ERC FUNDED PROJECTS

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

"Understanding how organisms regulate size is one of the most fascinating open questions in biology. The aim of the AMAIZE project is to unravel how growth of maize leaves is controlled. Maize leaf development offers great opportunities to study the dynamics of growth regulatory networks, essentially because leaf development is a linear system with cell division at the leaf basis followed by cell expansion and maturation. Furthermore, the growth zone is relatively large allowing easy access of tissues at different positions. Four different perturbations of maize leaf size will be analyzed with cellular resolution: wild-type and plants having larger leaves (as a consequence of GA20OX1 overexpression), both grown under either well-watered or mild drought conditions. Firstly, a 3D cellular map of the growth zone of the fourth leaf will be made. RNA-SEQ of three different tissues (adaxial- and abaxial epidermis; mesophyll) obtained by laser dissection with an interval of 2.5 mm along the growth zone will allow for the analysis of the transcriptome with high resolution. Additionally, the composition of fifty selected growth regulatory protein complexes and DNA targets of transcription factors will be determined with an interval of 5 mm along the growth zone. Computational methods will be used to construct comprehensive integrative maps of the cellular and molecular processes occurring along the growth zone. Finally, selected regulatory nodes of the growth regulatory networks will be further functionally analyzed using a transactivation system in maize. AMAIZE opens up new perspectives for the identification of optimal growth regulatory networks that can be selected for by advanced breeding or for which more robust variants (e.g. reduced susceptibility to drought) can be obtained through genetic engineering. The ability to improve the growth of maize and in analogy other cereals could have a high impact in providing food security"

2 418 429 €

Start date: 2014-02-01, End date: 2019-01-31

"Summary: the quest for a general functional tensor framework for blind source separation Our overall objective is the development of a general functional framework for solving tensor based blind source separation (BSS) problems in biomedical data fusion, using tensor decompositions (TDs) as basic core. We claim that TDs will allow the extraction of fairly complicated sources of biomedical activity from fairly complicated sets of uni- and multimodal data. The power of the new techniques will be demonstrated for three well-chosen representative biomedical applications for which extensive expertise and fully validated datasets are available in the PI’s team, namely: • Metabolite quantification and brain tumour tissue typing using Magnetic Resonance Spectroscopic Imaging, • Functional monitoring including seizure detection and polysomnography, • Cognitive brain functioning and seizure zone localization using simultaneous Electroencephalography-functional MR Imaging integration. Solving these challenging problems requires that algorithmic progress is made in several directions: • Algorithms need to be based on multilinear extensions of numerical linear algebra. • New grounds for separation, such as representability in a given function class, need to be explored. • Prior knowledge needs to be exploited via appropriate health relevant constraints. • Biomedical data fusion requires the combination of TDs, coupled via relevant constraints. • Algorithms for TD updating are important for continuous long-term patient monitoring. The algorithms are eventually integrated in an easy-to-use open source software platform that is general enough for use in other BSS applications. Having been involved in biomedical signal processing over a period of 20 years, the PI has a good overview of the field and the opportunities. By working directly at the forefront in close collaboration with the clinical scientists who actually use our software, we can have a huge impact."

2 500 000 €

Start date: 2014-04-01, End date: 2019-03-31

Natural language understanding (NLU) by the machine is of large scientific, economic and social value. Humans perform the NLU task in an efficient way by relying on their capability to imagine or anticipate situations. They engage commonsense and world knowledge that is often acquired through perceptual experiences to make explicit what is left implicit in language. Inspired by these characteristics CALCULUS will design, implement and evaluate innovative paradigms supporting NLU, where it will combine old but powerful ideas for language understanding from the early days of artificial intelligence with new approaches from machine learning. The project focuses on the effective learning of anticipatory, continuous, non-symbolic representations of event frames and narrative structures of events that are trained on language and visual data. The grammatical structure of language is grounded in the geometric structure of visual data while embodying aspects of commonsense and world knowledge. The reusable representations are evaluated in a selection of NLU tasks requiring efficient real-time retrieval of the representations and parsing of the targeted written texts. Finally, we will evaluate the inference potential of the anticipatory representations in situations not seen in the training data and when inferring spatial and temporal information in metric real world spaces that is not mentioned in the processed language. The machine learning methods focus on learning latent variable models relying on Bayesian probabilistic models and neural networks and focus on settings with limited training data that are manually annotated. The best models will be integrated in a demonstrator that translates the language of stories to events happening in a 3-D virtual world. The PI has interdisciplinary expertise in natural language processing, joint processing of language and visual data, information retrieval and machine learning needed for the successful realization of the project.

