Project acronym 2D-TOPSENSE
Project Tunable optoelectronic devices by strain engineering of 2D semiconductors
Researcher (PI) Andres CASTELLANOS
Host Institution (HI) AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
Call Details Starting Grant (StG), PE7, ERC-2017-STG
Summary The goal of 2D-TOPSENSE is to exploit the remarkable stretchability of two-dimensional semiconductors to fabricate optoelectronic devices where strain is used as an external knob to tune their properties.
While bulk semiconductors tend to break under strains larger than 1.5%, 2D semiconductors (such as MoS2) can withstand deformations of up to 10-20% before rupture. This large breaking strength promises a great potential of 2D semiconductors as ‘straintronic’ materials, whose properties can be adjusted by applying a deformation to their lattice. In fact, recent theoretical works predicted an interesting physical phenomenon: a tensile strain-induced semiconductor-to-metal transition in 2D semiconductors. By tensioning single-layer MoS2 from 0% up to 10%, its electronic band structure is expected to undergo a continuous transition from a wide direct band-gap of 1.8 eV to a metallic behavior. This unprecedented large strain-tunability will undoubtedly have a strong impact in a wide range of optoelectronic applications such as photodetectors whose cut-off wavelength is tuned by varying the applied strain or atomically thin light modulators.
To date, experimental works on strain engineering have been mostly focused on fundamental studies, demonstrating part of the potential of 2D semiconductors in straintronics, but they have failed to exploit strain engineering to add extra functionalities to optoelectronic devices. In 2D-TOPSENSE I will go beyond the state of the art in straintronics by designing and fabricating optoelectronic devices whose properties and performance can be tuned by means of applying strain. 2D-TOPSENSE will focus on photodetectors with a tunable bandwidth and detectivity, light emitting devices whose emission wavelength can be adjusted, light modulators based on 2D semiconductors such as transition metal dichalcogenides or black phosphorus and solar funnels capable of directing the photogenerated charge carriers towards a specific position.
Summary
The goal of 2D-TOPSENSE is to exploit the remarkable stretchability of two-dimensional semiconductors to fabricate optoelectronic devices where strain is used as an external knob to tune their properties.
While bulk semiconductors tend to break under strains larger than 1.5%, 2D semiconductors (such as MoS2) can withstand deformations of up to 10-20% before rupture. This large breaking strength promises a great potential of 2D semiconductors as ‘straintronic’ materials, whose properties can be adjusted by applying a deformation to their lattice. In fact, recent theoretical works predicted an interesting physical phenomenon: a tensile strain-induced semiconductor-to-metal transition in 2D semiconductors. By tensioning single-layer MoS2 from 0% up to 10%, its electronic band structure is expected to undergo a continuous transition from a wide direct band-gap of 1.8 eV to a metallic behavior. This unprecedented large strain-tunability will undoubtedly have a strong impact in a wide range of optoelectronic applications such as photodetectors whose cut-off wavelength is tuned by varying the applied strain or atomically thin light modulators.
To date, experimental works on strain engineering have been mostly focused on fundamental studies, demonstrating part of the potential of 2D semiconductors in straintronics, but they have failed to exploit strain engineering to add extra functionalities to optoelectronic devices. In 2D-TOPSENSE I will go beyond the state of the art in straintronics by designing and fabricating optoelectronic devices whose properties and performance can be tuned by means of applying strain. 2D-TOPSENSE will focus on photodetectors with a tunable bandwidth and detectivity, light emitting devices whose emission wavelength can be adjusted, light modulators based on 2D semiconductors such as transition metal dichalcogenides or black phosphorus and solar funnels capable of directing the photogenerated charge carriers towards a specific position.
Max ERC Funding
1 930 437 €
Duration
Start date: 2018-03-01, End date: 2023-02-28
Project acronym 3DNANOMECH
Project Three-dimensional molecular resolution mapping of soft matter-liquid interfaces
Researcher (PI) Ricardo Garcia
Host Institution (HI) AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
Call Details Advanced Grant (AdG), PE4, ERC-2013-ADG
Summary Optical, electron and probe microscopes are enabling tools for discoveries and knowledge generation in nanoscale sicence and technology. High resolution –nanoscale or molecular-, noninvasive and label-free imaging of three-dimensional soft matter-liquid interfaces has not been achieved by any microscopy method.
