Dissertations / Theses: 'Automated cell to signal'

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Taylor, Harriet Beverly. "Functional analysis of zebrafish innate immune responses to inflammatory signals." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4825.

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Injury, infection and tissue malfunction are triggers of inflammation which if not regulated may acquire new characteristics that result in pathological outcomes. Since innate immunity plays a key role in the resolution of acute inflammation knowledge of the regulation of this component of the host response is relevant to understanding processes in disease progression and therefore has potential clinical benefits. In this thesis I have applied zebrafish as a model organism to investigate the response of innate immune cells to qualitatively distinct inflammatory signals in the absence of adaptive immunity. Using a zebrafish embryo wound injury model I have investigated leukocyte migration profiles by in vivo imaging. In response to wound alone leukocytes migrated to the site of injury with predominantly random walk behaviour. However, the addition of lipopolysaccharide (LPS) enhanced recruitment and influenced the directionality of leukocyte migration to the wound. I demonstrate that leukocyte dynamic behaviour is also dependent on the location of the cells. The LPS enhanced directionality and reduced the random walk behaviour of the leukocytes, and these effects were ablated in the presence of the p38 mitogenactivated protein kinase (MAPK) specific inhibitor SB203580. Cytokine gene profiling in adult zebrafish leukocytes reveals that LPS can stimulate a pro-inflammatory response via the activation of p38 MAPK characteristic of mammalian innate immune responses. It is documented in mammalian innate immune cells that LPS can modulate Notch mediated signalling and thereby cell function. Using zebrafish with null mutations in Notch, which provide an unbiased in vivo model, I have investigated the influence of Notch signalling on leukocyte recruitment and demonstrate that migration to a wound injury is reduced. However, this effect is due to decreased cell numbers and not altered function as the Notch signalling inhibitor DAPT had no effect of recruitment to wound injury. The defect in myelomonocyte numbers was also present in adult zebrafish and this was partially compensated for by an increase in lymphocytes. The experimental results that I report here highlight zebrafish as a model 2 organism for studying the function and regulation of innate immunity. The unique optical translucency, which permits in vivo imaging of host responses in real-time, facilitates the analysis of the innate immune response to different inflammatory signals and immune modulators.

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O'Neill, Kieran. "Automated analysis of single cell leukemia data." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50867.

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Acute myeloid leukemia (AML) is a high grade malignancy of non-lymphoid cells of the hematopoietic system. AML is a heterogeneous disease, and numerous attempts have been made to risk-stratify AML so that appropriate treatment can be offered. Single cell analysis methods could provide insights into the biology of AML leading to risk-stratified and functionally tailored treatments and hence improved outcomes. Recent advances in flow cytometry allow the simultaneous measurement of up to 17 antibody markers per cell for up to millions of cells, and it is performed routinely during AML clinical workup. However, despite vast amounts of flow cytometry data being gathered, comprehensive, objective and automated studies of this data have not been undertaken. Another method, strand-seq, elucidates template strand inheritance in single cells, with a range of potential applications, none of which had been automated when this thesis work commenced. I have developed bioinformatic methods enabling research into AML using both these types of data. I present flowBin, a method for faithfully recombining multitube flow cytometry data. I present flowType-DP, a new version of flowType, able to process flow cytometry and other single cell data having more than 12 markers (including flowBin output). I demonstrate the application of flowBin to AML data, for digitally isolating abnormal cells, and classifying AML patients. I also use flowBin in conjunction with flowType to find cell types associated with clinically relevant gene mutations in AML. I present BAIT, a software package for accurately detecting sister chromatid exchanges in strand-seq data. I present functionality to place unbridged contigs in late-build genomes into their correct location, and have, with collaborators, published the corrected locations of more than half the unplaced contigs in the current build of the mouse genome. I present contiBAIT, a software package for assembling early-build genomes which consist entirely of unanchored, unbridged contigs. ContiBAIT has the potential to dramatically improve the quality of many model organism genomes at low cost. These developments enable rapid, automated, objective and reproducible deep profiling of AML flow cytometry data, subclonal cell analysis of AML cytogenetics, and improvements to model organisms used in AML research.
Science, Faculty of
Graduate

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Martin, Bailey-Van Kuren Michael. "Automated cell supervisory control for product disassembly." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/20158.

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Balraj, Navaneethakrishnan. "AUTOMATED ACCIDENT DETECTION IN INTERSECTIONS VIA DIGITAL AUDIO SIGNAL PROCESSING." MSSTATE, 2003. http://sun.library.msstate.edu/ETD-db/theses/available/etd-10212003-102715/.

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The aim of this thesis is to design a system for automated accident detection in intersections. The input to the system is a three-second audio signal. The system can be operated in two modes: two-class and multi-class. The output of the two-class system is a label of ?crash? or ?non-crash?. In the multi-class system, the output is the label of ?crash? or various non-crash incidents including ?pile drive?, ?brake?, and ?normal-traffic? sounds. The system designed has three main steps in processing the input audio signal. They are: feature extraction, feature optimization and classification. Five different methods of feature extraction are investigated and compared; they are based on the discrete wavelet transform, fast Fourier transform, discrete cosine transform, real cepstrum transform and Mel frequency cepstral transform. Linear discriminant analysis (LDA) is used to optimize the features obtained in the feature extraction stage by linearly combining the features using different weights. Three types of statistical classifiers are investigated and compared: the nearest neighbor, nearest mean, and maximum likelihood methods. Data collected from Jackson, MS and Starkville, MS and the crash signals obtained from Texas Transportation Institute crash test facility are used to train and test the designed system. The results showed that the wavelet based feature extraction method with LDA and maximum likelihood classifier is the optimum design. This wavelet-based system is computationally inexpensive compared to other methods. The system produced classification accuracies of 95% to 100% when the input signal has a signal-to-noise-ratio of at least 0 decibels. These results show that the system is capable of effectively classifying ?crash? or ?non-crash? on a given input audio signal.

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Sameeuddin, Sameeuddin. "Automated Ultrasonic Signal Classification of Carbon Fiber Reinforced Plastic Laminates." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1497.

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Carbon composites, particularly carbon fiber reinforced plastics (CFRPs) are increasingly being used in many commercial applications such as automobile, aerospace, and civil infrastructures. This increase in the demand of CFRPs has led the manufacturers to research for ways of early detection and classification of defects in CFRP. This thesis work discusses the implementation of a Hopfield neural network (HNN) to automatically detect and classify defects in CFRP by ultrasonic testing (UT). Three of the most common and critical defects found in CFRP, i.e. foreign object (FO) inclusion, impact damage (ID), and porosity, were the main focus of this research. These defects were engineered into three different CFRP panels during manufacturing and were provided by an outside supplier. These panels were inspected on a standard immersion ultrasonic testing system in pulse-echo mode. One hundred time-amplitude based ultrasonic A-scan signals were recorded from the defected areas of each of the panels. Additionally, a hundred ultrasonic A-scan signals were recorded for the defect-free region of the CFRP. Signal preprocessing in terms of signal alignment is a vital process in any classification procedure as unaligned signals are prone to bad classification accuracies. Therefore, the raw A-scan signals were start-point aligned prior to any classification using cross-correlation technique. This research also focused on developing a feature extraction technique that could be used in conjunction with the HNN to classify the UT signals with high classification accuracy. A feature extraction technique based on gating technique was developed which consisted of five features, namely mean value of the signal, standard deviation of the signal, peak-to-peak amplitude value of the front wall echo (FEW), peak-to-peak amplitude value of the back wall echo (BWE), and time of flight (TOF) between FWE and BWE of each signal. Four other feature extraction techniques based on mean value of the signal, standard deviation value of the signal, fast Fourier transform (FFT), and discrete wavelet transform (DWT) were also used for the comparison and validation of results obtained by the developed feature extraction technique. The 100 signals for each category were randomly partitioned into equal-sized training and testing data sets. The partitioning was repeated for 1000 iterations, to average the results and obtain a robust estimate of the classification performance. The classification of the signals was carried out by implementing two approaches. The first approach utilized a dichotomous classification between each defect type and the non-defected region. And the second approach utilized a 4-class classification in which the defect types and the non-defected signals were classified at the same time. The results of this research showed that the classification accuracies for the 2-class problem obtained through the developed feature extraction technique exceeded 99%, which were in agreement with the results of classification obtained through the four conventional feature extraction techniques. The results of the 4-class problem obtained through the developed feature extraction technique exceeded 96% classification accuracy. For direct comparison, the results obtained from the four conventional feature extraction techniques exceeded 99% classification accuracies. Based on the results obtained, it can be concluded that the developed feature extraction technique can be used in conjunction with HNN to successfully classify defects in CFRP. With few modifications, the developed technique can be implemented to classify other types of defects in CFRP and can be implemented in different applications.

