Project acronym 3DBIOLUNG
Project Bioengineering lung tissue using extracellular matrix based 3D bioprinting
Researcher (PI) Darcy WAGNER
Host Institution (HI) LUNDS UNIVERSITET
Call Details Starting Grant (StG), LS9, ERC-2018-STG
Summary Chronic lung diseases are increasing in prevalence with over 65 million patients worldwide. Lung transplantation remains the only potential option at end-stage disease. Around 4000 patients receive lung transplants annually with more awaiting transplantation, including 1000 patients in Europe. New options to increase available tissue for lung transplantation are desperately needed.
An exciting new research area focuses on generating lung tissue ex vivo using bioengineering approaches. Scaffolds can be generated from synthetic or biologically-derived (acellular) materials, seeded with cells and grown in a bioreactor prior to transplantation. Ideally, scaffolds would be seeded with cells derived from the transplant recipient, thus obviating the need for long-term immunosuppression. However, functional regeneration has yet to be achieved. New advances in 3D printing and 3D bioprinting (when cells are printed) indicate that this once thought of science-fiction concept might finally be mature enough for complex tissues, including lung. 3D bioprinting addresses a number of concerns identified in previous approaches, such as a) patient heterogeneity in acellular human scaffolds, b) anatomical differences in xenogeneic sources, c) lack of biological cues on synthetic materials and d) difficulty in manufacturing the complex lung architecture. 3D bioprinting could be a reproducible, scalable, and controllable approach for generating functional lung tissue.
The aim of this proposal is to use custom 3D bioprinters to generate constructs mimicking lung tissue using an innovative approach combining primary cells, the engineering reproducibility of synthetic materials, and the biologically conductive properties of acellular lung (hybrid). We will 3D bioprint hybrid murine and human lung tissue models and test gas exchange, angiogenesis and in vivo immune responses. This proposal will be a critical first step in demonstrating feasibility of 3D bioprinting lung tissue.
Summary
Chronic lung diseases are increasing in prevalence with over 65 million patients worldwide. Lung transplantation remains the only potential option at end-stage disease. Around 4000 patients receive lung transplants annually with more awaiting transplantation, including 1000 patients in Europe. New options to increase available tissue for lung transplantation are desperately needed.
An exciting new research area focuses on generating lung tissue ex vivo using bioengineering approaches. Scaffolds can be generated from synthetic or biologically-derived (acellular) materials, seeded with cells and grown in a bioreactor prior to transplantation. Ideally, scaffolds would be seeded with cells derived from the transplant recipient, thus obviating the need for long-term immunosuppression. However, functional regeneration has yet to be achieved. New advances in 3D printing and 3D bioprinting (when cells are printed) indicate that this once thought of science-fiction concept might finally be mature enough for complex tissues, including lung. 3D bioprinting addresses a number of concerns identified in previous approaches, such as a) patient heterogeneity in acellular human scaffolds, b) anatomical differences in xenogeneic sources, c) lack of biological cues on synthetic materials and d) difficulty in manufacturing the complex lung architecture. 3D bioprinting could be a reproducible, scalable, and controllable approach for generating functional lung tissue.
The aim of this proposal is to use custom 3D bioprinters to generate constructs mimicking lung tissue using an innovative approach combining primary cells, the engineering reproducibility of synthetic materials, and the biologically conductive properties of acellular lung (hybrid). We will 3D bioprint hybrid murine and human lung tissue models and test gas exchange, angiogenesis and in vivo immune responses. This proposal will be a critical first step in demonstrating feasibility of 3D bioprinting lung tissue.
Max ERC Funding
1 499 975 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym ActionContraThreat
Project Action selection under threat: the complex control of human defense
Researcher (PI) Dominik BACH
Host Institution (HI) UNIVERSITAT ZURICH
Call Details Consolidator Grant (CoG), SH4, ERC-2018-COG
Summary Run away, sidestep, duck-and-cover, watch: when under threat, humans immediately choreograph a large repertoire of defensive actions. Understanding action-selection under threat is important for anybody wanting to explain why anxiety disorders imply some of these behaviours in harmless situations. Current concepts of human defensive behaviour are largely derived from rodent research and focus on a small number of broad, cross-species, action tendencies. This is likely to underestimate the complexity of the underlying action-selection mechanisms. This research programme will take decisive steps to understand these psychological mechanisms and elucidate their neural implementation.