Force microscopy (AFM) is considered the second most relevant advance in materials science since 1960. Despite its impressive range of applications, the technique has some key limitations. Force microscopy has not three dimensional depth. What lies above or in the subsurface is not readily characterized.
3DNanoMech proposes to design, build and operate a high speed force-based method for the three-dimensional characterization soft matter-liquid interfaces (3D AFM). The microscope will combine a detection method based on force perturbations, adaptive algorithms, high speed piezo actuators and quantitative-oriented multifrequency approaches. The development of the microscope cannot be separated from its applications: imaging the error-free DNA repair and to understand the relationship existing between the nanomechanical properties and the malignancy of cancer cells. Those problems encompass the different spatial –molecular-nano-mesoscopic- and time –milli to seconds- scales of the instrument.
In short, 3DNanoMech aims to image, map and measure with picoNewton, millisecond and angstrom resolution soft matter surfaces and interfaces in liquid. The long-term vision of 3DNanoMech is to replace models or computer animations of bimolecular-liquid interfaces by real time, molecular resolution maps of properties and processes.
Summary
Optical, electron and probe microscopes are enabling tools for discoveries and knowledge generation in nanoscale sicence and technology. High resolution –nanoscale or molecular-, noninvasive and label-free imaging of three-dimensional soft matter-liquid interfaces has not been achieved by any microscopy method.
Force microscopy (AFM) is considered the second most relevant advance in materials science since 1960. Despite its impressive range of applications, the technique has some key limitations. Force microscopy has not three dimensional depth. What lies above or in the subsurface is not readily characterized.
3DNanoMech proposes to design, build and operate a high speed force-based method for the three-dimensional characterization soft matter-liquid interfaces (3D AFM). The microscope will combine a detection method based on force perturbations, adaptive algorithms, high speed piezo actuators and quantitative-oriented multifrequency approaches. The development of the microscope cannot be separated from its applications: imaging the error-free DNA repair and to understand the relationship existing between the nanomechanical properties and the malignancy of cancer cells. Those problems encompass the different spatial –molecular-nano-mesoscopic- and time –milli to seconds- scales of the instrument.
In short, 3DNanoMech aims to image, map and measure with picoNewton, millisecond and angstrom resolution soft matter surfaces and interfaces in liquid. The long-term vision of 3DNanoMech is to replace models or computer animations of bimolecular-liquid interfaces by real time, molecular resolution maps of properties and processes.
Max ERC Funding
2 499 928 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym 4SUNS
Project 4-Colours/2-Junctions of III-V semiconductors on Si to use in electronics devices and solar cells
Researcher (PI) María Nair LOPEZ MARTINEZ
Host Institution (HI) UNIVERSIDAD AUTONOMA DE MADRID
Call Details Starting Grant (StG), PE7, ERC-2017-STG
Summary It was early predicted by M. Green and coeval colleagues that dividing the solar spectrum into narrow ranges of colours is the most efficient manner to convert solar energy into electrical power. Multijunction solar cells are the current solution to this challenge, which have reached over 30% conversion efficiencies by stacking 3 junctions together. However, the large fabrication costs and time hinders their use in everyday life. It has been shown that highly mismatched alloy (HMA) materials provide a powerful playground to achieve at least 3 different colour absorption regions that enable optimised energy conversion with just one junction. Combining HMA-based junctions with standard Silicon solar cells will rocket solar conversion efficiency at a reduced price. To turn this ambition into marketable devices, several efforts are still needed and few challenges must be overcome.
4SUNS is a revolutionary approach for the development of HMA materials on Silicon technology, which will bring highly efficient multi-colour solar cells costs below current multijunction devices. The project will develop the technology of HMA materials on Silicon via material synthesis opening a new technology for the future. The understanding and optimization of highly mismatched alloy materials-using GaAsNP alloy- will provide building blocks for the fabrication of laboratory-size 4-colours/2-junctions solar cells.
Using a molecular beam epitaxy system, 4SUNS will grow 4-colours/2-junctions structure as well as it will manufacture the final devices. Structural and optoelectronic characterizations will carry out to determine the quality of the materials and the solar cells characteristic to obtain a competitive product. These new solar cells are competitive products to breakthrough on the solar energy sector solar cells and allowing Europe to take leadership on high efficiency solar cells.
