical systems, when their evolution depends on the solution at prior times. The central theme of this project is to forge strong links between the abstract theory of delay differential equations and practical aspects of epidemiology. Our research will combine competencies in different fields of mathematics and embrace theoretical issues as well as real life applications. In particular, the theory of equations with state dependent delays is extremely challenging, and this field is at present on the verge of a breakthrough. Developing new theories in this area and connecting them to relevant applications would go far beyond the current research frontier of mathematical epidemiology and could open a new chapter in disease modeling.
The aim of this project is to develop and analyse infinite dimensional dynamical models for the transmission dynamics and propagation of infectious diseases. We use an integrated approach which spans from the abstract theory of functional differential equations to the practical problems of epidemiology, with serious implications to public health policy, prevention, control and mitigation strategies in cases such as the ongoing battle against the nascent H1N1 pandemic. Delay differential equations are one of the most powerful mathematical modeling tools and they arise naturally in various applications from life sciences to engineering and physics, whenever temporal delays are important. In abstract terms, functional differential equations describe dynamical systems, when their evolution depends on the solution at prior times. The central theme of this project is to forge strong links between the abstract theory of delay differential equations and practical aspects of epidemiology. Our research will combine competencies in different fields of mathematics and embrace theoretical issues as well as real life applications. In particular, the theory of equations with state dependent delays is extremely challenging, and this field is at present on the verge of a breakthrough. Developing new theories in this area and connecting them to relevant applications would go far beyond the current research frontier of mathematical epidemiology and could open a new chapter in disease modeling.
Project acronym EVOLOR
Project Cognitive Ageing in Dogs
Researcher (PI) Eniko Kubinyi
Host Institution (HI) EOTVOS LORAND TUDOMANYEGYETEM
Summary The aim of this project is to understand the causal factors contributing to the cognitive decline during senescence and to develop sensitive and standardized behaviour tests for early detection in order to increase the welfare of affected species. With the rapidly ageing population of Europe, related research is a priority in the European Union. We will focus both on characterising the ageing phenotype and the underlying biological processes in dogs as a well-established natural animal model. We develop a reliable and valid test battery applying innovative multidisciplinary methods (e.g. eye-tracking, motion path analysis, identification of behaviour using inertial sensors, EEG, fMRI, candidate gene, and epigenetics) in both longitudinal and cross-sectional studies. We expect to reveal specific environmental risk factors which hasten ageing and also protective factors which may postpone it. We aim to provide objective criteria (behavioural, physiological and genetic biomarkers) to assess and predict the ageing trajectory for specific individual dogs. This would help veterinarians to recognise the symptoms early, and initiate necessary counter actions. This approach establishes the framework for answering the broad question that how we can extend the healthy life of ageing dogs which indirectly also contributes to the welfare of the owner and decreases veterinary expenses. The detailed description of the ageing phenotype may also facilitate the use of dogs as a natural model for human senescence, including the development and application of pharmaceutical interventions. We expect that our approach offers the scientific foundation to delay the onset of cognitive ageing in dog populations by 1-2 years, and also increase the proportion of dogs that enjoy healthy ageing.
The aim of this project is to understand the causal factors contributing to the cognitive decline during senescence and to develop sensitive and standardized behaviour tests for early detection in order to increase the welfare of affected species. With the rapidly ageing population of Europe, related research is a priority in the European Union. We will focus both on characterising the ageing phenotype and the underlying biological processes in dogs as a well-established natural animal model. We develop a reliable and valid test battery applying innovative multidisciplinary methods (e.g. eye-tracking, motion path analysis, identification of behaviour using inertial sensors, EEG, fMRI, candidate gene, and epigenetics) in both longitudinal and cross-sectional studies. We expect to reveal specific environmental risk factors which hasten ageing and also protective factors which may postpone it. We aim to provide objective criteria (behavioural, physiological and genetic biomarkers) to assess and predict the ageing trajectory for specific individual dogs. This would help veterinarians to recognise the symptoms early, and initiate necessary counter actions. This approach establishes the framework for answering the broad question that how we can extend the healthy life of ageing dogs which indirectly also contributes to the welfare of the owner and decreases veterinary expenses. The detailed description of the ageing phenotype may also facilitate the use of dogs as a natural model for human senescence, including the development and application of pharmaceutical interventions. We expect that our approach offers the scientific foundation to delay the onset of cognitive ageing in dog populations by 1-2 years, and also increase the proportion of dogs that enjoy healthy ageing.
Project acronym FORCEMAP
Project Intramolecular force mapping of enzymes in action: the role of strain in motor mechanisms
Researcher (PI) András Málnási-Csizmadia
Summary A fundamental but unexplored problem in biology is whether and how enzymes use mechanical strain during their functioning. It is now evident that the knowledge of atomic structures and chemical interactions is not sufficient to understand the intricate mechanisms underlying enzyme specificity and efficiency. Several lines of evidence suggest that mechanical effects play crucial roles in enzyme activity. Therefore we aim to create detailed force maps that reveal how the intramolecular distribution of mechanical strains changes during the enzyme cycle and how these rearrangements drive the enzyme processes. The applicability of current nanotechniques for the investigation of this problem is limited because they do not allow simultaneous measurement of mechanical and enzymatic parameters. Thus we seek to open new avenues of research by developing site-specific sensors and passive or photoinducible molecular springs to measure force-dependent chemical/structural changes with high spatiotemporal resolution in myosin. Since force perturbations occur very rapidly, we are able to combine experimental studies with quasi-realistic in silico simulations to describe the physical background of enzyme function. We expect that our research will yield fundamental insights into the role of intramolecular strains in enzymes and thus greatly aid the design and control of enzyme processes (specificity, activity, regulation). Our studies may also lead to new paradigms in the understanding of motor systems.
A fundamental but unexplored problem in biology is whether and how enzymes use mechanical strain during their functioning. It is now evident that the knowledge of atomic structures and chemical interactions is not sufficient to understand the intricate mechanisms underlying enzyme specificity and efficiency. Several lines of evidence suggest that mechanical effects play crucial roles in enzyme activity. Therefore we aim to create detailed force maps that reveal how the intramolecular distribution of mechanical strains changes during the enzyme cycle and how these rearrangements drive the enzyme processes. The applicability of current nanotechniques for the investigation of this problem is limited because they do not allow simultaneous measurement of mechanical and enzymatic parameters. Thus we seek to open new avenues of research by developing site-specific sensors and passive or photoinducible molecular springs to measure force-dependent chemical/structural changes with high spatiotemporal resolution in myosin. Since force perturbations occur very rapidly, we are able to combine experimental studies with quasi-realistic in silico simulations to describe the physical background of enzyme function. We expect that our research will yield fundamental insights into the role of intramolecular strains in enzymes and thus greatly aid the design and control of enzyme processes (specificity, activity, regulation). Our studies may also lead to new paradigms in the understanding of motor systems.
Project acronym GalNUC
Project Astrophysical Dynamics and Statistical Physics of Galactic Nuclei
Researcher (PI) Bence Kocsis
Summary We address some of the major unsolved questions of galactic nuclei using methods of condensed matter physics. Galactic nuclei host a central supermassive black hole, a dense population of stars and compact objects, and in many cases a bright gaseous disk feeding the supermassive black hole. The observed stellar distribution exhibits both spherical and counterrotating disk-like structures. Existing theoretical models cannot convincingly explain the origin of the stellar disks. Is there also a "dark cusp" or "dark disk" of stellar mass black holes? Are there intermediate mass black holes in the Galactic center? We examine the statistical physics of galactic nuclei and their long term dynamical evolution. A star orbiting a supermassive black hole on an eccentric precessing orbit covers an axisymmetric annulus. The long-term gravitational interaction between such annuli is similar to the Coulomb interaction between axisymmetric molecules constituting a liquid crystal. We apply standard methods of condensed matter physics to examine these astrophysical systems. The observed disk and spherical structures represent isotropic-nematic phase transitions. We derive the phase space distribution and time-evolution of different stellar components including a population of black holes. Further, we investigate the interaction of a stellar cluster with a gaseous disk, if present. This leads to the formation of gaps, warps, and spiral waves in the disk, the redistribution of stellar objects, and possibly the formation of intermediate mass black holes. We explore the implications for electromagnetic and gravitational wave observatories. Dark disks of black holes could provide the most frequent source of gravitational waves for LIGO and VIRGO. These detectors will open a new window on the Universe; the proposed project will open a new field in gravitational wave astrophysics to interpret the sources. We also explore implications for electromagnetic observations.
