Project acronym AMSEL
Project Atomic Force Microscopy for Molecular Structure Elucidation
Researcher (PI) Leo Gross
Host Institution (HI) IBM RESEARCH GMBH
Call Details Consolidator Grant (CoG), PE4, ERC-2015-CoG
Summary Molecular structure elucidation is of great importance in synthetic chemistry, pharmacy, life sciences, energy and environmental sciences, and technology applications. To date structure elucidation by atomic force microscopy (AFM) has been demonstrated for a few, small and mainly planar molecules. In this project high-risk, high-impact scientific questions will be solved using structure elucidation with the AFM employing a novel tool and novel methodologies.
A combined low-temperature scanning tunneling microscope/atomic force microscope (LT-STM/AFM) with high throughput and in situ electrospray deposition method will be developed. Chemical resolution will be achieved by novel measurement techniques, in particular the usage of different and novel tip functionalizations and combination with Kelvin probe force microscopy. Elements will be identified using substructure recognition provided by a database that will be erected and by refined theory and simulations.
The developed tools and techniques will be applied to molecules of increasing fragility, complexity, size, and three-dimensionality. In particular samples that are challenging to characterize with conventional methods will be studied. Complex molecular mixtures will be investigated molecule-by-molecule taking advantage of the single-molecule sensitivity. The absolute stereochemistry of molecules will be determined, resolving molecules with multiple stereocenters. The operation of single molecular machines as nanocars and molecular gears will be investigated. Reactive intermediates generated with atomic manipulation will be characterized and their on-surface reactivity will be studied by AFM.
Summary
Molecular structure elucidation is of great importance in synthetic chemistry, pharmacy, life sciences, energy and environmental sciences, and technology applications. To date structure elucidation by atomic force microscopy (AFM) has been demonstrated for a few, small and mainly planar molecules. In this project high-risk, high-impact scientific questions will be solved using structure elucidation with the AFM employing a novel tool and novel methodologies.
A combined low-temperature scanning tunneling microscope/atomic force microscope (LT-STM/AFM) with high throughput and in situ electrospray deposition method will be developed. Chemical resolution will be achieved by novel measurement techniques, in particular the usage of different and novel tip functionalizations and combination with Kelvin probe force microscopy. Elements will be identified using substructure recognition provided by a database that will be erected and by refined theory and simulations.
The developed tools and techniques will be applied to molecules of increasing fragility, complexity, size, and three-dimensionality. In particular samples that are challenging to characterize with conventional methods will be studied. Complex molecular mixtures will be investigated molecule-by-molecule taking advantage of the single-molecule sensitivity. The absolute stereochemistry of molecules will be determined, resolving molecules with multiple stereocenters. The operation of single molecular machines as nanocars and molecular gears will be investigated. Reactive intermediates generated with atomic manipulation will be characterized and their on-surface reactivity will be studied by AFM.
Max ERC Funding
2 000 000 €
Duration
Start date: 2016-06-01, End date: 2021-05-31
Project acronym Antibodyomics
Project Vaccine profiling and immunodiagnostic discovery by high-throughput antibody repertoire analysis
Researcher (PI) Sai Tota Reddy
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), LS7, ERC-2015-STG
Summary Vaccines and immunodiagnostics have been vital for public health and medicine, however a quantitative molecular understanding of vaccine-induced antibody responses is lacking. Antibody research is currently going through a big-data driven revolution, largely due to progress in next-generation sequencing (NGS) and bioinformatic analysis of antibody repertoires. A main advantage of high-throughput antibody repertoire analysis is that it provides a wealth of quantitative information not possible with other classical methods of antibody analysis (i.e., serum titers); this information includes: clonal distribution and diversity, somatic hypermutation patterns, and lineage tracing. In preliminary work my group has established standardized methods for antibody repertoire NGS, including an experimental-bioinformatic pipeline for error and bias correction that enables highly accurate repertoire sequencing and analysis. The overall goal of this proposal will be to apply high-throughput antibody repertoire analysis for quantitative vaccine profiling and discovery of next-generation immunodiagnostics. Using mouse subunit vaccination as our model system, we will answer for the first time, a fundamental biological question within the context of antibody responses - what is the link between genotype (antibody repertoire) and phenotype (serum antibodies)? We will expand upon this approach for improved rational vaccine design by quantitatively determining the impact of a comprehensive set of subunit vaccination parameters on complete antibody landscapes. Finally, we will develop advanced bioinformatic methods to discover immunodiagnostics based on antibody repertoire sequences. In summary, this proposal lays the foundation for fundamentally new approaches in the quantitative analysis of antibody responses, which long-term will promote the development of next-generation vaccines and immunodiagnostics.