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Bala, Divya Chandrakant. "Cell Phenotype Analyzer: Automated Techniques for Cell Phenotyping using Contactless Dielectrophoresis." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71428.

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Cancer is among the leading causes of death worldwide. In 2012, there were 14 million new cases and 8.2 million cancer-related deaths worldwide. The number of new cancer cases is expected rise to 22 million within the next two decades. Most chronic cancers cannot be cured. However, if the precise cancer cell type is diagnosed at an earlier, less aggressive stage then the chance of curing the disease increases with accurate drug delivery. This work is a humble contribution to the advancement of cancer research. This work delves into biological cell phenotyping under a dielectrophoresis setup using computer vision. Dielectrophoresis is a well-known phenomenon in which dielectric particles are subjected to a non-homogeneous electric field. This work is an analytical part of a larger proposed system replete with hardware, software and microfluidics integration to achieve cancer cell characterization, separation and enrichment using contactless dielectrophoresis. To analyze the cell morphology, various detection and tracking algorithms have been implemented and tested on a diverse dataset comprising cell-separation video sequences. Other related applications like cell-counting and cell-proximity detection have also been implemented. Performances were evaluated against ground truth using metrics like precision, recall and RMS cell-count error. A detection approach using difference of Gaussian and super-pixel algorithm gave the highest average F-measure of 0.745. A nearest neighbor tracker and Kalman tracking method gave the best overall tracking performance with an average F-measure of 0.95. This combination of detection and tracking methods proved to be best suited for this dataset. A graphical user interface to automate the experimentation process of the proposed system was also designed.
Master of Science

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Sundström, Magnus. "Signal Transduction in Mast Cell Migration." Doctoral thesis, Uppsala University, Department of Genetics and Pathology, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-1474.

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Mast cells are essential effector cells in the immune system as they release several inflammatory mediators. An accumulation of mast cells has been described in inflammatory conditions such as asthma and allergic rhinitis. Increased mast cell number, in the skin and other organs, is also a characteristic in mastocytosis, a disease without an effective treatment. One explanation for the increase in mast cell number is migration of mast cells in the tissue. In our studies we utilised mast cell lines, including HMC-1; cell lines transfected with the c-kit gene; and in vitro developed mast cells.

Our aim was to characterise, two variants of the HMC-1 cell line; the signalling pathways essential for mast cell migration towards TGF-β and SCF; and the mechanism regulating mast cell accumulation in mastocytosis.

Our results help to explain inconsistent findings regarding mast cell biology when HMC-1 cells have been used as a model system. The two variants, which we name HMC-1⁵⁶⁰ and HMC-1^{560, 816}, are used in different laboratories around the world. HMC-1⁵⁶⁰ and HMC-1^{560, 816} exhibited different characteristics regarding their karyotype, phenotype as well as their set of activating point mutations in the Kit receptor. Furthermore, divergent signalling pathways are of importance for mast cell migration towards TGF-β and SCF. The classical MAP kinase-signalling cascade was found to be of major relevance for TGF-β-induced migration. In contrast, this pathway had a modest impact on SCF-induced migration, which instead was highly dependent on p38 MAP kinase signalling. Finally, one mechanism for mast cell accumulation in mastocytosis appeared to be an activating point mutation in the gene for the Kit receptor. This mutation appeared to prone transfected cells and mast cell progenitors to a higher rate of migration towards SCF if compared with cells expressing wt Kit receptor.

In conclusion, our results show the importance of two different MAP kinase signalling pathways and mutations in the Kit receptor for mast cell migration induced by various types of stimuli. This knowledge helps us to understand the mechanism

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Lennartsson, Johan. "Stem Cell Factor Induced Signal Transduction." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2002. http://publications.uu.se/theses/91-554-5291-4/.

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Sundström, Magnus. "Signal transduction in mast cell migration /." Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2001. http://publications.uu.se/theses/91-554-5130-6/.

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Zou, Rui Ghosh Avijit. "Automated sensitivity analysis on spatio-temporal biochemical systems /." Philadelphia, Pa. : Drexel University, 2007. http://hdl.handle.net/1860/1565.

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Magnusson, Klas. "Cell tracking for automated analysis of timelapse microscopy." Thesis, KTH, Signalbehandling, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-53772.

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This document presents an algorithm to automatically perform two dimensional tracking of cells in in-vitro cultures. The developed software handles all the necessary data processing, from preprocessing the images to automaticallytracking the cells and it also provides an interface to manually correct the obtained cell trajectories and functions to analyze the data. The system is developed for, and tested on, muscle stem cells (MuSCs) but it can also be applied to other cell types that look and behave similarly. The software was used in a bio-medical study to investigate the effects on mouse MuSC fate caused by culturing the cells on substrates of different rigidities. In this study the software enabled important findings about cell behavior. The software is capable of handling automatic track initialization, false detections, adhering cells, death and cell division. These are functionalities that can all be problematic to achieve. Cell tracking is normally done manually, which is very labor intensive and limits the parameters that can be analyzed. Having reliable systems to analyze a wide range of cell types automatically would therefore greatly benefit research in cell biology. The software package described here was named the Baxter Algorithm after the Donald E. & Delia B. Baxter Foundation that funded it’s development.

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Fernyhough, Emma Nicole. "Automated segmentation of structures essential to cell movement." Thesis, University of Leeds, 2016. http://etheses.whiterose.ac.uk/13484/.