Summary
It was early predicted by M. Green and coeval colleagues that dividing the solar spectrum into narrow ranges of colours is the most efficient manner to convert solar energy into electrical power. Multijunction solar cells are the current solution to this challenge, which have reached over 30% conversion efficiencies by stacking 3 junctions together. However, the large fabrication costs and time hinders their use in everyday life. It has been shown that highly mismatched alloy (HMA) materials provide a powerful playground to achieve at least 3 different colour absorption regions that enable optimised energy conversion with just one junction. Combining HMA-based junctions with standard Silicon solar cells will rocket solar conversion efficiency at a reduced price. To turn this ambition into marketable devices, several efforts are still needed and few challenges must be overcome.
4SUNS is a revolutionary approach for the development of HMA materials on Silicon technology, which will bring highly efficient multi-colour solar cells costs below current multijunction devices. The project will develop the technology of HMA materials on Silicon via material synthesis opening a new technology for the future. The understanding and optimization of highly mismatched alloy materials-using GaAsNP alloy- will provide building blocks for the fabrication of laboratory-size 4-colours/2-junctions solar cells.
Using a molecular beam epitaxy system, 4SUNS will grow 4-colours/2-junctions structure as well as it will manufacture the final devices. Structural and optoelectronic characterizations will carry out to determine the quality of the materials and the solar cells characteristic to obtain a competitive product. These new solar cells are competitive products to breakthrough on the solar energy sector solar cells and allowing Europe to take leadership on high efficiency solar cells.
Max ERC Funding
1 499 719 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym AngioGenesHD
Project Epistasis analysis of angiogenes with high cellular definition
Researcher (PI) Rui Miguel Dos Santos Benedito
Host Institution (HI) CENTRO NACIONAL DE INVESTIGACIONESCARDIOVASCULARES CARLOS III (F.S.P.)
Call Details Starting Grant (StG), LS4, ERC-2014-STG
Summary Blood and lymphatic vessels have been the subject of intense investigation due to their important role in cancer development and in cardiovascular diseases. The significant advance in the methods used to modify and analyse gene function have allowed us to obtain a much better understanding of the molecular mechanisms involved in the regulation of the biology of blood vessels. However, there are two key aspects that significantly diminish our capacity to understand the function of gene networks and their intersections in vivo. One is the long time that is usually required to generate a given double mutant vertebrate tissue, and the other is the lack of single-cell genetic and phenotypic resolution. We have recently performed an in vivo comparative transcriptome analysis of highly angiogenic endothelial cells experiencing different VEGF and Notch signalling levels. These are two of the most important molecular mechanisms required for the adequate differentiation, proliferation and sprouting of endothelial cells. Using the information generated from this analysis, the overall aim of the proposed project is to characterize the vascular function of some of the previously identified genes and determine how they functionally interact with these two signalling pathways. We propose to use novel inducible genetic tools that will allow us to generate a spatially and temporally regulated fluorescent cell mosaic matrix for quantitative analysis. This will enable us to analyse with unprecedented speed and resolution the function of several different genes simultaneously, during vascular development, homeostasis or associated diseases. Understanding the genetic epistatic interactions that control the differentiation and behaviour of endothelial cells, in different contexts, and with high cellular definition, has the potential to unveil new mechanisms with high biological and therapeutic relevance.
Summary
Blood and lymphatic vessels have been the subject of intense investigation due to their important role in cancer development and in cardiovascular diseases. The significant advance in the methods used to modify and analyse gene function have allowed us to obtain a much better understanding of the molecular mechanisms involved in the regulation of the biology of blood vessels. However, there are two key aspects that significantly diminish our capacity to understand the function of gene networks and their intersections in vivo. One is the long time that is usually required to generate a given double mutant vertebrate tissue, and the other is the lack of single-cell genetic and phenotypic resolution. We have recently performed an in vivo comparative transcriptome analysis of highly angiogenic endothelial cells experiencing different VEGF and Notch signalling levels. These are two of the most important molecular mechanisms required for the adequate differentiation, proliferation and sprouting of endothelial cells. Using the information generated from this analysis, the overall aim of the proposed project is to characterize the vascular function of some of the previously identified genes and determine how they functionally interact with these two signalling pathways. We propose to use novel inducible genetic tools that will allow us to generate a spatially and temporally regulated fluorescent cell mosaic matrix for quantitative analysis. This will enable us to analyse with unprecedented speed and resolution the function of several different genes simultaneously, during vascular development, homeostasis or associated diseases. Understanding the genetic epistatic interactions that control the differentiation and behaviour of endothelial cells, in different contexts, and with high cellular definition, has the potential to unveil new mechanisms with high biological and therapeutic relevance.