We address some of the major unsolved questions of galactic nuclei using methods of condensed matter physics. Galactic nuclei host a central supermassive black hole, a dense population of stars and compact objects, and in many cases a bright gaseous disk feeding the supermassive black hole. The observed stellar distribution exhibits both spherical and counterrotating disk-like structures. Existing theoretical models cannot convincingly explain the origin of the stellar disks. Is there also a "dark cusp" or "dark disk" of stellar mass black holes? Are there intermediate mass black holes in the Galactic center? We examine the statistical physics of galactic nuclei and their long term dynamical evolution. A star orbiting a supermassive black hole on an eccentric precessing orbit covers an axisymmetric annulus. The long-term gravitational interaction between such annuli is similar to the Coulomb interaction between axisymmetric molecules constituting a liquid crystal. We apply standard methods of condensed matter physics to examine these astrophysical systems. The observed disk and spherical structures represent isotropic-nematic phase transitions. We derive the phase space distribution and time-evolution of different stellar components including a population of black holes. Further, we investigate the interaction of a stellar cluster with a gaseous disk, if present. This leads to the formation of gaps, warps, and spiral waves in the disk, the redistribution of stellar objects, and possibly the formation of intermediate mass black holes. We explore the implications for electromagnetic and gravitational wave observatories. Dark disks of black holes could provide the most frequent source of gravitational waves for LIGO and VIRGO. These detectors will open a new window on the Universe; the proposed project will open a new field in gravitational wave astrophysics to interpret the sources. We also explore implications for electromagnetic observations.
Project acronym GENECLOCKS
Project Reconstructing a dated tree of life using phylogenetic incongruence
Researcher (PI) Gergely Janos SZOLLOSI
Summary With the advent of genome-scale sequencing, molecular phylogeny, which reconstructs gene trees from homologous sequences, has reached an impasse. Instead of answering open questions, new genomes have reignited old debates. The problem is clear, gene trees are not species trees, each is the unique result of series of evolutionary events. If, however, we model these differences in the context of a common species tree, we can access a wealth of information on genome evolution and the diversification of species that is not available to traditional methods. For example, as horizontal gene transfer (HGT) can only occur between coexisting species, HGTs provide information on the order of speciations. When HGT is rare, lineage sorting can generate incongruence between gene trees and the dating problem can be formulated in terms of biologically meaningful parameters (such as population size), that are informative on the rate of evolution and hence invaluable to molecular dating. My first goal is to develop methods that systematically extract information on the pattern and timing of genomic evolution by explaining differences between gene trees. This will allow us to, for the first time, reconstruct a dated tree of life from genome-scale data. We will use parallel programming to maximise the number of genomes analysed. My second goal is to apply these methods to open problems, e.g.: i) to resolve the timing of microbial evolution and its relationship to Earth history, where the extreme paucity of fossils limits the use of molecular dating methods, by using HGT events as "molecular fossils"; ii) to reconstruct rooted phylogenies from complete genomes and harness phylogenetic incongruence to answer long standing questions, such as the of diversification of animals or the position of eukaryotes among archaea; and iii) for eukaryotic groups such as Fungi, where evidence of significant amounts of HGT is emerging our methods will also allow the quantification of the extent of HGT.
With the advent of genome-scale sequencing, molecular phylogeny, which reconstructs gene trees from homologous sequences, has reached an impasse. Instead of answering open questions, new genomes have reignited old debates. The problem is clear, gene trees are not species trees, each is the unique result of series of evolutionary events. If, however, we model these differences in the context of a common species tree, we can access a wealth of information on genome evolution and the diversification of species that is not available to traditional methods. For example, as horizontal gene transfer (HGT) can only occur between coexisting species, HGTs provide information on the order of speciations. When HGT is rare, lineage sorting can generate incongruence between gene trees and the dating problem can be formulated in terms of biologically meaningful parameters (such as population size), that are informative on the rate of evolution and hence invaluable to molecular dating. My first goal is to develop methods that systematically extract information on the pattern and timing of genomic evolution by explaining differences between gene trees. This will allow us to, for the first time, reconstruct a dated tree of life from genome-scale data. We will use parallel programming to maximise the number of genomes analysed. My second goal is to apply these methods to open problems, e.g.: i) to resolve the timing of microbial evolution and its relationship to Earth history, where the extreme paucity of fossils limits the use of molecular dating methods, by using HGT events as "molecular fossils"; ii) to reconstruct rooted phylogenies from complete genomes and harness phylogenetic incongruence to answer long standing questions, such as the of diversification of animals or the position of eukaryotes among archaea; and iii) for eukaryotic groups such as Fungi, where evidence of significant amounts of HGT is emerging our methods will also allow the quantification of the extent of HGT.
Project acronym HIGHACCTC
Project High-accuracy models in theoretical chemistry
Researcher (PI) Mihály Kállay
Summary Even today, quantum chemical calculations with experimental accuracy are only feasible for small molecules. This statement is especially true if the considered molecule is far from the equilibrium structure, where the overwhelming majority of quantum chemical models break down. The main purpose of this proposal is to develop new quantum chemical methods that are applicable to at least medium-sized molecules and simultaneously provide results sufficiently close to the experimental data and are capable of describing entire potential energy surfaces. The accuracy goal will be achieved through the reduction of the computational cost of high-precision quantum chemical calculations, which are currently practical for molecules of up to 15 atoms. The cost reduction will be accomplished principally by decreasing the number of numerical parameters to be optimized without sacrificing accuracy. To this end, the negligible parameters will be identified and dropped by adopting the corresponding techniques of computer science. The correct behavior of the models for distorted structures will be ensured by developing new approaches that use a linear combination of functions rather than a single function as a starting point for the description of electronic states. Since the programming work associated with the implementation of the proposed schemes is very complex, the project will rely on the automated programming tools previously developed by the proposer. In addition to the outlined challenging tasks, the proposal aims to implement several more straightforward objectives. In particular, the high-accuracy calculations will be extended to molecular properties that are presently not available. Furthermore, the developed methods will be applied to real-life problems, especially in the field of spectroscopy and atmospheric chemistry.
Even today, quantum chemical calculations with experimental accuracy are only feasible for small molecules. This statement is especially true if the considered molecule is far from the equilibrium structure, where the overwhelming majority of quantum chemical models break down. The main purpose of this proposal is to develop new quantum chemical methods that are applicable to at least medium-sized molecules and simultaneously provide results sufficiently close to the experimental data and are capable of describing entire potential energy surfaces. The accuracy goal will be achieved through the reduction of the computational cost of high-precision quantum chemical calculations, which are currently practical for molecules of up to 15 atoms. The cost reduction will be accomplished principally by decreasing the number of numerical parameters to be optimized without sacrificing accuracy. To this end, the negligible parameters will be identified and dropped by adopting the corresponding techniques of computer science. The correct behavior of the models for distorted structures will be ensured by developing new approaches that use a linear combination of functions rather than a single function as a starting point for the description of electronic states. Since the programming work associated with the implementation of the proposed schemes is very complex, the project will rely on the automated programming tools previously developed by the proposer. In addition to the outlined challenging tasks, the proposal aims to implement several more straightforward objectives. In particular, the high-accuracy calculations will be extended to molecular properties that are presently not available. Furthermore, the developed methods will be applied to real-life problems, especially in the field of spectroscopy and atmospheric chemistry.
