A key problem in Mental Health is that up to one third of patients suffering from major mental disorders develop resistance against drug therapy. However, patients showing early signs of treatment resistance (TR) do not receive adequate early intensive pharmacological treatment but instead they undergo a stepwise trial-and-error treatment approach. This situation originates from three major knowledge and translation gaps: i.) we lack effective methods to identify individuals at risk for TR early in the disease process, ii.) we lack effective, personalized treatment strategies grounded in insights into the biological basis of TR, and iii.) we lack efficient processes to translate scientific insights about TR into clinical practice, primary care and treatment guidelines. It is the central goal of PSYCH-STRATA to bridge these gaps and pave the way for a shift towards a treatment decision-making process tailored for the individual at risk for TR. To that end, we aim to establish evidence-based criteria to make decisions of early intense treatment in individuals at risk for TR across the major psychiatric disorders of schizophrenia, bipolar disorder and major depression. PSYCH-STRATA will i.) dissect the biological basis of TR and establish criteria to enable early detection of individuals at risk for TR based on the integrated analysis of an unprecedented collection of genetic, biological, digital mental health, and clinical data. ii.) Moreover, we will determine effective treatment strategies of individuals at risk for TR early in the treatment process, based on pan-European clinical trials in SCZ, BD and MDD. These efforts will enable the establishment of novel multimodal machine learning models to predict TR risk and treatment response. Lastly, iii.) we will enable the translation of these findings into clinical practice by prototyping the integration of personalized treatment decision support and patient-oriented decision-making mental health boards.

Multiple Sclerosis (MS) is the most frequent neuroinflammatory disease. Despite new treatments that slow the progression of the disease, patients with MS (PwMS) frequently evolve towards major disability. The pathogenesis of MS is controversially debated, but the recent discovery that infection with the Epstein-Barr virus (EBV) is a major risk factor will radically change research avenues. The BEHIND-MS consortium ambitions to understand how EBV promotes MS development. To this end, we have established a multidisciplinary team that will for the first time draw a comprehensive map of the interactions between the virus and all arms of the immune system in the blood and brain of PwMS and how they ultimately lead to neural damage, in the context of genetic risk factors. We will also develop an in vitro model of MS that integrates the virus, the immune system and brain cells reprogrammed from the blood of the same PwMS. Thus, for the first time, we will study in the laboratory the complex molecular mechanisms that give rise to MS. Finally, we will develop an animal model of prodromal MS that would be a ‘game changer’ for our understanding of MS pathogenesis and allow testing of promising new treatments. The pivotal knowledge developed in this project will empower the entire healthcare value chain to work towards better clinical management of MS. A detailed understanding of EBV-MS interactions, combined with newly identified biomarkers, and study models will open the doors for researchers, clinicians and industry to capitalize on the mechanisms underlying EBV-MS interactions, and develop new diagnostic, preventive and therapeutic tools and guidelines. Throughout the project, an open dialogue with the main stakeholder representatives will ensure a mutual understanding of patient needs and project results. Ultimately, by contributing to improved risk analysis, stratification and treatment strategies, BEHIND-MS has the potential to reduce the burden of MS on society.

Despite the abundance of organic compounds in Nature, only 12 contain fluorine. In contrast, fluorinated organic materials account for over 40% of all pharmaceuticals and agrochemicals. Closer inspection of the fluorination patterns in these functional molecules reveals striking extremes towards perfluorination (in both 2D and 3D scaffolds) or single site fluorination predominantly in aryl substituents. Consequently, most fluorinated moieties in functional materials lack stereochemical information and are thus achiral. This disparity between the paucity of naturally occurring organofluorine compounds and their venerable history in functional molecule design confirms the enormous potential of fluorinated materials in the discovery of novel properties. That progress has largely been confined to 3 dimensional achiral and 2 dimensional achiral architectures reflects the synthetic challenges associated with preparing stereochemical defined multiply fluorinated systems. A major limitation in the construction of C(sp3)-F units remains the need for substrate pre-functionalisation via oxidation and the competing substitution/elimination scenario that compromises efficiency in the deoxyfluorination. This problem is magnified in the synthesis of optically active fluorides where the deoxyfluorination can compromise the enantiopurity of the starting materials. The principle aim of RECON is to facilitate exploration of 3D, chiral space by providing access to multiply fluorinated, stereochemically complex organofluorine materials from simple feedstock using inexpensive, commercially available fluoride sources. In providing a modular platform to rationally place function on a structural basis, exploration of uncharted chemical space will accelerate the discovery of next generation materials for medicinal and agrochemistry, material sciences and bio-medicine.

