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Description: One of the important shortcomings of modern anticancer therapies is their limited penetration depth of only a few cell layers into the tumor. Concentrated around the heterogeneous vasculature, these drugs produce only a local therapeutic effect. In this project we propose a method of overcoming this limitation by engineering a novel class of gas-filled nanostructures capable of homing to tumor tissues, and using their vibration in response to ultrasound energy to deliver drugs deeper into the tumor core. The proposed approach is based on ultrasonic cavitation, a phenomenon in which gas bubbles expand and collapse under the influence of ultrasound waves. This process produces fluid streaming that propels drugs deeper into the tumor mass. The use of ultrasound for drug delivery is attractive due to its availability and affordability. However, the use of this technology is currently limited by the properties of conventional microbubble-based cavitation nuclei: their large size prevents them from penetrating into the tumor and their short circulation times do not match the pharmacokinetic time constants of many drugs. To overcome these challenges, we will utilize gas vesicles (GVs), a unique class of genetically encoded, gas-filled protein nanostructures derived from buoyant photosynthetic microbes, as cavitation nuclei. Unlike microbubbles, GVs are physically stable and their nanoscale dimensions have the potential to enable them to extravasate into tumors and bind to specific cellular targets. We hypothesize that GVs can act as both imaging agents and cavitation nuclei. If so, this therapeutic approach could have vastly improved efficacy and selectivity and the potential to combine cavitation-enhanced drug delivery with emerging advancements in cell based therapeutics. This project will enable the applicant to diversify his capabilities and experience beyond ultrasound imaging and signal processing and re-inforce a position of professional maturity.
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Description: Organisms across all kingdoms share several systems that are essential to life, one of the most central being protein synthesis. Living in a continuously changing environment, cells need to constantly respond to various environmental cues and change their protein landscape. In extreme cases, cells globally shut down protein synthesis and upregulate stress-protective proteins.
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Description: Imaging of hypoxia is important in many disease states in oncology, cardiology, and neurology. Hypoxia is a common condition encountered within the tumour microenvironment that drives proliferation, angiogenesis, and resistance to therapy. Despite on-going efforts to identify hypoxia, until now there is no clinically approved imaging biomarker, due to both low tumour uptake, and a low signal to background (S/B) ratio that affects the imaging quality. Nuclear Medicine is using labelled radio-isotopes for PET/CT and SPECT imaging. These radio-tracers diagnose the metabolic processes in the body. Among these tracers, 18F-FDG is the most routinely used as a marker of glucose metabolism. However, not all tumours consume glucose, and glucose consumption is not specific only for malignant tumours, which limits its application. Copper is a nutritional metal, recently examined as a radiotracer for hypoxia, owing to its to the oxidising environment. Clinical and in-vivo studies on various 64Cu(II)-PET radiotracers resulted in controversial reports on the specificity of the current tracers for hypoxia imaging due to non-selective bio-distribution & low S/B ratio. This multidisciplinary proposal focuses on the discovery of comprehensive signal pathways of the cellular copper cycle using advanced biophysical methods and a proprietary design of 64Cu(II) radiotracer. This radiotracer will be incorporated in the cellular copper cycle, and will enable to selectively target the oxidising environment in tumours. The design of the new radiotracer is based on systematic structural & functional mapping of the copper binding sites to the various copper proteins and the visualisation of the transfer mechanism. This new copper tracer should increase the selectivity of tumour uptake, stability, and improve bio-distribution. This project assimilates cold and hot chemistry and biology, while emphasising the clinical unmet need in metal based radiotracer that form stable complexes.
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Description: Critical for the function of many proteins, allosteric communication involves transmission of the effect of binding at one site of a protein to another through conformational changes. Yet the structural and dynamic basis for allostery remains poorly understood. In particular, there is no method to follow coordinated large-scale motions of domains and subunits in proteins as they occur. Since the subunits of allosteric proteins often contain multiple domains, any such method entails probing the dynamics along several intra-protein distances simultaneously.
