Project acronym AGALT
Project Asymptotic Geometric Analysis and Learning Theory
Researcher (PI) Shahar Mendelson
Host Institution (HI) TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
Call Details Starting Grant (StG), PE1, ERC-2007-StG
Summary In a typical learning problem one tries to approximate an unknown function by a function from a given class using random data, sampled according to an unknown measure. In this project we will be interested in parameters that govern the complexity of a learning problem. It turns out that this complexity is determined by the geometry of certain sets in high dimension that are connected to the given class (random coordinate projections of the class). Thus, one has to understand the structure of these sets as a function of the dimension - which is given by the cardinality of the random sample. The resulting analysis leads to many theoretical questions in Asymptotic Geometric Analysis, Probability (most notably, Empirical Processes Theory) and Combinatorics, which are of independent interest beyond the application to Learning Theory. Our main goal is to describe the role of various complexity parameters involved in a learning problem, to analyze the connections between them and to investigate the way they determine the geometry of the relevant high dimensional sets. Some of the questions we intend to tackle are well known open problems and making progress towards their solution will have a significant theoretical impact. Moreover, this project should lead to a more complete theory of learning and is likely to have some practical impact, for example, in the design of more efficient learning algorithms.
Summary
In a typical learning problem one tries to approximate an unknown function by a function from a given class using random data, sampled according to an unknown measure. In this project we will be interested in parameters that govern the complexity of a learning problem. It turns out that this complexity is determined by the geometry of certain sets in high dimension that are connected to the given class (random coordinate projections of the class). Thus, one has to understand the structure of these sets as a function of the dimension - which is given by the cardinality of the random sample. The resulting analysis leads to many theoretical questions in Asymptotic Geometric Analysis, Probability (most notably, Empirical Processes Theory) and Combinatorics, which are of independent interest beyond the application to Learning Theory. Our main goal is to describe the role of various complexity parameters involved in a learning problem, to analyze the connections between them and to investigate the way they determine the geometry of the relevant high dimensional sets. Some of the questions we intend to tackle are well known open problems and making progress towards their solution will have a significant theoretical impact. Moreover, this project should lead to a more complete theory of learning and is likely to have some practical impact, for example, in the design of more efficient learning algorithms.
Max ERC Funding
750 000 €
Duration
Start date: 2009-03-01, End date: 2014-02-28
Project acronym ANOPTSETCON
Project Analysis of optimal sets and optimal constants: old questions and new results
Researcher (PI) Aldo Pratelli
Host Institution (HI) FRIEDRICH-ALEXANDER-UNIVERSITAET ERLANGEN NUERNBERG
Call Details Starting Grant (StG), PE1, ERC-2010-StG_20091028
Summary The analysis of geometric and functional inequalities naturally leads to consider the extremal cases, thus
looking for optimal sets, or optimal functions, or optimal constants. The most classical examples are the (different versions of the) isoperimetric inequality and the Sobolev-like inequalities. Much is known about equality cases and best constants, but there are still many questions which seem quite natural but yet have no answer. For instance, it is not known, even in the 2-dimensional space, the answer of a question by Brezis: which set,
among those with a given volume, has the biggest Sobolev-Poincaré constant for p=1? This is a very natural problem, and it appears reasonable that the optimal set should be the ball, but this has never been proved. The interest in problems like this relies not only in the extreme simplicity of the questions and in their classical flavour, but also in the new ideas and techniques which are needed to provide the answers.
The main techniques that we aim to use are fine arguments of symmetrization, geometric constructions and tools from mass transportation (which is well known to be deeply connected with functional inequalities). These are the basic tools that we already used to reach, in last years, many results in a specific direction, namely the search of sharp quantitative inequalities. Our first result, together with Fusco and Maggi, showed what follows. Everybody knows that the set which minimizes the perimeter with given volume is the ball.
But is it true that a set which almost minimizes the perimeter must be close to a ball? The question had been posed in the 1920's and many partial result appeared in the years. In our paper (Ann. of Math., 2007) we proved the sharp result. Many other results of this kind were obtained in last two years.