Project acronym HybridSolarFuels
Project Efficient Photoelectrochemical Transformation of CO2 to Useful Fuels on Nanostructured Hybrid Electrodes
Researcher (PI) Csaba JANAKY
Summary Given that CO2 is a greenhouse gas, using the energy of sunlight to convert CO2 to transportation fuels (such as methanol) represents a value-added approach to the simultaneous generation of alternative fuels and environmental remediation of carbon emissions. Photoelectrochemistry has been proven to be a useful avenue for solar water splitting. CO2 reduction, however, is multi-electron in nature (e.g., 6 e- to methanol) with considerable kinetic barriers to electron transfer. It therefore requires the use of carefully designed electrode surfaces to accelerate e- transfer rates to levels that make practical sense. In addition, novel flow-cell configurations have to be designed to overcome mass transport limitations of this reaction. We are going to design and assemble nanostructured hybrid materials to be simultaneously applied as both adsorber and cathode-material to photoelectrochemically convert CO2 to valuable liquid fuels. The three main goals of this project are to (i) gain fundamental understanding of morphological-, size-, and surface functional group effects on the photoelectrochemical (PEC) behavior at the nanoscale (ii) design and synthesize new functional hybrid materials for PEC CO2 reduction, (iii) develop flow-reactors for PEC CO2 reduction. Rationally designed hybrid nanostructures of large surface area p-type semiconductors (e.g., SiC, CuMO2, or CuPbI3) and N-containing conducting polymers (e.g., polyaniline-based custom designed polymers) will be responsible for: (i) higher photocurrents due to facile charge transfer and better light absorption (ii) higher selectivity towards the formation of liquid fuels due to the adsorption of CO2 on the photocathode (iii) better stability of the photocathode. The challenges are great, but the possible rewards are enormous: performing CO2 adsorption and reduction on the same system may lead to PEC cells which can be deployed directly at the source point of CO2, which would go well beyond the state-of-the-art.
Given that CO2 is a greenhouse gas, using the energy of sunlight to convert CO2 to transportation fuels (such as methanol) represents a value-added approach to the simultaneous generation of alternative fuels and environmental remediation of carbon emissions. Photoelectrochemistry has been proven to be a useful avenue for solar water splitting. CO2 reduction, however, is multi-electron in nature (e.g., 6 e- to methanol) with considerable kinetic barriers to electron transfer. It therefore requires the use of carefully designed electrode surfaces to accelerate e- transfer rates to levels that make practical sense. In addition, novel flow-cell configurations have to be designed to overcome mass transport limitations of this reaction. We are going to design and assemble nanostructured hybrid materials to be simultaneously applied as both adsorber and cathode-material to photoelectrochemically convert CO2 to valuable liquid fuels. The three main goals of this project are to (i) gain fundamental understanding of morphological-, size-, and surface functional group effects on the photoelectrochemical (PEC) behavior at the nanoscale (ii) design and synthesize new functional hybrid materials for PEC CO2 reduction, (iii) develop flow-reactors for PEC CO2 reduction. Rationally designed hybrid nanostructures of large surface area p-type semiconductors (e.g., SiC, CuMO2, or CuPbI3) and N-containing conducting polymers (e.g., polyaniline-based custom designed polymers) will be responsible for: (i) higher photocurrents due to facile charge transfer and better light absorption (ii) higher selectivity towards the formation of liquid fuels due to the adsorption of CO2 on the photocathode (iii) better stability of the photocathode. The challenges are great, but the possible rewards are enormous: performing CO2 adsorption and reduction on the same system may lead to PEC cells which can be deployed directly at the source point of CO2, which would go well beyond the state-of-the-art.
Project acronym KNOWLEDGEFLOWS
Project Channels and Consequences of Knowledge Flows from Developed Economies to Central and Eastern Europe
Researcher (PI) Miklós Koren
Summary In this project, I study how economic development is shaped by cross-country knowledge flows via trade, foreign direct investment (FDI), and other channels. Using novel micro data for several Central and Eastern European (CEE) countries, I measure the quantitative importance of three channels: technical knowledge embodied in imported machinery, technical and organizational knowledge embodied in expatriate managers, and disembodied knowledge transfers taking place within multinational firms. I then analyze what impact foreign knowledge has on the firms and the workers of the host economy, and what are its implications for aggregate productivity and income inequality. The project relies on several existing databases for Hungary and Romania, which will be complemented with newly purchased, collected and compiled data. The outcome of the project will be seven research studies and a collection of firm-level data sets covering CEE countries, including a large cross-country firm survey on the local supplier linkages of multinational companies. My proposed project improves upon the state of the art in four ways. First, as a comprehensive study using novel micro data, it uncovers new facts about the relative importance of the channels of knowledge flows. Second, it improves the identification of causal effects relative to existing studies by exploiting the detailed micro data. Third, it uses the micro estimates to quantify the aggregate impact of foreign knowledge on the economy. Fourth, it discusses how foreign knowledge affects different firms and workers differently, and, more specifically, how it may contribute to income inequality. More broadly, the research findings help evaluate the relative efficacy of trade, FDI, and immigration policies in promoting economic growth and can inform theories about the channels and barriers of productivity convergence.
In this project, I study how economic development is shaped by cross-country knowledge flows via trade, foreign direct investment (FDI), and other channels. Using novel micro data for several Central and Eastern European (CEE) countries, I measure the quantitative importance of three channels: technical knowledge embodied in imported machinery, technical and organizational knowledge embodied in expatriate managers, and disembodied knowledge transfers taking place within multinational firms. I then analyze what impact foreign knowledge has on the firms and the workers of the host economy, and what are its implications for aggregate productivity and income inequality. The project relies on several existing databases for Hungary and Romania, which will be complemented with newly purchased, collected and compiled data. The outcome of the project will be seven research studies and a collection of firm-level data sets covering CEE countries, including a large cross-country firm survey on the local supplier linkages of multinational companies. My proposed project improves upon the state of the art in four ways. First, as a comprehensive study using novel micro data, it uncovers new facts about the relative importance of the channels of knowledge flows. Second, it improves the identification of causal effects relative to existing studies by exploiting the detailed micro data. Third, it uses the micro estimates to quantify the aggregate impact of foreign knowledge on the economy. Fourth, it discusses how foreign knowledge affects different firms and workers differently, and, more specifically, how it may contribute to income inequality. More broadly, the research findings help evaluate the relative efficacy of trade, FDI, and immigration policies in promoting economic growth and can inform theories about the channels and barriers of productivity convergence.
Project acronym MOLINFLAM
Project Molecular dissection of inflammatory pathways
Researcher (PI) Attila Mocsai
Host Institution (HI) SEMMELWEIS EGYETEM
Summary Inflammatory diseases are highly prevalent, often chronic diseases that cause diminished quality of life and are connected with major causes of death in Western societies. Despite their societal impact, their pathomechanism is incompletely understood, hindering development of novel therapeutic strategies. In particular, little is known about the intracellular signal transduction processes involved in the tissue destruction phase of aggressive autoimmune diseases such as rheumatoid arthritis. The present proposal aims to clarify this issue using in vivo and in vitro studies on genetically manipulated mice. During the proposed studies, mice deficient in various signal transduction molecules such as Syk, PLCg2, Gab2 and p190 RhoGAPs will be used to test their contribution to inflammatory responses. In vitro studies will test the activation of major effector cells of inflammation (neutrophils, macrophages and osteoclasts) while in vivo studies will utilize mouse models such as autoantibody- and cytokine-induced inflammatory arthritis or autoantibody-induced glomerulonephritis. Further studies will be performed to test the contribution of the above signaling molecules to disease pathogenesis in a lineage-restricted manner, using the Cre-lox approach. Finally, wild type and mutant versions of the signaling molecules tested will be retrovirally re-expressed into the relevant knockout hematopoietic stem cells in vivo to allow structure-function studies during in vivo inflammation. Two novel transgenic strains and a knock-in (floxed) mutant will also be generated during the course of the project. Using state-of-the-art approaches and techniques, this project will provide information at unprecedented molecular detail on signal transduction mechanisms involved in inflammatory diseases, and is expected to point to possible future targets of novel anti-inflammatory therapies.
