Single-molecule localisation microscopy (SMLM), has allowed for optical microscopy to probe biological systems beyond the diffraction limit. The intrinsic 3D nature of biology has motivated the development of 3D-SMLM with novel techniques, including the double-helix point spread function (DHPSF). A bespoke microscope platform employing the DHPSF transformation was built, achieving ~10 nm lateral and ~20 nm axial localisation precision over a ~4 μm axial depth. Until recently, the DHPSF has been limited by spherical aberration present when imaging away from coverslip surfaces to the study of small volumes close to the coverslip. By matching the refractive index of the objective lens immersion liquid to that of the imaging media, this aberration can be minimised, facilitating large-volume imaging away from unphysiological flat surfaces. The work presented in this thesis illustrates the capabilities of the DHPSF for 3D-SMLM and single-particle tracking (SPT) in previously inaccessible areas of biological samples (e.g. in the nucleus and on the apical cell surface). Application of the DHPSF for SPT in eukaryotic cells are presented; tracking the motion of T-cell membrane proteins on the apical surface and components of the chromosome remodelling complex in the nucleus of embryonic stem cells. For these applications, meansquared displacement and jump distance diffusion analysis methodologies were extended into 3D and benchmarked against simulated datasets. A variety imaging applications that are facilitated by the extended depth of focus of the DHPSF are presented, focusing on quantification of T-cell membrane protein reorganisation upon immunological activation. Finally, the clustering distribution of the T-cell receptor is investigated by Ripley’s K analysis enabled by duel labelling of its position and the outer membrane in primary T cells.

Recently, there are great interests in the location-based applications and the location-awareness of mobile wireless systems in indoor areas, which require accurate location estimation in indoor environments. The traditional geolocation systems such as the GPS are not designed for indoor applications, and cannot provide accurate location estimation in indoor environments. Therefore, there is a need for new location finding techniques and systems for indoor geolocation applications. In this thesis, a wide variety of technical aspects and challenging issues involved in the design and performance evaluation of indoor geolocation systems are presented first. Then the TOA estimation techniques are studied in details for use in indoor multipath channels, including the maximum-likelihood technique, the MUSIC super-resolution technique, and diversity techniques as well as various issues involved in the practical implementation. It is shown that due to the complexity of indoor radio propagation channels, dramatically large estimation errors may occur with the traditional techniques, and the super-resolution techniques can significantly improve the performance of the TOA estimation in indoor environments. Also, diversity techniques, especially the frequency-diversity with the CMDCS, can further improve the performance of the super-resolution techniques.

National security needs dictate the development of new radar systems capable of identifying and tracking exoatmospheric threats to aid our defense. These new radar systems feature reduced noise floors, electronic beam steering, and ultra-wide bandwidths, all of which facilitate threat discrimination. However, in order to identify missile attributes such as RF reflectivity, distance, and velocity, many existing processing algorithms rely upon narrow bandwidth assumptions that break down with increased signal bandwidth. We present a fresh investigation into these algorithms for removing bandwidth limitations and propose novel state-space and direct-data factoring formulations such as * the multidimensional extension to the Eigensystem Realization Algorithm, * employing state-space models in place of interpolation to obtain a form which admits a separation and isolation of solution components, * and side-stepping the joint diagonalization of state transition matrices, which commonly plagues methods like multidimensional ESPRIT. We then benchmark our approaches and relate the outcomes to the Cramer-Rao bound for the case of one and two adjacent reflectors to validate their conceptual design and identify those techniques that compare favorably to or improve upon existing practices.