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The study of cells is not only a key field in modern science, but has been an important area of study for hundreds of years. Despite this there is still a lot left unknown. As technology has progressed, so has our ability to photograph and film cells, but much of the processing of these images is still carried out by hand. This is not only difficult and time consuming, but is subject to opinion and error, and often not exactly reproducible. We are wishing to automate the process of segmenting cells, in order to provide biologists with that data they require to learn more about cells and their movement. This should be done in a quantitative and reproducible way. Crawling cells, such as those studied for this research, often need to move around the host body, such as the human or other mammal, in order to assist with growth, prevent disease, or to cure damage. To do this they employ other structures which protrude from the cell body to aid their motility. They use very fine hair like features (filopodia) to detect their surrounding, penetrate other cells, and determine direction. They then use thin, flat membranes (lamellipodia) to adhere both at the front and rear of the cell to pull and push forward in the direction of movement. These features are often extremely difficult to see by eye, making automation of their segmentation an awkward task. To do this, we need to use not only the information in the individual frames of video, but also information gained over time such as their movement between the frames. We firstly pre-process the images using an automated technique to correct for lighting variations in the footage. Our method is not only extremely efficient and reliable but works equally on different sizes and shapes of cell as well as frames with differing degrees of background coverage, from only one or two small cells in a frame to where the majority of the image is covered. This shading correction method was also tested on non-cellular images taken using the same kind of microscopy to show that it is suitable for all images rather than just those being studied in this work. This pre-processing allows us to make a simple segmentation of the main cell bodies, which on its own is suitable for cells which do not contain other thin structures. Using the cell bodies obtained from our pre-processing technique we then find the thinner membranes which are attached to the cell. Despite being a fully automated method, this was more accurate in two out of our three sets of videos than the most popular segmentation program using manual setting of parameters for each video individually. We improved upon this initial segmentation by incorporating the movement of the cell over time, using an iterative technique to compare the outcome of sequential frames. The result was that our segmentation was better than the manually parametrised segmentation program for every video. We then wished to find the hair like extensions and again used the information from our pre-processing stage. As these are so difficult to detect by eye we used the information of the movement to create candidate regions where these were believed to be located. Although these were usually not straight, we were able to build up small line segments in the candidate regions to recreate the features and detect the direction. This allowed us to identify all regions with filopodia present, and to separate them in order to find the required information such as the number, the length, what kind of clusters they grew in and the location compared to the direction of movement. No other method has been found which is able to detect these or segment them separately from the cell.

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Razban, Ali. "Intelligent control of an automated adhesive dispensing cell." Thesis, Imperial College London, 1993. http://hdl.handle.net/10044/1/7246.

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Guo, Shuman. "A Novel Method for Automated Cell Image Selection." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/math_theses/119.

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Retinal pigment epithelium (RPE) is a key site of pathogenesis of age-related macular degeneration (AMD). A key first step toward developing statistical quantifications of RPE morphology is image analysis of RPE flatmount. This thesis work aims to facilitate image analysis by developing a procedure for automated selecting regions with biological information from flatmount images. Our new approach, based on clustering analysis, can extract informative regions from a typical flatmount image of a mouse eye within one minute, a three order magnitude time saving improvement from the current manual procedure. This method is already contributing to the image analysis of RPE flatmounts.

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Lambert, Russell. "Signal processing and shielding of ultrasonic echoes for automated welding control." Thesis, Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/16000.

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McAllister, Christine Joan. "Automated design of high performance digital filter chips." Thesis, Queen's University Belfast, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318797.

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Valdimarsdóttir, Gudrun. "TGFβ Signal Transduction in Endothelial Cells." Doctoral thesis, Uppsala University, Ludwig Institute for Cancer Research, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4284.

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Transforming growth factor β (TGFβ) is a multifunctional cytokine that is involved in many biological effects, such as proliferation, migration, differentiation and cell survival. TGFβ regulates cellular responses by binding to a heteromeric complex of type I and type II serine/threonine kinase receptors. The type I receptor, termed activin receptor-like kinase (ALK), acts downstream of the type II receptor and propagates the signal to the nucleus by phosphorylating receptor regulated Smads (R-Smads). The activated R-Smads can associate with the common partner Smad, Smad4, and this complex translocates to the nucleus where it participates in transcriptional regulation of target genes. TGFβ plays an important role in vascular morphogenesis. The aim of this study was to obtain more insight into the mechanisms by which TGFβ can act as an inhibitor or stimulator of angiogenesis Our findings show that in endothelial cells (ECs), TGFβ can activate two distinct type I receptor/Smad signalling pathways with opposite cellular responses. In most cell types, TGFβ signals via the TGFβ type I receptor, ALK5. However, ECs express a predominant endothelial type I receptor, named ALK1. Whereas the TGFβ/ALK1 signalling leads to activation, the TGFβ/ALK5 pathway results in an inhibition of the activation state. This suggests that TGFβ regulates the activation state of the endothelium via a fine balance between these two pathways. We identified genes that are specifically induced by TGFβ mediated ALK1 or ALK5 activation. Id1 was found to be the target gene of the ALK1/Smad1/5 pathway while induction of plasminogen activator inhibitor-1 was activated only by ALK5/Smad2 pathway. Furthermore, ALK1 activated ECs are highly invasive but this property is lost if Id1 expression is specifically knocked-down. ECs invasiveness is highly dependent on αv integrin binding to its extracellular matrix (ECM) protein partner and the invasion requires proteolytic cleavage of the ECM by metalloproteases (MMPs). Hence, TGFβ/ALK1/Id1 pathway may promote invasion by modulating the expression or activity of integrins and MMPs that are well known components of the ECM. Timing and duration of TGFβ signalling are important specificity determinants for its effect on cellular behaviour. After binding to ALK1, TGFβ induces a transient phosphorylation of Smad1/5 but a stable phosphorylation of Smad2 via ALK5. Our studies indicate that Smad7 is potently induced by ALK1 signalling and may recruit a PP1α/TIMAP phosphatase complex to ALK1 to dephosphorylate the receptor and thereby turning off phosphorylation resulting in a temporal activation of TGFβ/ALK1-induced Smad1/5 pathway. This mechanism enables an efficient and tightly temporally controlled activation resulting in the dominance of ALK5 upon prolonged exposure to TGFβ. Bone morphogenetic protein (BMP) is a member of the TGFβ superfamily and signals through Smad1/5. The BMP/Smad1/5 pathway was found to potently activate the endothelium. Id1 was identified as an important BMP target gene in ECs and was sufficient and necessary for BMP-induced EC migration. These studies not only provide new insights into possible molecular mechanisms that underlie activation and quiescence of ECs during physiological angiogenesis but may also explain the vascular phenotypes observed in mice and humans with perturbed TGFβ signalling pathways.

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Gong, Yunchen 1965. "Analyses of alternative cell signal transduction pathways." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85552.

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Living cells keep sensing the changes in their environments, mostly, via cell surface receptors for different ligands. Attachment-dependent cells are sensitive to alterations in extracellular matrix (ECM). ECM is not only required for cell survival, but also prerequisite for epidermal growth factor (EGF) to stimulate cell proliferation. The receptors for the majority of ECM components are integrins and the receptor for EGF is EGF receptor (EGFR). When bound by their ligands, integrins and EGFR induce signal transduction cascades composed of alternative pathways. A quantitative assessment of relative contributions of alternative pathways to one final cell signaling will help understand designing principles of the network. Unfortunately, a methodology for such assessment is still not available, partly because of lack of relatively mature mathematical models. On the other hand, in most biochemical cascades, existence of alternative pathways increases the complexity and thus the robustness of networks. The relationships between the topology and robustness of large-scale biochemical networks have been studied intensively recently. In small-scale networks, while feedback has been revealed as an important contributor for adaptation and robustness, the quantitative correlation between the topology/pathway redundancy of small networks and their robustness remains unknown.
In this thesis, apoptosis of bovine mammary gland epithelial cells was demonstrated to be induced when fibronectin, one of the major components of ECM, was degraded by overexpressed tPA via two potential ways: deprivation of attachment and the effects of fibronectin fragments. Secondly, a mathematical model for EGFR activation of the MAPK cascade, in which alternative pathways exist, was explored and it was found that the Shc-dependent pathway is both redundant and dominant. We hypothesize that the Shc-dependent pathway is important for EGFR to compete with other receptors, which need Shc to transduce cell signals; and this pathway is not aimed to increase the robustness of the EGFR cascade. Finally, for the general importance of alternative pathways to the network topology and robustness, several concepts have been proposed to decompose and quantitatively characterize the networks. We demonstrate that the pathnet score is a better assessment for robustness than the molecular connectivity.