To elicit threat-related action in the laboratory, I will use virtual reality computer games with full body motion, and track actions with motion-capture technology. Based on a cognitive-computational framework, I will systematically characterise the space of actions under threat, investigate the psychological mechanisms by which actions are selected in different scenarios, and describe them with computational algorithms that allow quantitative predictions. To independently verify their neural implementation, I will use wearable magnetoencephalography (MEG) in freely moving subjects.
This proposal fills a lacuna between defence system concepts based on rodent research, emotion psychology, and clinical accounts of anxiety disorders. By combining a stringent experimental approach with the formalism of cognitive-computational psychology, it furnishes a unique opportunity to understand the mechanisms of action-selection under threat, and how these are distinct from more general-purpose action-selection systems. Beyond its immediate scope, the proposal has a potential to lead to a better understanding of anxiety disorders, and to pave the way towards improved diagnostics and therapies.
Summary
Run away, sidestep, duck-and-cover, watch: when under threat, humans immediately choreograph a large repertoire of defensive actions. Understanding action-selection under threat is important for anybody wanting to explain why anxiety disorders imply some of these behaviours in harmless situations. Current concepts of human defensive behaviour are largely derived from rodent research and focus on a small number of broad, cross-species, action tendencies. This is likely to underestimate the complexity of the underlying action-selection mechanisms. This research programme will take decisive steps to understand these psychological mechanisms and elucidate their neural implementation.
To elicit threat-related action in the laboratory, I will use virtual reality computer games with full body motion, and track actions with motion-capture technology. Based on a cognitive-computational framework, I will systematically characterise the space of actions under threat, investigate the psychological mechanisms by which actions are selected in different scenarios, and describe them with computational algorithms that allow quantitative predictions. To independently verify their neural implementation, I will use wearable magnetoencephalography (MEG) in freely moving subjects.
This proposal fills a lacuna between defence system concepts based on rodent research, emotion psychology, and clinical accounts of anxiety disorders. By combining a stringent experimental approach with the formalism of cognitive-computational psychology, it furnishes a unique opportunity to understand the mechanisms of action-selection under threat, and how these are distinct from more general-purpose action-selection systems. Beyond its immediate scope, the proposal has a potential to lead to a better understanding of anxiety disorders, and to pave the way towards improved diagnostics and therapies.
Max ERC Funding
1 998 750 €
Duration
Start date: 2019-10-01, End date: 2024-09-30
Project acronym AMADEUS
Project Advancing CO2 Capture Materials by Atomic Scale Design: the Quest for Understanding
Researcher (PI) Christoph Rüdiger MÜLLER
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Consolidator Grant (CoG), PE8, ERC-2018-COG
Summary Carbon dioxide capture and storage is a technology to mitigate climate change by removing CO2 from flue gas streams or the atmosphere and storing it in geological formations. While CO2 removal from natural gas by amine scrubbing is implemented on the large scale, the cost of such process is currently prohibitively expensive. Inexpensive alkali earth metal oxides (MgO and CaO) feature high theoretical CO2 uptakes, but suffer from poor cyclic stability and slow kinetics. Yet, the key objective of recent research on alkali earth metal oxide based CO2 sorbents has been the processing of inexpensive, naturally occurring CO2 sorbents, notably limestone and dolomite, to stabilize their modest CO2 uptake and to establish re-activation methods through engineering approaches. While this research demonstrated a landmark Megawatt (MW) scale viability of the process, our fundamental understanding of the underlying CO2 capture, regeneration and deactivation pathways did not improve. The latter knowledge is, however, vital for the rational design of improved, yet practical CaO and MgO sorbents. Hence this proposal is concerned with obtaining an understanding of the underlying mechanisms that control the ability of an alkali metal oxide to capture a large quantity of CO2 with a high rate, to regenerate and to operate with high cyclic stability. Achieving these aims relies on the ability to fabricate model structures and to characterize in great detail their surface chemistry, morphology, chemical composition and changes therein under reactive conditions. This makes the development of operando and in situ characterization tools an essential prerequisite. Advances in these areas shall allow achieving the overall goal of this project, viz. to formulate a roadmap to fabricate improved CO2 sorbents through their precisely engineered structure, composition and morphology.