Amyloidogenic neurodegenerative disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD) are an important health issue. However, the underlying molecular mechanisms of the disease-related protein aggregates, that are present in humans, are only understood partially. I have used and developed biophysical methods to study the structural and biological properties of individual aggregates of Amyloid β peptide and α-Synuclein, proteins whose aggregation is associated with the development of Alzheimer's and Parkinson's disease respectively. I expanded the single aggregate visualisation through enhancement (SAVE) technique, which is a method based on the fluorescent dye Thioflavin T (ThT) that reversibly bind to the aggregates and whose fluorescence increases upon binding. I firstly explored the use of other dyes for these experiments and found that a ThT dimer has higher affinity to α-Synuclein aggregates in vitro. I then applied the SAVE method to the cerebral spinal fluid (CSF) of a cohort of AD patients and control CSF and observed no clear difference in aggregate number. However, these experiments provided insights into how antibodies bind the aggregates in human CSF. I could show, that despite altering the Ca2+ influx into both cells and vesicles, the antibody did not measurably affect the aggregate structure. To study the size specific effects of the Amyloid β 42 (Aβ42) peptide in more detail, I used and optimised gradient ultracentrifugation combined with single aggregate imaging to study the structural properties of the isolated aggregates. This aggregation kinetic independent method allowed me to compare the properties of fluorescently labelled and unlabelled Aβ42 and characterize the size dependent properties of aggregates in a single experiment. Since I could measure the relative concentration of different size aggregates it was also possible to compare the properties of single aggregates of different sizes. I then used biological assays to examine the ability of aggregates to permeabilise membranes resulting in the entry of calcium ions, and their ability to induce TNFα production in microglia cells. Both processes are thought to play key roles in the development of AD. I found that small soluble oligomers are most potent at inducing Ca2+ influx, whereas longer protofilaments are the most potent inducers of TNFα production. My results suggest that the mechanism by which aggregates damage cells changes as aggregation proceeds, as longer aggregates with different structures are formed. Protofilaments with a diameter of 1 nm or less have a structure that could make them particularly potent at causing the signalling of toll-like receptors, providing a molecular basis for their ability to induce TNFα production.

Des techniques variées de visualisation de molécules d’intérêt sur cellules vivantes ou fixées ont permis de suivre leur synthèse, localisation, dégradation et autres activités. Dans cette étude, nous avons développé deux outils de fluorescence pour étudier la synthèse des protéines sur bactéries vivantes. Le premier décrit l’utilisation du système Spinach pour l’imagerie du ribosome. Cette approche diffère des méthodes conventionnelles qui utilisent des protéines fluorescentes puisque l’ARN ribosomal 16S contient un aptamère qui rend fluorescent un composé fluorogène. Une étude comparative de la performance de différents aptamères Spinach a été réalisée. Un deuxième outil se focalise sur l’accumulation d’un antibiotique de la famille des aminoglycosides (ligand du ribosome) conjugué à un fluorophore. Ce nouveau conjugué, qui a conservé son activité bactéricide permet pour la première fois de visualiser l’accumulation de l’antibiotique sur bactérie vivante. Cela permet une analyse au niveau de la cellule unique d’une population bactérienne exposée à l’antibiotique. Nous avons également obtenu des données sur la localisation de l’antibiotique une fois qu’il a pénétré dans la bactérie à une résolution inégalée par microscopie super-résolutive. Nous espérons que ces deux méthodes vont maintenant permettre une meilleure compréhension de la synthèse des protéines et fournir une vue nouvelle de la pénétration des antibiotiques dans les bactéries pour y produire leur action bactéricide. / Various visualizing techniques have previously enabled monitoring the fate of molecules of interest: their expression, localization, degradation and other activities in live or fixed cells. In this study, we have developed two fluorescent tools to study protein synthesis in live bacterial cell. The first one describes the application of Spinach system to ribosomes imaging. This is different from conventional methods (that use fluorescent proteins) in that 16S rRNA contains an inserted RNA aptamer that elicits fluorescence of a fluorogenic compound. A comparative study of the performance of different Spinach aptamers was performed here. A second system focuses on the uptake of a fluorescently labeled ligand of the ribosome, an antibiotic of the class of aminoglycosides. This novel conjugate, which kept its bactericidal activity allows for the first time imaging of aminoglycoside uptake on live bacteria. This opened the door to a single cell analysis of bacterial cell populations. We also obtained data about the localization of the antibiotic once inside the bacteria to an unprecedented resolution using super resolution microscopy. We hope that both of these methods will contribute to a better understanding of protein synthesis as well as provide a novel view on the way antibiotics penetrate into cells and perform their bactericidal action.

