4,952 research outputs found

    Detection of leukocytes stained with acridine orange using unique spectral features acquired from an image-based spectrometer

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    A leukocyte differential count can be used to diagnosis a myriad blood disorders, such as infections, allergies, and efficacy of disease treatments. In recent years, attention has been focused on developing point-of-care (POC) systems to provide this test in global health settings. Acridine orange (AO) is an amphipathic, vital dye that intercalates leukocyte nucleic acids and acidic vesicles. It has been utilized by POC systems to identify the three main leukocyte subtypes: granulocytes, monocytes, and lymphocytes. Subtypes of leukocytes can be characterized using a fluorescence microscope, where the AO has a 450 nm excitation wavelength and has two peak emission wavelengths between 525 nm (green) and 650 nm (red), depending on the cellular content and concentration of AO in the cells. The full spectra of AO stained leukocytes has not been fully explored for POC applications. Optical instruments, such as a spectrometer that utilizes a diffraction grating, can give specific spectral data by separating polychromatic light into distinct wavelengths. The spectral data from this setup can be used to create object-specific emission profiles. Yellow-green and crimson microspheres were used to model the emission peaks and profiles of AO stained leukocytes. Whole blood was collected via finger stick and stained with AO to gather preliminary leukocyte emission profiles. A MATLAB algorithm was designed to analyze the spectral data within the images acquired using the image-based spectrometer. The algorithm utilized watershed segmentation and centroid location functions to isolate independent spectra from an image. The output spectra represent the average line intensity profiles for each pixel across a slice of an object. First steps were also taken in processing video frames of manually translated microspheres. The high-speed frame rate allowed objects to appear in multiple consecutive images. A function was applied to each image cycle to identify repeating centroid locations. The yellow-green (515 nm) and crimson (645 nm) microspheres exhibited a distinct separation in colorimetric emission with a peak-to-peak difference of 36 pixels, which is related to the 130 nm peak emission difference. Two AO stained leukocytes exhibited distinct spectral profiles and peaks across different wavelengths. This could be due to variations in the staining method (incubation period and concentration) effecting the emissions or variations in cellular content indicating different leukocyte subtypes. The algorithm was also effective when isolating unique centroids between video frames. We have demonstrated the ability to extract spectral information from data acquired from the image-based spectrometer of microspheres, as a control, and AO stained leukocytes. We determined that the spectral information from yellow-green and crimson microspheres could be used to represent the wavelength range of AO stained leukocytes, thus providing a calibration tool. Also, preliminary spectral information was successfully extracted from yellow-green microspheres translated under the linear slit using stationary images and video frames, thus demonstrating the feasibility of collecting data from a large number of objects

    Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

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    The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions

    Structure-Property Relationships in Aluminum-Copper alloys using Transmission X-Ray Microscopy (TXM) and Micromechanical Testing

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    abstract: Aluminum alloys are ubiquitously used in almost all structural applications due to their high strength-to-weight ratio. Their superior mechanical performance can be attributed to complex dispersions of nanoscale intermetallic particles that precipitate out from the alloy’s solid solution and offer resistance to deformation. Although they have been extensively investigated in the last century, the traditional approaches employed in the past haven’t rendered an authoritative microstructural understanding in such materials. The effect of the precipitates’ inherent complex morphology and their three-dimensional (3D) spatial distribution on evolution and deformation behavior have often been precluded. In this study, for the first time, synchrotron-based hard X-ray nano-tomography has been implemented in Al-Cu alloys to measure growth kinetics of different nanoscale phases in 3D and reveal mechanistic insights behind some of the observed novel phase transformation reactions occurring at high temperatures. The experimental results were reconciled with coarsening models from the LSW theory to an unprecedented extent, thereby establishing a new paradigm for thermodynamic analysis of precipitate assemblies. By using a unique correlative approach, a non-destructive means of estimating precipitation-strengthening in such alloys has been introduced. Limitations of using existing mechanical strengthening models in such alloys have been discussed and a means to quantify individual contributions from different strengthening mechanisms has been established. The current rapid pace of technological progress necessitates the demand for more resilient and high-performance alloys. To achieve this, a thorough understanding of the relationships between material properties and its structure is indispensable. To establish this correlation and achieve desired properties from structural alloys, microstructural response to mechanical stimuli needs to be understood in three-dimensions (3D). To that effect, in situ tests were conducted at the synchrotron (Advanced Photon Source) using Transmission X-Ray Microscopy as well as in a scanning electron microscope (SEM) to study real-time damage evolution in such alloys. Findings of precipitate size-dependent transition in deformation behavior from these tests have inspired a novel resilient aluminum alloy design.Dissertation/ThesisDoctoral Dissertation Materials Science and Engineering 201
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