Inflammatory diseases are highly prevalent, often chronic diseases that cause diminished quality of life and are connected with major causes of death in Western societies. Despite their societal impact, their pathomechanism is incompletely understood, hindering development of novel therapeutic strategies. In particular, little is known about the intracellular signal transduction processes involved in the tissue destruction phase of aggressive autoimmune diseases such as rheumatoid arthritis. The present proposal aims to clarify this issue using in vivo and in vitro studies on genetically manipulated mice. During the proposed studies, mice deficient in various signal transduction molecules such as Syk, PLCg2, Gab2 and p190 RhoGAPs will be used to test their contribution to inflammatory responses. In vitro studies will test the activation of major effector cells of inflammation (neutrophils, macrophages and osteoclasts) while in vivo studies will utilize mouse models such as autoantibody- and cytokine-induced inflammatory arthritis or autoantibody-induced glomerulonephritis. Further studies will be performed to test the contribution of the above signaling molecules to disease pathogenesis in a lineage-restricted manner, using the Cre-lox approach. Finally, wild type and mutant versions of the signaling molecules tested will be retrovirally re-expressed into the relevant knockout hematopoietic stem cells in vivo to allow structure-function studies during in vivo inflammation. Two novel transgenic strains and a knock-in (floxed) mutant will also be generated during the course of the project. Using state-of-the-art approaches and techniques, this project will provide information at unprecedented molecular detail on signal transduction mechanisms involved in inflammatory diseases, and is expected to point to possible future targets of novel anti-inflammatory therapies.
Project acronym Multicellularity
Project The genetic basis of the convergent evolution of fungal multicellularity
Researcher (PI) Laszlo NAGY
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA SZEGEDIBIOLOGIAI KUTATOKOZPONT
Summary The evolution of multicellularity (MC) has been one of the major transitions in the history of life. Despite immense interest in its evolutionary origins, the genomic changes leading to the emergence of MC, especially that of complex MC (differentiated 3-dimensional structures) are poorly known. Previous comparative genomics projects aiming to understand the genetic bases of MC in one way or another relied on gene content-based analyses. However, a pattern emerging from these studies is that gene content provides only an incomplete explanation for the evolution of MC even at ancient timescales. We hypothesize that besides gene duplications, changes to cis-regulatory elements and gene expression patterns (including protein isoforms) have significantly contributed to the evolution of MC. To test this hypothesis, we will deploy a combination of computational methods, phylogenomics, comparative transcriptomics and genome-wide assays of regulatory elements. Our research focuses on fungi as a model system, where complex MC evolved convergently and in subsequent two steps. Fungi are ideal models to tackle this question for several reasons: a) multicellularity in fungi evolved multiple times, b) there are rich genomic resources (>500 complete genomes), c) complex multicellular structures can be routinely grown in the lab and d) genetic manipulations are feasible for several cornerstone species. We set out to examine which genes participate in the building of simple and complex multicellular structures and whether the evolution of regulome complexity and gene expression patterns can explain the evolution of MC better than can traditionally assayed sources of genetic innovations (e.g. gene duplications). Ultimately, our goal is to reach a general synthesis on the genetic bases of the evolution of MC and that of organismal complexity.
The evolution of multicellularity (MC) has been one of the major transitions in the history of life. Despite immense interest in its evolutionary origins, the genomic changes leading to the emergence of MC, especially that of complex MC (differentiated 3-dimensional structures) are poorly known. Previous comparative genomics projects aiming to understand the genetic bases of MC in one way or another relied on gene content-based analyses. However, a pattern emerging from these studies is that gene content provides only an incomplete explanation for the evolution of MC even at ancient timescales. We hypothesize that besides gene duplications, changes to cis-regulatory elements and gene expression patterns (including protein isoforms) have significantly contributed to the evolution of MC. To test this hypothesis, we will deploy a combination of computational methods, phylogenomics, comparative transcriptomics and genome-wide assays of regulatory elements. Our research focuses on fungi as a model system, where complex MC evolved convergently and in subsequent two steps. Fungi are ideal models to tackle this question for several reasons: a) multicellularity in fungi evolved multiple times, b) there are rich genomic resources (>500 complete genomes), c) complex multicellular structures can be routinely grown in the lab and d) genetic manipulations are feasible for several cornerstone species. We set out to examine which genes participate in the building of simple and complex multicellular structures and whether the evolution of regulome complexity and gene expression patterns can explain the evolution of MC better than can traditionally assayed sources of genetic innovations (e.g. gene duplications). Ultimately, our goal is to reach a general synthesis on the genetic bases of the evolution of MC and that of organismal complexity.
Project acronym NanoFab2D
Project Novel 2D quantum device concepts enabled by sub-nanometre precision nanofabrication
Researcher (PI) Levente Tapaszto
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA ENERGIATUDOMANYI KUTATOKOZPONT
Summary In today's electronics, the information storage and processing are performed by independent technologies. The information-processing is based on semiconductor (silicon) devices, while non-volatile data storage relies on ferromagnetic metals. Integrating these tasks on a single chip and within the same material technology would enable disruptively new device concepts opening the way towards ultra-high speed electronic circuits. Due to the unique versatility of its electronic and magnetic properties, graphene has a strong potential as a platform for the implementation of such devices. By engineering their structure at the atomic level, graphene nanostructures of metallic, semiconducting, as well as magnetic properties can be realized. Here we propose that the unmatched precision and full edge orientation control of our STM-based nanofabrication technique enables the reliable implementation of such graphene nanostructures, as well as their complex, functional networks. In particular, we propose to experimentally demonstrate the feasibility of (1) semiconductor graphene nanostructures based on the quantum confinement effect, (2) spin-based devices from graphene nanostructures with magnetic edges, as well as (3) novel operation principles based on the interplay of the electronic and spin-degrees of freedom. We propose to demonstrate the electrical control of magnetism in graphene nanostructures, as well as a novel switching mechanism for graphene field effect transistors induced by the transition between two magnetic edge configurations. Exploiting such novel operation mechanisms in graphene nanostructure engineered at the atomic scale is expected to lay the foundations of disruptively new device concepts combining electronic and spin-based mechanisms that can overcome some of the fundamental limitations of today's electronics.
In today's electronics, the information storage and processing are performed by independent technologies. The information-processing is based on semiconductor (silicon) devices, while non-volatile data storage relies on ferromagnetic metals. Integrating these tasks on a single chip and within the same material technology would enable disruptively new device concepts opening the way towards ultra-high speed electronic circuits. Due to the unique versatility of its electronic and magnetic properties, graphene has a strong potential as a platform for the implementation of such devices. By engineering their structure at the atomic level, graphene nanostructures of metallic, semiconducting, as well as magnetic properties can be realized. Here we propose that the unmatched precision and full edge orientation control of our STM-based nanofabrication technique enables the reliable implementation of such graphene nanostructures, as well as their complex, functional networks. In particular, we propose to experimentally demonstrate the feasibility of (1) semiconductor graphene nanostructures based on the quantum confinement effect, (2) spin-based devices from graphene nanostructures with magnetic edges, as well as (3) novel operation principles based on the interplay of the electronic and spin-degrees of freedom. We propose to demonstrate the electrical control of magnetism in graphene nanostructures, as well as a novel switching mechanism for graphene field effect transistors induced by the transition between two magnetic edge configurations. Exploiting such novel operation mechanisms in graphene nanostructure engineered at the atomic scale is expected to lay the foundations of disruptively new device concepts combining electronic and spin-based mechanisms that can overcome some of the fundamental limitations of today's electronics.