Max ERC Funding
1 481 375 €
Duration
Start date: 2015-03-01, End date: 2020-02-29
Project acronym BETTERSENSE
Project Nanodevice Engineering for a Better Chemical Gas Sensing Technology
Researcher (PI) Juan Daniel Prades Garcia
Host Institution (HI) UNIVERSITAT DE BARCELONA
Call Details Starting Grant (StG), PE7, ERC-2013-StG
Summary BetterSense aims to solve the two main problems in current gas sensor technologies: the high power consumption and the poor selectivity. For the former, we propose a radically new approach: to integrate the sensing components and the energy sources intimately, at the nanoscale, in order to achieve a new kind of sensor concept featuring zero power consumption. For the latter, we will mimic the biological receptors designing a kit of gas-specific molecular organic functionalizations to reach ultra-high gas selectivity figures, comparable to those of biological processes. Both cutting-edge concepts will be developed in parallel an integrated together to render a totally new gas sensing technology that surpasses the state-of-the-art.
As a matter of fact, the project will enable, for the first time, the integration of gas detectors in energetically autonomous sensors networks. Additionally, BetterSense will provide an integral solution to the gas sensing challenge by producing a full set of gas-specific sensors over the same platform to ease their integration in multi-analyte systems. Moreover, the project approach will certainly open opportunities in adjacent fields in which power consumption, specificity and nano/micro integration are a concern, such as liquid chemical and biological sensing.
In spite of the promising evidences that demonstrate the feasibility of this proposal, there are still many scientific and technological issues to solve, most of them in the edge of what is known and what is possible today in nano-fabrication and nano/micro integration. For this reason, BetterSense also aims to contribute to the global challenge of making nanodevices compatible with scalable, cost-effective, microelectronic technologies.
For all this, addressing this challenging proposal in full requires a funding scheme compatible with a high-risk/high-gain vision to finance the full dedication of a highly motivated research team with multidisciplinary skill
Summary
BetterSense aims to solve the two main problems in current gas sensor technologies: the high power consumption and the poor selectivity. For the former, we propose a radically new approach: to integrate the sensing components and the energy sources intimately, at the nanoscale, in order to achieve a new kind of sensor concept featuring zero power consumption. For the latter, we will mimic the biological receptors designing a kit of gas-specific molecular organic functionalizations to reach ultra-high gas selectivity figures, comparable to those of biological processes. Both cutting-edge concepts will be developed in parallel an integrated together to render a totally new gas sensing technology that surpasses the state-of-the-art.
As a matter of fact, the project will enable, for the first time, the integration of gas detectors in energetically autonomous sensors networks. Additionally, BetterSense will provide an integral solution to the gas sensing challenge by producing a full set of gas-specific sensors over the same platform to ease their integration in multi-analyte systems. Moreover, the project approach will certainly open opportunities in adjacent fields in which power consumption, specificity and nano/micro integration are a concern, such as liquid chemical and biological sensing.
In spite of the promising evidences that demonstrate the feasibility of this proposal, there are still many scientific and technological issues to solve, most of them in the edge of what is known and what is possible today in nano-fabrication and nano/micro integration. For this reason, BetterSense also aims to contribute to the global challenge of making nanodevices compatible with scalable, cost-effective, microelectronic technologies.