Summary
Carbon dioxide capture and storage is a technology to mitigate climate change by removing CO2 from flue gas streams or the atmosphere and storing it in geological formations. While CO2 removal from natural gas by amine scrubbing is implemented on the large scale, the cost of such process is currently prohibitively expensive. Inexpensive alkali earth metal oxides (MgO and CaO) feature high theoretical CO2 uptakes, but suffer from poor cyclic stability and slow kinetics. Yet, the key objective of recent research on alkali earth metal oxide based CO2 sorbents has been the processing of inexpensive, naturally occurring CO2 sorbents, notably limestone and dolomite, to stabilize their modest CO2 uptake and to establish re-activation methods through engineering approaches. While this research demonstrated a landmark Megawatt (MW) scale viability of the process, our fundamental understanding of the underlying CO2 capture, regeneration and deactivation pathways did not improve. The latter knowledge is, however, vital for the rational design of improved, yet practical CaO and MgO sorbents. Hence this proposal is concerned with obtaining an understanding of the underlying mechanisms that control the ability of an alkali metal oxide to capture a large quantity of CO2 with a high rate, to regenerate and to operate with high cyclic stability. Achieving these aims relies on the ability to fabricate model structures and to characterize in great detail their surface chemistry, morphology, chemical composition and changes therein under reactive conditions. This makes the development of operando and in situ characterization tools an essential prerequisite. Advances in these areas shall allow achieving the overall goal of this project, viz. to formulate a roadmap to fabricate improved CO2 sorbents through their precisely engineered structure, composition and morphology.
Max ERC Funding
1 994 900 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym Andrea
Project A Novel Detection protocols for REliable prostate cancer Assays
Researcher (PI) Jan TKAC
Host Institution (HI) CHEMICKY USTAV SLOVENSKEJ AKADEMIEVIED
Call Details Proof of Concept (PoC), ERC-2018-PoC
Summary The technology validation was successfully completed indicating a great commercial potential, and the innovative and inventive aspects of the assay platform are now covered by the filed priority European Patent Office (EPO) patent applications. Validated glycoprofiling of the proteins now uses lectins in a format, fully compatible with clinical PSA assay kits. This PoC grant focuses on 1. Pre-clinical retrospective validation of the early stage biomarker of prostate cancer (PCa) and 2. Commercialisation of the PCa diagnostics kit. Pre-clinical (60 human serum samples) is ongoing and retrospective validation study (450 human serum samples) of the assay will be performed by statistical analysis using a receiver operating characteristic (ROC) curve. The PoC describes all steps, which have been developed so far and all necessary steps, which need to be done for retrospective validation study, product development and commercialisation through our newly incorporated start-up Glycanostics Ltd. (www.glycanostics.com). We will provide PCa diagnostic test resulting in a second opinion to guide the right decision if the biopsy is needed. This will avoid the needless and unreliable biopsies and in the future rival an inaccurate PSA testing.
Summary
The technology validation was successfully completed indicating a great commercial potential, and the innovative and inventive aspects of the assay platform are now covered by the filed priority European Patent Office (EPO) patent applications. Validated glycoprofiling of the proteins now uses lectins in a format, fully compatible with clinical PSA assay kits. This PoC grant focuses on 1. Pre-clinical retrospective validation of the early stage biomarker of prostate cancer (PCa) and 2. Commercialisation of the PCa diagnostics kit. Pre-clinical (60 human serum samples) is ongoing and retrospective validation study (450 human serum samples) of the assay will be performed by statistical analysis using a receiver operating characteristic (ROC) curve. The PoC describes all steps, which have been developed so far and all necessary steps, which need to be done for retrospective validation study, product development and commercialisation through our newly incorporated start-up Glycanostics Ltd. (www.glycanostics.com). We will provide PCa diagnostic test resulting in a second opinion to guide the right decision if the biopsy is needed. This will avoid the needless and unreliable biopsies and in the future rival an inaccurate PSA testing.