Summary
The analysis of geometric and functional inequalities naturally leads to consider the extremal cases, thus
looking for optimal sets, or optimal functions, or optimal constants. The most classical examples are the (different versions of the) isoperimetric inequality and the Sobolev-like inequalities. Much is known about equality cases and best constants, but there are still many questions which seem quite natural but yet have no answer. For instance, it is not known, even in the 2-dimensional space, the answer of a question by Brezis: which set,
among those with a given volume, has the biggest Sobolev-Poincaré constant for p=1? This is a very natural problem, and it appears reasonable that the optimal set should be the ball, but this has never been proved. The interest in problems like this relies not only in the extreme simplicity of the questions and in their classical flavour, but also in the new ideas and techniques which are needed to provide the answers.
The main techniques that we aim to use are fine arguments of symmetrization, geometric constructions and tools from mass transportation (which is well known to be deeply connected with functional inequalities). These are the basic tools that we already used to reach, in last years, many results in a specific direction, namely the search of sharp quantitative inequalities. Our first result, together with Fusco and Maggi, showed what follows. Everybody knows that the set which minimizes the perimeter with given volume is the ball.
But is it true that a set which almost minimizes the perimeter must be close to a ball? The question had been posed in the 1920's and many partial result appeared in the years. In our paper (Ann. of Math., 2007) we proved the sharp result. Many other results of this kind were obtained in last two years.
Max ERC Funding
540 000 €
Duration
Start date: 2010-08-01, End date: 2015-07-31
Project acronym ANTHOS
Project Analytic Number Theory: Higher Order Structures
Researcher (PI) Valentin Blomer
Host Institution (HI) GEORG-AUGUST-UNIVERSITAT GOTTINGENSTIFTUNG OFFENTLICHEN RECHTS
Call Details Starting Grant (StG), PE1, ERC-2010-StG_20091028
Summary This is a proposal for research at the interface of analytic number theory, automorphic forms and algebraic geometry. Motivated by fundamental conjectures in number theory, classical problems will be investigated in higher order situations: general number fields, automorphic forms on higher rank groups, the arithmetic of algebraic varieties of higher degree. In particular, I want to focus on
- computation of moments of L-function of degree 3 and higher with applications to subconvexity and/or non-vanishing, as well as subconvexity for multiple L-functions;
- bounds for sup-norms of cusp forms on various spaces and equidistribution of Hecke correspondences;
- automorphic forms on higher rank groups and general number fields, in particular new bounds towards the Ramanujan conjecture;
- a proof of Manin's conjecture for a certain class of singular algebraic varieties.
The underlying methods are closely related; for example, rational points on algebraic varieties
will be counted by a multiple L-series technique.
Summary
This is a proposal for research at the interface of analytic number theory, automorphic forms and algebraic geometry. Motivated by fundamental conjectures in number theory, classical problems will be investigated in higher order situations: general number fields, automorphic forms on higher rank groups, the arithmetic of algebraic varieties of higher degree. In particular, I want to focus on
- computation of moments of L-function of degree 3 and higher with applications to subconvexity and/or non-vanishing, as well as subconvexity for multiple L-functions;
- bounds for sup-norms of cusp forms on various spaces and equidistribution of Hecke correspondences;
- automorphic forms on higher rank groups and general number fields, in particular new bounds towards the Ramanujan conjecture;
- a proof of Manin's conjecture for a certain class of singular algebraic varieties.
The underlying methods are closely related; for example, rational points on algebraic varieties
will be counted by a multiple L-series technique.
Max ERC Funding
1 004 000 €
Duration
Start date: 2010-10-01, End date: 2015-09-30
Project acronym AQSER
Project Automorphic q-series and their application
Researcher (PI) Kathrin Bringmann
Host Institution (HI) UNIVERSITAET ZU KOELN
Call Details Starting Grant (StG), PE1, ERC-2013-StG
Summary This proposal aims to unravel mysteries at the frontier of number theory and other areas of mathematics and physics. The main focus will be to understand and exploit “modularity” of q-hypergeometric series. “Modular forms are functions on the complex plane that are inordinately symmetric.” (Mazur) The motivation comes from the wide-reaching applications of modularity in combinatorics, percolation, Lie theory, and physics (black holes).