Ce travail de thèse concerne l'amélioration du pouvoir de résolution de la microscopie optique en champ lointain. Nous avons développé des techniques qui tirent profit de la relation liant le champ électromagnétique émis par un objet à l’éclairement utilisé. En utilisant plusieurs images obtenues pour différents éclairements, et à l’aide d’un algorithme d'inversion approprié, il est possible d'accéder à des fréquences spatiales de l'objet habituellement filtrées par le microscope.Ce concept est d’abord appliqué à une technique de microscopie cohérente : la tomographique optique de diffraction. Elle permet d’obtenir numériquement une carte quantitative de la permittivité diélectrique de l'objet, avec une résolution supérieure à celle d'un microscope classique, à partir de plusieurs hologrammes de l'échantillon. Dans ce cadre, nous montrons que le phénomène de diffusion multiple permet d’atteindre des résolutions encore plus spectaculaires s’il est pris en compte. Nous étudions ensuite la microscopie de fluorescence par éclairement structuré, que nous proposons d’améliorer de deux manières différentes. Dans la première, nous utilisons un algorithme d’inversion capable de retrouver simultanément la densité de fluorescence et les éclairements utilisés. Grâce à celui-ci, nous pouvons remplacer l’illumination périodique et contrôlée généralement utilisée, par des speckles aléatoires formés avec un montage remarquablement simple. Nous montrons expérimentalement l'efficacité de cette approche. Dans un second temps, nous proposons de remplacer la lamelle de verre sur laquelle est repose l’échantillon par un réseau diélectrique nanométrique. Celui-ci crée à sa surface une grille de lumière de période inférieure à la limite de diffraction, ce qui permet d’améliorer d’avantage la résolution finale de l’image reconstruite. Nous détaillons la conception, la fabrication et la caractérisation expérimentale de ce substrat nanostructuré. / This PhD work focuses on the resolution improvement of far-field optical microscopy. We have studied and developed different techniques that take advantage of the relationship between the sample, the illumination and the diffracted (or emitted) field, in order to increase final band-pass of the image beyond that imposed by the diffraction phenomenon. In In these approaches, several images of the same sample are recorded under different illuminations. An inversion algorithm in then used to reconstruct a super-resolved map of the sample from the set of measurements.This concept is first applied to coherent microscopy. In tomographic diffraction microscopy, many holograms of the same unstained sample are obtained under various incidences, then used to numerically reconstruct a quantitative map of permittivity of the sample. The resolution is usually better than that of classical wide-field microscopy. We show theoretically and experimentally that, far from being a drawback, the presence of multiple scattering within the sample can, if properly accounted for, lead a to an even better resolution.We then study structured illumination fluorescence microscopy. We present two different ways for improving this method. The first one takes advantage of an inversion algorithm, which is able to retrieve the fluorescence density without knowing the illumination patterns. This algorithm permits one to replace the periodic light pattern classically used in structured illumination microscopy by unknown random speckle patterns. The implementation of the technique is thus considerably simplified while the resolution improvement remains. In the second approach, we propose to replace the coverslip on which the sample usually lays, by a sub-lambda grating. The latter is used to form, in near field, a light grid with sub-diffraction period that is able to probe the finest details of the sample. The design, fabrication and optical characterization of this key structure are detailed.

Num cenário em que dispositivos de aquisição de imagens e vídeo possuem recursos limitados ou as imagens disponíveis não possuem boa qualidade, as técnicas de super-resolução (SR) apresentam uma excelente alternativa para melhorar a qualidade das imagens. Nesta tese é apresentada uma proposta para super-resolução de imagem única que combina os benefícios da interpolação no domínio da transformada DCT e a eficiência dos métodos de reconstrução baseados no conceito de representação esparsa de sinais. A proposta busca aproveitar as melhorias já alcançadas na qualidade e eficiência computacional dos principais algoritmos de super-resolução existentes. O método de super-resolução proposto implementa algumas melhorias nas etapas de treinamento e reconstrução da imagem final. Na etapa de treinamento foi incluída uma nova etapa de extração de características utilizando técnicas de aguçamento por máscara de nitidez e construção de um novo dicionário. Esta estratégia busca extrair mais informações estruturais dos fragmentos de baixa e alta resolução do conjunto de treinamento e ao mesmo tempo reduzir o tamanho dos dicionários. Outra importante contribuição foi a inclusão de um processo iterativo e escalonável no algoritmo, reinserindo no conjunto de treinamento e na etapa de reconstrução, uma imagem de alta resolução obtida numa primeira iteração. Esta solução possibilitou uma melhora na qualidade da imagem de alta resolução final utilizando poucas imagens no conjunto de treinamento. As simulações computacionais demonstraram a capacidade do método proposto em produzir imagens com qualidade e com tempo computacional reduzido. / In a scenario in which the acquisition systems have limited resources or available images do not have good quality, the super-resolution (SR) techniques have become an excellent alternative for improving the image quality. In this thesis, we propose a single-image super-resolution (SR) method that combines the benefits of the DCT interpolation and efficiency of sparse representation method for image reconstruction. Also, the proposed method seeks to take advantage of the improvements already achieved in quality and computational efficiency of the existing SR algorithms. The proposed method implements some improvements in the dictionary training and the reconstruction process. A new dictionary was built by using an unsharp mask technique to characteristics extraction. Simultaneously, this strategy aim to extract more structural information of the low resolution and high resolution patches and reduce the dictionaries size. Another important contribution was the inclusion of an iterative and scalable process by reinserting the HR image obtained of first iteration. This solution aim to improve the quality of the final HR image using a few images in the training set. The results have demonstrated the ability of the proposed method to produce high quality images with reduced computational time.