For all this, addressing this challenging proposal in full requires a funding scheme compatible with a high-risk/high-gain vision to finance the full dedication of a highly motivated research team with multidisciplinary skill
Max ERC Funding
1 498 452 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym BIO2CHEM-D
Project Biomass to chemicals: Catalysis design from first principles for a sustainable chemical industry
Researcher (PI) Nuria Lopez
Host Institution (HI) FUNDACIO PRIVADA INSTITUT CATALA D'INVESTIGACIO QUIMICA
Call Details Starting Grant (StG), PE4, ERC-2010-StG_20091028
Summary The use of renewable feedstocks by the chemical industry is fundamental due to both the depletion of fossil
resources and the increasing pressure of environmental concerns. Biomass can act as a sustainable source of
organic industrial chemicals; however, the establishment of a renewable chemical industry that is
economically competitive with the present oil-based one requires the development of new processes to
convert biomass-derived compounds into useful industrial materials following the principles of green
chemistry. To achieve these goals, developments in several fields including heterogeneous catalysis are
needed. One of the ways to accelerate the discovery of new potentially active, selective and stable catalysts is
the massive use of computational chemistry. Recent advances have demonstrated that Density Functional
Theory coupled to ab initio thermodynamics, transition state theory and microkinetic analysis can provide a
full view of the catalytic phenomena.
The aim of the present project is thus to employ these well-tested computational techniques to the
development of a theoretical framework that can accelerate the identification of new catalysts for the
conversion of biomass derived target compounds into useful chemicals. Since compared to petroleum-based
materials-biomass derived ones are multifuncionalized, the search for new catalytic materials and processes
has a strong requirement in the selectivity of the chemical transformations. The main challenges in the
project are related to the high functionalization of the molecules, their liquid nature and the large number of
potentially competitive reaction paths. The requirements of specificity and selectivity in the chemical
transformations while keeping a reasonably flexible framework constitute a major objective. The work will
be divided in three main work packages, one devoted to the properties of small molecules or fragments
containing a single functional group; the second addresses competition in multiple functionalized molecules;
and third is dedicated to the specific transformations of two molecules that have already been identified as
potential platform generators. The goal is to identify suitable candidates that could be synthetized and tested
in the Institute facilities.
Summary
The use of renewable feedstocks by the chemical industry is fundamental due to both the depletion of fossil
resources and the increasing pressure of environmental concerns. Biomass can act as a sustainable source of
organic industrial chemicals; however, the establishment of a renewable chemical industry that is
economically competitive with the present oil-based one requires the development of new processes to
convert biomass-derived compounds into useful industrial materials following the principles of green
chemistry. To achieve these goals, developments in several fields including heterogeneous catalysis are
needed. One of the ways to accelerate the discovery of new potentially active, selective and stable catalysts is
the massive use of computational chemistry. Recent advances have demonstrated that Density Functional
Theory coupled to ab initio thermodynamics, transition state theory and microkinetic analysis can provide a
full view of the catalytic phenomena.
The aim of the present project is thus to employ these well-tested computational techniques to the
development of a theoretical framework that can accelerate the identification of new catalysts for the
conversion of biomass derived target compounds into useful chemicals. Since compared to petroleum-based
materials-biomass derived ones are multifuncionalized, the search for new catalytic materials and processes
has a strong requirement in the selectivity of the chemical transformations. The main challenges in the
project are related to the high functionalization of the molecules, their liquid nature and the large number of
potentially competitive reaction paths. The requirements of specificity and selectivity in the chemical
transformations while keeping a reasonably flexible framework constitute a major objective. The work will
be divided in three main work packages, one devoted to the properties of small molecules or fragments
containing a single functional group; the second addresses competition in multiple functionalized molecules;
and third is dedicated to the specific transformations of two molecules that have already been identified as
potential platform generators. The goal is to identify suitable candidates that could be synthetized and tested
in the Institute facilities.
