1,303 research outputs found

    The medical applications of hyperpolarized Xe and nonproton magnetic resonance imaging

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    Hyperpolarized 129Xe (HP 129Xe) magnetic resonance imaging (MRI) is a relatively young field which is experiencing significant advancements each year. Conventional proton MRI is widely used in clinical practice as an anatomical medical imaging due to its superb soft tissue contrast. HP 129Xe MRI, on the other hand, may provide valuable information about internal organs functions and structure. HP 129Xe MRI has been recently clinically approved for lung imaging in the United Kingdom and the United States. It allows quantitative assessment of the lung function in addition to structural imaging. HP 129Xe has unique properties of anaesthetic, and may transfer to the blood stream and be further carried to the highly perfused organs. This gives the opportunity to assess brain perfusion with HP 129Xe and perform molecular imaging. However, the further progression of the HP 129Xe utilization for brain perfusion quantification and molecular imaging implementation is limited by the absence of certain crucial milestones. This thesis focused on providing important stepping stones for the further development of HP 129Xe molecular imaging and brain imaging. The effect of glycation on the spectroscopic characteristics of HP 129Xe was studied in whole sheep blood with magnetic resonance spectroscopy. An additional peak of HP 129Xe bound to glycated hemoglobin was observed. This finding should be implemented in the spectroscopic HP 129Xe studies in patients with diabetes. [...

    The 2023 terahertz science and technology roadmap

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    Terahertz (THz) radiation encompasses a wide spectral range within the electromagnetic spectrum that extends from microwaves to the far infrared (100 GHz–∌30 THz). Within its frequency boundaries exist a broad variety of scientific disciplines that have presented, and continue to present, technical challenges to researchers. During the past 50 years, for instance, the demands of the scientific community have substantially evolved and with a need for advanced instrumentation to support radio astronomy, Earth observation, weather forecasting, security imaging, telecommunications, non-destructive device testing and much more. Furthermore, applications have required an emergence of technology from the laboratory environment to production-scale supply and in-the-field deployments ranging from harsh ground-based locations to deep space. In addressing these requirements, the research and development community has advanced related technology and bridged the transition between electronics and photonics that high frequency operation demands. The multidisciplinary nature of THz work was our stimulus for creating the 2017 THz Science and Technology Roadmap (Dhillon et al 2017 J. Phys. D: Appl. Phys. 50 043001). As one might envisage, though, there remains much to explore both scientifically and technically and the field has continued to develop and expand rapidly. It is timely, therefore, to revise our previous roadmap and in this 2023 version we both provide an update on key developments in established technical areas that have important scientific and public benefit, and highlight new and emerging areas that show particular promise. The developments that we describe thus span from fundamental scientific research, such as THz astronomy and the emergent area of THz quantum optics, to highly applied and commercially and societally impactful subjects that include 6G THz communications, medical imaging, and climate monitoring and prediction. Our Roadmap vision draws upon the expertise and perspective of multiple international specialists that together provide an overview of past developments and the likely challenges facing the field of THz science and technology in future decades. The document is written in a form that is accessible to policy makers who wish to gain an overview of the current state of the THz art, and for the non-specialist and curious who wish to understand available technology and challenges. A such, our experts deliver a 'snapshot' introduction to the current status of the field and provide suggestions for exciting future technical development directions. Ultimately, we intend the Roadmap to portray the advantages and benefits of the THz domain and to stimulate further exploration of the field in support of scientific research and commercial realisation

    Molekulardynamik-Simulationen zur Untersuchung der wechselseitigen AbhÀngigkeit von Lösungsmittel- und Proteindynamik

