The design and precise construction of protein-inspired nanostructures through folding and metal-directed self-assembly is a challenging yet potentially rewarding endeavor for the development of new classes of functional materials. Peptides have been well established as flexible starting points for the construction of bioinspired architectures with a high level of sophistication and precise control over morphologies and functions. Concurrently, the power of metal coordination to drive assembly has been extensively explored to design functionally versatile metal-organic frameworks (MOFs). Yet, the synthesis of such coordination networks by a process that would combine folding, self-assembly and metal coordination in aqueous media is still partially unaccomplished. Foldamers - artificial synthetic folded oligomers - possess the advantages of structural robustness and high programmability which bodes well for their use in the construction of well-defined higher-order nanostructures. The project will move a step forward towards the design, synthesis and structural characterization of metal-foldamer porous frameworks and will focus on foldamer sequence evolution and metal variation to influence the main features of the assembly (shape and catalytic property). The applicant has been trained in peptide synthesis and has acquired a high level of expertise in the design and structural characterization of peptide-based assemblies and advanced materials. He will join and bring his expertise to a host laboratory that has pioneered the design of oligourea-based foldamers as peptide mimics. Secondment in an internationally renowned group in the chemistry of metalloenzyme active sites and the design of bio-inspired catalysts will provide the appropriate combination of knowledge required for this multidisciplinary study. This project represents a significant leap forward in the creation of a whole new range of fully synthetic and functional higher-order foldamer nanostructures.

Connected devices that monitor human biology in real-time represent the next frontier in biosensors. Monitoring hormones is of significant interest as hormones play critical roles in multiple physiological processes including stress adaptation, blood pressure control, reproductive rhythms, and body odor. However, the real-time monitoring of hormones is challenging from a biology, chemistry, and engineering perspective, insulin detection being the one notable success. This project proposes to design a novel wearable device to sense estradiol (through sweat), a hormone responsible for fertility issues and mood disorders in women. This project is highly innovative and ambitious since it combines microbial genetics and protein identification, new polymer and nanoparticles compositions, and a novel sensor design. The wearable device (i.e., bracelet) will contain an optical-to-electrical interface for recording the fluorescence output of a biosensor, based on estradiol sensitive transcription factor isolated from a microbial organism. The biosensor is composed of biopolymers (dendrimers and polypeptides nanoparticles) functionalized with fluorescent molecular beacons (MB) and a hormone-sensitive transcription factor. Without the hormone, the two fluorescent entities of the MB are linked by the protein and no signal is emitted because of fluorescence resonance energy transfer (FRET), while in the presence of estradiol, the MB separate and a fluorescent signal is emitted. The project will be conducted in two international prestigious laboratories in France and in the USA to give to the applicant the best interdisciplinary scientific environment, and ensure the ultimate success of this project. The applicant will be the main spokesperson and lead investigator of the project. This international exposure and this fellowship will provide the applicant a unique and multidisciplinary profile, while facilitating her future academic career as a researcher in France.

This two-year project aims at exploiting both the intrinsic robustness and wide diversity of topological structures that naturally appear in soft condensed matter systems such as liquid crystals in order to fabricate advanced materials, possibly reconfigurable, towards emerging photonics applications such as high-dimensional data storage and topological shaping of light at small scale. Our proposal basically relies on the use of geometrically confined chiral nematic liquid crystals that have been theoretically predicted to exhibit a rich variety of distinct metastable topological defects. Our ambition is to establish the related experimental foundations, to develop techniques for on-demand reconfiguration the generated topological structures, and to bring proof-of-principle of a few applications that we foresee. To this aim, the project will focus on one of the simplest case, namely the case of spherical microscopic droplets. The required scientific expertise and experimental facilities for successful completion of the project mainly cover the physics of liquid crystals defects, field-induced reorientation of liquid crystals and the topology of light fields. This will be ensured by the long-standing experience of the Supervisor as well as broad experimental capacities of the host group whereas present skills of the Researcher in the physics of liquid crystals and molecular photochemistry in confined media guarantee an efficient start of the project. Since the research topics of this proposal are encompassed in the global scientific policy of the host University, this project offers a unique opportunity to initiate perennial cooperation between the Researcher the host University. The successful implementation of the project will therefore be beneficial both to Supervisor’s research group and to Researcher’s career, who aims at obtaining a permanent position and eventually leading her own research group.

With the growing popularity of herbal drugs an increasing number of scientific studies report information about herb-drug interactions that can significantly alter the effects of a drug. Keeping up with the current publication rate is not feasible, therefore there is a clear need for computational methods for early detection of herb-drug interactions that will enable better public and physician understanding of herbal products. But the costs of manually representing knowledge about herb-drug interactions in a machine processable way are prohibitive, therefore domain expertise has to be leveraged indirectly from domain-specific corpora using Information Extraction. This Marie Curie European Fellowship proposes a Deep Learning approach based on Artificial Neural Networks (ANN) and Information Extraction to monitor medical literature and construct a knowledge base of herb-drug interactions together with supporting evidence in the form of interaction mechanisms. To cope with the problem of incorrect or missing information we will consolidate the resulting knowledge graph using knowledge graph completion that predicts the probability of existence or correctness of typed edges in the graph. Advanced graph visualization techniques will be employed to develop intuitive interfaces for analyzing and comparing herb-drug interactions and underlying mechanisms. The Fellowship is expected to increase knowledge on clinically significant herb-drug interactions which will contribute to improved public safety. The Host will provide training on Deep Learning approaches for knowledge extraction which will open opportunities for a senior researcher position, in turn the Fellow will transfer Natural Language Processing skills and European collaborations to the host.

The CA3 subregion of the hippocampus is crucial for the formation of episodic memories on a short timescale, possibly due to synaptic plasticity in the recurrent connections between pyramidal cells. Previously, in vivo observations of these changes due to a learning event were elusive; however, in the current proposal we will use new methods to allow us to observe and manipulate the changes that occur in cells and synapses correlated with memory formation. To achieve this, we will combine optogenetic stimulation techniques with both intra- and extracellular in vivo electrophysiology to measure cellular properties, network dynamics, and both artificially- and naturally-induced synaptic plasticity. Additionally, we will restrict optogenetic expression to only those cells involved in the memory, allowing us to selectively identify and manipulate these cells. Stimulation of a subset of CA3 pyramidal cells while recording the intracellular trace from an individual CA3 pyramidal cell will provide the first insights into the nature of the recurrent network in vivo; incorporating stimulation protocols designed to induce synaptic plasticity will allow us to characterize different forms of plasticity in vivo. Adding stimulation of DG inputs to this protocol will allow us to measure the modulation of both activity and synaptic plasticity. Finally, we will test the effect of natural learning on the CA3 network, by recording extracellular activity in vivo, and taking measurements of cellular properties and synapse strength ex vivo. This project will allow us, for the first time, to link the single-synapse changes hypothesized to be crucial for memory with whole-animal learning.