Max ERC Funding
1 496 200 €
Duration
Start date: 2010-10-01, End date: 2015-09-30
Project acronym CANCERMETAB
Project Metabolic requirements for prostate cancer cell fitness
Researcher (PI) Arkaitz Carracedo Perez
Host Institution (HI) ASOCIACION CENTRO DE INVESTIGACION COOPERATIVA EN BIOCIENCIAS
Call Details Starting Grant (StG), LS4, ERC-2013-StG
Summary The actual view of cellular transformation and cancer progression supports the notion that cancer cells must undergo metabolic reprogramming in order to survive in a hostile environment. This field has experienced a renaissance in recent years, with the discovery of cancer genes regulating metabolic homeostasis, in turn being accepted as an emergent hallmark of cancer. Prostate cancer presents one of the highest incidences in men mostly in developed societies and exhibits a significant association with lifestyle environmental factors. Prostate cancer recurrence is thought to rely on a subpopulation of cancer cells with low-androgen requirements, high self-renewal potential and multidrug resistance, defined as cancer-initiating cells. However, whether this cancer cell fraction presents genuine metabolic properties that can be therapeutically relevant remains undefined. In CancerMetab, we aim to understand the potential benefit of monitoring and manipulating metabolism for prostate cancer prevention, detection and therapy. My group will carry out a multidisciplinary strategy, comprising cellular systems, genetic mouse models of prostate cancer, human epidemiological and clinical studies and bioinformatic analysis. The singularity of this proposal stems from the approach to the three key aspects that we propose to study. For prostate cancer prevention, we will use our faithful mouse model of prostate cancer to shed light on the contribution of obesity to prostate cancer. For prostate cancer detection, we will overcome the consistency issues of previously reported metabolic biomarkers by adding robustness to the human studies with mouse data integration. For prostate cancer therapy, we will focus on a cell population for which the metabolic requirements and the potential of targeting them for therapy have been overlooked to date, that is the prostate cancer-initiating cell compartment.
Summary
The actual view of cellular transformation and cancer progression supports the notion that cancer cells must undergo metabolic reprogramming in order to survive in a hostile environment. This field has experienced a renaissance in recent years, with the discovery of cancer genes regulating metabolic homeostasis, in turn being accepted as an emergent hallmark of cancer. Prostate cancer presents one of the highest incidences in men mostly in developed societies and exhibits a significant association with lifestyle environmental factors. Prostate cancer recurrence is thought to rely on a subpopulation of cancer cells with low-androgen requirements, high self-renewal potential and multidrug resistance, defined as cancer-initiating cells. However, whether this cancer cell fraction presents genuine metabolic properties that can be therapeutically relevant remains undefined. In CancerMetab, we aim to understand the potential benefit of monitoring and manipulating metabolism for prostate cancer prevention, detection and therapy. My group will carry out a multidisciplinary strategy, comprising cellular systems, genetic mouse models of prostate cancer, human epidemiological and clinical studies and bioinformatic analysis. The singularity of this proposal stems from the approach to the three key aspects that we propose to study. For prostate cancer prevention, we will use our faithful mouse model of prostate cancer to shed light on the contribution of obesity to prostate cancer. For prostate cancer detection, we will overcome the consistency issues of previously reported metabolic biomarkers by adding robustness to the human studies with mouse data integration. For prostate cancer therapy, we will focus on a cell population for which the metabolic requirements and the potential of targeting them for therapy have been overlooked to date, that is the prostate cancer-initiating cell compartment.
Max ERC Funding
1 498 686 €
Duration
Start date: 2013-11-01, End date: 2019-10-31
Project acronym CELLPLASTICITY
Project New Frontiers in Cellular Reprogramming: Exploiting Cellular Plasticity
Researcher (PI) Manuel SERRANO MARUGAN
Host Institution (HI) FUNDACIO INSTITUT DE RECERCA BIOMEDICA (IRB BARCELONA)
Call Details Advanced Grant (AdG), LS4, ERC-2014-ADG
Summary "Our research group has worked over the years at the interface between cancer and ageing, with a strong emphasis on mouse models. More recently, we became interested in cellular reprogramming because we hypothesized that understanding cellular plasticity could yield new insights into cancer and ageing. Indeed, during the previous ERC Advanced Grant, we made relevant contributions to the fields of cellular reprogramming (Nature 2013), cellular senescence (Cell 2013), cancer (Cancer Cell 2012), and ageing (Cell Metabolism 2012). Now, we take advantage of our diverse background and integrate the above processes. Our unifying hypothesis is that cellular plasticity lies at the basis of tissue regeneration (“adaptive cellular plasticity”), as well as at the origin of cancer (“maladaptive gain of cellular plasticity”) and ageing (“maladaptive loss of cellular plasticity”). A key experimental system will be our “reprogrammable mice” (with inducible expression of the four Yamanaka factors), which we regard as a tool to induce cellular plasticity in vivo. The project is divided as follows: Objective #1 – Cellular plasticity and cancer: role of tumour suppressors in in vivo de-differentiation and reprogramming / impact of transient de-differentiation on tumour initiation / lineage tracing of Oct4 to determine whether a transient pluripotent-state occurs during cancer. Objective #2 – Cellular plasticity in tissue regeneration and ageing: impact of transient de-differentiation on tissue regeneration / contribution of the damage-induced microenvironment to tissue regeneration / impact of transient de-differentiation on ageing. Objective #3: New frontiers in cellular plasticity: chemical manipulation of cellular plasticity in vivo / new states of pluripotency / characterization of in vivo induced pluripotency and its unique properties. We anticipate that the completion of this project will yield new fundamental insights into cancer, regeneration and ageing."