Current single molecule localisation microscopy methods allow for multicolour imaging of macromolecules in cells, and for a degree quantification on molecule numbers in one colour. However, that has not yet been an attempt to develop tools capable of quantitative imaging with multiple colours in cells. This work addressed this challenge by designing linker peptides with chemospecific groups to allow attachment of activator and emitter dyes for STORM imaging, and a targeting module. The design ensured a stoichiometric ratio of targeting module to activator and emitter dyes. Peptides with HaloTag ligands attached were labelled with various activator and emitter pairs and used to label HaloTag fusions of S. pombe and mouse embryonic stem cells. These peptides were found to bind non-specifically to various areas of both cell types, and did not localise to HaloTag protein, whereas controls did. Another peptide was also labelled with activator-emitter pairs and attached to expressed anti-GFP and ant-mCherry nanobodies via native chemical ligation. The labelled anti-GFP nanobody was to demonstrate ensemble and single molecule imaging in S. pombe, as well as characterisation on single molecule surfaces in comparison to a conventional randomly labelled antibody. The stoichiometrically labelled nanobody had a more consistent number of photons detected per localisation, number of localisation per molecule and number of blinks per molecule, which implied that it could be more useful than randomly labelled nanobodies for counting experiments. It was also shown to be capable of specific laser activation for STORM imaging with both an Alexa405Cy5 and Cy3Cy5 pairs. These anti-GFP and anti-mCherry nanobodies and peptide linker are new tools for both counting and multicolour imaging in super-resolution, which could be widely applied to constructs that are already tagged with GFP or mCherry.

This work explores if combining information from multiple Magnetic Resonance Imaging (MRI) modalities provides improved interpretation of brain biological architecture as each MR modality can reveal different characteristics of underlying anatomical structures. Structural MRI provides a means for high-resolution quantitative study of brain morphometry. Diffusion-weighted MR imaging (DWI) allows for low-resolution modeling of diffusivity properties of water molecules. Structural and diffusion-weighted MRI modalities are commonly used for monitoring the biological architecture of the brain in normal development or neurodegenerative disease processes. Structural MRI provides an overall map of brain tissue organization that is useful for identifying distinct anatomical boundaries that define gross organization of the brain. DWI models provide a reflection of the micro-structure of white matter (WM), thereby providing insightful information for measuring localized tissue properties or for generating maps of brain connectivity. Multispectral information from different structural MR modalities can lead to better delineation of anatomical boundaries, but careful considerations should be taken to deal with increased partial volume effects (PVE) when input modalities are provided in different spatial resolutions. Interpretation of diffusion-weighted MRI is strongly limited by its relatively low spatial resolution. PVE's are an inherent consequence of the limited spatial resolution in low-resolution images like DWI. This work develops novel methods to enhance tissue classification by addressing challenges of partial volume effects encountered from multi-modal data that are provided in different spatial resolutions. Additionally, this project addresses PVE in low-resolution DWI scans by introducing a novel super-resolution reconstruction approach that uses prior information from multi-modal structural MR images provided in higher spatial resolution. The major contributions of this work include: 1) Enhancing multi-modal tissue classification by addressing increased PVE when multispectral information come from different spatial resolutions. A novel method was introduced to find pure spatial samples that are not affected by partial volume composition. Once detecting pure samples, we can safely integrate multi-modal information in training/initialization of the classifier for an enhanced segmentation quality. Our method operates in physical spatial domain and is not limited by the constraints of voxel lattice spaces of different input modalities. 2) Enhancing the spatial resolution of DWI scans by introducing a novel method for super-resolution reconstruction of diffusion-weighted imaging data using high biological-resolution information provided by structural MRI data such that the voxel values at tissue boundaries of the reconstructed DWI image will be in agreement with the actual anatomical definitions of morphological data. We used 2D phantom data and 3D simulated multi-modal MR scans for quantitative evaluation of introduced tissue classification approach. The phantom study result demonstrates that the segmentation error rate is reduced when training samples were selected only from the pure samples. Quantitative results using Dice index from 3D simulated MR scans proves that the multi-modal segmentation quality with low-resolution second modality can approach the accuracy of high-resolution multi-modal segmentation when pure samples are incorporated in the training of classifier. We used high-resolution DWI from Human Connectome Project (HCP) as a gold standard for super-resolution reconstruction evaluation to measure the effectiveness of our method to recover high-resolution extrapolations from low-resolution DWI data using three evaluation approaches consisting of brain tractography, rotationally invariant scalars and tensor properties. Our validation demonstrates a significant improvement in the performance of developed approach in providing accurate assessment of brain connectivity and recovering the high-resolution rotationally invariant scalars (RIS) and tensor property measurements when our approach was compared with two common methods in the literature. The novel methods of this work provide important improvements in tools that assist with improving interpretation of brain biological architecture. We demonstrate an increased sensitivity for volumetric and diffusion measures commonly used in clinical trials to advance our understanding of both normal development and disease induced degeneration. The improved sensitivity may lead to a substantial decrease in the necessary sample size required to demonstrate statistical significance and thereby may reduce the cost of future studies or may allow more clinical and observational trials to be performed in parallel.