The interplay between automorphic forms, q-series, and other areas of mathematics and physics is often two-sided. On the one hand, the other areas provide interesting examples of automorphic objects and predict their behavior. Sometimes these even motivate new classes of automorphic objects which have not been previously studied. On the other hand, knowing that certain generating functions are modular gives one access to deep theoretical tools to prove results in other areas. “Mathematics is a language, and we need that language to understand the physics of our universe.”(Ooguri) Understanding this interplay has attracted attention of researchers from a variety of areas. However, proofs of modularity of q-hypergeometric series currently fall far short of a comprehensive theory to describe the interplay between them and automorphic forms. A recent conjecture of W. Nahm relates the modularity of such series to K-theory. In this proposal I aim to fill this gap and provide a better understanding of this interplay by building a general structural framework enveloping these q-series. For this I will employ new kinds of automorphic objects and embed the functions of interest into bigger families
A successful outcome of the proposed research will open further horizons and also answer open questions, even those in other areas which were not addressed in this proposal; for example the new theory could be applied to better understand Donaldson invariants.
Summary
This proposal aims to unravel mysteries at the frontier of number theory and other areas of mathematics and physics. The main focus will be to understand and exploit “modularity” of q-hypergeometric series. “Modular forms are functions on the complex plane that are inordinately symmetric.” (Mazur) The motivation comes from the wide-reaching applications of modularity in combinatorics, percolation, Lie theory, and physics (black holes).
The interplay between automorphic forms, q-series, and other areas of mathematics and physics is often two-sided. On the one hand, the other areas provide interesting examples of automorphic objects and predict their behavior. Sometimes these even motivate new classes of automorphic objects which have not been previously studied. On the other hand, knowing that certain generating functions are modular gives one access to deep theoretical tools to prove results in other areas. “Mathematics is a language, and we need that language to understand the physics of our universe.”(Ooguri) Understanding this interplay has attracted attention of researchers from a variety of areas. However, proofs of modularity of q-hypergeometric series currently fall far short of a comprehensive theory to describe the interplay between them and automorphic forms. A recent conjecture of W. Nahm relates the modularity of such series to K-theory. In this proposal I aim to fill this gap and provide a better understanding of this interplay by building a general structural framework enveloping these q-series. For this I will employ new kinds of automorphic objects and embed the functions of interest into bigger families
A successful outcome of the proposed research will open further horizons and also answer open questions, even those in other areas which were not addressed in this proposal; for example the new theory could be applied to better understand Donaldson invariants.
Max ERC Funding
1 240 500 €
Duration
Start date: 2014-01-01, End date: 2019-04-30
Project acronym ARMOR-T
Project Armoring multifunctional T cells for cancer therapy
Researcher (PI) Sebastian Kobold
Host Institution (HI) LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN
Call Details Starting Grant (StG), LS7, ERC-2017-STG
Summary Adoptive T cell therapy (ACT) is a powerful approach to treat even advanced cancer diseases where poor prognosis calls for innovative treatments. However ACT is critically limited by insufficient T cell infiltration into the tumor, T cell activation at the tumor site and local T cell suppression. Few advances have been made in the field to tackle these limitations besides increasing T cell activation. My group has focussed on these unaddressed issues but came to realise that tackling these one by one will not be sufficient. I have developed a panel of unpublished chemokine receptors and innovative modular antibody-activated receptors which have the potential to overcome the limitations of ACT against solid tumors. This ground-breaking portfolio places my group in the unique position to address combination of synergistic receptors and enable cellular therapies in previously unsuccessful indications. My project will provide the rationale for provision of an effective cancer treatment. The goal is to develop the next generation of ACT through T cell engineering both by forced expression of migratory and activating receptors and simultaneous deletion of immune suppressive molecules by gene editing. ARMOR-T will provide the basis for further preclinical and clinical development of a pioneering cellular product devoid of the limitations of available products to date. I will prove 1) synergy between migratory and modular activating receptors, 2) feasibility to integrate gene editing into a T cell expansion protocol, 3) synergy between gene editing, migratory and modular receptors and 4) efficacy, safety and mode of action. The main work of the project will be carried out in models of pancreatic cancer. The ARMOR-T platform will subsequently be translated to other cancer entities where response to ACT is likely such as melanoma, breast or colon cancer, providing less toxic and more effective therapies to otherwise untreatable disease.