This project focuses on three iron-base alloys that have growing potential for high-temperature, high-strength and strong- magnet applications: Fe-Cr, Fe-Mn and Fe-Co. Because of the key role of magnetism, an innovative materials design based on advanced modeling approaches is necessary to control key properties of these materials. Such a design strategy requires the combination of (i) highly accurate methods to determine atomic features with (ii) efficient coarse-graining techniques to access target physical properties and to perform the screening of materials compositions. For the former, density functional theory (DFT) has for many materials classes already proven to be a highly successful tool. For Fe-based alloys, however, a critical bottleneck is the role that magnetic ordering, excitations and transitions have on thermodynamic, defect and kinetic properties. Therefore, a complete and accurate modeling of magnetism is urgently needed to address the materials-design challenges: the resistance to radiation damage related to the chemical decomposition in Fe-Cr, the grain-boundary embrittlement in ferritic Fe-Mn and the high-strength of austenitic Fe-Mn, and the phase ordering and the relative stability of a and ? phases in Fe-Co cannot be fully understood without properly accounting for the magnetic effects. The novelty of the current approach is twofold: First, on the DFT-side, we will make use of the recent important progress in treating magnetism in pure idealized Fe lattices, in order to go towards an accurate modeling of magnetic multi-component systems with point/extended defects, and beyond the standard collinear approximation. Second, we will develop new methods that allow us to bridge the gap between (i) highly accurate electronic calculations and (ii) large-scale atomistic thermodynamic and kinetic simulations for iron based alloys by – and this is decisive – fully taking into account the impact of magnetism on defect properties, diffusion and microstructural evolution. For the latter, lattice-based effective interaction models (EIMs) and tight-binding (TB) models will be developed based on data from DFT, including magnetic configurations, excitations and transitions. This will allow us to provide a coherent description of the role of magnetism on various properties of Fe-based alloys at different length scales and at finite temperature. It will further give us the ability to perform the optimization of key parameters controlling the relevant properties like phase decomposition in Fe-Cr, phase ordering in Fe-Co or decohesion of grain boundaries in Fe-Mn. Dedicated experiments in bulk alloys and along intergranular / interphase boundaries grown on demand will be performed in the project, which are essential for verifying the robustness of the theoretical predictions. The three chosen alloys exhibit a large variety of magnetic behavior. The methods developed and applied in this proposal are therefore expected to be transferrable to the modeling of other magnetic materials. The results of our simulations will lead to the improvement of thermo¬dynamic and diffusion databases and tools (such as DICTRA) that are nowadays routinely used in industrial R&D but that at present have difficulties in accounting for magnetism. In this way a better and more systematic understanding of the role of magnetism in Fe-based alloys will help to improve significantly the predictive power of the simulations and thus contribute to a more efficient and accurate development of new steel grades. Once fully implemented, the availability of such computational tools is expected to boost the efficiency, change the strategy in designing new steel grades and to form an important contribution for the future competitiveness of steelmakers.

This project intends to design, fabricate and study advanced III-V semiconductor nanostructures-based devices for the generation of coherent optical frequency combs (OFCs) with controllable transverse patterns dynamics. Our approach consists in an optically-injected vertical-emission Kerr Gires-Tournois Interferometer (KGTI) integrated in a compact free-space cavity. The KGTI shall consist in a (Al)GaAs/InGaAs metasurface-based VCSEL, with controlled light confinement and phase dispersion, to enhance fast nonlinear light-matter interaction. The coupled-cavity system will be designed to reach the bistable regime and achieve coherent light states with properties overcoming current limitations for telecom and imaging applications. This new experimental framework will be complemented by the development and bifurcation analysis of a hybrid time-delayed, partial differential equations 3D theoretical model, that includes both transverse 2D diffraction and on-axis temporal dynamics. The external cavity design will allow to pass from a single transverse mode to a highly transverse degenerate (self-imaging) system. In that latter case, we envision the possibility to generate multiple, spatially independent, OFCs. We expect this project to yield as a final product, a first experimental demonstrator of vertically-emitted 1D and 3D OFCs in a mature planar III-V semiconductor based platform. Our vertical KGTI will allow to produce combs with high coherence, low power consumption, GHz repetition rates, and containing hundreds of lines in the near infrared spectral domain, with, thanks to the planar vertical architecture, potentially 10 × 10 transversally multiplexed and reconfigurable beams.These results will have groundbreaking applications for instance in massively parallel comb generation or for double comb sensing application and it will help to overcome several limitations for telecom applications. On the technological and experimental sides, the technical barriers to be lifted consists in developing a microcavity containing a nonlinear material having a very high value of the Kerr nonlinear coefficient. For this objective we plan on using the almost untapped potential of AlGaAs-based semiconductor materials operated below their band-gap. The nonlinear interaction will benefit from the strong light confinement in the microcavity. The microcavity design shall find a compromise between the width of the frequency comb targeted as well as the value of the optical power one wishes to inject into the KGTI system. Critical power threshold for the formation of Kerr combs can be controlled via the external cavity reflectivity and imaging configuration, and detuning of the optical pumping with respect to the microcavity resonance; the sign of the latter allowing also to explore both anomalous and normal dispersion regimes. On the theoretical side, the modeling of the system we wish to realize necessitates using Delay Algebraic Equations (DAEs). While the latter have a great potential for the modeling of dispersive phenomena in photonic systems, their studies is comparatively less developed than those of partial differential equations (PDEs). In addition, if DAEs are the natural choice for studying temporal dispersive dynamics, the diffractive propagation of light in the transverse plane of the cavity as well as field curvature effects induced by lenses and mirrors require using PDEs. As such, a full 3D model shall consists of a hybrid DAE-PDE system whose analysis is way beyond the state of the art and represents an exciting and challenging endeavor. The theoretical aspects of KOGIT will also significantly advance the study of spatio-temporal phenomena in nonlinear media. The proposed experimental framework will be complemented by the development of bifurcation analysis method of a hybrid DAE-PDE system that will constitute a qualitative jump in the state of the art.