Characterization of Sodium Alginate Hydrogels Reinforced with Nanoparticles of Hydroxyapatite for Biomedical Applications

In recent years, researchers working in biomedical science and technology have investigated alternatives for enhancing the mechanical properties of biomedical materials. In this work, sodium alginate (SA) hydrogel-reinforced nanoparticles (NPs) of hydroxyapatite (HA) were prepared to enhance the mechanical properties of this polymer. Compression tests showed an increase of 354.54% in ultimate compressive strength (UCS), and 154.36% in Young’s modulus with the addition of these NPs compared with pure SA. Thermogravimetric analysis (TGA) revealed that the amount of residual water is not negligible and covered a range from 20 to 35 wt%, and the decomposition degree of the alginate depends on the hydroxyapatite content, possibly due to the displacement of sodium ions by the hydroxyapatite and not by calcium chloride. Further, there is an important effect possibly due to the existence of an interaction of hydrogen bonds between the hydroxyl of the alginate and the oxygen atoms of the hydroxyapatite, so signals appear upfield in nuclear magnetic resonance (NMR) data. An increase in the accumulation of HA particles was observed with the use of X-ray microtomography, in which the quantified volume of particles per reconstructed volume corresponded accordingly to the increase in the mechanical properties of the hydrogel.

Fetal Brain Biometric Measurements on 3D Super-Resolution Reconstructed T2-Weighted MRI: An Intra- and Inter-observer Agreement Study

We present the comparison of two-dimensional (2D) fetal brain biometry on magnetic resonance (MR) images using orthogonal 2D T2-weighted sequences (T2WSs) vs. one 3D super-resolution (SR) reconstructed volume and evaluation of the level of confidence and concordance between an experienced pediatric radiologist (obs1) and a junior radiologist (obs2). Twenty-five normal fetal brain MRI scans (18–34 weeks of gestation) including orthogonal 3-mm-thick T2WSs were analyzed retrospectively. One 3D SR volume was reconstructed per subject based on multiple series of T2WSs. The two observers performed 11 2D biometric measurements (specifying their level of confidence) on T2WS and SR volumes. Measurements were compared using the paired Wilcoxon rank sum test between observers for each dataset (T2WS and SR) and between T2WS and SR for each observer. Bland–Altman plots were used to assess the agreement between each pair of measurements. Measurements were made with low confidence in three subjects by obs1 and in 11 subjects by obs2 (mostly concerning the length of the corpus callosum on T2WS). Inter-rater intra-dataset comparisons showed no significant difference (p > 0.05), except for brain axial biparietal diameter (BIP) on T2WS and for brain and skull coronal BIP and coronal transverse cerebellar diameter (DTC) on SR. None of them remained significant after correction for multiple comparisons. Inter-dataset intra-rater comparisons showed statistical differences in brain axial and coronal BIP for both observers, skull coronal BIP for obs1, and axial and coronal DTC for obs2. After correction for multiple comparisons, only axial brain BIP remained significantly different, but differences were small (2.95 ± 1.73 mm). SR allows similar fetal brain biometry as compared to using the conventional T2WS while improving the level of confidence in the measurements and using a single reconstructed volume.

Petascale neural circuit reconstruction: automated methods

3D electron microscopy (EM) has been successful at mapping invertebrate nervous systems, but the approach has been limited to small chunks of mammalian brains. To scale up to larger volumes, we have built a computational pipeline for processing petascale image datasets acquired by serial section EM, a popular form of 3D EM. The pipeline employs convolutional nets to compute the nonsmooth transformations required to align images of serial sections containing numerous cracks and folds, detect neuronal boundaries, label voxels as axon, dendrite, soma, and other semantic categories, and detect synapses and assign them to presynaptic and postsynaptic segments. The output of neuronal boundary detection is segmented by mean affinity agglomeration with semantic and size constraints. Pipeline operations are implemented by leveraging distributed and cloud computing. Intermediate results of the pipeline are held in cloud storage, and can be effortlessly viewed as images, which aids debugging. We applied the pipeline to create an automated reconstruction of an EM image volume spanning four visual cortical areas of a mouse brain. Code for the pipeline is publicly available, as is the reconstructed volume.

Characterisation of diamond abrasive grains of grinding tools using industrial X-ray computed tomography

In this paper, a characterisation of diamond abrasive grains of grinding tools using industrial X-ray computed tomography (XCT) is carried out. One of the most challenge tasks in the characterisation is extracting the diamond abrasive grains from the XCT volume data. Methods that are able to extract the grains are then developed and introduced in this paper. The first step is to create a triangular mesh surface from the reconstructed volume file using a gradient anisotropic diffusion filter. The second step is to convert the measured greyscale volume into a signed distance field using a global threshold value and then a localised method for grain segmentation. To validate the proposed method, three different types of grinding tool specimens are measured and analysed. Each abrasive grain is segmented and the distributions of grains (with both random and designed patterns) are then calculated, plotted and analysed. The quantitative analysis clearly shows the deviations between the measured distribution and the designed pattern of the grinding tool, which indicates that the proposed method can provide an accurate and comprehensive characterisation of the grinding tools.