Max ERC Funding
149 500 €
Duration
Start date: 2018-12-01, End date: 2020-05-31
Project acronym ANTHROPOID
Project Great ape organoids to reconstruct uniquely human development
Researcher (PI) Jarrett CAMP
Host Institution (HI) INSTITUT FUR MOLEKULARE UND KLINISCHE OPHTHALMOLOGIE BASEL
Call Details Starting Grant (StG), LS2, ERC-2018-STG
Summary Humans diverged from our closest living relatives, chimpanzees and other great apes, 6-10 million years ago. Since this divergence, our ancestors acquired genetic changes that enhanced cognition, altered metabolism, and endowed our species with an adaptive capacity to colonize the entire planet and reshape the biosphere. Through genome comparisons between modern humans, Neandertals, chimpanzees and other apes we have identified genetic changes that likely contribute to innovations in human metabolic and cognitive physiology. However, it has been difficult to assess the functional effects of these genetic changes due to the lack of cell culture systems that recapitulate great ape organ complexity. Human and chimpanzee pluripotent stem cells (PSCs) can self-organize into three-dimensional (3D) tissues that recapitulate the morphology, function, and genetic programs controlling organ development. Our vision is to use organoids to study the changes that set modern humans apart from our closest evolutionary relatives as well as all other organisms on the planet. In ANTHROPOID we will generate a great ape developmental cell atlas using cortex, liver, and small intestine organoids. We will use single-cell transcriptomics and chromatin accessibility to identify cell type-specific features of transcriptome divergence at cellular resolution. We will dissect enhancer evolution using single-cell genomic screens and ancestralize human cells to resurrect pre-human cellular phenotypes. ANTHROPOID utilizes quantitative and state-of-the-art methods to explore exciting high-risk questions at multiple branches of the modern human lineage. This project is a ground breaking starting point to replay evolution and tackle the ancient question of what makes us uniquely human?
Summary
Humans diverged from our closest living relatives, chimpanzees and other great apes, 6-10 million years ago. Since this divergence, our ancestors acquired genetic changes that enhanced cognition, altered metabolism, and endowed our species with an adaptive capacity to colonize the entire planet and reshape the biosphere. Through genome comparisons between modern humans, Neandertals, chimpanzees and other apes we have identified genetic changes that likely contribute to innovations in human metabolic and cognitive physiology. However, it has been difficult to assess the functional effects of these genetic changes due to the lack of cell culture systems that recapitulate great ape organ complexity. Human and chimpanzee pluripotent stem cells (PSCs) can self-organize into three-dimensional (3D) tissues that recapitulate the morphology, function, and genetic programs controlling organ development. Our vision is to use organoids to study the changes that set modern humans apart from our closest evolutionary relatives as well as all other organisms on the planet. In ANTHROPOID we will generate a great ape developmental cell atlas using cortex, liver, and small intestine organoids. We will use single-cell transcriptomics and chromatin accessibility to identify cell type-specific features of transcriptome divergence at cellular resolution. We will dissect enhancer evolution using single-cell genomic screens and ancestralize human cells to resurrect pre-human cellular phenotypes. ANTHROPOID utilizes quantitative and state-of-the-art methods to explore exciting high-risk questions at multiple branches of the modern human lineage. This project is a ground breaking starting point to replay evolution and tackle the ancient question of what makes us uniquely human?
Max ERC Funding
1 500 000 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym ARTSILK
Project Novel approaches to the generation of artificial spider silk superfibers
Researcher (PI) Anna RISING
Host Institution (HI) KAROLINSKA INSTITUTET
Call Details Consolidator Grant (CoG), LS9, ERC-2018-COG
Summary Spider silk is Nature’s high performance material that has the potential to revolutionize the materials industry. However, production and spinning of artificial spider silk fibers are challenging, and current methods to produce silk fibers include denaturing conditions which prevent the silk proteins from assembling into fibers in the same complex way as native silk proteins do. In order to fulfill the potential of spider silk we need to increase our understanding of the silk formation process and decipher how protein folding and interactions relate to mechanical properties of the resulting silk fiber. Recent insights into the physiology and molecular mechanisms of the spinning process has made it possible to develop a biomimetic artificial spider silk spinning device (see our publications Andersson et al. Nat Chem Biol. 2017; Otikovs et al. Angew Chemie Int Engl Ed. 2017). We are, for the first time, able to spin artificial silk fibers in which the proteins adopt correct secondary, tertiary and quaternary structures.