Summary
Adoptive T cell therapy (ACT) is a powerful approach to treat even advanced cancer diseases where poor prognosis calls for innovative treatments. However ACT is critically limited by insufficient T cell infiltration into the tumor, T cell activation at the tumor site and local T cell suppression. Few advances have been made in the field to tackle these limitations besides increasing T cell activation. My group has focussed on these unaddressed issues but came to realise that tackling these one by one will not be sufficient. I have developed a panel of unpublished chemokine receptors and innovative modular antibody-activated receptors which have the potential to overcome the limitations of ACT against solid tumors. This ground-breaking portfolio places my group in the unique position to address combination of synergistic receptors and enable cellular therapies in previously unsuccessful indications. My project will provide the rationale for provision of an effective cancer treatment. The goal is to develop the next generation of ACT through T cell engineering both by forced expression of migratory and activating receptors and simultaneous deletion of immune suppressive molecules by gene editing. ARMOR-T will provide the basis for further preclinical and clinical development of a pioneering cellular product devoid of the limitations of available products to date. I will prove 1) synergy between migratory and modular activating receptors, 2) feasibility to integrate gene editing into a T cell expansion protocol, 3) synergy between gene editing, migratory and modular receptors and 4) efficacy, safety and mode of action. The main work of the project will be carried out in models of pancreatic cancer. The ARMOR-T platform will subsequently be translated to other cancer entities where response to ACT is likely such as melanoma, breast or colon cancer, providing less toxic and more effective therapies to otherwise untreatable disease.
Max ERC Funding
1 636 710 €
Duration
Start date: 2018-03-01, End date: 2023-02-28
Project acronym BARCODE DIAGNOSTICS
Project Next-Generation Personalized Diagnostic Nanotechnologies for Predicting Response to Cancer Medicine
Researcher (PI) Avraham Dror Schroeder
Host Institution (HI) TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
Call Details Starting Grant (StG), LS7, ERC-2015-STG
Summary Cancer is the leading cause of death in the Western world and the second cause of death worldwide. Despite advances in medical research, 30% of cancer patients are prescribed a medication the tumor does not respond to, or, alternatively, drugs that induce adverse side effects patients' cannot tolerate.
Nanotechnologies are becoming impactful therapeutic tools, granting tissue-targeting and cellular precision that cannot be attained using systems of larger scale.
In this proposal, I plan to expand far beyond the state-of-the-art and develop a conceptually new approach in which diagnostic nanoparticles are designed to retrieve drug-sensitivity information from malignant tissue inside the body. The ultimate goal of this program is to be able to predict, ahead of time, which treatment will be best for each cancer patient – an emerging field called personalized medicine. This interdisciplinary research program will expand our understandings and capabilities in nanotechnology, cancer biology and medicine.
To achieve this goal, I will engineer novel nanotechnologies that autonomously maneuver, target and diagnose the various cells that compose the tumor microenvironment and its disseminated metastasis. Each nanometric system will contain a miniscule amount of a biologically-active agent, and will serve as a nano lab for testing the activity of the agents inside the tumor cells.
To distinguish between system to system, and to grant single-cell sensitivity in vivo, nanoparticles will be barcoded with unique DNA fragments.
We will enable nanoparticle' deep tissue penetration into primary tumors and metastatic microenvironments using enzyme-loaded particles, and study how different agents, including small-molecule drugs, proteins and RNA, interact with the malignant and stromal cells that compose the cancerous microenvironments. Finally, we will demonstrate the ability of barcoded nanoparticles to predict adverse, life-threatening, side effects, in a personalized manner.
Summary
Cancer is the leading cause of death in the Western world and the second cause of death worldwide. Despite advances in medical research, 30% of cancer patients are prescribed a medication the tumor does not respond to, or, alternatively, drugs that induce adverse side effects patients' cannot tolerate.
Nanotechnologies are becoming impactful therapeutic tools, granting tissue-targeting and cellular precision that cannot be attained using systems of larger scale.
In this proposal, I plan to expand far beyond the state-of-the-art and develop a conceptually new approach in which diagnostic nanoparticles are designed to retrieve drug-sensitivity information from malignant tissue inside the body. The ultimate goal of this program is to be able to predict, ahead of time, which treatment will be best for each cancer patient – an emerging field called personalized medicine. This interdisciplinary research program will expand our understandings and capabilities in nanotechnology, cancer biology and medicine.
To achieve this goal, I will engineer novel nanotechnologies that autonomously maneuver, target and diagnose the various cells that compose the tumor microenvironment and its disseminated metastasis. Each nanometric system will contain a miniscule amount of a biologically-active agent, and will serve as a nano lab for testing the activity of the agents inside the tumor cells.
To distinguish between system to system, and to grant single-cell sensitivity in vivo, nanoparticles will be barcoded with unique DNA fragments.