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    Proteine sind an vielen physiologischen Prozessen in Zellen beteiligt und als solche unverzichtbar fĂŒr das Leben. Es gilt als gesichert, dass fĂŒr die AusĂŒbung biologischer Funktionen, die Dynamik des Proteins von zentraler Bedeutung ist. Es wird angenommen, dass die molekulare Umgebung des Proteins entscheidend fĂŒr dessen Dynamik ist. Insbesondere das Lösungsmittel spielt eine zentrale Rolle, da davon ausgegangen wird, dass Proteine ohne ein geeignetes Lösungsmittel keine funktionsrelevante Dynamik aufweisen. Trotz intensivster BemĂŒhungen gibt es bis heute kein qualitatives Modell, das die dynamischen PhĂ€nomene von Proteinen erklĂ€ren könnte. Im Rahmen dieser Arbeit wird untersucht, wie Protein- und Lösungsmitteldynamik zusammenhĂ€ngen. Zu diesem Zweck werden Molekulardynamik-Simulation verwendet, da sie ein vielseitiges Werkzeug sind, um ZusammenhĂ€nge auf konzeptioneller Ebene anhand von Modellsystemen zu verstehen. Proteine werden der weichen Materie zugeordnet. Als solche sind sie insbesondere glasbildende Systeme, wodurch angenommen werden kann, dass bestehende theoretische Überlegungen zum GlasĂŒbergang fĂŒr das VerstĂ€ndnis der Proteindynamik relevant sind. In diesem Kontext werden zunĂ€chst Systeme zu Glyzerin, einem prominenten Glasbildner, implementiert, simuliert und analysiert. Dabei gelingt es durch Analysen an einzelnen Untergruppen des Systems die experimentell beobachtete ungewöhnlich große Trennung zwischen Rotation- und Translationsdynamik nachzubilden. Es wird gezeigt, dass – entgegen der Annahme einer großen FlexibilitĂ€t – das GlyzerinmolekĂŒl auf der Zeitskala der untersuchten Reorientierungsdynamik als starr angenommen werden muss. Die Analyse einzelner MolekĂŒlkomponenten bestĂ€tigt, dass die experimentell beobachteten Anomalien bei Glyzerin auf die anisotrope Spinverteilung des MolekĂŒls zurĂŒckzufĂŒhren sind. DarĂŒber hinaus konnten zuvor heuristisch eingefĂŒhrte experimentelle Auswerteverfahren durch Replikation im Modellsystem verifiziert werden. ZusĂ€tzlich werden Protein-Wasser-Mischsysteme in neutralen, geometrisch beschrĂ€nkten Systemen untersucht, deren Form an die Startkonfiguration des Proteins angepasst wird. Die GrĂ¶ĂŸe der so entstandenen Pore und die Starrheit der begrenzenden Wand können systematisch variiert werden. Diese gezielte Variation der Umgebungsparameter erlaubt es, die gegenseitige AbhĂ€ngigkeit von Protein- und Lösungsmitteldynamik zu zeigen, was der weit verbreiteten Annahme eines einseitigen Einflusses des Lösungsmittels auf die Proteindynamik widerspricht. Der funktionale Zusammenhang der Korrelationszeiten fĂŒr Systemkomponenten in der NĂ€he der gemeinsamen GrenzflĂ€che deutet auf eine AbhĂ€ngigkeit in Form eines Potenzgesetzes hin. Unterhalb eines kritischen Hydratationsgrades nimmt die ProteinmobilitĂ€t bei weiterer Verringerung des Hydratationswassers rapide ab; oberhalb stellt sich bulk-artige Dynamik ein. In den untersuchten Systemen ist diese Grenze erreicht, wenn die Masse des Hydratationswassers das 1.5-fache der Masse des Proteins betrĂ€gt. Die rĂ€umlich aufgelösten Analysen zeigen, dass die Wirkung der Porenwand auf die Wasserdynamik zwar stark, aber kurzreichweitig und damit im Wesentlichen auf die ersten beiden Wasserschichten beschrĂ€nkt ist

    Markov field models of molecular kinetics

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    Computer simulations such as molecular dynamics (MD) provide a possible means to understand protein dynamics and mechanisms on an atomistic scale. The resulting simulation data can be analyzed with Markov state models (MSMs), yielding a quantitative kinetic model that, e.g., encodes state populations and transition rates. However, the larger an investigated system, the more data is required to estimate a valid kinetic model. In this work, we show that this scaling problem can be escaped when decomposing a system into smaller ones, leveraging weak couplings between local domains. Our approach, termed independent Markov decomposition (IMD), is a first-order approximation neglecting couplings, i.e., it represents a decomposition of the underlying global dynamics into a set of independent local ones. We demonstrate that for truly independent systems, IMD can reduce the sampling by three orders of magnitude. IMD is applied to two biomolecular systems. First, synaptotagmin-1 is analyzed, a rapid calcium switch from the neurotransmitter release machinery. Within its C2A domain, local conformational switches are identified and modeled with independent MSMs, shedding light on the mechanism of its calcium-mediated activation. Second, the catalytic site of the serine protease TMPRSS2 is analyzed with a local drug-binding model. Equilibrium populations of different drug-binding modes are derived for three inhibitors, mirroring experimentally determined drug efficiencies. IMD is subsequently extended to an end-to-end deep learning framework called iVAMPnets, which learns a domain decomposition from simulation data and simultaneously models the kinetics in the local domains. We finally classify IMD and iVAMPnets as Markov field models (MFM), which we define as a class of models that describe dynamics by decomposing systems into local domains. Overall, this thesis introduces a local approach to Markov modeling that enables to quantitatively assess the kinetics of large macromolecular complexes, opening up possibilities to tackle current and future computational molecular biology questions