The overall objective of ARTSILK is to build on these recent technical leaps and use state-of-the-art technologies to generate artificial silk fibers that are equal or superior to native spider silk in terms of toughness and tensile strength.
To reach the overall objective we will use the recently mapped spider genome, protein engineering and single cell RNA (ScRNA) sequencing to design novel silk proteins for fiber production. We will also study the relationship between protein secondary structure formation and fiber mechanical properties in order to decipher the ques that determine mechanical properties of the fiber. This knowledge will be important also for the basic understanding of how soluble proteins covert into b-sheet rich fibrils in, e.g., Alzheimer’s disease. Finally, we will use microfluidic chips to engineer the next generation spinning device and 3D-printing techniques to make reproducible three-dimensional structures of spider silk.
Summary
Spider silk is Nature’s high performance material that has the potential to revolutionize the materials industry. However, production and spinning of artificial spider silk fibers are challenging, and current methods to produce silk fibers include denaturing conditions which prevent the silk proteins from assembling into fibers in the same complex way as native silk proteins do. In order to fulfill the potential of spider silk we need to increase our understanding of the silk formation process and decipher how protein folding and interactions relate to mechanical properties of the resulting silk fiber. Recent insights into the physiology and molecular mechanisms of the spinning process has made it possible to develop a biomimetic artificial spider silk spinning device (see our publications Andersson et al. Nat Chem Biol. 2017; Otikovs et al. Angew Chemie Int Engl Ed. 2017). We are, for the first time, able to spin artificial silk fibers in which the proteins adopt correct secondary, tertiary and quaternary structures.
The overall objective of ARTSILK is to build on these recent technical leaps and use state-of-the-art technologies to generate artificial silk fibers that are equal or superior to native spider silk in terms of toughness and tensile strength.
To reach the overall objective we will use the recently mapped spider genome, protein engineering and single cell RNA (ScRNA) sequencing to design novel silk proteins for fiber production. We will also study the relationship between protein secondary structure formation and fiber mechanical properties in order to decipher the ques that determine mechanical properties of the fiber. This knowledge will be important also for the basic understanding of how soluble proteins covert into b-sheet rich fibrils in, e.g., Alzheimer’s disease. Finally, we will use microfluidic chips to engineer the next generation spinning device and 3D-printing techniques to make reproducible three-dimensional structures of spider silk.
Max ERC Funding
2 000 000 €
Duration
Start date: 2019-05-01, End date: 2024-04-30
Project acronym AUTOMATION
Project AUTOMATION AND INCOME DISTRIBUTION: A QUANTITATIVE ASSESSMENT
Researcher (PI) David Hémous
Host Institution (HI) UNIVERSITAT ZURICH
Call Details Starting Grant (StG), SH1, ERC-2018-STG
Summary Since the invention of the spinning frame, automation has been one of the drivers of economic growth. Yet, workers, economist or the general public have been concerned that automation may destroy jobs or create inequality. This concern is particularly prevalent today with the sustained rise in economic inequality and fast technological progress in IT, robotics or self-driving cars. The empirical literature has showed the impact of automation on income distribution. Yet, the level of wages itself should also affect the incentives to undertake automation innovations. Understanding this feedback is key to assess the long-term effect of policies. My project aims to provide the first quantitative account of the two-way relationship between automation and the income distribution.
It is articulated around three parts. First, I will use patent data to study empirically the causal effect of wages on automation innovations. To do so, I will build firm-level variation in the wages of the customers of innovating firms by exploiting variations in firms’ exposure to international markets. Second, I will study empirically the causal effect of automation innovations on wages. There, I will focus on local labour market and use the patent data to build exogenous variations in local knowledge. Third, I will calibrate an endogenous growth model with firm dynamics and automation using Danish firm-level data. The model will replicate stylized facts on the labour share distribution across firms. It will be used to compute the contribution of automation to economic growth or the decline of the labour share. Moreover, as a whole, the project will use two different methods (regression analysis and calibrated model) and two different types of data, to answer questions of crucial policy importance such as: Taking into account the response of automation, what are the long-term effects on wages of an increase in the minimum wage, a reduction in labour costs, or a robot tax?
