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Abstract: Advanced imaging is useful for understanding the three-dimensional (3D) growth of cells. X-ray tomography serves as a powerful noninvasive, nondestructive technique that can fulfill these purposes by providing information about cell growth within 3D platforms. There are a limited number of studies taking advantage of synchrotron X-rays, which provides a large field of view and suitable resolution to image cells within specific biomaterials. In this study, X-ray synchrotron radiation microtomography at Diamond Light Source and advanced image processing were used to investigate cellular infiltration of HeLa cells within poly L-lactide (PLLA) scaffolds. This study demonstrates that synchrotron X-rays using phase contrast is a useful method to understand the 3D growth of cells in PLLA electrospun scaffolds. Two different fiber diameter (2 and 4 µm) scaffolds with different pore sizes, grown over 2, 5 and 8 days in vitro, were examined for infiltration and cell connectivity. After performing visualization by segmentation of the cells from the fibers, the results clearly show deeper cell growth and higher cellular interconnectivity in the 4 µm fiber diameter scaffold. This indicates the potential for using such 3D technology to study cell–scaffold interactions for future medical use.

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Abstract: Determining the oxidation state of Fe through parameterization of X-ray absorption near-edge structure (XANES) spectral features is highly dependent on accurate and repeatable energy calibration between spectra. Small errors in energy calibration can lead to vastly different interpretations. While simultaneous measurement of a reference foil is often undertaken on X-ray spectroscopy beamlines, other beamlines measure XANES spectra without a reference foil and therefore lack a method for correcting energy drift. Here a method is proposed that combines two measures of Fe oxidation state taken from different parts of the spectrum to iteratively correct for an unknown energy offset between spectra, showing successful iterative self-calibration not only during individual beam time but also across different beamlines.

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Abstract: In macromolecular crystallography, a great deal of effort has been invested in understanding radiation-damage progression. While the sensitivity of protein crystals has been well characterized, crystals of DNA and of DNA–protein complexes have not thus far been studied as thoroughly. Here, a systematic investigation of radiation damage to a crystal of a DNA 16-mer diffracting to 1.8 Å resolution and held at 100 K, up to an absorbed dose of 45 MGy, is reported. The RIDL (Radiation-Induced Density Loss) automated computational tool was used for electron-density analysis. Both the global and specific damage to the DNA crystal as a function of dose were monitored, following careful calibration of the X-ray flux and beam profile. The DNA crystal was found to be fairly radiation insensitive to both global and specific damage, with half of the initial diffraction intensity being lost at an absorbed average diffraction-weighted dose, D1/2, of 19 MGy, compared with 9 MGy for chicken egg-white lysozyme crystals under the same beam conditions but at the higher resolution of 1.4 Å. The coefficient of sensitivity of the DNA crystal was 0.014 Å2 MGy−1, which is similar to that observed for proteins. These results imply that the significantly greater radiation hardness of DNA and RNA compared with protein observed in a DNA–protein complex and an RNA–protein complex could be due to scavenging action by the protein, thereby protecting the DNA and RNA in these studies. In terms of specific damage, the regions of DNA that were found to be sensitive were those associated with some of the bound calcium ions sequestered from the crystallization buffer. In contrast, moieties farther from these sites showed only small changes even at higher doses.

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Abstract: Cr/C multilayer optics are a suitable choice for the tender X-ray range (1–4 keV) that covers the K absorption edges of P, S, Cl and 3d transition metals as well as the L absorption edges of 4d transition metals. In particular, these optics are studied in order to optimize the optical properties of collimated plane-grating monochromators. In this paper, the structure, stress and optical properties of Cr/C multilayers (fabricated using direct-current magnetron sputtering) with bi-layer number of 20 and the same period (about 11.64 nm) but different Cr thickness ratio (0.20–0.80) are investigated. Firstly, the grazing-incidence X-ray reflectivity at 8.04 keV was measured. These measurements were fitted assuming a multilayer structure with a four-layer and non-periodic model. Results and fitting show that interface widths increase with the Cr thickness ratio. The results obtained from X-ray diffraction at 8.04 keV were consistent with high-resolution transmission electron microscopy which showed an increase in grain size of the Cr layers. In addition, the stresses of the Cr/C multilayers have been measured and the results show that the stress value approaches zero when the Cr thickness ratio is about 0.45. The reflectivity of a Cr/C multilayer with Cr thickness ratio of 0.37 was measured and reaches 26.6% at 1.04 keV. The measured reflectivity matches very well with the predicted value using the four-layer and non-periodic model, which confirmed the viability of the prediction. Thus, the reflectivity at 1.04 keV of a Cr/C multilayer with different Cr thickness ratio was predicted and was found to drastically decrease when the Cr thickness ratio is larger than 0.37. It has been determined that a Cr thickness ratio value of 0.37 is the best choice for a Cr/C multilayer in view of high reflectivity and low stress.

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Abstract: X-ray computed tomography and, specifically, time-resolved volumetric tomography data collections (4D datasets) routinely produce terabytes of data, which need to be effectively processed after capture. This is often complicated due to the high rate of data collection required to capture at sufficient time-resolution events of interest in a time-series, compelling the researchers to perform data collection with a low number of projections for each tomogram in order to achieve the desired `frame rate'. It is common practice to collect a representative tomogram with many projections, after or before the time-critical portion of the experiment without detrimentally affecting the time-series to aid the analysis process. For this paper these highly sampled data are used to aid feature detection in the rapidly collected tomograms by assisting with the upsampling of their projections, which is equivalent to upscaling the θ-axis of the sinograms. In this paper, a super-resolution approach is proposed based on deep learning (termed an upscaling Deep Neural Network, or UDNN) that aims to upscale the sinogram space of individual tomograms in a 4D dataset of a sample. This is done using learned behaviour from a dataset containing a high number of projections, taken of the same sample and occurring at the beginning or the end of the data collection. The prior provided by the highly sampled tomogram allows the application of an upscaling process with better accuracy than existing interpolation techniques. This upscaling process subsequently permits an increase in the quality of the tomogram's reconstruction, especially in situations that require capture of only a limited number of projections, as is the case in high-frequency time-series capture. The increase in quality can prove very helpful for researchers, as downstream it enables easier segmentation of the tomograms in areas of interest, for example. The method itself comprises a convolutional neural network which through training learns an end-to-end mapping between sinograms with a low and a high number of projections. Since datasets can differ greatly between experiments, this approach specifically develops a lightweight network that can easily and quickly be retrained for different types of samples. As part of the evaluation of our technique, results with different hyperparameter settings are presented, and the method has been tested on both synthetic and real-world data. In addition, accompanying real-world experimental datasets have been released in the form of two 80 GB tomograms depicting a metallic pin that undergoes corruption from a droplet of salt water. Also a new engineering-based phantom dataset has been produced and released, inspired by the experimental datasets.