2 227 500 €

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

In the gastrointestinal tract, the balance between activation of the mucosal immune system and tolerance should be tightly regulated to maintain immune homeostasis to prevent chronic inflammation and tissue damage. Recently, the new concept was introduced that the vagus nerve plays an important role in modulating immune homeostasis as part of a so-called inflammatory reflex. We provided evidence for this concept in the gastrointestinal tract and showed that vagus nerve stimulation (VNS) reduced inflammation of the intestinal muscle layer. Moreover, we showed that this effect was mediated by activation of enteric cholinergic neurons (cholinergic tone) interacting with intestinal macrophages in the muscle layer. Of interest, we have collected exciting data that the vagus nerve (and thus the cholinergic tone) also significantly contributes to mucosal immune homeostasis. Mice that underwent vagotomy lost their ability to develop tolerance to oral feeding of an antigen, whereas VNS reduced mucosal inflammation in a model of food allergy. Based on these data, we hypothesize that the cholinergic tone is a major determinant of the tolerogenic microenvironment of the mucosal immune system, and want to further explore the immune-modulatory effect of the vagal innervation and enteric neurons on the macrophages residing in the lamina propria. In addition, we will further explore the therapeutic potential and the mechanisms involved of chronic VNS in colitis and food allergy. Finally, we will translate our preclinical findings to the human situation. The anti-inflammatory effect of VNS (applied during surgery) will be studied in human intestinal tissue whereas the therapeutic potential of chronic VNS in Crohn’s disease will be studied in a pilot trial. The outcome of this project will be ground-breaking and will have an immense impact on clinical management as it will provide new therapeutic opportunities for the treatment of immune-mediated gastrointestinal disorders.

2 495 200 €

Start date: 2014-04-01, End date: 2019-03-31

The belief that ‘the end of music is to move human affections’ (Descartes, Compendium musicae) has been a central issue in European musical thought since Plato. Opera was invented to recover the power of Ancient music to move the human heart, and its history is a permanent exploration of the capacity of action, words and music to convey emotions. In the eighteenth century a new type of opera consolidated with the chief concern of expressing the character’s emotions as they changed throughout the drama, inspired by Descartes’ theory of human passions. The key expressive medium was the aria col da capo, where a single, distinct passion was represented, like a concentrated pill of emotional meaning. The ideal corpus to study this issue are the 900 operas set to music by 300 composers on the 27 dramas by Pietro Metastasio (1698-1782). It contains a comprehensive catalogue of emotions in music, a unique window of opportunity to scrutinize conventions that defined music expression and meaning for over a century, paving the way for the emergence of ‘absolute’ instrumental music, autonomous from any other art form. DIDONE presents an innovative approach to unveil these conventions: the creation of a corpus of 4,000 digitized arias from 200 opera scores based on Metastasio’s eight most popular dramas, to be analysed using traditional methods and big data computer technology. The comparative scrutiny of dozens of different musical settings of the same librettos will reveal how composers correlate specific dramatic circumstances and emotions with distinct poetic and musical features. The results will be applicable to three main fields: (i) opera performance; (ii) analysis and interpretation of other types of music; and (iii) composition in several scenarios, from film soundtracks to creation by Artificial Intelligence. An opera festival will be designed to recover and disseminate this hitherto ignored repertoire, which was essential to define the European musical identity.