Summary
Since the invention of the spinning frame, automation has been one of the drivers of economic growth. Yet, workers, economist or the general public have been concerned that automation may destroy jobs or create inequality. This concern is particularly prevalent today with the sustained rise in economic inequality and fast technological progress in IT, robotics or self-driving cars. The empirical literature has showed the impact of automation on income distribution. Yet, the level of wages itself should also affect the incentives to undertake automation innovations. Understanding this feedback is key to assess the long-term effect of policies. My project aims to provide the first quantitative account of the two-way relationship between automation and the income distribution.
It is articulated around three parts. First, I will use patent data to study empirically the causal effect of wages on automation innovations. To do so, I will build firm-level variation in the wages of the customers of innovating firms by exploiting variations in firms’ exposure to international markets. Second, I will study empirically the causal effect of automation innovations on wages. There, I will focus on local labour market and use the patent data to build exogenous variations in local knowledge. Third, I will calibrate an endogenous growth model with firm dynamics and automation using Danish firm-level data. The model will replicate stylized facts on the labour share distribution across firms. It will be used to compute the contribution of automation to economic growth or the decline of the labour share. Moreover, as a whole, the project will use two different methods (regression analysis and calibrated model) and two different types of data, to answer questions of crucial policy importance such as: Taking into account the response of automation, what are the long-term effects on wages of an increase in the minimum wage, a reduction in labour costs, or a robot tax?
Max ERC Funding
1 295 890 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym AXPLAST
Project Deep brain imaging of cellular mechanisms of sensory processing and learning
Researcher (PI) Jan GRUNDEMANN
Host Institution (HI) UNIVERSITAT BASEL
Call Details Starting Grant (StG), LS5, ERC-2018-STG
Summary Learning and memory are the basis of our behaviour and mental well-being. Understanding the mechanisms of structural and cellular plasticity in defined neuronal circuits in vivo will be crucial to elucidate principles of circuit-specific memory formation and their relation to changes in neuronal ensemble dynamics.
Structural plasticity studies were technically limited to cortex, excluding deep brain areas like the amygdala, and mainly focussed on the input site (dendritic spines), whilst the plasticity of the axon initial segment (AIS), a neuron’s site of output generation, was so far not studied in vivo. Length and location of the AIS are plastic and strongly affects a neurons spike output. However, it remains unknown if AIS plasticity regulates neuronal activity upon learning in vivo.
We will combine viral expression of AIS live markers and genetically-encoded Ca2+-sensors with novel deep brain imaging techniques via gradient index (GRIN) lenses to investigate how AIS location and length are regulated upon associative learning in amygdala circuits in vivo. Two-photon time-lapse imaging of the AIS of amygdala neurons upon fear conditioning will help us to track learning-driven AIS location dynamics. Next, we will combine miniature microscope imaging of neuronal activity in freely moving animals with two-photon imaging to link AIS location, length and plasticity to the intrinsic activity as well as learning-related response plasticity of amygdala neurons during fear learning and extinction in vivo. Finally, we will test if AIS plasticity is a general cellular plasticity mechanisms in brain areas afferent to the amygdala, e.g. thalamus.
Using a combination of two-photon and miniature microscopy imaging to map structural dynamics of defined neural circuits in the amygdala and its thalamic input areas will provide fundamental insights into the cellular mechanisms underlying sensory processing upon learning and relate network level plasticity with the cellular level.
Summary
Learning and memory are the basis of our behaviour and mental well-being. Understanding the mechanisms of structural and cellular plasticity in defined neuronal circuits in vivo will be crucial to elucidate principles of circuit-specific memory formation and their relation to changes in neuronal ensemble dynamics.
Structural plasticity studies were technically limited to cortex, excluding deep brain areas like the amygdala, and mainly focussed on the input site (dendritic spines), whilst the plasticity of the axon initial segment (AIS), a neuron’s site of output generation, was so far not studied in vivo. Length and location of the AIS are plastic and strongly affects a neurons spike output. However, it remains unknown if AIS plasticity regulates neuronal activity upon learning in vivo.