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Description: E-commerce, modern-day government auctions, the sharing economy – these all have in common the optimization of resource allocation through the combination of economics and computation. This trend holds enormous socio-economic opportunity: for example, it allows online auctions, personalized advertising that supports the internet ecosystem, government repacking of radio spectrum to support growing communication needs, and flexible pricing that reflects true demand. It also poses an enormous challenge due to the sophisticated treatment of resources it requires, a challenge which theoretical computer science and algorithmic game theory in particular are uniquely positioned to address. 'Modern cryptography has successfully followed an 'all-or-nothing' design paradigm over the years. For example, the most fundamental task of data encryption requires that encrypted data be fully recoverable using the encryption key, but be completely useless without it. Nowadays, however, this paradigm is insufficient for a wide variety of evolving applications, and a more subtle approach is urgently needed. This has recently motivated the cryptography community to put forward a vision of 'functional cryptography': Designing cryptographic primitives that allow fine-grained access to sensitive data.
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CountryCode: IL
Coordinator: THE HEBREW UNIVERSITY OF JERUSALEM, THE HEBREW UNIVERSITY OF JERUSALEM
Country: Israel
Description: Face recognition is a fascinating domain: no other domain seems to present as much value when analysing casual photos; it is one of the few domains in machine learning in which millions of classes are routinely learned; and the trade-off between subtle inter-identity variations and pronounced intra-identity variations forms a unique challenge.
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Description: Bacteria use various mechanisms to combat competitors and colonize new niches. The Type VI Secretion System (T6SS), a contact-dependent protein delivery apparatus, is a widespread, recently discovered machine used by Gram-negative bacteria to target competitors. Its toxicity is mediated by secreted proteins called effectors, yet the identity of many effectors, the mechanism of secretion of different effector classes, and their toxic activities remain largely unknown. I recently uncovered a widespread class of T6SS effectors that share a domain called MIX. MIX-effectors are polymorphic proteins carrying various toxin domains, many of which with unknown activities.
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Description: The evolution of specificity between interacting biological molecules underlies the diversification and expansion of biological pathways. A shift in specificity poses a serious theoretical problem; it requires coordinated mutations in the interacting partners, but mutation in one partner may lead to loss of interaction and functional failure. While some theoretical suggestions were proposed to solve this 'specificity valley crossing' problem, it remains a challenge to study this problem empirically at the molecular level. In bacteria, there are numerous divergent evolving pathways. Many of these pathways are involved in mediating conflicts between selfish genes, cells and populations. We and others have speculated that such multilevel selection can facilitate pathway divergence. Here we propose to study this link using the Rap-Phr cell-cell communication system, which has diversified to ~100 specific systems in the B. subtilis lineage. These systems consist of a receptor (Rap) and its cognate peptide pheromone (Phr) that influence multiple levels of selection. They promote their own horizontal transfer, modulate core cellular pathways, and manipulate cooperation between cells. Combining modelling with deep mutational scanning, competition assays and time-lapse microscopy we will quantitatively study all these levels of selection and their implication for diversification on a large fitness landscape. Specifically, we will (1) map the Rap-Phr interaction landscape at unprecedented resolution, constructing and screening libraries of ~106 Phr peptide variants and ~104 Rap variants. (2) Quantify the fitness effects of these systems at multiple levels of selection in biofilms. (3) Theoretically generate and experimentally verify predictions about how Rap-Phr co-evolve and diversify. Our work will pioneer the study of fitness landscapes under multilevel selection and provide a direct, quantitative, and predictive framework for understanding the evolution of specificity.
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Description: Symplectic geometry combines a broad spectrum of interrelated disciplines lying in the mainstream of modern mathematics. The past two decades have given rise to several exciting developments in this field, which introduced new mathematical tools and opened challenging new questions. Nowadays symplectic geometry reaches out to an amazingly wide range of areas, such as differential and algebraic geometry, complex analysis, dynamical systems, as well as quantum mechanics, and string theory. Moreover, symplectic geometry serves as a basis for Hamiltonian dynamics, a discipline providing efficient tools for modeling a variety of physical and technological processes, such as orbital motion of satellites (telecommunication and GPS navigation), and propagation of light in optical fibers (with significant applications to medicine).