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Grundström, Tobias. "Automated Measurements of Liver Fat Using Machine Learning." Thesis, Linköpings universitet, Datorseende, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151286.

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The purpose of the thesis was to investigate the possibility of using machine learn-ing for automation of liver fat measurements in fat-water magnetic resonancei maging (MRI). The thesis presents methods for texture based liver classificationand Proton Density Fat Fraction (PDFF) regression using multi-layer perceptrons utilizing 2D and 3D textural image features. The first proposed method was a data classification method with the goal to distinguish between suitable andunsuitable regions to measure PDFF in. The second proposed method was a combined classification and regression method where the classification distinguishes between liver and non-liver tissue. The goal of the regression model was to predict the difference d = pdff mean − pdff ROI between the manual ground truth mean and the fat fraction of the active Region of Interest (ROI).Tests were performed on varying sizes of Image Feature Regions (froi) and combinations of image features on both of the proposed methods. The tests showed that 3D measurements using image features from discrete wavelet transforms produced measurements similar to the manual fat measurements. The first method resulted in lower relative errors while the second method had a higher method agreement compared to manual measurements.

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Ansin, Rasmus, and Didrik Lundberg. "Automated Inference of Excitable Cell Models as Hybrid Automata." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-154065.

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In this paper, we explore from an experimental point of view the possibilities and limitations of the new HYCGE learning algorithm for hybrid automata. As an example of a practical application, we study the algorithm’s performance on learning the behaviour of the action potential in excitable cells, specifically the Hodgkin-Huxley model of a squid giant axon, the Luo-Rudy model of a guinea pig ventricular cell, and the Entcheva model of a neonatal rat ventricular cell. The validity and accuracy of the algorithm is also visualized through graphical means.
I denna uppsats undersöker vi från en experimentell synvinkel möjligheter och begränsningar i den nya inlärningsalgoritmen HYCGE för hybridautomater. Som ett exempel på en praktisk tillämpning, studerar vi algoritmens förmåga att lära sig aktionspotentialens beteende i retbara celler, specifikt Hodgkin-Huxleymodellen av en bläckfisks jätteaxon, Luo-Rudymodellen av en ventrikulärcell i marsvin, och Entchevas modell av en ventrikulär cell i nyfödd råtta .Giltigheten och noggrannheten hos algoritmen visualiseras även genom grafiskamedel.

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Ait-Boudaoud, Djamel. "Novel cell architectures for systolic signal processing arrays." Thesis, University of Nottingham, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334976.

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Interdonato, Giovanni. "Signal Processing Aspects of Cell-Free Massive MIMO." Licentiate thesis, Linköpings universitet, Kommunikationssystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151026.

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The fifth generation of mobile communication systems (5G) promises unprecedented levels of connectivity and quality of service (QoS) to satisfy the incessant growth in the number of mobile smart devices and the huge increase in data demand. One of the primary ways 5G network technology will be accomplished is through network densification, namely increasing the number of antennas per site and deploying smaller and smaller cells. Massive MIMO, where MIMO stands for multiple-input multiple-output, is widely expected to be a key enabler of 5G. This technology leverages an aggressive spatial multiplexing, from using a large number of transmitting/receiving antennas, to multiply the capacity of a wireless channel. A massive MIMO base station (BS) is equipped with a large number of antennas, much larger than the number of active users. The users are coherently served by all the antennas, in the same time-frequency resources but separated in the spatial domain by receiving very directive signals. By supporting such a highly spatially-focused transmission (precoding), massive MIMO provides higher spectral and energy efficiency, and reduces the inter-cell interference compared to existing mobile systems. The inter-cell interference is however becoming the major bottleneck as we densify the networks. It cannot be removed as long as we rely on a network-centric implementation, since the inter-cell interference concept is inherent to the cellular paradigm. Cell-free massive MIMO refers to a massive MIMO system where the BS antennas, herein referred to as access points (APs), are geographically spread out. The APs are connected, through a fronthaul network, to a central processing unit (CPU) which is responsible for coordinating the coherent joint transmission. Such a distributed architecture provides additional macro-diversity, and the co-processing at multiple APs entirely suppresses the inter-cell interference. Each user is surrounded by serving APs and experiences no cell boundaries. This user-centric approach, combined with the system scalability that characterizes the massive MIMO design, constitutes a paradigm shift compared to the conventional centralized and distributed wireless communication systems. On the other hand, such a distributed system requires higher capacity of back/front-haul connections, and the signal co-processing increases the signaling overhead. In this thesis, we focus on some signal processing aspects of cell-free massive MIMO. More specifically, we firstly investigate if the downlink channel estimation, via downlink pilots, brings gains to cell-free massive MIMO or the statistical channel state information (CSI) knowledge at the users is enough to reliably perform data decoding, as in conventional co-located massive MIMO. Allocating downlink pilots is costly resource-wise, thus we also propose resource saving-oriented strategies for downlink pilot assignment. Secondly, we study further fully distributed and scalable precoding schemes in order to outperform cell-free massive MIMO in its canonical form, which consists in single-antenna APs implementing conjugate beamforming (also known as maximum ratio transmission).

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Yeroshenko, O. A., and I. V. Prasol. "Automated determination of the parameters electric miographic signalsfor diagnostics and rehabilitation." Thesis, ХНУРЕ, 2018. http://openarchive.nure.ua/handle/document/7609.

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Automated systems for measuring and processing medical and biological information, using modern software, significantly expand the diagnostic capabilities of modern medicine. The method makes it possible to increase the informative value of diagnosis of the neuromuscular apparatus of man by matching the parameters of the electrical stimulation signal with the physiological characteristics of the stimulated muscle.

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Stefansson, Anne. "Mechanisms of Integrin Signal Transduction." Doctoral thesis, Uppsala University, Department of Medical Biochemistry and Microbiology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8221.

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Integrins are a protein family of cell surface receptors, expressed in all cell types in the human body, except the red blood cells. Besides their importance in mediating physical connections with the surrounding environment, the integrin family members are also vital signalling mediators. They have no intrinsic kinase activity; instead the signals are transduced through conformational changes.

In this thesis, work is presented which is focused on molecular mechanisms of integrin signal transduction. The signal transduction was first studied from a structural point of view, determining the transmembrane domain borders of a few selected integrin family members and ruling out a signalling model involving a “piston-like” movement.

Then, downstream signalling events involved in the beta1 integrin-induced activation of Akt via the PI3kinase family were characterized. Our results identify a novel pathway for PI3K/Akt activation by beta1 integrins, which is independent of focal adhesion kinase (FAK), Src and EGF receptor. Furthermore, both beta1 integrins and EGF receptors induced phosphorylation of Akt at the regulatory sites Thr308 and Ser473, but only EGF receptor stimulation induced tyrosine phosphorylation of Akt.

Finally, signals from beta1 integrins underlying the morphologic changes during cell spreading were studied. A rapid integrin-induced cell spreading dependent on actin polymerisation was observed by using total internal reflection fluorescence (TIRF) microscopy. This integrin-induced actin polymerisation was shown to be dependent on PI3K p110alpha catalytic subunit and to involve the conserved Lys756 in the beta1-integrin membrane proximal part.

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Settipalli, Praveen. "AUTOMATED CLASSIFICATION OF POWER QUALITY DISTURBANCES USING SIGNAL PROCESSING TECHNIQUES AND NEURAL NETWORKS." UKnowledge, 2007. http://uknowledge.uky.edu/gradschool_theses/430.