We will combine viral expression of AIS live markers and genetically-encoded Ca2+-sensors with novel deep brain imaging techniques via gradient index (GRIN) lenses to investigate how AIS location and length are regulated upon associative learning in amygdala circuits in vivo. Two-photon time-lapse imaging of the AIS of amygdala neurons upon fear conditioning will help us to track learning-driven AIS location dynamics. Next, we will combine miniature microscope imaging of neuronal activity in freely moving animals with two-photon imaging to link AIS location, length and plasticity to the intrinsic activity as well as learning-related response plasticity of amygdala neurons during fear learning and extinction in vivo. Finally, we will test if AIS plasticity is a general cellular plasticity mechanisms in brain areas afferent to the amygdala, e.g. thalamus.
Using a combination of two-photon and miniature microscopy imaging to map structural dynamics of defined neural circuits in the amygdala and its thalamic input areas will provide fundamental insights into the cellular mechanisms underlying sensory processing upon learning and relate network level plasticity with the cellular level.
Max ERC Funding
1 475 475 €
Duration
Start date: 2018-12-01, End date: 2023-11-30
Project acronym AxScale
Project Axions and relatives across different mass scales
Researcher (PI) Babette DÖBRICH
Host Institution (HI) EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH
Call Details Starting Grant (StG), PE2, ERC-2018-STG
Summary Pseudoscalar QCD axions and axion-like Particles (ALPs) are an excellent candidate for Dark Matter or can act as a mediator particle for Dark Matter. Since the discovery of the Higgs boson, we know that fundamental scalars exist and it is timely to explore the Axion/ALP parameter space more intensively. A look at the allowed axion/ALP parameter space makes it clear that these might exist at low mass (below few eV), as (part of) Dark Matter. Alternatively they might exist at higher mass, above roughly the MeV scale, potentially as a Dark Matter mediator particle. AxScale explores parts of these different mass regions, with complementary techniques but with one research team.
Firstly, with RADES, it develops a novel concept for a filter-like cavity for the search of QCD axion Dark matter at a few tens of a micro-eV. Dark Matter Axions can be discovered by their resonant conversion in that cavity embedded in a strong magnetic field. The `classical axion window' has recently received much interest from cosmological model-building and I will implement a novel cavity concept that will allow to explore this Dark Matter parameter region.
Secondly, AxScale searches for axions and ALPs using the NA62 detector at CERN's SPS. Especially the mass region above a few MeV can be efficiently searched by the use of a proton fixed-target facility. During nominal data taking NA62 investigates a Kaon beam. NA62 can also run in a mode in which its primary proton beam is fully dumped. With the resulting high interaction rate, the existence of weakly coupled particles can be efficiently probed. Thus, searches for ALPs from Kaon decays as well as from production in dumped protons with NA62 are foreseen in AxScale. More generally, NA62 can look for a plethora of `Dark Sector' particles with recorded and future data. With the AxScale program I aim at maximizing the reach of NA62 for these new physics models.
Summary
Pseudoscalar QCD axions and axion-like Particles (ALPs) are an excellent candidate for Dark Matter or can act as a mediator particle for Dark Matter. Since the discovery of the Higgs boson, we know that fundamental scalars exist and it is timely to explore the Axion/ALP parameter space more intensively. A look at the allowed axion/ALP parameter space makes it clear that these might exist at low mass (below few eV), as (part of) Dark Matter. Alternatively they might exist at higher mass, above roughly the MeV scale, potentially as a Dark Matter mediator particle. AxScale explores parts of these different mass regions, with complementary techniques but with one research team.
Firstly, with RADES, it develops a novel concept for a filter-like cavity for the search of QCD axion Dark matter at a few tens of a micro-eV. Dark Matter Axions can be discovered by their resonant conversion in that cavity embedded in a strong magnetic field. The `classical axion window' has recently received much interest from cosmological model-building and I will implement a novel cavity concept that will allow to explore this Dark Matter parameter region.
