Estimation of mass thickness response of embedded aggregated silica nanospheres from high angle annular dark-field scanning transmission electron micrographs

In this study we investigate the functional behavior of the intensity in high-angle annular dark field (HAADF) scanning transmission electron micrograph (STEM) images. The model material is a silica particle (20 nm) gel at 5 wt%. By assuming that the intensity response is monotonically increasing with increasing mass thickness of silica, an estimate of the functional form is calculated using a maximum likelihood approach. We conclude that a linear functional form of the intensity provides a fair estimate but that a power function is significantly better for estimating the amount of silica in the z-direction. The work adds to the development of quantifying material properties from electron micrographs, especially in the field of tomography methods and three-dimensional quantitative structural characterization from a STEM micrograph. It also provides means for direct three-dimensional quantitative structural characterization from a STEM micrograph

Valid and efficient manual estimates of intracranial volume from magnetic resonance images

Background: Manual segmentations of the whole intracranial vault in high-resolution magnetic resonance images are often regarded as very time-consuming. Therefore it is common to only segment a few linearly spaced intracranial areas to estimate the whole volume. The purpose of the present study was to evaluate how the validity of intracranial volume estimates is affected by the chosen interpolation method, orientation of the intracranial areas and the linear spacing between them. Methods: Intracranial volumes were manually segmented on 62 participants from the Gothenburg MCI study using 1.5 T, T-1-weighted magnetic resonance images. Estimates of the intracranial volumes were then derived using subsamples of linearly spaced coronal, sagittal or transversal intracranial areas from the same volumes. The subsamples of intracranial areas were interpolated into volume estimates by three different interpolation methods. The linear spacing between the intracranial areas ranged from 2 to 50 mm and the validity of the estimates was determined by comparison with the entire intracranial volumes. Results: A progressive decrease in intra-class correlation and an increase in percentage error could be seen with increased linear spacing between intracranial areas. With small linear spacing (<= 15 mm), orientation of the intracranial areas and interpolation method had negligible effects on the validity. With larger linear spacing, the best validity was achieved using cubic spline interpolation with either coronal or sagittal intracranial areas. Even at a linear spacing of 50 mm, cubic spline interpolation on either coronal or sagittal intracranial areas had a mean absolute agreement intra-class correlation with the entire intracranial volumes above 0.97. Conclusion: Cubic spline interpolation in combination with linearly spaced sagittal or coronal intracranial areas overall resulted in the most valid and robust estimates of intracranial volume. Using this method, valid ICV estimates could be obtained in less than five minutes per patient

Hemocompatibility of siRNA loaded dextran nanogels

Although the behavior of nanoscopic delivery systems in blood is an important parameter when contemplating their intravenous injection, this aspect is often poorly investigated when advancing from in vitro to in vivo experiments. In this paper, the behavior of siRNA loaded dextran nanogels in human plasma and blood is examined using fluorescence fluctuation spectroscopy, platelet aggregometry, flow cytometry and single particle tracking. Our results show that, in contrast to their negatively charged counterparts, positively charged siRNA loaded dextran nanogels cause platelet aggregation and show increased binding to human blood cells. Although PEGylating the nanogels did not have a significant effect on their interaction with blood cells, single particle tracking revealed that it is necessary to prevent their aggregation in human plasma. We therefore conclude that PEGylated negatively charged dextran nanogels are the most suited for further in vivo studies as they do not aggregate in human plasma and exhibit minimal interactions with blood cells

On-chip light sheet illumination enables diagnostic size and concentration measurements of membrane vesicles in biofluids

Cell-derived membrane vesicles that are released in biofluids, like blood or saliva, are emerging as potential non-invasive biomarkers for diseases, such as cancer. Techniques capable of measuring the size and concentration of membrane vesicles directly in biofluids are urgently needed. Fluorescence single particle tracking microscopy has the potential of doing exactly that by labelling the membrane vesicles with a fluorescent label and analysing their Brownian motion in the biofluid. However, an unbound dye in the biofluid can cause high background intensity that strongly biases the fluorescence single particle tracking size and concentration measurements. While such background intensity can be avoided with light sheet illumination, current set-ups require specialty sample holders that are not compatible with high-throughput diagnostics. Here, a microfluidic chip with integrated light sheet illumination is reported, and accurate fluorescence single particle tracking size and concentration measurements of membrane vesicles in cell culture medium and in interstitial fluid collected from primary human breast tumours are demonstrated

Empirical Bayes models for multiple probe type microarrays at the probe level

<p>Abstract</p> <p>Background</p> <p>When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are adjusted towards a global estimate, producing more stable results compared to ordinary t-tests. However, for Affymetrix type data a clear dependency between variability and intensity-level generally exists, even for logged intensities, most clearly for data at the probe level but also for probe-set summarizes such as the MAS5 expression index. As a consequence, adjustment towards a global estimate results in an intensity-level dependent false positive rate.</p> <p>Results</p> <p>We propose two new methods for finding differentially expressed genes, Probe level Locally moderated Weighted median-t (PLW) and Locally Moderated Weighted-t (LMW). Both methods use an empirical Bayes model taking the dependency between variability and intensity-level into account. A global covariance matrix is also used allowing for differing variances between arrays as well as array-to-array correlations. PLW is specially designed for Affymetrix type arrays (or other multiple-probe arrays). Instead of making inference on probe-set summaries, comparisons are made separately for each perfect-match probe and are then summarized into one score for the probe-set.</p> <p>Conclusion</p> <p>The proposed methods are compared to 14 existing methods using five spike-in data sets. For RMA and GCRMA processed data, PLW has the most accurate ranking of regulated genes in four out of the five data sets, and LMW consistently performs better than all examined moderated t-tests when used on RMA, GCRMA, and MAS5 expression indexes.</p

Models for Point Processes Observed with Noise

this paper holds exactly for points X i such that the corresponding support lies within A, and it is a good approximation when A is large compared to, say, the 95% contour curves for the displacement distribution