Summary
Vaccines and immunodiagnostics have been vital for public health and medicine, however a quantitative molecular understanding of vaccine-induced antibody responses is lacking. Antibody research is currently going through a big-data driven revolution, largely due to progress in next-generation sequencing (NGS) and bioinformatic analysis of antibody repertoires. A main advantage of high-throughput antibody repertoire analysis is that it provides a wealth of quantitative information not possible with other classical methods of antibody analysis (i.e., serum titers); this information includes: clonal distribution and diversity, somatic hypermutation patterns, and lineage tracing. In preliminary work my group has established standardized methods for antibody repertoire NGS, including an experimental-bioinformatic pipeline for error and bias correction that enables highly accurate repertoire sequencing and analysis. The overall goal of this proposal will be to apply high-throughput antibody repertoire analysis for quantitative vaccine profiling and discovery of next-generation immunodiagnostics. Using mouse subunit vaccination as our model system, we will answer for the first time, a fundamental biological question within the context of antibody responses - what is the link between genotype (antibody repertoire) and phenotype (serum antibodies)? We will expand upon this approach for improved rational vaccine design by quantitatively determining the impact of a comprehensive set of subunit vaccination parameters on complete antibody landscapes. Finally, we will develop advanced bioinformatic methods to discover immunodiagnostics based on antibody repertoire sequences. In summary, this proposal lays the foundation for fundamentally new approaches in the quantitative analysis of antibody responses, which long-term will promote the development of next-generation vaccines and immunodiagnostics.
Max ERC Funding
1 492 586 €
Duration
Start date: 2016-06-01, End date: 2021-05-31
Project acronym ARTIVISM
Project Art and Activism : Creativity and Performance as Subversive Forms of Political Expression in Super-Diverse Cities
Researcher (PI) Monika Salzbrunn
Host Institution (HI) UNIVERSITE DE LAUSANNE
Call Details Consolidator Grant (CoG), SH5, ERC-2015-CoG
Summary ARTIVISM aims at exploring new artistic forms of political expression under difficult, precarious and/or oppressive conditions. It asks how social actors create belonging and multiple forms of resistance when they use art in activism or activism in art. What kind of alliances do these two forms of social practices generate in super-diverse places, in times of crisis and in precarious situations? Thus, ARTIVISM seeks to understand how social actors engage artistically in order to bring about social, economic and political change. Going beyond former research in urban and migration studies, and beyond the anthropology of art, ARTIVISM focuses on a broad range of artistic tools, styles and means of expression, namely festive events and parades, cartoons and comics and street art. By articulating performance studies, street anthropology and the sociology of celebration with migration and diversity studies, the project challenges former concepts, which took stable social groups for granted and reified them with ethnic lenses. The applied methodology considerably renews the field by bringing together event-, actor- and condition-centred approaches and a multi-sensory framework. Besides its multidisciplinary design, the ground-breaking nature of ARTIVISM lies in the application of the core concepts of performativity and liminality, as well as in an examination of the way to advance and refine these concepts and to create new analytical tools to respond to recent social phenomena. We have developed and tested innovative methods that respond to a postmodern type of fluid and temporary social action: audio-visual ethnography, urban event ethnography, street ethnography, field-crossing, and sensory ethnography (apprenticeship). Therefore, ARTIVISM develops new methods and theories in order to introduce a multi-faceted trans-disciplinary approach to the study of an emerging field of social transformations that is of challenging significance to the social sciences.