2 498 690 €

Start date: 2019-01-01, End date: 2023-12-31

A hallmark of cancer is tumor cell heterogeneity, which results from combinations of multiple genetic and epigenetic alterations within an individual tumor. In contrast, we have recently discovered that most human colorectal cancers (CRCs) are composed of mixtures of phenotypically distinct tumor cells organized into a stem cell hierarchy that displays a striking resemblance to the healthy colonic epithelium. We showed that long-term regeneration potential of tumor cells is largely influenced by the position that they occupy within the tumor's hierarchy. To analyze the organization of CRCs without the constraints imposed by tumor cell transplantation experiments, we have developed a method that allows for the first time tracking and manipulating the fate of specific cell populations in whole human tumors. This technology is based on editing the genomes of primary human CRCs cultured in the form of tumor organoids using Zinc-Finger Nucleases to knock-in either lineage tracing or cell ablation alleles in genes that define colorectal cancer stem cells (CRC-SCs) or differentiated-like tumor cells. Edited tumor organoids generate CRCs in mice that reproduce the tumor of origin while carrying the desired genetic modifications. This technological advance opens the gate to perform classical genetic and developmental analysis in human tumors. We will exploit this advantage to address fundamental questions about the cell heterogeneity and organization of human CRCs that cannot be tackled through currently existing experimental approaches such as: Are CRC-SCs the only tumor cell population with long term regenerating potential? Can we cure CRC with anti-CRC-SC specific therapies? Will tumor cell plasticity contribute to the regeneration of the CRC-SC pool after therapy? Do quiescent-SCs regenerate CRC tumors after standard chemotherapy? Can we identify these cells? How do common genetic alterations in CRC influence the CRC hierarchy? Do they affect the stem cell phenotype?

2 499 405 €

Start date: 2014-04-01, End date: 2019-03-31

Since a few decades, human patients who suffer from severe illnesses or multiple trauma, conditions that were previously lethal, are being treated in intensive care units (ICUs). Modern intensive care medicine bridges patients from life-threatening conditions to recovery with use of mechanical devices, vasoactive drugs and powerful anti-microbial agents. By postponing death, a new unnatural condition, intensive-care-dependent prolonged (>1 week) critical illness, has been created. About 25% of ICU patients today require prolonged intensive care, sometimes for weeks or months, and these patients are at high risk of death while consuming 75% of resources. Although the primary insult was adequately dealt with, many long-stay patients typically suffer from hypercatabolism, ICU-acquired brain dysfunction and polyneuropathy/myopathy leading to severe muscle weakness, further increasing the risk of late death. As hypercatabolism was considered the culprit, several anabolic interventions were tested, but these showed harm instead of benefit. We previously showed that fasting early during illness is superior to forceful feeding, pointing to certain benefits of catabolic responses. In healthy humans, fasting activates catabolism to provide substrates essential to protect and maintain brain and muscle function. This proposal aims to investigate whether evolutionary conserved catabolic fasting pathways, specifically lipolysis and ketogenesis, can be exploited in the search for prevention of brain dysfunction and muscle weakness in long-stay ICU patients, with the goal to identify a new metabolic intervention to enhance their recovery. The project builds further on our experience with bi-directional translational research - using human material whenever possible and a validated mouse model of sepsis-induced critical illness for objectives that cannot be addressed in patients - and aims to close the loop, from a novel concept to a large randomized controlled trial in patients.

2 500 000 €

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

The nature of the Dark Universe is an outstanding question in modern science, and is connected with our understanding of the reality at the most fundamental level. Despite the enormous success of the Standard Model (SM) of particle physics, a number of shortcomings of the theory and the fact that it does not account for the Dark Matter and Energy, prompt theorists to propose possible hypothetical extensions. Some of these extensions predict the existence of very-light and very-weakly-coupled axions (or axion-like particles, ALPs). Recent theoretical and phenomenological work is sharpening the physics case of these particles. They are now considered as very motivated portals for physics beyond the SM, and in particular as very plausible Dark Matter candidates. In addition, some intriguing astrophysical observations might be interpreted as hints for their existence. The International Axion Observatory IAXO is one of the most ambitious proposals to find the axion. Its baseline configuration relies on the search for solar axions, but could also host relic axion detectors. IAXO will go well beyond current experiments' sensitivity and will probe a large fraction of the -still unexplored- parameter space of the axion and ALPs. The scope of the present proposal encompasses the realization of a first complete intermediate experimental stage, BabyIAXO, including prototypes of the IAXO magnet and detection systems. It will already provide relevant physics outcome in the time-frame of the current grant, while preparing the ground for, and extending the physics reach of, the full IAXO. In particular, BabyIAXO will already be able to test a number of axion and ALP models that are invoked by the aforementioned astrophysical hints and therefore already at this stage there is potential for discovery. The detection of a new fundamental pseudoscalar -potentially solving the DM problem- would lead to a breakthrough in Particle Physics, Cosmology and Astrophysics.