Project acronym NETWORK EVOLUTION
Project Integrated evolutionary analyses of genetic and drug interaction networks in yeast
Researcher (PI) Csaba Pal
Summary The ability of cellular systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process both at the molecular and evolutionary level. There are both physiological and evolutionary reasonings why mutations often have limited impact on cellular growth. First, perturbations that hit one target often have no effect on the overall performance of a complex system (such as metabolic networks), as perturbations can be adjusted by reorganizing fluxes in metabolic networks, or changing regulation and expression of genes. Second, due to the fast evolvability of microbes, the effect of a perturbation can readily be alleviated by the evolution of compensatory mutations at other sites of the network. Understanding the extent of intrinsic and evolved robustness in cellular systems demands integrated analyses that combine functional genomics and computational systems biology with microbial evolutionary experiments. In collaboration with several leading research teams in the field, we plan to investigate the following issues. First, we will ask how accurately genome-scale metabolic network models can predict the impact of genetic deletions and other non-heritable perturbations. Second, to understand how the impact of genetic and drug perturbations can be mitigated during evolution, we will pursue a large-scale lab evolutionary protocol, and compare the results with predictions of computational models. Our work may suggest avenues of research on the general rules of acquired drug resistance in microbes.
The ability of cellular systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process both at the molecular and evolutionary level. There are both physiological and evolutionary reasonings why mutations often have limited impact on cellular growth. First, perturbations that hit one target often have no effect on the overall performance of a complex system (such as metabolic networks), as perturbations can be adjusted by reorganizing fluxes in metabolic networks, or changing regulation and expression of genes. Second, due to the fast evolvability of microbes, the effect of a perturbation can readily be alleviated by the evolution of compensatory mutations at other sites of the network. Understanding the extent of intrinsic and evolved robustness in cellular systems demands integrated analyses that combine functional genomics and computational systems biology with microbial evolutionary experiments. In collaboration with several leading research teams in the field, we plan to investigate the following issues. First, we will ask how accurately genome-scale metabolic network models can predict the impact of genetic deletions and other non-heritable perturbations. Second, to understand how the impact of genetic and drug perturbations can be mitigated during evolution, we will pursue a large-scale lab evolutionary protocol, and compare the results with predictions of computational models. Our work may suggest avenues of research on the general rules of acquired drug resistance in microbes.
Project acronym NETWORKS
Project Economic Allocations in Social Networks: Evidence and Theory
Researcher (PI) Adam Gyorgy Szeidl
Summary Social networks affect many economic interactions, and the social capital embedded in them may help explain broad, macro level outcomes. A recent theory literature develops models of economic allocations in networks. But at this point, we have little evidence on which network mechanisms are most important in practice, how networks interact with markets, and how these micro forces translate into aggregate outcomes. In this proposal I combine micro level measurement with theory to evaluate various mechanisms through which networks affect economic allocations. I explore this theme in four domains. (1) Borrowing and informal insurance in development. I measure the value of connections for borrowing, and study how transfers propagate through the network using field experiments in Peru. (2) Peer effects and the social multiplier. In field experiments I measure financial and peer-based incentives, and how they reinforce each other. I also measure knowledge diffusion about exporting in corporate networks, and the resulting multiplier effect of reducing trade barriers. (3) Information aggregation. I measure how different pieces of information are filtered and aggregated in the social network. (4) Favouritism. I study the economic causes and consequences of favouring friends in a field experiment. I also measure economic misallocation resulting from politicians favouring connected firms in Hungarian data, and the cost to aggregate productivity. In all projects, my measurement emphasizes causality through field experiments and a unique firm level dataset with many sources of variation. Estimating models allows me to contrast theories and generalize the empirical findings. The results will help evaluate the importance of social networks for microeconomic and aggregate allocations, yield lessons on how organizations and policies leverage social mechanisms, and may open a new research area on mechanism design with network effects.
Social networks affect many economic interactions, and the social capital embedded in them may help explain broad, macro level outcomes. A recent theory literature develops models of economic allocations in networks. But at this point, we have little evidence on which network mechanisms are most important in practice, how networks interact with markets, and how these micro forces translate into aggregate outcomes. In this proposal I combine micro level measurement with theory to evaluate various mechanisms through which networks affect economic allocations. I explore this theme in four domains. (1) Borrowing and informal insurance in development. I measure the value of connections for borrowing, and study how transfers propagate through the network using field experiments in Peru. (2) Peer effects and the social multiplier. In field experiments I measure financial and peer-based incentives, and how they reinforce each other. I also measure knowledge diffusion about exporting in corporate networks, and the resulting multiplier effect of reducing trade barriers. (3) Information aggregation. I measure how different pieces of information are filtered and aggregated in the social network. (4) Favouritism. I study the economic causes and consequences of favouring friends in a field experiment. I also measure economic misallocation resulting from politicians favouring connected firms in Hungarian data, and the cost to aggregate productivity. In all projects, my measurement emphasizes causality through field experiments and a unique firm level dataset with many sources of variation. Estimating models allows me to contrast theories and generalize the empirical findings. The results will help evaluate the importance of social networks for microeconomic and aggregate allocations, yield lessons on how organizations and policies leverage social mechanisms, and may open a new research area on mechanism design with network effects.
Project acronym OscillInterference
Project Therapeutic Mechanisms and Long Term Effects of Directed Transcranial Alternating Current Stimulation in Epileptic Seizures
Researcher (PI) Antal Berényi
Summary A significant proportion of patients with epilepsy are refractive to pharmaceutical treatments. Recurrent, untreated epileptic seizures are associated with risk of adverse neurological, cognitive, and psychological outcomes. Despite years of study, there are still significant barriers to the management of these disorders. In my proposal I advance the hypothesis that time-targeted perturbation of neural network oscillations by transcranial electric stimulation (TES) decreases the duration of seizures. I hypothesize further that spatially focused TES and chronically applied TES intervention can also permanently reduce seizure occurrence. Our specific aims are designed to perform in vivo studies in rodent models of two seizure types (absence seizures and complex partial seizures) to evaluate the effectiveness of TES in abrogating pathologic network activity, and to use high resolution recording techniques and optogenetical methods to assess the neural mechanisms involved. Our results may help to establish general principles of the diverse epilepsy pathophysiology and introduce novel therapeutic approaches. We will establish a focal TES stimulation protocol to selectively interfere with brain regions previously identified as key structures in the pathomechanism of epilepsy. The deliverables of these experiments will make a significant advancement in the understanding of the pathomechanisms of these disorders, and will offer a new alternative treatment option as a complimentary therapeutic approach to the state of the art pharmaceutical products. The methods used in this project are unique and advanced as the first attempt to perform 512 channel extracellular recordings in the behaving animal to investigate the evolution of epileptic seizures at the neuronal network and cellular levels and by achieving spatially selective TES. The combination of these methods are deployed for both understanding the mechanisms of seizure evolution, and termination of seizures.