Depuis quelques temps, les physiciens théoriciens de la matière condensée sont confrontés à un problème majeur : la puissance de calcul nécessaire pour simuler numériquement et étudier certains systèmes à N corps est insuffisante. Comme le contrôle et l’utilisation des systèmes d’atomes ultra-froids se sont développés de manière importante,principalement durant les deux dernières décennies, nous sommes peut-être en mesure d eproposer une solution alternative : utiliser des atomes ultra-froids piégés dans des réseaux optiques en tant que simulateur quantique. En effet, la physique des électrons se déplaçant sur la structure cristalline d’un solide, ainsi que celle des atomes piégés dans des réseaux optiques, sont toutes les deux décrites par le même modèle de Fermi-Hubbard, qui est une présentation simplifiée du comportement des fermions sur un réseau périodique. Les simulateurs quantiques peuvent donc simuler des propriétés électriques des matériaux, telle sque la conductivité ou le comportement isolant, et potentiellement aussi des propriété smagnétiques telles que l’ordre antiferromagnétique.L’expérience AUFRONS, sur laquelle j’ai travaillé pendant mon doctorat, a pour but d’étudie rla physique des fermions fortement corrélés, avec un simulateur quantique basé sur l’utilisation d’atomes ultra-froids de rubidium 87 et de potassium 40, piégés dans le potentiel nanostructuré des réseaux optiques bidimensionnels, générés en champ proche. Pour détecter la distribution atomique à d’aussi courtes distances, nous avons développé une technique d’imagerie novatrice, qui nous permettra de contourner la limite de diffraction. Une fois terminé, notre système d’imagerie pourrait potentiellement détecter et identifier des sites individuels du réseau optique sub-longueur d’onde.Dans ce manuscrit, je décris le travail que j’ai effectué pour construire l’expérience AUFRONS,ainsi que l’étude de faisabilité que j’ai réalisée pour la technique d’imagerie à super-résolution. / For some time now, theoretical physicists in condensed matter face a majorproblem: the computing power needed to numerically simulate and study some interactingmany-body systems is insufficient. As the control and use of ultracold atomic systems hasexperimented a significant development in recent years, an alternative to this problem is to usecold atoms trapped in optical lattices as a quantum simulator. Indeed, the physics of electronsmoving on a crystalline structure of a solid, and the one of trapped atoms in optical lattices areboth described by the same model, the Fermi-Hubbard model, which is a simplifiedrepresentation of fermions moving on a periodic lattice. The quantum simulators can thusreproduce the electrical properties of materials such as conductivity or insulating behavior, andpotentially also the magnetic ones such as antiferromagnetism.The AUFRONS experiment, in which I worked during my PhD, aims at building a quantumsimulator based on cooled atoms of 87Rb and 40K trapped in near field nanostructured opticalpotentials. In order to detect the atom distribution at such small distances, we have developedan innovative imaging technique for getting around the diffraction limit. This imaging systemcould potentially allow us to detect single-site trapped atoms in a sub-wavelength lattice.In this thesis, I introduce the work I have done for building the AUFRONS experiment, as wellas the feasability study that I did for the super-resolution imaging technique.