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Description: Plants evolved a unique molecular mechanism that spatially regulate auxin, forming finely tuned gradients and local maxima of auxin that inform and direct developmental patterning and adaptive growth processes. Recent findings call into question the uniqueness of polar auxin transport in the sense that more plant hormones seem to be actively transported. Although still lacking many mechanistic details, as well as comprehensive functional connotations, these findings warrant a more thorough investigation into the prospect of a broader scope for plants spatial regulation capacity in the context of additional hormones. Critically, we lack an effective set of tools to directly investigate and dissect the particulars of plant hormones mobility at the molecular level. My long-term goal is to provide a molecular and mechanistic understanding of plant hormones dynamics that will augment our evolving model of how they are regulated and how they convey information. Here, I hypothesize that GA mobility in plants is controlled and directed by an active transport mechanism to form distinct distribution patterns that affect signaling. I will test my hypothesis with a multi-faceted and multi-disciplinary approach, combining: fluorescent labeling of key gibberellins to map their accumulation sites in whole plants and at the sub-cellular level; chemical-biology strategies that facilitate manipulation of GA “origin point” in planta to map and quantify GA flow pathways; probe-based genetic screens and un-biased photo-affinity labeling to identify proteins affecting GA mobility; and genetic and molecular biology techniques to characterize identified proteins’ functions. I expect to offer an exceptional, detailed view into the inner workings of gibberellins dynamics in planta and into the mechanisms driving it. I further anticipate that the strategies developed here to specifically address gibberellins could be straightforwardly re-tailored to investigate additional plant hormones.
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Description: Experimental time-domain astrophysics is on the verge of a new era as technological, computational, and operational progress combine to revolutionise the manner in which we study the time-variable sky. This proposal consolidates previous breakthrough work on wide-field surveys into a coherent program to advance our study of the variable sky on ever decreasing time-scales: from days, through hours, to minutes. We will watch how stars explode in real time in order to study the complex physics of stellar death, build new tools to handle and analyse the uniquely new data sets we are collecting, and shed light on some of the most fundamental questions in modern astrophysics: from the origin of the elements, via the explosions mechanism of supernova explosions, to the feedback processes that drive star formation and galaxy evolution.
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Description: Cancer is a growing medical problem which genetic and environmental basis is not clearly understood. Massive efforts over the last decade have identified differences in cancer gene expression that cannot be explained by coding sequences or promoter variations, whereas the effect of transcriptional enhancers remains unclear due to the lack of an effective way to link enhancers with their controlled genes. Recently, we discovered a class of inter-tumor, inter-patient DNA methylation variations in putative enhancers that predict changes in gene expression levels with much greater power than promoter or sequence analyses. The overall goal of this proposal is to determine if changes in enhancer methylation form part of the genomic basis of cancer. Our aim is to elucidate methylation-influenced disease regulatory circuits that affect cancer driver and risk genes and may ultimately serve as markers for disease progression and drug response. Utilizing a new genomic methodology, which allows systematic prediction and verification of gene-enhancer pairing, I will test the above hypothesis in two disease models: breast cancer and glioblastoma. I will methodologically assess numerous potential enhancers across the disease genomes and explore the effects of genetic and epigenetic mutations and variations at these sites. Informative sites will then be evaluated as markers of gene expression level in tumor biopsies. Ultimately, I will apply novel tools to manipulate selected enhancers genetically and epigenetically, thus investigating the causal relationships between enhancer methylation and gene expression, and assessing the potential for tuning gene expression levels by enhancer methylation modification. This study may transform our understanding of the mechanisms underlying disease predisposition, determine the regulatory circuits of key disease genes, lead to improved diagnosis and predictive abilities, and may pave the way for precision epigenetic therapy.