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This thesis focuses on simulating, detecting, localizing and classifying the power quality disturbances using advanced signal processing techniques and neural networks. Primarily discrete wavelet and Fourier transforms are used for feature extraction, and classification is achieved by using neural network algorithms. The proposed feature vector consists of a combination of features computed using multi resolution analysis and discrete Fourier transform. The proposed feature vectors exploit the benefits of having both time and frequency domain information simultaneously. Two different classification algorithms based on Feed forward neural network and adaptive resonance theory neural networks are proposed for classification. This thesis demonstrates that the proposed methodology achieves a good computational and error classification efficiency rate.

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Randolph, Tyler W. "Development of automated method of optimizing strength of signal received by laser interferometer." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29686.

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Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Ume, I. Charles; Committee Member: Mayor, J. Rhett; Committee Member: Sadegh, Nader. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Mickey, Katherine Morgan. "Cell-cell interactions and the specification of cell fates during C. elegans embryogenesis /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/5043.

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Zhang, Hao. "T cell antigen receptor binding and initial signal transduction." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669994.

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Choudhuri, Kaushik. "The mechanism of T cell receptor-mediated signal transduction." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433379.

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Noble, Jane Mary. "Cell membrane dynamics and signal transduction in human ageing." Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324872.

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Ellison, Cara Jane. "Sphingomyelin as a danger signal in cell-autonomous immunity." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/267993.

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Individual cells employ mechanisms of cell-autonomous immunity to defend their cytosol against bacterial invasion. One such mechanism involves indirect detection of the pathogen through recognition of pathogen-induced disturbances causing the appearance of specific host molecules in an abnormal location. For example, glycans, which are located on the extracellular leaflet of the plasma membrane under homeostatic conditions, become hidden inside bacteria-containing vacuoles (BCVs) during bacterial entry into the cell. Upon BCV rupture, glycans become exposed to the cytosol where they act as a danger signal and are detected by the cytosolic danger receptor, Galectin 8. My research reveals that sphingomyelin, a host lipid predominantly located on the outer leaflet of the plasma membrane, is exposed to the cytosol on damaged BCVs. I visualised the appearance of intracellular sphingomyelin by utilising Lysenin - a sphingomyelin-specific toxin from earthworms – as a cytosolic sphingomyelin reporter. Lysenin is recruited to BCVs in a sphingomyelin-dependent manner upon cytosolic entry of both Gram-negative and Gram-positive bacteria. Lysenin co-localises with Galectin 8 on a proportion of BCVs, indicating that sphingomyelin exposure occurs upon membrane damage. Moreover, I elucidated that sphingomyelin exposure occurs before glycan exposure on damaged BCVs indicating that BCV rupture may proceed through two stages: ‘minor’ and ‘major’ damage. My investigations into possible causes of vacuole rupture are on going. To identify endogenous cellular receptors for cytosol-exposed sphingomyelin, I established and executed an assay to compare enrichment of mammalian cell lysate proteins on liposomes containing or lacking sphingomyelin. Following mass spectrometry analysis, 49 candidate proteins were tested for recruitment to Salmonella. Twelve candidates were recruited to BCVs upon infection. Of these twelve, I pursued five candidates in greater detail due to their recruitment to Salmonella being either entirely unknown, or known, but via a non-sphingomyelin mechanism. Further analysis of one candidate in particular, TECPR1, elucidated that TECPR1 is recruited to Salmonella in a sphingomyelin-dependent manner and possesses sphingomyelin-specific binding properties in vitro. Therefore, my thesis research identifies TECPR1 as an endogenous sphingomyelin-binding protein.

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Humphrey, Peter Saah. "Signal transduction mechanisms for stem cell differentation into cardiomyocytes." Thesis, University of Hertfordshire, 2009. http://hdl.handle.net/2299/3760.

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Cardiovascular diseases are among the leading causes of death worldwide and particularly in the developed World. The search for new therapeutic approaches for improving the functions of the damaged heart is therefore a critical endeavour. Myocardial infarction, which can lead to heart failure, is associated with irreversible loss of functional cardiomyocytes. The loss of cardiomyocytes poses a major difficulty for treating the damaged heart since terminally differentiated cardiomyocytes have very limited regeneration potential. Currently, the only effective treatment for severe heart failure is heart transplantation but this option is limited by the acute shortage of donor hearts. The high incidence of heart diseases and the scarcity donor hearts underline the urgent need to find alternative therapeutic approaches for treating cardiovascular diseases. Pluripotent embryonic stem (ES) cells can differentiate into functional cardiomyocytes. Therefore the engraftment of ES cell-derived functional cardiomyocytes or cardiac progenitor cells into the damaged heart to regenerate healthy myocardial tissues may be used to treat damaged hearts. Stem cell-based therapy therefore holds a great potential as a very attractive alternative to heart transplant for treating heart failure and other cardiovascular diseases. A major obstacle to the realisation of stem cell-based therapy is the lack of donor cells and this in turn is due to the fact that, currently, the molecular mechanisms or the regulatory signal transduction mechanisms that are responsible for mediating ES cell differentiation into cardiomyocytes are not well understood. Overcoming this huge scientific challenge is absolutely necessary before the use of stem cell-derived cardiomyocytes to treat the damaged heart can become a reality. Therefore the aim of this thesis was to investigate the signal transduction pathways that are involved in the differentiation of stem cells into cardiomyocytes. The first objective was the establishment and use of cardiomyocyte differentiation models using H9c2 cells and P19 stem cells to accomplish the specific objectives of the thesis. The specific objectives of the thesis were, the investigation of the roles of (i) nitric oxide (ii) protein kinase C (PKC), (iii) p38 mitogen-activated protein kinase (p38 MAPK) (vi) phosphoinositide 3-kinase (PI3K) and (vi) nuclear factor-kappa B (NF-kB) signalling pathways in the differentiation of stem cells to cardiomyocytes and, more importantly, to identify where possible any points of convergence and potential cross-talk between pathways that may be critical for differentiation to occur. P19 cells were routinely cultured in alpha minimal essential medium (α-MEM) supplemented with 100 units/ml penicillin /100 μg/ml streptomycin and 10% foetal bovine serum (FBS). P19 cell differentiation was initiated by culturing the cells in microbiological plates in medium containing 0.8 % DMSO to form embryoid bodies (EB). This was followed by transfer of EBs to cell culture grade dishes after four days. H9c2 cells were cultured in Dulbecco’s Modified Eagle’s medium (DMEM) supplemented with 10% FBS. Differentiation was initiated by incubating the cells in medium containing 1% FBS. In both models, when drugs were employed, they were added to cells for one hour prior to initiating differentiation. Cell monolayers were monitored daily over a period of 12 or 14 days. H9c2 cells were monitored for morphological changes and P19 cells were monitored for beating cardiomyocytes. Lysates were generated in parallel for western blot analysis of changes in cardiac myosin heavy chain (MHC), ventricular myosin chain light chain 1(MLC-1v) or troponin I (cTnI) using specific monoclonal antibodies. H9c2 cells cultured in 1% serum underwent differentiation as shown by the timedependent formation of myotubes, accompanied by a parallel increase in expression of both MHC and MLC-1v. These changes were however not apparent until 4 to 6 days after growth arrest and increased with time, reaching a peak at day 12 to 14. P19 stem cells cultured in DMSO containing medium differentiated as shown by the timedependent appearance of beating cardiomyocytes and this was accompanied by the expression of cTnI. The differentiation of both P19 stem cells and H9c2 into cardiomyocytes was blocked by the PI3K inhibitor LY294002, PKC inhibitor BIM-I and the p38 MAPK inhibitor SB2035800. However when LY294002, BIM-I or SB2035800 were added after the initiation of DMSO-induced P19 stem cell differentiation, each inhibitor failed to block the cell differentiation into beating cardiomyocytes. The NF-kB activation inhibitor, CAPE, blocked H9c2 cell differentiation into cardiomyocytes. Fast nitric oxide releasing donors (SIN-1 and NOC-5) markedly delayed the onset of differentiation of H9c2 cells into cardiomyocytes while slow nitric oxide releasing donors (SNAP and NOC-18) were less effective in delaying the onset of differentiation or long term differentiation of H9c2 cells into cardiomyocytes. Akt (protein kinase B) is the key downstream target of PI3K. Our cross-talk data also showed that PKC inhibition and p38 MAPK inhibition respectively enhanced and reduced the activation of Akt, as determined by the phosphorylation of Akt at serine residue 473. In conclusion, PKC, PI3K, p38 MAPK and NF-kB are relevant for the differentiation of stem cells into cardiomyocytes. Our data also show that the PKC, PI3K and p38 MAPK signalling pathways are activated as very early events during the differentiation of stem cells into cardiomyocytes. Our data also suggest that PKC may negatively regulate Akt activation while p38 MAPK inhibition inhibits Akt activation. Our fast NO releasing donor data suggest that nitric oxide may negatively regulate H9c2 cell differentiation.