Summary
ARTIVISM aims at exploring new artistic forms of political expression under difficult, precarious and/or oppressive conditions. It asks how social actors create belonging and multiple forms of resistance when they use art in activism or activism in art. What kind of alliances do these two forms of social practices generate in super-diverse places, in times of crisis and in precarious situations? Thus, ARTIVISM seeks to understand how social actors engage artistically in order to bring about social, economic and political change. Going beyond former research in urban and migration studies, and beyond the anthropology of art, ARTIVISM focuses on a broad range of artistic tools, styles and means of expression, namely festive events and parades, cartoons and comics and street art. By articulating performance studies, street anthropology and the sociology of celebration with migration and diversity studies, the project challenges former concepts, which took stable social groups for granted and reified them with ethnic lenses. The applied methodology considerably renews the field by bringing together event-, actor- and condition-centred approaches and a multi-sensory framework. Besides its multidisciplinary design, the ground-breaking nature of ARTIVISM lies in the application of the core concepts of performativity and liminality, as well as in an examination of the way to advance and refine these concepts and to create new analytical tools to respond to recent social phenomena. We have developed and tested innovative methods that respond to a postmodern type of fluid and temporary social action: audio-visual ethnography, urban event ethnography, street ethnography, field-crossing, and sensory ethnography (apprenticeship). Therefore, ARTIVISM develops new methods and theories in order to introduce a multi-faceted trans-disciplinary approach to the study of an emerging field of social transformations that is of challenging significance to the social sciences.
Max ERC Funding
1 999 287 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym AXIAL.EC
Project PRINCIPLES OF AXIAL POLARITY-DRIVEN VASCULAR PATTERNING
Researcher (PI) Claudio Franco
Host Institution (HI) INSTITUTO DE MEDICINA MOLECULAR JOAO LOBO ANTUNES
Call Details Starting Grant (StG), LS4, ERC-2015-STG
Summary The formation of a functional patterned vascular network is essential for development, tissue growth and organ physiology. Several human vascular disorders arise from the mis-patterning of blood vessels, such as arteriovenous malformations, aneurysms and diabetic retinopathy. Although blood flow is recognised as a stimulus for vascular patterning, very little is known about the molecular mechanisms that regulate endothelial cell behaviour in response to flow and promote vascular patterning.
Recently, we uncovered that endothelial cells migrate extensively in the immature vascular network, and that endothelial cells polarise against the blood flow direction. Here, we put forward the hypothesis that vascular patterning is dependent on the polarisation and migration of endothelial cells against the flow direction, in a continuous flux of cells going from low-shear stress to high-shear stress regions. We will establish new reporter mouse lines to observe and manipulate endothelial polarity in vivo in order to investigate how polarisation and coordination of endothelial cells movements are orchestrated to generate vascular patterning. We will manipulate cell polarity using mouse models to understand the importance of cell polarisation in vascular patterning. Also, using a unique zebrafish line allowing analysis of endothelial cell polarity, we will perform a screen to identify novel regulators of vascular patterning. Finally, we will explore the hypothesis that defective flow-dependent endothelial polarisation underlies arteriovenous malformations using two genetic models.
This integrative approach, based on high-resolution imaging and unique experimental models, will provide a unifying model defining the cellular and molecular principles involved in vascular patterning. Given the physiological relevance of vascular patterning in health and disease, this research plan will set the basis for the development of novel clinical therapies targeting vascular disorders.
Summary
The formation of a functional patterned vascular network is essential for development, tissue growth and organ physiology. Several human vascular disorders arise from the mis-patterning of blood vessels, such as arteriovenous malformations, aneurysms and diabetic retinopathy. Although blood flow is recognised as a stimulus for vascular patterning, very little is known about the molecular mechanisms that regulate endothelial cell behaviour in response to flow and promote vascular patterning.
Recently, we uncovered that endothelial cells migrate extensively in the immature vascular network, and that endothelial cells polarise against the blood flow direction. Here, we put forward the hypothesis that vascular patterning is dependent on the polarisation and migration of endothelial cells against the flow direction, in a continuous flux of cells going from low-shear stress to high-shear stress regions. We will establish new reporter mouse lines to observe and manipulate endothelial polarity in vivo in order to investigate how polarisation and coordination of endothelial cells movements are orchestrated to generate vascular patterning. We will manipulate cell polarity using mouse models to understand the importance of cell polarisation in vascular patterning. Also, using a unique zebrafish line allowing analysis of endothelial cell polarity, we will perform a screen to identify novel regulators of vascular patterning. Finally, we will explore the hypothesis that defective flow-dependent endothelial polarisation underlies arteriovenous malformations using two genetic models.