We will enable nanoparticle' deep tissue penetration into primary tumors and metastatic microenvironments using enzyme-loaded particles, and study how different agents, including small-molecule drugs, proteins and RNA, interact with the malignant and stromal cells that compose the cancerous microenvironments. Finally, we will demonstrate the ability of barcoded nanoparticles to predict adverse, life-threatening, side effects, in a personalized manner.
Max ERC Funding
1 499 250 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BeyondA1
Project Set theory beyond the first uncountable cardinal
Researcher (PI) Assaf Shmuel Rinot
Host Institution (HI) BAR ILAN UNIVERSITY
Call Details Starting Grant (StG), PE1, ERC-2018-STG
Summary We propose to establish a research group that will unveil the combinatorial nature of the second uncountable cardinal. This includes its Ramsey-theoretic, order-theoretic, graph-theoretic and topological features. Among others, we will be directly addressing fundamental problems due to Erdos, Rado, Galvin, and Shelah.
While some of these problems are old and well-known, an unexpected series of breakthroughs from the last three years suggest that now is a promising point in time to carry out such a project. Indeed, through a short period, four previously unattainable problems concerning the second uncountable cardinal were successfully tackled: Aspero on a club-guessing problem of Shelah, Krueger on the club-isomorphism problem for Aronszajn trees, Neeman on the isomorphism problem for dense sets of reals, and the PI on the Souslin problem. Each of these results was obtained through the development of a completely new technical framework, and these frameworks could now pave the way for the solution of some major open questions.
A goal of the highest risk in this project is the discovery of a consistent (possibly, parameterized) forcing axiom that will (preferably, simultaneously) provide structure theorems for stationary sets, linearly ordered sets, trees, graphs, and partition relations, as well as the refutation of various forms of club-guessing principles, all at the level of the second uncountable cardinal. In comparison, at the level of the first uncountable cardinal, a forcing axiom due to Foreman, Magidor and Shelah achieves exactly that.
To approach our goals, the proposed project is divided into four core areas: Uncountable trees, Ramsey theory on ordinals, Club-guessing principles, and Forcing Axioms. There is a rich bilateral interaction between any pair of the four different cores, but the proposed division will allow an efficient allocation of manpower, and will increase the chances of parallel success.
Summary
We propose to establish a research group that will unveil the combinatorial nature of the second uncountable cardinal. This includes its Ramsey-theoretic, order-theoretic, graph-theoretic and topological features. Among others, we will be directly addressing fundamental problems due to Erdos, Rado, Galvin, and Shelah.
While some of these problems are old and well-known, an unexpected series of breakthroughs from the last three years suggest that now is a promising point in time to carry out such a project. Indeed, through a short period, four previously unattainable problems concerning the second uncountable cardinal were successfully tackled: Aspero on a club-guessing problem of Shelah, Krueger on the club-isomorphism problem for Aronszajn trees, Neeman on the isomorphism problem for dense sets of reals, and the PI on the Souslin problem. Each of these results was obtained through the development of a completely new technical framework, and these frameworks could now pave the way for the solution of some major open questions.
A goal of the highest risk in this project is the discovery of a consistent (possibly, parameterized) forcing axiom that will (preferably, simultaneously) provide structure theorems for stationary sets, linearly ordered sets, trees, graphs, and partition relations, as well as the refutation of various forms of club-guessing principles, all at the level of the second uncountable cardinal. In comparison, at the level of the first uncountable cardinal, a forcing axiom due to Foreman, Magidor and Shelah achieves exactly that.
To approach our goals, the proposed project is divided into four core areas: Uncountable trees, Ramsey theory on ordinals, Club-guessing principles, and Forcing Axioms. There is a rich bilateral interaction between any pair of the four different cores, but the proposed division will allow an efficient allocation of manpower, and will increase the chances of parallel success.
Max ERC Funding
1 362 500 €
Duration
Start date: 2018-10-01, End date: 2023-09-30
Project acronym BIO-IRT
Project Biologically individualized, model-based radiotherapy on the basis of multi-parametric molecular tumour profiling
Researcher (PI) Daniela Thorwarth
Host Institution (HI) EBERHARD KARLS UNIVERSITAET TUEBINGEN
Call Details Starting Grant (StG), LS7, ERC-2013-StG
Summary High precision radiotherapy (RT) allows extremely flexible tumour treatments achieving highly conformal radiation doses while sparing surrounding organs at risk. Nevertheless, failure rates of up to 50% are reported for head and neck cancer (HNC) due to radiation resistance induced by pathophysiologic factors such as hypoxia and other clinical factors as HPV-status, stage and tumour volume.