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Description: The metabolism of cancer cells is altered to meet cellular requirements for growth, providing novel means to selectively target tumorigenesis. While extensively studied, our current view of cancer cellular metabolism is fundamentally limited by lack of information on variability in metabolic activity between distinct subcellular compartments and cells.
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Description: Geometric data is prevalent in many areas of science and technology. From the surface of the brain to the intricate shapes of free-form architecture, complex geometric structures arise in many fields, and problems such as analysis, processing and synthesis of geometric data are of great importance.
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Description: Can we program computers in our native tongue? This idea, termed natural language programming, has attracted attention almost since the inception of computers themselves.
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Description: The comparative research of long-term trends largely neglects structural mechanisms of gender inequality, i.e. the gender bias in which jobs and activities are evaluated and rewarded. I argue that as more women become integrated in positions of power, the stronger the role of structural elements is likely to become. However, because these are less visible and amenable to empirical assessment, they are under-researched compared to individual aspects, and are commonly assumed to be gender-neutral. The implication is that the importance of gender as a determinant of economic inequality in the labour market becomes insufficiently acknowledged, and thus difficult to track and eradicate.
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Description: The ability to direct drug delivery to specific tissues is a central challenge in treating diseases as it determines the balance between drug selectivity and toxicity. Clinical drug failures, commonly due to safety issues or poor efficacy, are extremely costly to the pharmaceutical industry. In light of this, there is a global effort to develop Targeted Drug Delivery Systems (DDS) and Nanomedicine-based drugs to increase the therapeutic efficacy of a drug while substantially reducing its off-target exposure. In oncology, this issue is critical since chemotherapies have poor selectivity, thus causing severe side effects due to undesired systemic exposure. However, the enormous heterogeneity and dynamic nature of tumors makes it extremely challenging to identify universal target molecules. In this ERC I introduce a novel concept according to which the specificity of DDS can be dramatically enhanced by tuning the physical parameters of DDS based on mechanical cues of target and non-target cells. In many cancers, it is well-established that the flexibility and deformability of cells are correlated with their metastatic potential. This leads to our hypothesis that the enhanced deformability of cancer cells allows them to engulf and uptake particles whose internalization requires massive shape change, unlike the stiffer and normal cells. The rationale of the proposed study is that by considering physical parameters of cells, the mechanical properties of DDS can be tuned to achieve selective uptake. We thus propose to develop tools for rational design of DDS for personalized nanomedicine that will use simple tests performed on a patient’s own cells. This is the basis of our visionary Mechanical Targeting (MT) scheme, a crosstalk between experimental and computational models, for drug specificity. Accordingly, this ERC is expected to yield breakthroughs, both conceptual and technical.
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Description: Cancer is the leading cause of death in the Western world and the second cause of death worldwide. Despite advances in medical research, 30% of cancer patients are prescribed a medication the tumor does not respond to, or, alternatively, drugs that induce adverse side effects patients' cannot tolerate.
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Description: The metrology domain (which could be considered as the ‘eyes and ears’ for both R&D&I and production) is a key enabler for productivity enhancements in many industries across the electronic components and system (ECS) value chain and have to be an integral part of any Cyber Physical Systems (CPS) which consist of metrology equipment, virtual metrology or Industrial internet of things (IIoT) sensors, edge and high-performance computing (HPC). The requirements from the metrology is to support ALL process steps toward the final product. However, for any given ECS technology, there is a significant trade-off between the metrology sensitivity, precision and accuracy to its productivity. MADEin4 address this deficiency by focusing on two productivity boosters which are independent from the sensitivity, precision and accuracy requirements: • Productivity booster 1: High throughput, next generation metrology and inspection tools development for the nanoelectronics industry (all nodes down to 5nm). This booster will be developed by the metrology equipment’s manufacturers and demonstrated in an industry 4.0 pilot line at imec and address the ECS equipment, materials and manufacturing major challenges (MASP Chapter 15, major challenges 1 – 3). • Productivity booster 2: CPS development which combines Machine Learning (ML) of design (EDA) and metrology data for predictive diagnostics of the process and tools performances predictive diagnostics of the process and tools performances (predictive yield and tools performance). This booster will be developed and demonstrated in an industry 4.0 pilot line at imec, for the 5nm node, by the EDA, computing and metrology partners (MASP Chapter 15, major challenge 4). The same CPS concept will be demonstrated for the ‘digital industries’ two major challenges of the nanoelectronics (all nodes down to 5nm) and automotive end user’s partners (MASP Chapter 9, major challenges 1and 3).