This integrative approach, based on high-resolution imaging and unique experimental models, will provide a unifying model defining the cellular and molecular principles involved in vascular patterning. Given the physiological relevance of vascular patterning in health and disease, this research plan will set the basis for the development of novel clinical therapies targeting vascular disorders.
Max ERC Funding
1 618 750 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym BactInd
Project Bacterial cooperation at the individual cell level
Researcher (PI) Rolf Kümmerli
Host Institution (HI) UNIVERSITAT ZURICH
Call Details Consolidator Grant (CoG), LS8, ERC-2015-CoG
Summary All levels of life entail cooperation and conflict. Genes cooperate to build up a functional genome, which can yet be undermined by selfish genetic elements. Humans and animals cooperate to build up societies, which can yet be subverted by cheats. There is a long-standing interest among biologists to comprehend the tug-of-war between cooperation and conflict. Recently, research on bacteria was successful in identifying key factors that can tip the balance in favour or against cooperation. Bacteria cooperate through the formation of protective biofilms, cell-to-cell communication, and the secretion of shareable public goods. However, the advantage of bacteria being fast replicating units, easily cultivatable in high numbers, is also their disadvantage: they are small and imperceptible, such that measures of cooperation typically rely on averaged responses across millions of cells. Thus, we still know very little about bacterial cooperation at the biological relevant scale: the individual cell level. Here, I present research using the secretion of public goods in the opportunistic human pathogen Pseudomonas aeruginosa, to tackle this issue. I will explore new dimensions of bacterial cooperation by asking whether bacteria engage in collective-decision making to find optimal group-level solutions; whether bacteria show division of labour to split up work efficiently; and whether bacteria can distinguish between trustworthy and cheating partners. The proposed research will make two significant contributions. First, it will reveal whether bacteria engage in complex forms of cooperation (collective decision-making, division of labour, partner recognition), which have traditionally been associated with higher organisms. Second, it will provide insights into the evolutionary stability of cooperation – key knowledge for designing therapies that interfere with virulence-inducing public goods in infections, and the design of stable public-good based remediation processes.
Summary
All levels of life entail cooperation and conflict. Genes cooperate to build up a functional genome, which can yet be undermined by selfish genetic elements. Humans and animals cooperate to build up societies, which can yet be subverted by cheats. There is a long-standing interest among biologists to comprehend the tug-of-war between cooperation and conflict. Recently, research on bacteria was successful in identifying key factors that can tip the balance in favour or against cooperation. Bacteria cooperate through the formation of protective biofilms, cell-to-cell communication, and the secretion of shareable public goods. However, the advantage of bacteria being fast replicating units, easily cultivatable in high numbers, is also their disadvantage: they are small and imperceptible, such that measures of cooperation typically rely on averaged responses across millions of cells. Thus, we still know very little about bacterial cooperation at the biological relevant scale: the individual cell level. Here, I present research using the secretion of public goods in the opportunistic human pathogen Pseudomonas aeruginosa, to tackle this issue. I will explore new dimensions of bacterial cooperation by asking whether bacteria engage in collective-decision making to find optimal group-level solutions; whether bacteria show division of labour to split up work efficiently; and whether bacteria can distinguish between trustworthy and cheating partners. The proposed research will make two significant contributions. First, it will reveal whether bacteria engage in complex forms of cooperation (collective decision-making, division of labour, partner recognition), which have traditionally been associated with higher organisms. Second, it will provide insights into the evolutionary stability of cooperation – key knowledge for designing therapies that interfere with virulence-inducing public goods in infections, and the design of stable public-good based remediation processes.