3 106 875 €

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

This proposal aims at the discovery of robust transition-metal catalyzed transformations that can take place in aqueous media and cellular lysates, and are susceptible of being exported to living cells. Specifically, we will exploit the special coordination and activation ability of different metal complexes towards pi-systems to induce chemo-selective reactions of designed, abiotic, unsaturated substrates. Moreover, and importantly, the metal catalysts will be conjugated to designed ligands or biopolymers so that the catalytic power of the metal complex can be transferred to specific “in vivo” locations. Initial designs in this latter “high risk” endeavor will be guided by the current knowledge on metal-catalyzed bio-orthogonal chemistry as well as by some precedents on catalysis-based metal-sensing tactics. Ultimately, we want to install catalytic power in specific cellular sites and/or endow catalytic properties to any selected bio-molecular target. The catalytic activity could then be used to trigger the amplified generation of fluorescent signals or boost the production of bioactive drugs from inert, non-toxic precursors. This will set the basis for the development of efficient bio-sensing and imaging tools, and “in cellulo” diagnosis tactics, and of novel target-directed therapeutic strategies. With the crescent identification of disease-related biomarkers, the development of biomarker-associated diagnosis and therapy protocols is becoming one of the more urgent challenges in modern life sciences. Advances in early diagnosis can have a profound impact in public health, and boost new technology developments. The transversal expertise of my group in synthesis, metal catalysis, molecular recognition and chemical biology (see PI profile) places us in a rather unique position to tackle this type of interdisciplinary project.

2 356 276 €

Start date: 2014-02-01, End date: 2020-01-31

"Graphene is a new class of promising material with exceptional properties and thus warrants a plethora of potential applications in various domains of science and technology. However, due to intrinsic zero bandgap and inherently low solubility, a prerequisite for the use of graphene in several applications is its controlled and reproducible functionalization in a nanostructured fashion. Being a ‘surface-only’ nanomaterial, its properties are extremely sensitive not only to chemical modification but also to noncovalent interactions with simple organic molecules. A systematic knowledge base for targeted functionalization of graphene still eludes the scientific community. The present experimental protocols suffer from important shortcomings. Firstly, graphene functionalization occurs randomly in solution based methods and there is scarcity of methods that can exert precise control over how and where the reactions/interactions occur. Secondly, due to random functionalization, producing reproducible samples of structurally uniform graphene and graphitic materials remains a major challenge. Lastly, a molecular level understanding of the functionalization process is still lacking which precludes systematic strategies for manipulation of graphene and graphitic materials. NANOGRAPH@LSI aims to develop systematic experimental protocols for controlled and reproducible (covalent, non-covalent as well as the combination of both) functionalization of graphene and graphitic materials in a nanostructured fashion at the liquid-solid interface (LSI), along with the implementation of new nanoscale characterisation tools, targeting a broad range of applications in the fields of electronics, i.e. graphene bandgap engineering, sensing, and separation. Supramolecular self-assembly of organic building blocks at the liquid-solid interface will be employed as a basic strategy. In view of the above mentioned applications, also upscaling protocols will be developed and implemented."

2 495 740 €

Start date: 2013-11-01, End date: 2018-10-31

The goal of this project is to pursue new methods in the mathematical analysis of non-local and non-linear partial differential equations. For this purpose we present several physical scenarios of interest in the context of incompressible fluids, from a mathematical point of view as well as for its applications: both from the standpoint of global well-posedness, existence and uniqueness of weak solutions and as candidates for blowup. The equations we consider are the incompressible Euler equations, incompressible porous media equation and the generalized Quasi-geostrophic equation. This research will lead to a deeper understanding of the nature of the set of initial data that develops finite time singularities as well as those solutions that exist for all time for incompressible flows.