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Manyam, Venkata Narasimha. "Mixed-signal predistortion for small-cell 5G wireless nodes." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT015/document.

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Les stations de base à petite échelle (picocellules et femtocellules) seront un des leviers principaux qui permettront d'atteindre l'objectif 1000X, objectif fixé par les grands acteurs du domaine des télécommunications visant à augmenter la capacité des réseaux mobiles sans fil 5G d'un facteur 1000 par rapport aux réseaux 4G. Dans ce type de réseau, l'amplificateur de puissance (PA) est responsable de la majorité de la consommation de puissance de la station de base. Pour minimiser sa consommation de puissance, le PA est polarisé proche de sont point de compression mais avec l'augmentation des largeurs de bande, ce dernier subit des effets de mémoire accrus qui viennent s'ajouter aux problèmes classiques de non-linéarités. Les systèmes de prédistorsion numérique (DPD), et analogique/RF(ARFPD) peuvent être utilisés pour améliorer le compromis linéarité / efficacité des PAs. Cependant pour les pico-cellules et femto-cellules utilisées dans le standard 5G, les prédistorseurs conventionnels ne sont adaptés pour des raisons de complexité et de consommation de puissance.Le modèle "Memory Polynomilal" (MP) est l'un des modèles de prédistorsion les plus attractifs pour modéliser les PAs, fournissant des performances intéressantes avec peu de coefficients. Cependant, la précision de ce modèle se dégrade pour les signaux large bance. Pour palier ce problème, nous proposons un nouveau modèle, le FIR-MP qui combine un filtre FIR au modèle MP classique. Pour valider et quantifier la précision du modèle proposé, nous avons effectué des simulations avec un modèle extrait par mesure de l'amplificateur sur étagère ADL5606 (GaAs 1W HBT PA). Les résultats de ces simulations présentent des améliorations du taux de fuite des canaux adjacents (ACLR) de 7,2 dB et 15,6 dB, respectivement, pour des signaux à 20 MHz et 80 MHz par rapport au modèle MP classique. Le FIR-MP a été également synthétisé en technologie CMOS FDSOI 28 nm. Les résultats de la synthèse ont donné une puissance globale de 9,18 mW and 116,2 mW, respectivement, pour les signaux de 20 MHz and 80 MHz.Basé sur le modèle proposé de FIR-MP, une nouvelle approche à signaux mixtes pour linéariser les PAs a été aussi étudiée. En fait, le filtre numérique FIR améliore la performance de correction de la mémoire sans aucune expansion de la bande passante et la linéarisation en bande de base permet d'éviter l'utilisation de composants RF dans la linéariseur. Ainsi, les contraintes en bande passante requises pour le DAC, les filtres de reconstruction et les blocs RF de l'émetteur sont relâchées comparés aux techniques conventionnelles de linéarisation numériques et RF. Nous avons ainsi étudié l'impact des diverses non-idéalités en utilisant un signal modulé à 80 MHz afin de dériver les exigences pour la mise en œuvre du circuit. Les simulations ont montré qu'une résolution de 8 bits pour les coefficients et un SNR de 60 dB sont nécessaires pour atteindre un ACLR1 supérieur à 45 dBc. Ces résultats constituent un premier signe favorable dans l'optique d'une implémentation matérielle de la solution proposée, étape indispensable pour évaluer précisément sa consommation de puissance et sa complexité pour pouvoir la comparer à l'état de l'art des linéariseurs
Small-cell base stations (picocells and femtocells) handling high bandwidths (> 100 MHz) will play a vital role in realizing the 1000X network capacity objective of the future 5G wireless networks. Power Amplifier (PA) consumes the majority of the base station power, whose linearity comes at the cost of efficiency. With the increase in bandwidths, PA also suffers from increased memory effects. Digital predistortion (DPD) and analog RF predistortion (ARFPD) tries to solve the linearity/efficiency trade-off. In the context of 5G small-cell base stations, the use of conventional predistorters becomes prohibitively power-hungry.Memory polynomial (MP) model is one of the most attractive predistortion models, providing significant performance with very few coefficients. We propose a novel FIR memory polynomial (FIR-MP) model which significantly augments the performance of the conventional memory polynomial predistorter. Simulations with models extracted on ADL5606 which is a 1 W GaAs HBT PA show improvements in adjacent channel leakage ratio (ACLR) of 7.2 dB and 15.6 dB, respectively, for 20 MHz and 80 MHz signals, in comparison with MP predistorter. Digital implementation of the proposed FIR-MP model has been carried out in 28 nm FDSOI CMOS technology. With a fraction of the power and die area of that of the MP a huge improvement in ACLR is attained.An overall estimated power consumption of 9.18 mW and 116.2 mW, respectively, for 20 MHz and 80 MHz signals is obtained.Based on the proposed FIR-MP model a novel low-power mixed-signal approach to linearize RF power amplifiers (PAs) is presented. The digital FIR filter improves the memory correction performance without any bandwidth expansion and the MP predistorter in analog baseband provides superior linearization. MSPD avoids 5X bandwidth requirement for the DAC and reconstruction filters of the transmitter and the power-hungry RF components when compared to DPD and ARFPD, respectively.The impact of various non-idealities is simulated with ADL5606 (1 W GaAs HBT PA) MP PA model using 80 MHz modulated signal to derive the requirements for the integrated circuit implementation. A resolution of 8 bits for the coefficients and a signal path SNR of 60 dB is required to achieve ACLR1 above 45 dBc, with as little as 9 coefficients in the analog domain. Discussion on the potential circuit architectures of subsystems is provided. It results that an analog implementation is feasible. It will be worth in the future to continue the design of this architecture up to a silicon prototype to evaluate its performance and power consumption

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Sharma, Saurabh. "Automated pulsed signal reflectometer for time-domain RF-MEMS characterization in the UHF band." abstract and full text PDF (free order & download UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1460777.

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Sanders, Teresa H. "Multimodal assessment of Parkinson's disease using electrophysiology and automated motor scoring." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51970.