Max ERC Funding
1 994 981 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym BATMAN
Project Development of Quantitative Metrologies to Guide Lithium Ion Battery Manufacturing
Researcher (PI) Vanessa Wood
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), PE8, ERC-2015-STG
Summary Lithium ion batteries offer tremendous potential as an enabling technology for sustainable transportation and development. However, their widespread usage as the energy storage solution for electric mobility and grid-level integration of renewables is impeded by the fact that current state-of-the-art lithium ion batteries have energy densities that are too small, charge- and discharge rates that are too low, and costs that are too high. Highly publicized instances of catastrophic failure of lithium ion batteries raise questions of safety. Understanding the limitations to battery performance and origins of the degradation and failure is highly complex due to the difficulties in studying interrelated processes that take place at different length and time scales in a corrosive environment. In the project, we will (1) develop and implement quantitative methods to study the complex interrelations between structure and electrochemistry occurring at the nano-, micron-, and milli-scales in lithium ion battery active materials and electrodes, (2) conduct systematic experimental studies with our new techniques to understand the origins of performance limitations and to develop design guidelines for achieving high performance and safe batteries, and (3) investigate economically viable engineering solutions based on these guidelines to achieve high performance and safe lithium ion batteries.
Summary
Lithium ion batteries offer tremendous potential as an enabling technology for sustainable transportation and development. However, their widespread usage as the energy storage solution for electric mobility and grid-level integration of renewables is impeded by the fact that current state-of-the-art lithium ion batteries have energy densities that are too small, charge- and discharge rates that are too low, and costs that are too high. Highly publicized instances of catastrophic failure of lithium ion batteries raise questions of safety. Understanding the limitations to battery performance and origins of the degradation and failure is highly complex due to the difficulties in studying interrelated processes that take place at different length and time scales in a corrosive environment. In the project, we will (1) develop and implement quantitative methods to study the complex interrelations between structure and electrochemistry occurring at the nano-, micron-, and milli-scales in lithium ion battery active materials and electrodes, (2) conduct systematic experimental studies with our new techniques to understand the origins of performance limitations and to develop design guidelines for achieving high performance and safe batteries, and (3) investigate economically viable engineering solutions based on these guidelines to achieve high performance and safe lithium ion batteries.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym BIGCODE
Project Learning from Big Code: Probabilistic Models, Analysis and Synthesis
Researcher (PI) Martin Vechev
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), PE6, ERC-2015-STG
Summary The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches.
These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer.
Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language).
We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems.
We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.
Summary
The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches.
These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer.
Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language).
We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems.
We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BINDING FIBRES
Project Soluble dietary fibre: unraveling how weak bonds have a strong impact on function
Researcher (PI) Laura Nyström
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), LS9, ERC-2015-STG
Summary Dietary fibres are recognized for their health promoting properties; nevertheless, many of the physicochemical mechanisms behind these effects remain poorly understood. While it is understood that dietary fibres can associate with small molecules influencing, both positively or negatively their absorption, the molecular mechanism, by which these associations take place, have yet to be elucidated We propose a study of the binding in soluble dietary fibres at a molecular level to establish binding constants for various fibres and nutritionally relevant ligands. The interactions between fibres and target compounds may be quite weak, but still have a major impact on the bioavailability. To gain insight to the binding mechanisms at a level of detail that has not earlier been achieved, we will apply novel combinations of analytical techniques (MS, NMR, EPR) and both natural as well as synthetic probes to elucidate the associations in these complexes from macromolecular to atomic level. Glucans, xyloglucans and galactomannans will serve as model soluble fibres, representative of real food systems, allowing us to determine their binding constants with nutritionally relevant micronutrients, such as monosaccharides, bile acids, and metals. Furthermore, we will examine supramolecular interactions between fibre strands to evaluate possible contribution of several fibre strands to the micronutrient associations. At the atomic level, we will use complementary spectroscopies to identify the functional groups and atoms involved in the bonds between fibres and the ligands. The proposal describes a unique approach to quantify binding of small molecules by dietary fibres, which can be translated to polysaccharide interactions with ligands in a broad range of biological systems and disciplines. The findings from this study may further allow us to predictably utilize fibres in functional foods, which can have far-reaching consequences in human nutrition, and thereby also public health.