1 779 369 €

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

OCONTSOLAR aims to develop new control methods to use mobile sensors mounted on drones and unmanned ground vehicles (UGV) as an integral part of the control systems. Sensors mounted on vehicles have been used for surveillance and for gathering information, however these mobile sensors have not been used so far as an integral part of control systems. Solar power plants will be used as a case study, with the aim of optimizing their operation using spatial irradiance estimations and predictions. Many results will be applicable to other systems such as traffic control in highways and cities, energy management in buildings, micro-grids, agriculture (irrigation and plague control) and flood control. The main objectives and challenges are: 1. Methods to control mobile sensor fleets and integrate them as an essential part of the overall control systems. 2. Spatially distributed solar irradiance estimation methods using a variable fleet of sensors mounted on drones and UGVs. 3. New model predictive control (MPC) algorithms that use mobile solar sensor estimations and predictions to yield safer and more efficient operation of the plants allowing the effective integration of solar energy in systems delivering energy to grids or other systems while satisfying production commitments. OCONTSOLAR includes proofs of concepts by implementation on the Solar Platform of Almeria and on a solar air conditioning plant installed at the host institution.

2 500 000 €

Start date: 2018-09-01, End date: 2024-02-29

"This proposal concerns open systems, i.e. systems interacting with the environment, and their fundamental role in natural sciences. The main objectives are: i) to develop theory of Brownian motion for molecules in biological environments; ii) to adapt classical many-body open systems such as kinetic or/and diffusion-aggregation models to the quantum domain; iii) to develop theory of open systems as quantum simulators; finally iv) to develop theory of quantum Brownian motion in inhomogeneous media. Although all these objectives may seem to be quite unrelated, our main goal will be to connect them in order to unambiguously asses the relevance of open systems in specific areas of physics, biology and beyond. Accordingly, objective i) will be explored in close collaboration with experimentalists in which the diffusion of biomolecules on cell membranes requires a description in terms of Brownian motion in correlated disordered potentials. In ii) we will search for many-body kinetic and growth models that provide the configurations that may serve as samples of random potentials desired in i). These models can be regarded as quantum models with non-Hermitian generators of evolution; in some situations they can be generalized to genuine quantum ones, described by a quantum master equation, linking ii) and iii). In iii) we will look for applications of quantum open systems as quantum simulators of condensed matter/high energy physics. We will also look at single particle interactions with quantum many body environment, linking the objectives iii) with iv) and i). Expected results are: a) understanding the relationship between biological function and the spatiotemporal dynamics of single molecules in living cells; b) understanding of the structure of classical many body stochastic models and their relation to quantum ones; c) concrete proposals for open systems quantum simulators; and d) development of tools to characterize and observe quantum Brownian motion."

1 787 565 €

Start date: 2014-01-01, End date: 2018-12-31

The precipitation of alkaline-earth carbonates in silica-rich alkaline solutions yields nanocrystalline aggregates that develop non-crystallographic morphologies. These purely inorganic hierarchical materials, discovered by the IP of this project, form under geochemically plausible conditions and closely resemble typical biologically induced mineral textures and shapes, thus the name ‘biomorphs’. The existence of silica biomorphs has questioned the use morphology as an unambiguous criterion for detection of primitive life remnants. Beyond applications, the study of silica biomorphs has revealed a totally new morphogenetic mechanism capable of creating crystalline materials with positive or negative constant curvature and biomineral-like textures which lead to the design of new pathways towards concerted morphogenesis and bottom-up self-assembly created by a self-triggered chemical coupling mechanism. The potential interest of these fascinating structures in Earth Sciences has never been explored mostly because of their complexity and multidisciplinary nature. PROMETHEUS proposes an in depth investigation of the nature of mineral structures such as silica biomorphs and chemical gardens, and the role of mineral self-organization in extreme alkaline geological environments. The results will impact current understanding of the early geological and biological history of Earth by pushing forward the unexplored field of inorganic biomimetic pattern formation. PROMETHEUS will provide this discipline with much needed theoretical and experimental foundations for its quantitative application to Earth Sciences. The ambitious research program in PROMETHEUS will require the development of high-end methods and instruments for the non-intrusive in-situ characterization of geochemically important variables, including pH mapping with microscopic resolution, time resolved imaging of concentration gradients, microscopic fluid dynamics, and characterization of ultraslow growth rates.