Summary
"Our research group has worked over the years at the interface between cancer and ageing, with a strong emphasis on mouse models. More recently, we became interested in cellular reprogramming because we hypothesized that understanding cellular plasticity could yield new insights into cancer and ageing. Indeed, during the previous ERC Advanced Grant, we made relevant contributions to the fields of cellular reprogramming (Nature 2013), cellular senescence (Cell 2013), cancer (Cancer Cell 2012), and ageing (Cell Metabolism 2012). Now, we take advantage of our diverse background and integrate the above processes. Our unifying hypothesis is that cellular plasticity lies at the basis of tissue regeneration (“adaptive cellular plasticity”), as well as at the origin of cancer (“maladaptive gain of cellular plasticity”) and ageing (“maladaptive loss of cellular plasticity”). A key experimental system will be our “reprogrammable mice” (with inducible expression of the four Yamanaka factors), which we regard as a tool to induce cellular plasticity in vivo. The project is divided as follows: Objective #1 – Cellular plasticity and cancer: role of tumour suppressors in in vivo de-differentiation and reprogramming / impact of transient de-differentiation on tumour initiation / lineage tracing of Oct4 to determine whether a transient pluripotent-state occurs during cancer. Objective #2 – Cellular plasticity in tissue regeneration and ageing: impact of transient de-differentiation on tissue regeneration / contribution of the damage-induced microenvironment to tissue regeneration / impact of transient de-differentiation on ageing. Objective #3: New frontiers in cellular plasticity: chemical manipulation of cellular plasticity in vivo / new states of pluripotency / characterization of in vivo induced pluripotency and its unique properties. We anticipate that the completion of this project will yield new fundamental insights into cancer, regeneration and ageing."
Max ERC Funding
2 488 850 €
Duration
Start date: 2015-10-01, End date: 2020-09-30
Project acronym CHEMAGEB
Project CHEMometric and High-throughput Omics Analytical Methods for Assessment of Global Change Effects on Environmental and Biological Systems
Researcher (PI) Roman Tauler Ferrer
Host Institution (HI) AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
Call Details Advanced Grant (AdG), PE4, ERC-2012-ADG_20120216
Summary We propose to develop new chemometric and high-throughput analytical methods to assess the effects of environmental and climate changes on target biological systems which are representative of ecosystems. This project will combine powerful chemometric and analytical high-throughput methodologies with toxicological tests to examine the effects of environmental stressors (like chemical pollution) and of climate change (like temperature, water scarcity or food shortage), on genomic and metabonomic profiles of target biological systems. The complex nature of experimental data produced by high-throughput analytical techniques, such as DNA microarrays, hyphenated chromatography-mass spectrometry or multi-dimensional nuclear magnetic resonance spectroscopy, requires powerful data analysis tools to extract, summarize and interpret the large amount of information that such megavariate data sets may contain. There is a need to improve and automate every step in the analysis of the data generated from genomic and metabonomic studies using new chemometric and multi- and megavariate tools. The main purpose of this project is to develop such tools. As a result of the whole study, a detailed report on the effects of global change and chemical pollution on the genomic and metabonomic profiles of a selected set of representative target biological systems will be delivered and used for global risk assessment. The information acquired, data sets and computer software will be stored in public data bases using modern data compression and data management technologies. And all the methodologies developed in the project will be published.