Summary
Dietary fibres are recognized for their health promoting properties; nevertheless, many of the physicochemical mechanisms behind these effects remain poorly understood. While it is understood that dietary fibres can associate with small molecules influencing, both positively or negatively their absorption, the molecular mechanism, by which these associations take place, have yet to be elucidated We propose a study of the binding in soluble dietary fibres at a molecular level to establish binding constants for various fibres and nutritionally relevant ligands. The interactions between fibres and target compounds may be quite weak, but still have a major impact on the bioavailability. To gain insight to the binding mechanisms at a level of detail that has not earlier been achieved, we will apply novel combinations of analytical techniques (MS, NMR, EPR) and both natural as well as synthetic probes to elucidate the associations in these complexes from macromolecular to atomic level. Glucans, xyloglucans and galactomannans will serve as model soluble fibres, representative of real food systems, allowing us to determine their binding constants with nutritionally relevant micronutrients, such as monosaccharides, bile acids, and metals. Furthermore, we will examine supramolecular interactions between fibre strands to evaluate possible contribution of several fibre strands to the micronutrient associations. At the atomic level, we will use complementary spectroscopies to identify the functional groups and atoms involved in the bonds between fibres and the ligands. The proposal describes a unique approach to quantify binding of small molecules by dietary fibres, which can be translated to polysaccharide interactions with ligands in a broad range of biological systems and disciplines. The findings from this study may further allow us to predictably utilize fibres in functional foods, which can have far-reaching consequences in human nutrition, and thereby also public health.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BioBarPro
Project A Hot-Spot Bio-Barcode Strategy for Prognostic Biomarkers In Colorectal Cancer
Researcher (PI) Shana Sturla
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Proof of Concept (PoC), ERC-2015-PoC, ERC-2015-PoC
Summary Colorectal cancer (CRC) is caused by alterations in genes that regulate tissue growth and the risk of developing CRC is influenced by a combination of environmental and genetic factors. Although CRC is often preventable by removing precursor lesions, screening efforts have been hampered by low participation rates and by performance limitations of the screening tools themselves. Detection of blood in faeces is currently the most common screening tool, while stool DNA testing of molecular markers has emerged as a biologically rational and user-friendly strategy for the non-invasive detection of CRC and critical precursor lesions. This advance has significantly increased performance in detecting CRC, but still more than half of the precancerous lesions cannot be detected. The stool DNA test performance for detecting precancerous lesions is expected to be improved substantively by including a completely new type of biomarker, those formed earlier than genetic mutations in the process of carcinogenesis. Such biomarkers are DNA adducts; DNA molecules bound to chemicals. If not repaired, these DNA adducts generate mutations. Herein, we propose to expand an ERC-funded research result into a kit for measuring CRC-initiating DNA adducts in a stool sample. This kit will enable personalized feedback that quantitatively integrates environmental and genetic factors in colon-cancer associated DNA damage. We have filed a patent application for the chemical basis of the technology and have partnered with an ETH spin-off for the scientific development of our existing proof of principle assay to a prototype kit. In parallel to the scientific work, during the Proof of Concept phase, we will address a phase of the overall commercialization plan that involves licensing the technology to a business partner in the life sciences sector.
Summary
Colorectal cancer (CRC) is caused by alterations in genes that regulate tissue growth and the risk of developing CRC is influenced by a combination of environmental and genetic factors. Although CRC is often preventable by removing precursor lesions, screening efforts have been hampered by low participation rates and by performance limitations of the screening tools themselves. Detection of blood in faeces is currently the most common screening tool, while stool DNA testing of molecular markers has emerged as a biologically rational and user-friendly strategy for the non-invasive detection of CRC and critical precursor lesions. This advance has significantly increased performance in detecting CRC, but still more than half of the precancerous lesions cannot be detected. The stool DNA test performance for detecting precancerous lesions is expected to be improved substantively by including a completely new type of biomarker, those formed earlier than genetic mutations in the process of carcinogenesis. Such biomarkers are DNA adducts; DNA molecules bound to chemicals. If not repaired, these DNA adducts generate mutations. Herein, we propose to expand an ERC-funded research result into a kit for measuring CRC-initiating DNA adducts in a stool sample. This kit will enable personalized feedback that quantitatively integrates environmental and genetic factors in colon-cancer associated DNA damage. We have filed a patent application for the chemical basis of the technology and have partnered with an ETH spin-off for the scientific development of our existing proof of principle assay to a prototype kit. In parallel to the scientific work, during the Proof of Concept phase, we will address a phase of the overall commercialization plan that involves licensing the technology to a business partner in the life sciences sector.