This project aims at developing a multi-parametric model for individualized RT (iRT) dose prescriptions in HNC based on biological markers and functional PET/MR imaging. This project goes far beyond current research standards and clinical practice as it aims for establishing hypoxia PET and f-MRI as well as biological markers in HNC as a role model for a novel concept from anatomy-based to biologically iRT.
During this project, a multi-parametric model will be developed on a preclinical basis that combines biological markers such as different oncogenes and hypoxia gene classifier with functional PET/MR imaging, such as FMISO PET in combination with different f-MRI techniques, like DW-, DCE- and BOLD-MRI in addition to MR spectroscopy. The ultimate goal of this project is a multi-parametric model to predict therapy outcome and guide iRT.
In a second part, a clinical study will be carried out to validate the preclinical model in patients. Based on the most informative radiobiological and imaging parameters as identified during the pre-clinical phase, biological markers and advanced PET/MR imaging will be evaluated in terms of their potential for iRT dose prescription.
Successful development of a model for biologically iRT prescription on the basis of multi-parametric molecular profiling would provide a unique basis for personalized cancer treatment. A validated multi-parametric model for RT outcome would represent a paradigm shift from anatomy-based to biologically iRT concepts with the ultimate goal of improving cancer cure rates.
Summary
High precision radiotherapy (RT) allows extremely flexible tumour treatments achieving highly conformal radiation doses while sparing surrounding organs at risk. Nevertheless, failure rates of up to 50% are reported for head and neck cancer (HNC) due to radiation resistance induced by pathophysiologic factors such as hypoxia and other clinical factors as HPV-status, stage and tumour volume.
This project aims at developing a multi-parametric model for individualized RT (iRT) dose prescriptions in HNC based on biological markers and functional PET/MR imaging. This project goes far beyond current research standards and clinical practice as it aims for establishing hypoxia PET and f-MRI as well as biological markers in HNC as a role model for a novel concept from anatomy-based to biologically iRT.
During this project, a multi-parametric model will be developed on a preclinical basis that combines biological markers such as different oncogenes and hypoxia gene classifier with functional PET/MR imaging, such as FMISO PET in combination with different f-MRI techniques, like DW-, DCE- and BOLD-MRI in addition to MR spectroscopy. The ultimate goal of this project is a multi-parametric model to predict therapy outcome and guide iRT.
In a second part, a clinical study will be carried out to validate the preclinical model in patients. Based on the most informative radiobiological and imaging parameters as identified during the pre-clinical phase, biological markers and advanced PET/MR imaging will be evaluated in terms of their potential for iRT dose prescription.
Successful development of a model for biologically iRT prescription on the basis of multi-parametric molecular profiling would provide a unique basis for personalized cancer treatment. A validated multi-parametric model for RT outcome would represent a paradigm shift from anatomy-based to biologically iRT concepts with the ultimate goal of improving cancer cure rates.
Max ERC Funding
1 370 799 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym BIOSENSORIMAGING
Project Hyperpolarized Biosensors in Molecular Imaging
Researcher (PI) Leif Schröder
Host Institution (HI) FORSCHUNGSVERBUND BERLIN EV
Call Details Starting Grant (StG), LS7, ERC-2009-StG
Summary Xenon biosensors have an outstanding potential to increase the significance of magnetic resonance imaging (MRI) in molecular imaging and to combine the advantages of MRI with the high sensitivity of hyperpolarized Xe-129 and the specificity of a functionalized contrast agent. Based on new detection schemes (Hyper-CEST method) in Xe MRI, this novel concept in molecular diagnostics will be made available for biomedical applications. The advancement focuses on high-sensitivity in vitro diagnostics for localization of tumour cells in cell cultures and first demonstrations on animal models based on a transferrin-functionalized biosensor. Such a sensor will enable detection of subcutaneous tumours at high sensitivity without any background signal. More detailed work on the different available Hyper-CEST contrast parameters focuses on an absolute quantification of new molecular markers that will improve non-invasive tumour diagnostics significantly. NMR detection of functionalized Xe biosensors have the potential to close the sensitivity gap between modalities of nuclear medicine like PET/SPECT and MRI without using ionizing radiation or making compromises in penetration depth like in optical methods.