    Single-molecule detection and characterisation of alpha-synuclein aggregates

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    Aberrant protein aggregation is a predominant feature of many neurodegenerative disorders. It has long been recognised that aggregates of alpha-synuclein (α-syn) drive pathogenesis in Parkinson’s Disease (PD), and it is widely accepted that small α-syn oligomers are the key cytotoxic species in PD. Notably, however, these oligomeric species are difficult to characterise using traditional biochemical ensemble methods due to their high level of heterogeneity and low abundance. Single-molecule fluorescence microscopy techniques have emerged as a suitable approach to circumventing this problem, enabling the detection of individual aggregates amongst monomeric protein and thus facilitating the identification, quantification, and characterisation of rare oligomeric species. However, cellular mechanisms of α-syn aggregation are poorly understood. Furthermore, there remains some limitations to the singlemolecule techniques currently available. This thesis describes the work completed to address some of these issues. Chapter 1 provides the contextual background for the work presented in this thesis, detailing the biological aspects of α-syn, its aggregation, and its implications in PD, as well as outlining the single-molecule techniques used to investigate aggregate species. Chapter 2 describes the methodologies undertaken in this thesis, and chapters 3 to 5 describe the findings made using the single-molecule techniques which were utilised and developed in this work. One primary approach for studying species in single-molecule experiments involves directly labelling biomolecules of interest with a suitable fluorophore. Early steps in α-syn aggregation have previously been identified using fluorescently tagged α-syn and single-molecule Förster resonance energy transfer (smFRET) in vitro; however, the characterisation of early aggregate formation in cells has thus far been difficult to achieve. Chapter 3 describes the use of duallabelled α-syn to detect and characterise aggregates formed both intracellularly and in vitro via smFRET, using both single-molecule confocal microscopy coupled with microfluidics and iii total internal reflection fluorescence microscopy (TIRFM) to determine both the sizes and structures of the oligomers formed. This work reveals the presence of distinct oligomeric species in vitro and in neurons resulting from structural conversion during early aggregate formation. The approach taken in Chapter 3 is highly suitable for investigating aggregate formation resulting from the addition of exogenous α-syn to samples of interest. However, such an approach is not ideal for the detection and characterisation of endogenous aggregates due to issues with the covalent labelling of cellular protein. Extrinsic amyloid dyes are typically used as an alternative approach to labelled protein; however, such dyes are non-protein-specific and bind to the common amyloid beta-sheet motif. As an alternative, the work presented in Chapter 4 describes a novel single-molecule method to specifically detect and characterise α-syn aggregates with high sensitivity, making use of a high-affinity antibody labelled with orthogonal fluorophores which is combined with fast-flow microfluidics and single-molecule confocal microscopy. This enables the quantification and size approximation of α-syn aggregates at picomolar concentrations, both in vitro and in biological samples. Although the kinetics of α-syn aggregation have been studied extensively, much of our current knowledge stems from ensemble averaging techniques which are associated with high levels of variability and are not conducive to detecting the earliest steps in aggregate formation. In addition, there remains uncertainty surrounding the effect of familial variants and posttranslational modifications (PTM) on aggregation. Chapter 5 encompasses the study of the effects of the ubiquitous N-terminal acetylation PTM, in addition to the familial, rapid-onset G51D mutation, on α-syn aggregation, using the novel detection method developed in Chapter 4. This is used in conjunction with single-molecule detection with thioflavin-T (ThT) to reveal new insights into the aggregation of α-syn variants. Overall, the work presented here provides new insights into the aggregation of α-syn via the use and development of single-molecule techniques. The advancements made have added to the current understanding of the molecular mechanisms of α-syn aggregation, both in vitro and in neurons, and have also been used to develop a novel single-molecule detection method for α-syn aggregates. The work presented in this thesis has resulted in two published papers, ’Pathological structural conversion of alpha-synuclein at the mitochondria induces neuronal toxicity’ in Nature Neuroscience, and ’Single-molecule two-color coincidence detection of unlabeled alpha-synuclein aggregates’ in Angewandte Chemie International Edition. Furthermore, the novel detection method presented here holds promise for measuring α-syn oligomeric load in clinical samples due to its high sensitivity and specificity for α-syn aggregates. This may therefore be used in future studies for identifying, detecting, and studying potential biomarkers in PD, with potential use in disease diagnosis. It is therefore expected that the work from this thesis will be used to aid researchers towards better understanding the mechanisms of α-syn aggregation, both in vitro and in clinical samples