2 431 771 €

Start date: 2014-08-01, End date: 2019-07-31

Carbohydrates (glycans, sugars) play key roles in virtually all biological events. Given their chemical complexity, understanding their roles in nature requires a multidisciplinary approach. Research in the field is growing, since advances in the area could be part of the solution to many health issues. However, we lack full knowledge on the role of most glycan-mediated events especially at the resolution required from a chemical perspective to manipulate them and create new probes and eventually drugs. Understanding sugar recognition remains a major challenge in science. Although X-ray diffraction has been employed to study sugar/protein complexes, a recent report has highlighted that most sugar conformers deposited in the Protein Data Bank are incorrect. Flexible glycans are handled poorly in X-ray: errors reflect incorrect refinement of sugars, with huge implications when interpreted in the biocontext.I propose to address glycan recognition by using a multidisciplinary approach, combining synthesis, molecular biology and biophysics, with a prominent role for NMR. In RECGLYCANMR I will develop new NMR protocols to decipher key glycan recognition aspects beyond current knowledge: the role of presentation and dynamics and understanding the mechanisms behind the exquisite receptor and ligand selectivity. Importantly, till now, sugar recognition NMR studies have been exclusively limited to in vitro. RECGLYCANMR will break the limits of NMR, studying the interactions in-cell, a crowded ambient where viscosity is doubled respect to water. I am in a unique position to approach this project due to my wide expertise in NMR and the network of collaborators I have established for years, enabling me to access a large variety of synthetic sugars. Discovering the molecular bases of in-cell interactions will provide groundbreaking information on sugar chemical biology and will open unexplored avenues for approaching sugar-associated diseases, as inflammation and viral infections

2 499 980 €

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

Future robots are expected to perform a multitude of complex tasks with high variability, in close collaboration or even physical contact with humans, and in industrial as well as in non-industrial settings. Both human-robot interaction and task variability are major challenges. A lot of progress is needed so that: (1) robots recognize the intention of the human and react with human-like motions; (2) robot end-users, such as operators on the factory floor or people at home, are able to deploy robots for new tasks or new situations in an intuitive way, for example by just demonstrating the task to the robot. The fundamental challenge addressed in this proposal is: how can a robot generalize a skill that has been demonstrated in a particular situation and apply it to new situations? This project focuses on skills involving rigid objects manipulated by a robot or a human and follows a model-based approach consisting of: (1) conversion of the demonstrated data to an innovative invariant representation of motion and interaction forces; (2) generalization of this representation to a new situation by solving an optimal control problem in which similarity with the invariant representation is maintained while complying with the constraints imposed by the new context. Additional knowledge about the task can be added in the constraints. Major breakthroughs are that the required number of demonstrations and hence the training effort decrease drastically, similarity with the demonstration is maintained in view of preserving the human-like nature, and task knowledge is easily included. The methodology is applied to program robot skills involving motion in free space (e.g. human-robot hand over tasks) as well as advanced manipulation skills involving contact (e.g. assembly, cleaning), aiming at impact in industrial and non-industrial settings. Application of the invariant motion representation in the neighbouring field of biomechanics will further leverage impact.

2 494 971 €

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

"Cataract is the opacification of the crystalline lens of the human eye. It is usually related with age and is one of the leading causes of blindness. The increase in light scatter in the lens reduces the contrast in the retinal images severely degrading vision. The current solution is to perform surgery to remove the natural lens that is substituted by an artificial intraocular lens. This is a successful procedure restoring good quality of vision in most patients. However, in many situations it would be incredible advantageous to actually “see” through a cataractous eye. The optics of the eye is affected by two factors: aberrations and scatter. In the last decade, correcting optical aberrations in the eye was accomplished by using adaptive optics techniques. This permitted to obtain high resolution images of the retina and also to improve vision. However, the possibility of correcting scatter in the eye was never considered before. We propose here the use of spatial and temporal advanced photonics techniques for imaging through the turbid media of the cataractous lens. We envision two direct applications of this technology: a dedicated fundus camera to register images of the retina in patients affected by cataracts and a novel type of opto-electronics spectacles restoring some vision in cataract patients. The fundus camera would offer clinicians the unique opportunity to determine if there is any retinal pathology underneath the cataractous eye. The scatter-correcting goggles would be useful in those cases where surgery were not possible for any reason or as a temporarily relieve until the surgery is performed. The same type of technology could be applied in the case of normal eyes with lower levels of scatter but desiring to achieve a better than normal vision for some specific tasks. This proposal presents a completely new and disruptive idea, which if successful would render immediate and significant benefits to patients worldwide."

2 374 910 €

Start date: 2014-02-01, End date: 2019-01-31