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Description: Central tolerance is shaped in the thymus, a primary lymphoid organ, where immature T lymphocytes are “educated” into mature cells, capable of recognizing foreign antigens, while tolerating the body’s own components. This process is driven mainly by two separate lineages of thymic epithelial cells (TECs), the cortical (cTEC) and the medullary (mTEC). While cTECs are critical at the early stages of T cell development, mTECs play a pivotal role in negative selection of self-reactive thymocytes and the generation of Foxp3\ regulatory T (Treg) cells. Crucial to the key role of mTECs in the screening of self-reactive T cell clones, is their unique capacity to promiscuously express and present almost all self-antigens, including thousands of tissue-specific antigen (TSA) genes. Strikingly, the expression of most of this TSA repertoire in mTECs is regulated by a single transcriptional regulator called Aire. Indeed, Aire deficiency in mice and human patients results to multi-organ autoimmunity. Although there has been dramatic progress in our understanding of how thymic epithelial cells shape and govern the establishment of adaptive immunity and of immunological self-tolerance, there are still several outstanding questions with no comprehensive answers. Therefore, in the research proposed herein, we wish to provide more comprehensive answers to these still elusive, but very fundamental questions. Specifically we will aim at: 1.) Delineation of molecular mechanisms controlling TEC development and thymus organogenesis; 2.) Delineation of molecular mechanisms underlying promiscuous gene expression in the thymus; 3.) Identification and characterization of molecular determinants responsible for the breakdown of thymus-dependent self-tolerance. To this end, we will build upon our recently published data, as well as unpublished preliminary data and utilize several state-of-the-art and interdisciplinary approaches, which have become an integral part of our lab’s toolbox.
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Description: Major advances were made in understanding circuits that underlie aversive emotional learning. The majority gained by using classical associative models, mainly tone/context-shock conditioning. Failure to extinguish the response or to discriminate from other safe stimuli (generalization), form two main animal models for human anxiety-disorders and post-traumatic-stress. These simple yet powerful approaches enabled cutting-edge techniques in rodents to unveil amygdala circuitry and its connectivity with the medial-prefrontal-cortex. Yet, we have less understanding of the mechanisms that underlie elaborated behavioural models of mal-adaptive behaviour, as well as less understanding of neural codes and computations in the evolutionary-expanded primate amygdala. Our lab recently embarked on exploring these venues by pioneering physiological studies of generalization and extinction protocols in primates. The goal of the current project is to develop behavioural models of complex learning and maladaptive behaviour, and then examine and shed light on the underlying computations in primate amygdala-PFC circuit. We design a novel rule-based learning task, and examine its acquisition, extinction, generalization and exploration-exploitation trade-off in dangerous environments. Specifically, the concepts of rule learning and exploration-exploitation tradeoff form novel insights and aspects of [mal-]adaptive behaviours, and will suggest new animal models of learned anxiety. We record dozens of neurons in the amygdala and prefrontal-cortex simultaneously using deep multi-contact arrays, supplemented by stimulation to address functional connectivity, and development of modelling approaches for the behaviour and neural codes. We posit that the development of more [complex] models is crucial and the next logical step in achieving translation of animal models of anxiety disorders, as well as in understanding basic mechanisms behind the rich repertoire of emotional behaviours.
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Page 1 of 1 (21 Total Results)