Max ERC Funding
150 000 €
Duration
Start date: 2015-12-01, End date: 2017-05-31
Project acronym BrainControl
Project Stable Brain-Machine control via a learnable standalone interface
Researcher (PI) Rui Manuel Marques Fernandes da Costa
Host Institution (HI) FUNDACAO D. ANNA SOMMER CHAMPALIMAUD E DR. CARLOS MONTEZ CHAMPALIMAUD
Call Details Proof of Concept (PoC), PC1, ERC-2015-PoC
Summary Non-invasive Brain Machine Interfaces (BMI) bring great promise for neuro-rehabilitation and neuro-prosthesis, as well as for brain control of everyday devices and performance of simple tasks. Over the last 15 years the interest in BMIs has grown substantially, and a variety of interfaces have been developed. The field has been growing dramatically, and market studies reveal an estimated market size of $1.46 billion by 2020. However, non-invasive BMIs have failed to reach the impressive control seen by BMIs implanted in the brain. To date, they require considerable training to reach a moderate level of control, they are susceptible to noise and interference, do not generalize between people and devices, and performance does not show long-term consolidation. Results from our ERC-funded work uncovered a new paradigm that dramatically improves these issues. We propose to develop a prototype for a novel, standalone, non-invasive, noise-resistant BMI, based on an unexplored BMI learning paradigm. In this POC we will 1) refine the brain signal interface (decoder) to be automatically customizable to each individual and produces faster training, 2) implement our BMI technology into a portable hardware-based system, and 3) develop a virtual reality/gaming training platform that will increase learning, performance and consolidation of BMI control. In addition to these technical aims, we propose to explore commercial opportunities and societal benefits, in particular in the health sector. We will conduct market analysis and develop a business case for this product, while expanding industry contacts for production and commercialization.
The work proposed in this PoC grant will permit, for the first time to our knowledge, the development of a portable, stand-alone, noise-resistant, and easy to learn BMI, applicable across a wide set of devices, which will bring a significant social impact in health, entertainment and other applications.
Summary
Non-invasive Brain Machine Interfaces (BMI) bring great promise for neuro-rehabilitation and neuro-prosthesis, as well as for brain control of everyday devices and performance of simple tasks. Over the last 15 years the interest in BMIs has grown substantially, and a variety of interfaces have been developed. The field has been growing dramatically, and market studies reveal an estimated market size of $1.46 billion by 2020. However, non-invasive BMIs have failed to reach the impressive control seen by BMIs implanted in the brain. To date, they require considerable training to reach a moderate level of control, they are susceptible to noise and interference, do not generalize between people and devices, and performance does not show long-term consolidation. Results from our ERC-funded work uncovered a new paradigm that dramatically improves these issues. We propose to develop a prototype for a novel, standalone, non-invasive, noise-resistant BMI, based on an unexplored BMI learning paradigm. In this POC we will 1) refine the brain signal interface (decoder) to be automatically customizable to each individual and produces faster training, 2) implement our BMI technology into a portable hardware-based system, and 3) develop a virtual reality/gaming training platform that will increase learning, performance and consolidation of BMI control. In addition to these technical aims, we propose to explore commercial opportunities and societal benefits, in particular in the health sector. We will conduct market analysis and develop a business case for this product, while expanding industry contacts for production and commercialization.
The work proposed in this PoC grant will permit, for the first time to our knowledge, the development of a portable, stand-alone, noise-resistant, and easy to learn BMI, applicable across a wide set of devices, which will bring a significant social impact in health, entertainment and other applications.
Max ERC Funding
149 625 €
Duration
Start date: 2016-09-01, End date: 2018-02-28