    The 2023 terahertz science and technology roadmap

    Get PDF
    Terahertz (THz) radiation encompasses a wide spectral range within the electromagnetic spectrum that extends from microwaves to the far infrared (100 GHz–∌30 THz). Within its frequency boundaries exist a broad variety of scientific disciplines that have presented, and continue to present, technical challenges to researchers. During the past 50 years, for instance, the demands of the scientific community have substantially evolved and with a need for advanced instrumentation to support radio astronomy, Earth observation, weather forecasting, security imaging, telecommunications, non-destructive device testing and much more. Furthermore, applications have required an emergence of technology from the laboratory environment to production-scale supply and in-the-field deployments ranging from harsh ground-based locations to deep space. In addressing these requirements, the research and development community has advanced related technology and bridged the transition between electronics and photonics that high frequency operation demands. The multidisciplinary nature of THz work was our stimulus for creating the 2017 THz Science and Technology Roadmap (Dhillon et al 2017 J. Phys. D: Appl. Phys. 50 043001). As one might envisage, though, there remains much to explore both scientifically and technically and the field has continued to develop and expand rapidly. It is timely, therefore, to revise our previous roadmap and in this 2023 version we both provide an update on key developments in established technical areas that have important scientific and public benefit, and highlight new and emerging areas that show particular promise. The developments that we describe thus span from fundamental scientific research, such as THz astronomy and the emergent area of THz quantum optics, to highly applied and commercially and societally impactful subjects that include 6G THz communications, medical imaging, and climate monitoring and prediction. Our Roadmap vision draws upon the expertise and perspective of multiple international specialists that together provide an overview of past developments and the likely challenges facing the field of THz science and technology in future decades. The document is written in a form that is accessible to policy makers who wish to gain an overview of the current state of the THz art, and for the non-specialist and curious who wish to understand available technology and challenges. A such, our experts deliver a 'snapshot' introduction to the current status of the field and provide suggestions for exciting future technical development directions. Ultimately, we intend the Roadmap to portray the advantages and benefits of the THz domain and to stimulate further exploration of the field in support of scientific research and commercial realisation

    The Influence of Allostery Governing the Changes in Protein Dynamics Upon Substitution

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    The focus of this research is to investigate the effects of allostery on the function/activity of an enzyme, human immunodeficiency virus type 1 (HIV-1) protease, using well-defined statistical analyses of the dynamic changes of the protein and variants with unique single point substitutions 1. The experimental data1 evaluated here only characterized HIV-1 protease with one of its potential target substrates. Probing the dynamic interactions of the residues of an enzyme and its variants can offer insight of the developmental importance for allosteric signaling and their connection to a protein’s function. The realignment of the secondary structure elements can modulate the mobility along with the frequency of residue contacts as well as which residues are making contact together2-5. We postulate that if there are more contacts occurring within a structure the mobility is being constrained and therefore gaining novel contacts can negatively influence the function of a protein. The evolutionary importance of protein dynamics is probed by analyzing the residue positions possessing significant correlations and the relationship between experimental information1 (variant activities). We propose that the correlated dynamics of residues observed to have considerable correlations, if disrupted, can be used to infer the function of HIV-1 protease and its variants. Given the robustness of HIV-1 protease the identification of any significant constraint imposed on the dynamics from a potential allosteric site found to disrupt the catalytic activity of the variant is not plainly evident. We also develop machine learning (ML) algorithms to predict the protein function/activity change caused by a single point substitution by using the DCC of each residue pair. Recognition of any substantial association between the dynamics of specific residues and allosteric communication or mechanism requires detailed examination of the dynamics of HIV-1 protease and its variants. We also explore the non-linear dependency between each pair of residues using Mutual Information (MI) and how it can influence the dynamics of HIV-1 protease and its variants. We suggest that if the residues of a protein receive more or less information than that of the WT it will adversely impact the function of the protein and can be used to support the classification of a variant structure. Furthermore, using the MI of residues obtained from the MD simulations for the HIV-1 protease structure, we build a ML model to predict a protein’s change in function caused by a single point substitution. Effectively the mobility, dynamics, and non-linear features tested in these studies are found to be useful towards the prediction of potentially drug resistant substitutions related to the catalytic efficiency of HIV-1 protease and the variants
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