Summary
We propose to develop new chemometric and high-throughput analytical methods to assess the effects of environmental and climate changes on target biological systems which are representative of ecosystems. This project will combine powerful chemometric and analytical high-throughput methodologies with toxicological tests to examine the effects of environmental stressors (like chemical pollution) and of climate change (like temperature, water scarcity or food shortage), on genomic and metabonomic profiles of target biological systems. The complex nature of experimental data produced by high-throughput analytical techniques, such as DNA microarrays, hyphenated chromatography-mass spectrometry or multi-dimensional nuclear magnetic resonance spectroscopy, requires powerful data analysis tools to extract, summarize and interpret the large amount of information that such megavariate data sets may contain. There is a need to improve and automate every step in the analysis of the data generated from genomic and metabonomic studies using new chemometric and multi- and megavariate tools. The main purpose of this project is to develop such tools. As a result of the whole study, a detailed report on the effects of global change and chemical pollution on the genomic and metabonomic profiles of a selected set of representative target biological systems will be delivered and used for global risk assessment. The information acquired, data sets and computer software will be stored in public data bases using modern data compression and data management technologies. And all the methodologies developed in the project will be published.
Max ERC Funding
2 454 280 €
Duration
Start date: 2013-04-01, End date: 2018-03-31
Project acronym CLOTHILDE
Project CLOTH manIpulation Learning from DEmonstrations
Researcher (PI) Carmen TORRAS GENIS
Host Institution (HI) AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
Call Details Advanced Grant (AdG), PE7, ERC-2016-ADG
Summary Textile objects pervade human environments and their versatile manipulation by robots would open up a whole range of
possibilities, from increasing the autonomy of elderly and disabled people, housekeeping and hospital logistics, to novel
automation in the clothing internet business and upholstered product manufacturing. Although efficient procedures exist for
the robotic handling of rigid objects and the virtual rendering of deformable objects, cloth manipulation in the real world has
proven elusive, because the vast number of degrees of freedom involved in non-rigid deformations leads to unbearable
uncertainties in perception and action outcomes.
This proposal aims at developing a theory of cloth manipulation and carrying it all the way down to prototype implementation in our Lab. By combining powerful recent tools from computational topology and machine learning, we plan to characterize the state of textile objects and their transformations under given actions in a compact operational way (i.e., encoding task-relevant topological changes), which would permit probabilistic planning of actions (first one handed, then bimanual) that ensure reaching a desired cloth configuration despite noisy perceptions and inaccurate actions.
In our approach, the robot will learn manipulation skills from an initial human demonstration, subsequently refined through
reinforcement learning, plus occasional requests for user advice. The skills will be encoded as parameterised dynamical
systems, and safe interaction with humans will be guaranteed by using a predictive controller based on a model of the robot
dynamics. Prototypes will be developed for 3 envisaged applications: recognizing and folding clothes, putting an elastic
cover on a mattress or a car seat, and helping elderly and disabled people to dress. The broad Robotics and AI background
of the PI and the project narrow focus on clothing seem most appropriate to obtain a breakthrough in this hard fundamental
research topic.
Summary
Textile objects pervade human environments and their versatile manipulation by robots would open up a whole range of
possibilities, from increasing the autonomy of elderly and disabled people, housekeeping and hospital logistics, to novel
automation in the clothing internet business and upholstered product manufacturing. Although efficient procedures exist for
the robotic handling of rigid objects and the virtual rendering of deformable objects, cloth manipulation in the real world has
proven elusive, because the vast number of degrees of freedom involved in non-rigid deformations leads to unbearable
uncertainties in perception and action outcomes.
This proposal aims at developing a theory of cloth manipulation and carrying it all the way down to prototype implementation in our Lab. By combining powerful recent tools from computational topology and machine learning, we plan to characterize the state of textile objects and their transformations under given actions in a compact operational way (i.e., encoding task-relevant topological changes), which would permit probabilistic planning of actions (first one handed, then bimanual) that ensure reaching a desired cloth configuration despite noisy perceptions and inaccurate actions.
In our approach, the robot will learn manipulation skills from an initial human demonstration, subsequently refined through
reinforcement learning, plus occasional requests for user advice. The skills will be encoded as parameterised dynamical
systems, and safe interaction with humans will be guaranteed by using a predictive controller based on a model of the robot
dynamics. Prototypes will be developed for 3 envisaged applications: recognizing and folding clothes, putting an elastic
cover on a mattress or a car seat, and helping elderly and disabled people to dress. The broad Robotics and AI background
of the PI and the project narrow focus on clothing seem most appropriate to obtain a breakthrough in this hard fundamental
research topic.
Max ERC Funding
2 499 149 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