Interpolated Multichannel Singular Spectrum Analysis (I-MSSA): a reconstruction method that honors true trace coordinates

The Multichannel Singular Spectrum Analysis (MSSA) reconstruction algorithm denoises and reconstructs seismic traces on a regular grid. We present a modified version of MSSA that can cope with denoising and reconstruction of traces with irregular coordinates. The proposed method, Interpolated Multichannel Singular Spectrum Analysis (I-MSSA), connects off-the-grid observations to the desired gridded data via a non-invertible bilinear interpolation operator. The algorithm consists of two steps. In the first step, we use the steepest descent method to estimate the gridded data that honors off-the-grid observations. The second step guarantees convergence to a solution by applying the MSSA filter to the gridded data. The final solution is the reconstructed volume that honors off-the-grid observations. We apply the algorithm to synthetic and field data. We also provide an application where 3D prestack data corresponding to an orthogonal survey is fully reconstructed using cross-spread gathers. We use I-MSSA to reconstruct each subset individually. The output is a complete seismic volume described in a regular CMP grid.

Bragg-edge attenuation spectra at voxel level from 4D wavelength-resolved neutron tomography

4D wavelength-resolved neutron tomography of a reference sample made of several polycrystalline materials, namely nickel, iron, titanium, lead, copper and aluminium, is presented. Data were acquired using the time-of-flight transmission imaging method at the IMAT beamline at the ISIS pulsed neutron source. Wavelength-dispersive tomography reconstruction was computed using filtered back projection, allowing wavelength-resolved total-cross-section retrieval for each voxel in the reconstructed volume of the sample. The need for background correction to enable quantitative results and analysis is discussed, and the achieved 3D spatial resolution with respect to the obtained Bragg-edge pattern quality is investigated.

Emplacement of unusual rhyolitic to basaltic ignimbrites during collapse of a basalt-dominated caldera: The Halarauður eruption, Krafla (Iceland)

Deposits of the ca. 110 ka Halarauður eruption of Krafla caldera (reconstructed volume = 7 ± 6 km3 dense rock equivalent) include the only spatter-rich ignimbrite known in Iceland, and an exceptionally rare lava-like basaltic ignimbrite. We present a revised stratigraphy and new whole-rock major-element data set for products of this unusual event, one of only three Quaternary ignimbrite eruptions identified in Iceland. Compositions of Halarauður products span a broad range (50.0–74.6 wt% SiO2), reflecting mixing of rhyolite with underplating basalt. Small-volume, valley-ponded, basal pumice- and spatter-bearing lithic breccias and ignimbrite (rhyolite to andesite) reflect rapid column collapse during early opening of ring-fault vents. A transition to voluminous, regionally dispersed spatter agglomerates (dacite to basaltic andesite) marks an abrupt eruptive intensification, as gas-poor magma was squeezed into a developing ring-fault system by the subsiding chamber roof. Spatial heterogeneities in ascent rates and outgassing through this variably dilated fault system caused coeval formation of collapsing plumes and spatter fountains at separate vents. Spatter was entrained into flows from the more explosive vents, which deposited proximal spatter agglomerates and more distal spatter-bearing ignimbrite. Overlying lava-like ignimbrite deposits (basaltic andesite to basalt) reflect a final opening of vents, as mafic magma from deep levels of the chamber was squeezed through a dilated ring-fault system by the subsiding roof block and erupted at uncharacteristically high mass flux. Development of a mature ring-fault conduit system during early tapping of silicic magma appears to be a prerequisite for the emplacement of welded basaltic ignimbrites, and it should be considered as a possible eruption scenario in basalt-dominated systems where silicic magma has been known to also accumulate. Poor preservation of the Halarauður deposits exemplifies the challenges of studying ignimbrite eruptions in frequently glaciated regions like Iceland, where they may be more common than the geological record suggests.

Tomographic Collection of Block-Based Sparse STEM Images: Practical Implementation and Impact on the Quality of the 3D Reconstructed Volume

The reduction of the electron dose in electron tomography of biological samples is of high significance to diminish radiation damages. Simulations have shown that sparse data collection can perform efficient electron dose reduction. Frameworks based on compressive-sensing or inpainting algorithms have been proposed to accurately reconstruct missing information in sparse data. The present work proposes a practical implementation to perform tomographic collection of block-based sparse images in scanning transmission electron microscopy. The method has been applied on sections of chemically-fixed and resin-embedded Trypanosoma brucei cells. There are 3D reconstructions obtained from various amounts of downsampling, which are compared and eventually the limits of electron dose reduction using this method are explored.

Debris-flow volume quantile prediction from catchment morphometry

Estimation of the volumes of potential future debris flows is a key factor in hazard assessment and mitigation. Worldwide, however, there are few catchments for which detailed volume-frequency information is available. We (1) reconstructed volume-frequency curves for 10 debris-flow catchments in Saline Valley, California (USA), from a large number of well-preserved, unmodified surficial flow deposits, and (2) assessed the correlations between lobe-volume quantiles and a set of morphometric catchment characteristics. We found statistically significant correlations between lobe-volume quantiles, including median and maximum, and catchment relief, length (planimetric distance from the fan apex to the most distant point along the watershed boundary), perimeter, and Melton ratio (relief divided by the square root of catchment area). These findings show that it may be possible to roughly estimate debris-flow lobe-volume quantiles from basic catchment characteristics that can be obtained from globally available elevation data. This may assist in design-volume estimation for debris-flow catchments where past flow volumes are otherwise unknown.