Secondly, AxScale searches for axions and ALPs using the NA62 detector at CERN's SPS. Especially the mass region above a few MeV can be efficiently searched by the use of a proton fixed-target facility. During nominal data taking NA62 investigates a Kaon beam. NA62 can also run in a mode in which its primary proton beam is fully dumped. With the resulting high interaction rate, the existence of weakly coupled particles can be efficiently probed. Thus, searches for ALPs from Kaon decays as well as from production in dumped protons with NA62 are foreseen in AxScale. More generally, NA62 can look for a plethora of `Dark Sector' particles with recorded and future data. With the AxScale program I aim at maximizing the reach of NA62 for these new physics models.
Max ERC Funding
1 134 375 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym BALANCE
Project Mapping Dispersion Spectroscopically in Large Gas-Phase Molecular Ions
Researcher (PI) Peter CHEN
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Advanced Grant (AdG), PE4, ERC-2018-ADG
Summary We use IR spectroscopy of trapped ions in a cryogenic FT-ICR spectrometer to probe non-covalent, “dispersion” interactions in large, gas-phase molecular ions. We will measure conformational equilibria by N-H frequency shifts, and correlate gas-phase IR frequency to the N-H-N bond angle in an ionic H-bond. Substituents on “onium” cations can adopt various conformations, whose energies map interaction potentials. Substituents on their proton-bound dimers interact non-covalently through dispersion forces, whose quantitative evaluation in large molecules has remained difficult despite dispersion becoming increasingly cited as a design principle in the construction of catalysts and materials. The non-covalent interactions bend the N-H-N bond, leading to large shifts in the IR frequency. The proton-bound dimer acts like a molecular balance where the non-covalent interaction, is set against the bending potential in an ionic hydrogen bond. Despite encouragingly accurate calculations for small molecules, experimental benchmarks for large molecules in the gas phase remain scarce, and there is evidence that the good results for small molecules may not extrapolate reliably to large molecules. The present proposal introduces a new experimental probe of non-covalent interactions, providing a sensitive test of the diverging results coming from various computational methods and other experiments. The experiment must be done on isolated molecules in the gas phase, as previous work has shown that solvation substantially cancels out the attractive potential. Accordingly, the proposed experimental design, which involves a custom-built spectrometer, newly available tunable IR sources, chemical synthesis of custom substrates, and quantum calculations up to coupled-cluster levels of theory, showcases how an interdisciplinary approach combining physical and organic chemistry can solve a fundamental problem that impacts how we understand steric effects in organic chemistry.
Summary
We use IR spectroscopy of trapped ions in a cryogenic FT-ICR spectrometer to probe non-covalent, “dispersion” interactions in large, gas-phase molecular ions. We will measure conformational equilibria by N-H frequency shifts, and correlate gas-phase IR frequency to the N-H-N bond angle in an ionic H-bond. Substituents on “onium” cations can adopt various conformations, whose energies map interaction potentials. Substituents on their proton-bound dimers interact non-covalently through dispersion forces, whose quantitative evaluation in large molecules has remained difficult despite dispersion becoming increasingly cited as a design principle in the construction of catalysts and materials. The non-covalent interactions bend the N-H-N bond, leading to large shifts in the IR frequency. The proton-bound dimer acts like a molecular balance where the non-covalent interaction, is set against the bending potential in an ionic hydrogen bond. Despite encouragingly accurate calculations for small molecules, experimental benchmarks for large molecules in the gas phase remain scarce, and there is evidence that the good results for small molecules may not extrapolate reliably to large molecules. The present proposal introduces a new experimental probe of non-covalent interactions, providing a sensitive test of the diverging results coming from various computational methods and other experiments. The experiment must be done on isolated molecules in the gas phase, as previous work has shown that solvation substantially cancels out the attractive potential. Accordingly, the proposed experimental design, which involves a custom-built spectrometer, newly available tunable IR sources, chemical synthesis of custom substrates, and quantum calculations up to coupled-cluster levels of theory, showcases how an interdisciplinary approach combining physical and organic chemistry can solve a fundamental problem that impacts how we understand steric effects in organic chemistry.
Max ERC Funding
2 446 125 €
Duration
Start date: 2019-05-01, End date: 2024-04-30
