ERC FUNDED PROJECTS

Optical bioimaging is limited by visible light penetration depth and stability of fluorescent dyes over extended periods of time. Surface enhanced Raman scattering (SERS) offers the possibility to overcome these drawbacks, through SERS-encoded nanoparticle tags, which can be excited with near-IR light (within the biological transparency window), providing high intensity, stable, multiplexed signals. SERS can also be used to monitor relevant bioanalytes within cells and tissues, during the development of diseases, such as tumours. In 4DBIOSERS we shall combine both capabilities of SERS, to go well beyond the current state of the art, by building three-dimensional scaffolds that support tissue (tumour) growth within a controlled environment, so that not only the fate of each (SERS-labelled) cell within the tumour can be monitored in real time (thus adding a fourth dimension to SERS bioimaging), but also recording the release of tumour metabolites and other indicators of cellular activity. Although 4DBIOSERS can be applied to a variety of diseases, we shall focus on cancer, melanoma and breast cancer in particular, as these are readily accessible by optical methods. We aim at acquiring a better understanding of tumour growth and dynamics, while avoiding animal experimentation. 3D printing will be used to generate hybrid scaffolds where tumour and healthy cells will be co-incubated to simulate a more realistic environment, thus going well beyond the potential of 2D cell cultures. Each cell type will be encoded with ultra-bright SERS tags, so that real-time monitoring can be achieved by confocal SERS microscopy. Tumour development will be correlated with simultaneous detection of various cancer biomarkers, during standard conditions and upon addition of selected drugs. The scope of 4DBIOSERS is multidisciplinary, as it involves the design of high-end nanocomposites, development of 3D cell culture models and optimization of emerging SERS tomography methods.

2 410 771 €

Start date: 2018-10-01, End date: 2023-09-30

The amazing rate of progress in the computer technologies and telecommunications presents many new challenges for Optimization Theory. New problems are usually very big in size, very special in structure and possibly have a distributed data support. This makes them unsolvable by the standard optimization methods. In these situations, old theoretical models, based on the hidden Black-Box information, cannot work. New theoretical and algorithmic solutions are urgently needed. In this project we will concentrate on development of fast optimization methods for problems of big and very big size. All the new methods will be endowed with provable efficiency guarantees for large classes of optimization problems, arising in practical applications. Our main tool is the acceleration technique developed for the standard Black-Box methods as applied to smooth convex functions. However, we will have to adapt it to deal with different situations. The first line of development will be based on the smoothing technique as applied to a non-smooth functions. We propose to substantially extend this approach to generate approximate solutions in relative scale. The second line of research will be related to applying acceleration techniques to the second-order methods minimizing functions with sparse Hessians. Finally, we aim to develop fast gradient methods for huge-scale problems. The size of these problems is so big that even the usual vector operations are extremely expensive. Thus, we propose to develop new methods with sublinear iteration costs. In our approach, the main source for achieving improvements will be the proper use of problem structure. Our overall aim is to be able to solve in a routine way many important problems, which currently look unsolvable. Moreover, the theoretical development of Convex Optimization will reach the state, when there is no gap between theory and practice: the theoretically most efficient methods will definitely outperform any homebred heuristics.

2 090 038 €

Start date: 2018-09-01, End date: 2023-08-31

In an era of rapid climate change there is a pressing need to understand whether and how organisms are able to adapt to novel environments. Such understanding is hampered by a major divide in the life sciences. Disciplines like systems biology or neurobiology make rapid progress in unravelling the mechanisms underlying the responses of organisms to their environment, but this knowledge is insufficiently integrated in eco-evolutionary theory. Current eco-evolutionary models focus on the response patterns themselves, largely neglecting the structures and mechanisms producing these patterns. Here I propose a new, mechanism-oriented framework that views the architecture of adaptation, rather than the resulting responses, as the primary target of natural selection. I am convinced that this change in perspective will yield fundamentally new insights, necessitating the re-evaluation of many seemingly well-established eco-evolutionary principles. My aim is to develop a comprehensive theory of the eco-evolutionary causes and consequences of the architecture underlying adaptive responses. In three parallel lines of investigation, I will study how architecture is shaped by selection, how evolved response strategies reflect the underlying architecture, and how these responses affect the eco-evolutionary dynamics and the capacity to adapt to novel conditions. All three lines have the potential of making ground-breaking contributions to eco-evolutionary theory, including: the specification of evolutionary tipping points; resolving the puzzle that real organisms evolve much faster than predicted by current theory; a new and general explanation for the evolutionary emergence of individual variation; and a framework for studying the evolution of learning and other general-purpose mechanisms. By making use of concepts from information theory and artificial intelligence, the project will also introduce various methodological innovations.

2 500 000 €

Start date: 2018-12-01, End date: 2023-11-30

Microporous materials are an important class of solid; the two main members of this family are zeolites and metal-organic frameworks (MOFs). Zeolites are industrial solids whose applications range from catalysis, through ion exchange and adsorption technologies to medicine. MOFs are some of the most exciting new materials to have been developed over the last two decades, and they are just beginning to be applied commercially. Over recent years the applicant’s group has developed new synthetic strategies to prepare microporous materials, called the Assembly-Disassembly-Organisation-Reassembly (ADOR) process. In significant preliminary work the ADOR process has shown to be an extremely important new synthetic methodology that differs fundamentally from traditional solvothermal methods. In this project I will look to overturn the conventional thinking in materials science by developing methodologies that can target both zeolites and MOF materials that are difficult to prepare using traditional methods – the so-called ‘unfeasible’ materials. The importance of such a new methodology is that it will open up routes to materials that have different properties (both chemical and topological) to those we currently have. Since zeolites and MOFs have so many actual and potential uses, the preparation of materials with different properties has a high chance of leading to new technologies in the medium/long term. To complete the major objective I will look to complete four closely linked activities covering the development of design strategies for zeolites and MOFs (activities 1 & 2), mechanistic studies to understand the process at the molecular level using in situ characterisation techniques (activity 3) and an exploration of potential applied science for the prepared materials (activity 4).

2 489 220 €

Start date: 2018-10-01, End date: 2023-09-30