A significant proportion of patients with epilepsy are refractive to pharmaceutical treatments. Recurrent, untreated epileptic seizures are associated with risk of adverse neurological, cognitive, and psychological outcomes. Despite years of study, there are still significant barriers to the management of these disorders. In my proposal I advance the hypothesis that time-targeted perturbation of neural network oscillations by transcranial electric stimulation (TES) decreases the duration of seizures. I hypothesize further that spatially focused TES and chronically applied TES intervention can also permanently reduce seizure occurrence. Our specific aims are designed to perform in vivo studies in rodent models of two seizure types (absence seizures and complex partial seizures) to evaluate the effectiveness of TES in abrogating pathologic network activity, and to use high resolution recording techniques and optogenetical methods to assess the neural mechanisms involved. Our results may help to establish general principles of the diverse epilepsy pathophysiology and introduce novel therapeutic approaches. We will establish a focal TES stimulation protocol to selectively interfere with brain regions previously identified as key structures in the pathomechanism of epilepsy. The deliverables of these experiments will make a significant advancement in the understanding of the pathomechanisms of these disorders, and will offer a new alternative treatment option as a complimentary therapeutic approach to the state of the art pharmaceutical products. The methods used in this project are unique and advanced as the first attempt to perform 512 channel extracellular recordings in the behaving animal to investigate the evolution of epileptic seizures at the neuronal network and cellular levels and by achieving spatially selective TES. The combination of these methods are deployed for both understanding the mechanisms of seizure evolution, and termination of seizures.
Project acronym PARAMTIGHT
Project Parameterized complexity and the search for tight complexity results
Researcher (PI) Dániel Marx
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA SZAMITASTECHNIKAI ES AUTOMATIZALASI KUTATOINTEZET
Summary The joint goal of theoretical research in algorithms and computational complexity is to discover all the relevant algorithmic techniques in a problem domain and prove the optimality of these techniques. We propose that the search for such tight results should be done by a combined exploration of the dimensions running time, quality of solution, and generality. Furthermore, the theory of parameterized complexity provides a framework for this exploration. Parameterized complexity is a theory whose goal is to produce efficient algorithms for hard combinatorial problems using a multi-dimensional analysis of the running time. Instead of expressing the running time as a function of the input size only (as it is done in classical complexity theory), parameterized complexity tries to find algorithms whose running time is polynomial in the input size, but exponential in one or more well-defined parameters of the input instance. The first objective of the project is to go beyond the state of the art in the complexity and algorithmic aspects of parameterized complexity in order to turn it into a theory producing tight optimality results. With such theory at hand, we can start the exploration of other dimensions and obtain tight optimality results in a larger context. Our is goal is being able to prove in a wide range of settings that we understand all the algorithmic ideas and their optimality.
The joint goal of theoretical research in algorithms and computational complexity is to discover all the relevant algorithmic techniques in a problem domain and prove the optimality of these techniques. We propose that the search for such tight results should be done by a combined exploration of the dimensions running time, quality of solution, and generality. Furthermore, the theory of parameterized complexity provides a framework for this exploration. Parameterized complexity is a theory whose goal is to produce efficient algorithms for hard combinatorial problems using a multi-dimensional analysis of the running time. Instead of expressing the running time as a function of the input size only (as it is done in classical complexity theory), parameterized complexity tries to find algorithms whose running time is polynomial in the input size, but exponential in one or more well-defined parameters of the input instance. The first objective of the project is to go beyond the state of the art in the complexity and algorithmic aspects of parameterized complexity in order to turn it into a theory producing tight optimality results. With such theory at hand, we can start the exploration of other dimensions and obtain tight optimality results in a larger context. Our is goal is being able to prove in a wide range of settings that we understand all the algorithmic ideas and their optimality.
Project acronym PreLog
Project Precursors of logical reasoning in human infants
Researcher (PI) Erno Teglas
Summary There is no other field that is more controversial in psychology than that of human reasoning. This project advances a novel theoretical framework focused on the nature and the origins of rationality and could potentially resolve some of these controversies. Theories targeting the mechanisms that allow rational inferences have defined rationality as a function of how much reasoning adheres to formal rules of probability calculus and logic. Classical research with adults and older children collected a large amount of data both in favor and against human rationality, suggesting that reasoning abilities follow a slow maturation. Recent findings on infants' probabilistic reasoning, including my own earlier research, however, do not support this view. Already preverbal infants seem to form expectations about probabilistic events in accordance with Bayesian rules of inference (Téglás et al, 2011). Here I argue for a similar paradigm change in a related domain, that of deductive reasoning. In contrast to earlier accounts, I propose that even preverbal infants may possess a core set of logical operations that empower them with sophisticated inferential abilities. First, I focus on the representational precursors of this competence. I argue that infants recruit specific abilities to exploit the conceptual structure of specific event categories that enable them to form logical representations. Thus, information could be stored in a format that can potentially serve as input for subsequent inferences. Further, I will investigate infants' core logical operations and test how they integrate multiple steps of inferences. This system - indispensable for integrating different bits of knowledge - helps infants to discover information that was not actually present in the input. Such investigations, informed also by adequate neuropsychological evidence would thus contribute to understand the unique nature of human rationality.
There is no other field that is more controversial in psychology than that of human reasoning. This project advances a novel theoretical framework focused on the nature and the origins of rationality and could potentially resolve some of these controversies. Theories targeting the mechanisms that allow rational inferences have defined rationality as a function of how much reasoning adheres to formal rules of probability calculus and logic. Classical research with adults and older children collected a large amount of data both in favor and against human rationality, suggesting that reasoning abilities follow a slow maturation. Recent findings on infants' probabilistic reasoning, including my own earlier research, however, do not support this view. Already preverbal infants seem to form expectations about probabilistic events in accordance with Bayesian rules of inference (Téglás et al, 2011). Here I argue for a similar paradigm change in a related domain, that of deductive reasoning. In contrast to earlier accounts, I propose that even preverbal infants may possess a core set of logical operations that empower them with sophisticated inferential abilities. First, I focus on the representational precursors of this competence. I argue that infants recruit specific abilities to exploit the conceptual structure of specific event categories that enable them to form logical representations. Thus, information could be stored in a format that can potentially serve as input for subsequent inferences. Further, I will investigate infants' core logical operations and test how they integrate multiple steps of inferences. This system - indispensable for integrating different bits of knowledge - helps infants to discover information that was not actually present in the input. Such investigations, informed also by adequate neuropsychological evidence would thus contribute to understand the unique nature of human rationality.
Project acronym QCDTHERMO
Project QCD thermodynamics on the lattice
Researcher (PI) Sándor Katz
Summary Quantum Chromodynamics (QCD) at finite temperature and non-zero density describes phenomena relevant to the early universe and heavy-ion collisions. The applicability of perturbation theory is limited to large temperatures and densities. We plan to use lattice simulations to study QCD thermodynamics. There are different regularizations of QCD on the lattice. The computationally most effective one is the staggered formulation, while Wilson or chiral fermions are theoretically more established. We have to distinguish studies at vanishing baryon densities from the ones concerning non-zero density. At vanishing densities the order of the QCD transition between the hadronic phase and the quark-gluon plasma was studied using staggered fermions. In the physical, continuum limit the transition was found to be a crossover. The transition temperature has also been determined. These studies should be and will be extended using Wilson and chiral fermions. This way the staggered results can be checked. At non-vanishing densities direct lattice simulations are prohibited by the infamous sign problem. Recently the multi-parameter reweighting method was developed to study moderate densities using simulations at zero baryon density. The phase diagram as well as the critical point of QCD was determined using staggered fermions with a single lattice resolution. We plan to extend these studies in two ways. In the first step finer lattices will be studied with staggered fermions and a continuum extrapolation will be attempted. In the second step Wilson and possibly chiral fermions will be used. At large densities where the sign problem is the most severe the density of states method will be used. Based on our experience with PC clusters we will build a new, high performance cluster to achieve these goals. The establishment of a strong new research group certainly will improve the competitivity of the European lattice community.