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A suite of signal processing algorithms designed for extracting information from brain electrophysiology and movement signals, along with new insights gained by applying these tools to understanding parkinsonism, were presented in this dissertation. The approach taken does not assume any particular stimulus, underlying activity, or synchronizing event, nor does it assume any particular encoding scheme. Instead, novel signal processing applications of complex continuous wavelet transforms, cross-frequency-coupling, feature selection, and canonical correlation were developed to discover the most significant electrophysiologic changes in the basal ganglia and cortex of parkinsonian rhesus monkeys and how these changes are related to the motor signs of parkinsonism. The resulting algorithms effectively characterize the severity of parkinsonism and, when combined with motor signal decoding algorithms, allow technology-assisted multi-modal grading of the primary pathological signs. Based on these results, parallel data collection algorithms were implemented in real-time embedded software and off-the-shelf hardware to develop a new system to facilitate monitoring of the severity of Parkinson's disease signs and symptoms in human patients. Off -line analysis of data collected with the system was subsequently shown to allow discrimination between normal and simulated parkinsonian conditions. The main contributions of the work were in three areas: 1) Evidence of the importance of optimally selecting multiple, non-redundant features for understanding neural information, 2) Discovery of signi ficant correlations between certain pathological motor signs and brain electrophysiology in different brain regions, and 3) Implementation and human subject testing of multi-modal monitoring technology.

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Tibbitt, Christopher Andrew. "The role of T cell receptor signal intensity in T helper 17 cell development." Thesis, University of Newcastle upon Tyne, 2015. http://hdl.handle.net/10443/2885.

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T-helper (Th) 17 cells are a subset of CD4+ T cells defined through the release of the cytokine interleukin-17a (IL-17a). Activation of these cells is critical for protection against some extracellular bacterial and fungal pathogens. However, a dysregulated Th17 response targeted against self is thought to play an important role in the immunopathology of a number of autoimmune conditions including Inflammatory Bowel Disease (IBD), Multiple Sclerosis (MS) or inflammatory arthritides. Further understanding of the mechanisms that influence the development of Th17 cells may aid future therapeutic targeting of these cells. Whilst the role of the cytokine milieu in Th cell polarisation is relatively well characterised, the degree of signalling through the TCR can also shape the form of the Th cell response. Both the density of antigenic peptide available and the affinity of the antigenic peptide for a particular TCR can contribute to the degree of TCR signalling. The hypothesis of this project was that TCR signal intensity could alter the development of Th17 cells from a naive precursor population. In particular, it was of interest to determine how citrullination of a putative TCR contact amino acid in an antigenic peptide could alter the Th cell response observed. The 5/4E8 T-cell receptor transgenic (TCR Tg) mouse provides a model in which >80% of T-cells specifically recognise an immunodominant epitope derived from the G1 domain of aggrecan – peptide-84-103 (p84-103). This model allowed for the examination of these factors and the underlying mechanism ex vivo using a purified naive CD4+ T cell population in coculture with LPS-matured dendritic cells (mDCs). The data presented in this thesis show the activation, proliferation and effector responses of naive 5/4E8 TCR Tg T cells to alterations in both cognate peptide (p89- 103) density and affinity through citrullination of a putative TCR contact residue (R93Cit). Interestingly, by reducing TCR signal strength the observed response shifts from one dominated by the Th2 phenotype to Th17 cells. Linking the degree of TCR activation to Th cell phenotype was the intensity of IL-2 signalling that in turn shaped the balance between phosphorylated STAT3 and STAT5. Compared to p89-103-primed T cells, T cells responding to R93Cit produced less IL-2, expressed lower levels of the ILiii 2 receptor subunit CD25, and showed reduced levels of STAT5 phosphorylation, whilst STAT3 activation was unaltered. IL-2 blockade in p89-103-primed T-cells selectively reduced STAT5 but not STAT3 phosphorylation, and concomitantly enhanced Th17 development. In summary, this work indicates the impact that changes to the intensity of TCR signalling can have on the murine Th17 response. Indeed, these data illustrate how a disease-relevant post-translational modification such as citrullination can promote Th17 development by altering the balance between STAT5 and STAT3 activation in responding T cells.

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Bell, Andrea Dorothy Lee. "Insulin and TSH signal transduction pathways in human preadipocytes." Thesis, University of Ottawa (Canada), 2000. http://hdl.handle.net/10393/8646.

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Signaling through the rapamycin-sensitive mammalian target of rapamycin-p70 S6 kinase (p70 S6K) pathway was examined in human preadipocytes in primary culture. The inhibitory effect of rapamycin on insulin-induced differentiation of preadipose cell lines has been attributed to a blockade of clonal expansion. We demonstrate that rapamycin inhibits the differentiation of human preadipocytes in primary culture, even though these cells do not undergo clonal expansion. Glycerol-3-phosphate-dehydrogenase (GPDH) activity, an indicator of differentiation, was reduced in omental and subcutaneous preadipocytes to 17 +/- 10% (mean +/- 95% confidence limits, n = 10) of standard differentiation. Our data suggest rapamycin-sensitive pathways operate independently of clonal expansion. Our second objective addressed a novel route of p70 S6K activation. We have detected the presence of TSH receptor in human preadipocytes, and have shown it activates PKB and p70 S6K in a wortmannin-sensitive manner. A model depicting the convergence of insulin and TSH signaling in human preadipocytes is proposed.

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D'Souza, Aswin Cletus. "Automated counting of cell bodies using Nissl stained cross-sectional images." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2035.

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Xia, Dongchun. "An automated image acquisition and analysis system for cell membrane detection." Thesis, Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/17251.

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40

Petrak, David. "Automated, Spatio-Temporally Controlled Cell Microprinting with Polymeric Aqueous Biphasic Systems." University of Akron / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=akron1375364313.

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Hur, In Ae. "Novel computer vision algorithms for automated cell event detection and analysis." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/2900.

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Live cell imaging is the study of living cells using microscope images and is used by biomedical researchers to provide a novel way to analyze biological functions through cell behavior and motion studies. Cell events are seen as morphological changes in image sequences, and their analysis has great potential for the study of normal/abnormal phenotypes and the effectiveness of drugs. While current quantitative cell analysis typically focuses on measuring whole populations of cells, we need to be able to recognize cell events at the single cell level, identify these events automatically, and analyze these events over time. For this reason, we developed and evaluated several novel automatic single cell event detection and analysis methods based on a detailed knowledge of the cell cycle and other cell event characteristics. The first method detects significant events within the temporal sequence using a machine learning method to use features derived from segmented cell images. We used a Neural Network (NN) algorithm to classify cell events to pre-defined categories. The second and third methods apply statistical and econometric techniques originally developed for time-series analysis of financial markets to facilitate the identification of cell entry into mitosis. We developed graph trend analysis and paired graph analysis methods from trend analysis and pairs trading to determine significant data points in cell feature data. The final method determines the position of cells in order to associate daughter cells with their parent cells after mitosis using Kalman filter techniques. By using the Kalman filter approach, we estimated future cell border centroid positions and successfully associated daughter cells with their parent cells after mitosis. In this study, the performance of these novel computer vision algorithms for automatic cell event detection and analysis were evaluated and verified by applying models to different image sequences from the Large Scale Digital Cell Analysis System (LSDCAS). The results show that the approaches developed can yield significant improvements over existing algorithms.

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Shewinvanakitkul, Prapan. "Automated Detection and Prediction of Sleep Apnea Events." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1486490112558014.

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Vieira, Elaine. "Signal Transduction of Glucagon Secretion." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6319.

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Myjak, Mitchell John. "A two-level reconfigurable cell array for digital signal processing." Online access for everyone, 2004. http://www.dissertations.wsu.edu/Thesis/Spring2004/m%5Fmyjak%5F050504.pdf.