Summary
Xenon biosensors have an outstanding potential to increase the significance of magnetic resonance imaging (MRI) in molecular imaging and to combine the advantages of MRI with the high sensitivity of hyperpolarized Xe-129 and the specificity of a functionalized contrast agent. Based on new detection schemes (Hyper-CEST method) in Xe MRI, this novel concept in molecular diagnostics will be made available for biomedical applications. The advancement focuses on high-sensitivity in vitro diagnostics for localization of tumour cells in cell cultures and first demonstrations on animal models based on a transferrin-functionalized biosensor. Such a sensor will enable detection of subcutaneous tumours at high sensitivity without any background signal. More detailed work on the different available Hyper-CEST contrast parameters focuses on an absolute quantification of new molecular markers that will improve non-invasive tumour diagnostics significantly. NMR detection of functionalized Xe biosensors have the potential to close the sensitivity gap between modalities of nuclear medicine like PET/SPECT and MRI without using ionizing radiation or making compromises in penetration depth like in optical methods.
Max ERC Funding
1 848 600 €
Duration
Start date: 2009-12-01, End date: 2014-11-30
Project acronym BIOSTRUCT
Project Multiscale mathematical modelling of dynamics of structure formation in cell systems
Researcher (PI) Anna Marciniak-Czochra
Host Institution (HI) RUPRECHT-KARLS-UNIVERSITAET HEIDELBERG
Call Details Starting Grant (StG), PE1, ERC-2007-StG
Summary The aim of this transdisciplinary project is to develop and analyse multiscale mathematical models of pattern formation in multicellular systems controlled by the dynamics of intracellular signalling pathways and cell-to-cell communication and to develop new mathematical methods for the modelling of such complex processes. This aim will be achieved through a close collaboration with experimental groups and comprehensive analytical investigations of the mathematical problems arising in the modelling of these biological processes. The mathematical methods and techniques to be employed will be the analysis of systems of partial differential equations, asymptotic analysis, as well as methods of dynamical systems. These techniques will be used to formulate the models and to study the spatio-temporal behaviour of solutions, especially stability and dependence on characteristic scales, geometry, initial data and key parameters. Advanced numerical methods will be applied to simulate the models. This comprehensive methodology goes beyond the state-of-the-art, since usually the analyses are limited to a single aspect of model behaviour. Groundbreaking impacts envisioned are threefold: (i) The project will contribute to the understanding of mechanisms of structure formation in the developmental process, in the context of recently discovered signalling pathways. In addition, some of the factors and mechanisms playing a role in developmental processes, such as Wnt signalling, are implicated in carcinogenesis, for instance colon and lung cancer. (ii) Accurate quantitative and predictive mathematical models of cell proliferation and differentiation are important for the control of tumour growth and tissue egeneration; (iii) Qualitative analysis of multiscale mathematical models of biological phenomena generates challenging mathematical problems and, therefore, the project will lead to the development of new mathematical theories and tools.
Summary
The aim of this transdisciplinary project is to develop and analyse multiscale mathematical models of pattern formation in multicellular systems controlled by the dynamics of intracellular signalling pathways and cell-to-cell communication and to develop new mathematical methods for the modelling of such complex processes. This aim will be achieved through a close collaboration with experimental groups and comprehensive analytical investigations of the mathematical problems arising in the modelling of these biological processes. The mathematical methods and techniques to be employed will be the analysis of systems of partial differential equations, asymptotic analysis, as well as methods of dynamical systems. These techniques will be used to formulate the models and to study the spatio-temporal behaviour of solutions, especially stability and dependence on characteristic scales, geometry, initial data and key parameters. Advanced numerical methods will be applied to simulate the models. This comprehensive methodology goes beyond the state-of-the-art, since usually the analyses are limited to a single aspect of model behaviour. Groundbreaking impacts envisioned are threefold: (i) The project will contribute to the understanding of mechanisms of structure formation in the developmental process, in the context of recently discovered signalling pathways. In addition, some of the factors and mechanisms playing a role in developmental processes, such as Wnt signalling, are implicated in carcinogenesis, for instance colon and lung cancer. (ii) Accurate quantitative and predictive mathematical models of cell proliferation and differentiation are important for the control of tumour growth and tissue egeneration; (iii) Qualitative analysis of multiscale mathematical models of biological phenomena generates challenging mathematical problems and, therefore, the project will lead to the development of new mathematical theories and tools.
Max ERC Funding
750 000 €
Duration
Start date: 2008-09-01, End date: 2013-08-31