Quantum Chromodynamics (QCD) at finite temperature and non-zero density describes phenomena relevant to the early universe and heavy-ion collisions. The applicability of perturbation theory is limited to large temperatures and densities. We plan to use lattice simulations to study QCD thermodynamics. There are different regularizations of QCD on the lattice. The computationally most effective one is the staggered formulation, while Wilson or chiral fermions are theoretically more established. We have to distinguish studies at vanishing baryon densities from the ones concerning non-zero density. At vanishing densities the order of the QCD transition between the hadronic phase and the quark-gluon plasma was studied using staggered fermions. In the physical, continuum limit the transition was found to be a crossover. The transition temperature has also been determined. These studies should be and will be extended using Wilson and chiral fermions. This way the staggered results can be checked. At non-vanishing densities direct lattice simulations are prohibited by the infamous sign problem. Recently the multi-parameter reweighting method was developed to study moderate densities using simulations at zero baryon density. The phase diagram as well as the critical point of QCD was determined using staggered fermions with a single lattice resolution. We plan to extend these studies in two ways. In the first step finer lattices will be studied with staggered fermions and a continuum extrapolation will be attempted. In the second step Wilson and possibly chiral fermions will be used. At large densities where the sign problem is the most severe the density of states method will be used. Based on our experience with PC clusters we will build a new, high performance cluster to achieve these goals. The establishment of a strong new research group certainly will improve the competitivity of the European lattice community.
Project acronym REPCOLLAB
Project Representational preconditions for understanding other minds in the service of human collaboration and social learning
Researcher (PI) Agnes Melinda Kovacs
Summary The central aim of the proposed research project is to systematically explore the empirical implications of a novel theoretical approach to the early representational preconditions and the functional structure of the mechanisms dedicated for understanding other minds. We aim to explore and shed new theoretical light on the basic cognitive and brain mechanisms of the human social mind. One of these mechanisms that has received much attention by earlier approaches to 'theory-of-mind' research concerns the ability to infer and represent the mental states of others. Standard theories and research in the last twenty five years have suggested that representing other's beliefs is an effortful and late developing capacity (Wellman et al., 2001) whose main function is to explain others' behavior. Here we advance and propose to explore a new theoretical perspective according to which the mechanisms of mental state monitoring and representation involve primarily automatic and effortless processes grounded in on-line cooperative social interactions. Our approach is part of an on-going paradigm change in the field of theory-of-mind research motivated by the recent evidence showing that infants in their second year understand mental states (Onishi & Baillargeon, 2005). Our own research has gone a significant step further by demonstrating that these mechanisms are present as early as 7 month of age, and by showing that both young infants and adults seem to automatically compute others' beliefs even in situations where they are not required to do so (Kovács et al., 2010). The present project explores the functional sub-components and triggering conditions of young infants' powerful belief computation abilities and to chart their developmental unfolding. Furthermore, we shall explore the implications of the new theoretical proposal that this dedicated system presupposes as its proper domain the on-going collaborative and communicative interactions.
The central aim of the proposed research project is to systematically explore the empirical implications of a novel theoretical approach to the early representational preconditions and the functional structure of the mechanisms dedicated for understanding other minds. We aim to explore and shed new theoretical light on the basic cognitive and brain mechanisms of the human social mind. One of these mechanisms that has received much attention by earlier approaches to 'theory-of-mind' research concerns the ability to infer and represent the mental states of others. Standard theories and research in the last twenty five years have suggested that representing other's beliefs is an effortful and late developing capacity (Wellman et al., 2001) whose main function is to explain others' behavior. Here we advance and propose to explore a new theoretical perspective according to which the mechanisms of mental state monitoring and representation involve primarily automatic and effortless processes grounded in on-line cooperative social interactions. Our approach is part of an on-going paradigm change in the field of theory-of-mind research motivated by the recent evidence showing that infants in their second year understand mental states (Onishi & Baillargeon, 2005). Our own research has gone a significant step further by demonstrating that these mechanisms are present as early as 7 month of age, and by showing that both young infants and adults seem to automatically compute others' beliefs even in situations where they are not required to do so (Kovács et al., 2010). The present project explores the functional sub-components and triggering conditions of young infants' powerful belief computation abilities and to chart their developmental unfolding. Furthermore, we shall explore the implications of the new theoretical proposal that this dedicated system presupposes as its proper domain the on-going collaborative and communicative interactions.
Project acronym SACCRED
Project Structured ACCREtion Disks: initial conditions for planet formation in the time domain
Researcher (PI) Ágnes KÓSPÁL
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA CSILLAGASZATI ES FOLDTUDOMANYI KUTATOKOZPONT
Summary In this ERC Starting Grant, I propose an ambitious research program to target important challenges in predicting realistic initial conditions for the planet formation process. I will perform a large systematic study of the accretion-driven eruptions of newborn stars, and evaluate their influence on the structure, composition, and chemistry of the terrestrial planet forming zone in the circumstellar disk. The research will focus on three main questions: - How does the mass accretion proceed in realistic, structured, non-axisymmetric disks? - What physical mechanisms explain the accretion-driven eruptions? - What is the effect of the eruptions on the disk? My new research group will study young eruptive stars, pre-main sequence objects prone to episodes of extremely powerful accretion-driven outbursts, and combine new observations, state-of-the-art numerical modelling, and information from the literature. With a novel concept, we will first model the time-dependence of mass accretion in circumstellar disks, taking into account the latest observational results on inhomogeneous disk structure, and determine what fraction of young stellar objects is susceptible to high mass accretion peaks. Next, we will revise the paradigm of the eruptive phenomenon, compelled by recently discovered young eruptive stars whose outbursts are inconsistent with current outburst theories. Finally, we will determine the impact of accretion-driven eruptions on the disk, by considering the increased external irradiation, internal accretion heating, and stellar winds. With my experience and track record, I am in a position to comprehensively synthesize existing and newly acquired information to reach the proposed goals. The expected outcome of the ERC project is a conclusive demonstration of the ubiquity and profound impact of episodic accretion on disk structure, providing the initial physical conditions for disk evolution and planet formation models.
In this ERC Starting Grant, I propose an ambitious research program to target important challenges in predicting realistic initial conditions for the planet formation process. I will perform a large systematic study of the accretion-driven eruptions of newborn stars, and evaluate their influence on the structure, composition, and chemistry of the terrestrial planet forming zone in the circumstellar disk. The research will focus on three main questions: - How does the mass accretion proceed in realistic, structured, non-axisymmetric disks? - What physical mechanisms explain the accretion-driven eruptions? - What is the effect of the eruptions on the disk? My new research group will study young eruptive stars, pre-main sequence objects prone to episodes of extremely powerful accretion-driven outbursts, and combine new observations, state-of-the-art numerical modelling, and information from the literature. With a novel concept, we will first model the time-dependence of mass accretion in circumstellar disks, taking into account the latest observational results on inhomogeneous disk structure, and determine what fraction of young stellar objects is susceptible to high mass accretion peaks. Next, we will revise the paradigm of the eruptive phenomenon, compelled by recently discovered young eruptive stars whose outbursts are inconsistent with current outburst theories. Finally, we will determine the impact of accretion-driven eruptions on the disk, by considering the increased external irradiation, internal accretion heating, and stellar winds. With my experience and track record, I am in a position to comprehensively synthesize existing and newly acquired information to reach the proposed goals. The expected outcome of the ERC project is a conclusive demonstration of the ubiquity and profound impact of episodic accretion on disk structure, providing the initial physical conditions for disk evolution and planet formation models.