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Lingelbach, Frank. "Path planning using probabilistic cell decomposition." Licentiate thesis, Stockholm, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-294.

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Al-Habaibeh, Amin. "Rapid design of condition monitoring systems for machining operations." Thesis, University of Nottingham, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326780.

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Machiraju, Naga Kiran. "Semi Automated Bullet GroupAnalysis for Shooting Target Training." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17046.

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Competitive Shooting as a sport is becoming famous these days and analysis of shooting group or bullet group which is a process of analysis location of bullet holes in one shooting session and stands as a metric for Precision of the weapon, Shooter's Accuracy, his Consistency and helps in finding Accurate load for the Cartridge. Knowledge of these factors can help in improving one's shooting and fine-tuning skills as a Shooter. Bullet group is alsoinuenced by the Accuracy of Rie, Optimal hand load, free run distance, environmental conditions like humidity, temperature, ambient light, windspeed, Shooter's position. Analyzing the Bullet group can be done in various ways, one way of doing it is by taking a Digital Image and analyzing the Image and detecting positions of bullet holes and Calculating metrics from this Metrics like Geometry of bullet group, largest distance between two bullets, compactness of the bullet group on target. In this work, detection of bullet holes is done by using these techniques: Template matching, Histogram equalization, White Balancing, Median andGaussian altering and Peak detection algorithms. After obtaining positions of the bullet holes in the Image. Complete Automation can be done by using the training the Algorithm with a Machine learning framework with the help of Articial neural networks. The existing bullet group analysis software require the bullet group shot on a specifc target, which limits the shooters to shoot on a target of shooter's choice every time and, those targets are not universal and vary from place to place. This algorithm aims to work on various types of target, and taking a step towards making a more generalized and more versatile algorithm.

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Lioubin, Mario N. "Fms signal transduction, p150S̳h̳i̳p̳ : a signal transduction molecule with inositol 5-phosphatase activity /." Thesis, Connect to this title online; UW restricted, 1996. http://hdl.handle.net/1773/6339.

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Machado, Daniel. "Improving automated redshift detection in the low signal-to-noise regime for Large Sky Surveys." Thesis, Paris 11, 2015. http://www.theses.fr/2014PA112427.

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Le décalage vers le rouge est la principale mesure par laquelle les astronomes peuvent cartographier l’Univers dans la direction radiale. Afin de tester les hypothèses d’homogénéité et d’isotropie, il est nécessaire de mesurer avec precision le décalage vers le rouge d’un grand nombre de galaxies. De plus, différents modèles cosmologiques ne peuvent être distingués qu’au travers d’une analyse précise des structures à grandes échelles tracées par ces galaxies. Pour obtenir un grand nombre de ces mesures, il est nécessaire de mener d'importantes campagnes d’observations pour établir des relevés couvrant une large portion du ciel. Ces mesures trouvent aussi d’autres applications en astronomie comme par exemple l’analyse du cisaillement gravitationnel, la calibration des mesures photométriques, l’étude des halos de matière noire, de la morphologie des galaxies, des structures à grandes échelles et de la distribution des galaxies.Dans tous les relevés de galaxies, les mesures les plus problématiques sont pour les objets de plus faible luminosité, où le bruit instrumental devient gênant, et qui se trouvent être en général les objets les plus lointains. Pour ces objets, les mesures de décalages vers le rouge peuvent souvent devenir imprécise et, la plupart du temps, elles sont simplement exclues de l’analyse en appliquant des coupures en magnitudes ou en rapport signal à bruit. Cette procédure est une méthode brutale pour séparer les mesures probablement imprécises des mesures fiables.Dans cette thèse, nous développons un algorithme permettant la mesure du décalage vers le rouge des spectres de galaxies dans le regime de faible rapport signal à bruit. La première partie de cette thèse présente les différents concepts relatifs à l’estimation du décalage vers le rouge et au débruitrage de signaux par transformation en ondelettes et filtrage par taux de fausse détection (False Detection Rate, FDR en anglais). La seconde partie détaille comment ces concepts sont mis à contribution dans l’élaboration de l’algorithme Darth Fader (Denoised and Automatic Redshifts THresholded with a False DEtection Rate). Enfin, la dernière partie présente l’application de cet algorithme à des données synthétiques générées à partir du COSMOS Mock Catalogue, mais aussi sur des données réelles tirées du relevé WiggleZ.Nous montrons que Darth Fader fonctionne efficacement à bas rapport signal à bruit étant donné un choix approprié du taux de fausse détection et d’un critère de comptage de traits caractéristiques judicieux. Nous montrons aussi que Darth Fader permet d’éliminer le continuum des spectres à bas rapport signal à bruit, ce qui rend possible l’estimation du décalage vers le rouge par corrélation croisée. Enfin, nous montrons sur des spectres de test issues du relevé WiggleZ que notre algorithme est capable d’analyser une part importante du relevé de façon autonome avec une haute précision, sans nécessiter d'inspection visuelle (alors que les données WiggleZ ont à l’origine été entièrement soumises à l’inspection visuelle). En conclusion, Darth Fader est un algorithme prometteur pour l’analyse des grands relevés de galaxies, en particulier pour exploiter les objets à faible rapport signal à bruit qui sont habituellement simplement ignorés
Summary: Redshift is the primary measure by which astronomers can map the Universe in the radial direction. In order to test the assumptions of homogeneity and isotropy, accurate redshifts of galaxies are needed, and for a great many of them. Additionally different cosmological models can only be distinguished by careful observations of the large scale structure traced by these galaxies. Large sky surveys are the only mechanism by which redshifts for a large number of galaxies can be obtained. Accurate redshift estimation is additionally required for many other fields of astronomy including but not limited to: weak lensing, studies of dark matter haloes, galaxy morphology studies, chemical evolution studies, photometric calibration, and studies of large scale structure and galaxy clustering.Problems exist in all surveys at the dim limit of observation, which usually corresponds to the higher redshift objects in the survey, where noise becomes problematic. Magnitude or signal-to-noise ratio cuts are often employed in order to eliminate potentially troublesome objects; such a procedure is a blunt tool for separating good redshift candidates from ones likely to be inaccurate.In this thesis we develop an algorithm to tackle redshift estimation of galaxy spectra in the low signal-to-noise regime. The first part of this thesis introduces the concepts of denoising, particularly False Detection Rate denoising, wavelet transforms and redshift estimation algorithms. The second part details how these concepts are united into the Darth Fader (Denoised and Automatic Redshifts THresholded with a FAlse DEtection Rate) algorithm. The final parts of this thesis apply the algorithm both to idealised synthetic data generated from the COSMOS Mock Catalogue, and to a subset of real data from the WiggleZ survey.We show that Darth Fader can operate effectively at low signal-to-noise given an appropriate choice of FDR parameter for denoising, and an appropriate feature-counting criterion. We also show that Darth Fader can remove the continua of spectra effectively at low signal-to-noise for the purposes of redshift estimation by cross-correlation. Additionally we show from tests on spectra from the WiggleZ survey that our algorithm has the ability to process a substantial subset of that data without the need for visual inspection (to which the entire WiggleZ spectral survey has been subjected), and to a high degree of accuracy. We conclude that the Darth Fader algorithm has potential to be used in large-sky survey pipelines, particularly where signal-to-noise is expected to be poor

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Homer, Daniel C. "Population Fit Threshold: Fully Automated Signal Map generation for Baseline Correction in NMR-based Metabolomics." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1271689072.

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