Project acronym SYLO
Project Spin dynamics and transport at the quantum edge in low dimensional nanomaterials
Researcher (PI) Ferenc Simon
Summary Sustainable development in information technology calls for an ever increasing information processing and storage capability. A promising route to maintain exponential growth capability, i.e. to keep on the Moore's roadmap, is to turn to the electron spins as information carriers rather than their charge. This field, spintronics, has enormous potential whose exploitation requires solid knowledge in the fundamentals of spin dynamics and spin transport. Herein, novel nanomaterials are suggested for spintronics purposes, such as graphene and single-wall carbon nanotubes (SWCNTs). These, fundamental two- and one-dimensional carbon allotropes are promising candidates for such purposes, carbon being a light element with a low spin-orbit coupling which results in a long spin coherence. There are several fundamental open issues, e.g. the dominant spin orbit coupling mechanism in graphene, whether bulk electron spin resonance can be observed for this material, and the length of the spin diffusion length. For SWCNTs, the ground state of isolated metallic tubes is known to be the Tomonaga-Luttinger liquid (TLL), which greatly limit the spin coherence, but it is at present open whether this state is destroyed when an ensemble of interacting metallic tubes is studied. The decay time and spin symmetry of optical excitations (excitons) in semiconducting SWCNTs is yet unknown. Our goal is to pursue electron spin resonance in graphene and carbon nanotubes and to perform optically detected magnetic resonance in carbon nanotubes. We will commission a magnetoptical spectrometer with a substantial added value. The expected results are characterization of spin transport capabilities of these materials and understanding of the spin decoherence mechanisms. The PI leads magnetic resonance studies of these materials, shown by his more than 300 citations to this field (the total being over 470) and his 15 Physical Review Letters papers in this field (of which for 9 he is main Author).
Sustainable development in information technology calls for an ever increasing information processing and storage capability. A promising route to maintain exponential growth capability, i.e. to keep on the Moore's roadmap, is to turn to the electron spins as information carriers rather than their charge. This field, spintronics, has enormous potential whose exploitation requires solid knowledge in the fundamentals of spin dynamics and spin transport. Herein, novel nanomaterials are suggested for spintronics purposes, such as graphene and single-wall carbon nanotubes (SWCNTs). These, fundamental two- and one-dimensional carbon allotropes are promising candidates for such purposes, carbon being a light element with a low spin-orbit coupling which results in a long spin coherence. There are several fundamental open issues, e.g. the dominant spin orbit coupling mechanism in graphene, whether bulk electron spin resonance can be observed for this material, and the length of the spin diffusion length. For SWCNTs, the ground state of isolated metallic tubes is known to be the Tomonaga-Luttinger liquid (TLL), which greatly limit the spin coherence, but it is at present open whether this state is destroyed when an ensemble of interacting metallic tubes is studied. The decay time and spin symmetry of optical excitations (excitons) in semiconducting SWCNTs is yet unknown. Our goal is to pursue electron spin resonance in graphene and carbon nanotubes and to perform optically detected magnetic resonance in carbon nanotubes. We will commission a magnetoptical spectrometer with a substantial added value. The expected results are characterization of spin transport capabilities of these materials and understanding of the spin decoherence mechanisms. The PI leads magnetic resonance studies of these materials, shown by his more than 300 citations to this field (the total being over 470) and his 15 Physical Review Letters papers in this field (of which for 9 he is main Author).
Project acronym Tamed Cancer
Project Personalized Cancer Therapy by Model-based Optimal Robust Control Algorithm
Researcher (PI) Levente Adalbert Kovács
Host Institution (HI) OBUDAI EGYETEM
Summary Imagine if tumor growth would be reduced and then kept in a minimal and safe volume in an automated manner and in a personalized way, i.e. cancer drug would be injected using a continuous therapy improving the patient's quality of life. By control engineering approaches it is possible to create model-based strategies for health problems. Artificial pancreas is an adequate example for this, where by continuous glucose measurement device and insulin pump it is possible to improve diabetes treatment. Gaining expertise from this problem, the current proposal focuses on taming the cancer by developing an engineering-based medical therapy. The interdisciplinary approach focuses on modern robust control algorithm development in order to stop the angiogenesis process (i.e. vascular system development) of the tumor; hence, to stop tumor growth, maintaining it in a minimal, "tamed" form. This breakthrough concept could revitalize cancer treatment. It is the right time to do it as some investigations regarding tumor growth modeling have been already done; now, it should be refined by model identification tools and validated on animal trials. The benefit of robust control was already demonstrated in artificial pancreas; hence, it could be adapted to cancer research. The result could end with a personalized healthcare approach for drug-delivery in cancer, improving quality of life, optimizing drug infusion and minimizing treatment costs. This interdisciplinary approach combines control engineering with mathematics, computer science and medical sciences. As a result, the model-based robust control approach envisage refining the currently existing tumor growth modeling aspects, design an optimal control algorithm and extend it by robust control theory to guarantee its general applicability. Based on our research background, validation will be done first in a manually controlled way, but then in an automatic mode to propose it for further human investigations.
Imagine if tumor growth would be reduced and then kept in a minimal and safe volume in an automated manner and in a personalized way, i.e. cancer drug would be injected using a continuous therapy improving the patient's quality of life. By control engineering approaches it is possible to create model-based strategies for health problems. Artificial pancreas is an adequate example for this, where by continuous glucose measurement device and insulin pump it is possible to improve diabetes treatment. Gaining expertise from this problem, the current proposal focuses on taming the cancer by developing an engineering-based medical therapy. The interdisciplinary approach focuses on modern robust control algorithm development in order to stop the angiogenesis process (i.e. vascular system development) of the tumor; hence, to stop tumor growth, maintaining it in a minimal, "tamed" form. This breakthrough concept could revitalize cancer treatment. It is the right time to do it as some investigations regarding tumor growth modeling have been already done; now, it should be refined by model identification tools and validated on animal trials. The benefit of robust control was already demonstrated in artificial pancreas; hence, it could be adapted to cancer research. The result could end with a personalized healthcare approach for drug-delivery in cancer, improving quality of life, optimizing drug infusion and minimizing treatment costs. This interdisciplinary approach combines control engineering with mathematics, computer science and medical sciences. As a result, the model-based robust control approach envisage refining the currently existing tumor growth modeling aspects, design an optimal control algorithm and extend it by robust control theory to guarantee its general applicability. Based on our research background, validation will be done first in a manually controlled way, but then in an automatic mode to propose it for further human investigations.
Project acronym X-CITED!
Project Electronic transitions and bistability: states, switches, transitions and dynamics studied with high-resolution X-ray spectroscopy
Researcher (PI) György Albert Vankó
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA WIGNER FIZIKAI KUTATOKOZPONT
Summary We propose to study transition metal compounds of uncommon transport properties and excitation characteristics applying emerging high-resolution X-ray spectroscopy. The objective is to determine the microscopic origin of the unconventional behaviour of systems with strong electron correlation through systematic investigations, as well as to reveal bistability conditions and excitation characteristics of switchable molecular systems. The main techniques involved are synchrotron radiation (SR)-based spectroscopies, which can explore the fine details of the electronic structure. Besides using existing end stations of SR facilities, we plan to build a portable spectrometer that can be advantageously used both in a laboratory (e.g., with a radioactive source) and at specially dedicated beamlines of SR facilities, in order to benefit from their specializations in extreme conditions and advanced sample environments, in particular unconventional experiments. This spectrometer should also be able to work in a time-resolved mode so that it could address the dynamics of electronic excitations on the attosecond to nanosecond time scale. The suggested work is expected to push high-resolution X-ray spectroscopies toward maturity, which should open up new horizons in electronic structure and dynamics studies of condensed matter research.
We propose to study transition metal compounds of uncommon transport properties and excitation characteristics applying emerging high-resolution X-ray spectroscopy. The objective is to determine the microscopic origin of the unconventional behaviour of systems with strong electron correlation through systematic investigations, as well as to reveal bistability conditions and excitation characteristics of switchable molecular systems. The main techniques involved are synchrotron radiation (SR)-based spectroscopies, which can explore the fine details of the electronic structure. Besides using existing end stations of SR facilities, we plan to build a portable spectrometer that can be advantageously used both in a laboratory (e.g., with a radioactive source) and at specially dedicated beamlines of SR facilities, in order to benefit from their specializations in extreme conditions and advanced sample environments, in particular unconventional experiments. This spectrometer should also be able to work in a time-resolved mode so that it could address the dynamics of electronic excitations on the attosecond to nanosecond time scale. The suggested work is expected to push high-resolution X-ray spectroscopies toward maturity, which should open up new horizons in electronic structure and dynamics studies of condensed matter research.