The rapid increase in medical and biomedical image acquisition rates has opened up new avenues for image analysis, but has also introduced formidable challenges. This is evident, for example, in selective plane illumination microscopy where acquisition rates of about 1-4 GB/s sustained over several days have redefined the scale of I/O bandwidth required by image analysis tools. Although the effective bandwidth could, principally, be increased by lossy-to-lossless data compression, this is of limited value in practice due to the high computational demand of current schemes such as JPEG2000 that reach compression throughput of one order of magnitude below that of image acquisition. Here we present a novel lossy-to-lossless data compression scheme with a compression throughput well above 4 GB/s and compression rates and rate-distortion curves competitive with those achieved by JPEG2000 and JP3D.

We present simulations of blood and cancer cell separation in complex microfluidic channels with subcellular resolution, demonstrating unprecedented time to solution, performing at 65.5% of the available 39.4 PetaInstructions/s in the 18, 688 nodes of the Titan supercomputer. These simulations outperform by one to three orders of magnitude the current state of the art in terms of numbers of simulated cells and computational elements. The computational setup emulates the conditions and the geometric complexity of microfluidic experiments and our results reproduce the experimental findings. These simulations provide sub-micron resolution while accessing time scales relevant to engineering designs. We demonstrate an improvement of up to 45X over competing state-of-the-art solvers, thus establishing the frontiers of simulations by particle based methods. Our simulations redefine the role of computational science for the development of microfluidics -- a technology that is becoming as important to medicine as integrated circuits have been to computers.

Background: The meninges, formed by dura, arachnoid and pia mater, cover the central nervous system and provide important barrier functions. Located between arachnoid and pia mater, the cerebrospinal fluid (CSF)-filled subarachnoid space (SAS) features a variety of trabeculae, septae and pillars. Like the arachnoid and the pia mater, these structures are covered with leptomeningeal or meningothelial cells (MECs) that form a barrier between CSF and the parenchyma of the optic nerve (ON). MECs contribute to the CSF proteome through extensive protein secretion. In vitro, they were shown to phagocytose potentially toxic proteins, such as α-synuclein and amyloid beta, as well as apoptotic cell bodies. They therefore may contribute to CSF homeostasis in the SAS as a functional exchange surface. Determining the total area of the SAS covered by these cells that are in direct contact with CSF is thus important for estimating their potential contribution to CSF homeostasis. Methods: Using synchrotron radiation-based micro-computed tomography (SRµCT), two 0.75 mm-thick sections of a human optic nerve were acquired at a resolution of 0.325 µm/pixel, producing images of multiple terabytes capturing the geometrical details of the CSF space. Special-purpose supercomputing techniques were employed to obtain a pixel-accurate morphometric description of the trabeculae and estimate internal volume and surface area of the ON SAS. Results: In the bulbar segment, the ON SAS microstructure is shown to amplify the MECs surface area up to 4.85-fold compared to an “empty” ON SAS, while just occupying 35% of the volume. In the intraorbital segment, the microstructure occupies 35% of the volume and amplifies the ON SAS area 3.24-fold. Conclusions: We provided for the first time an estimation of the interface area between CSF and MECs. This area is of importance for estimating a potential contribution of MECs on CSF homeostasis.

Approximated forms of the RII and RIII redistribution matrices are frequently applied to simplify the numerical solution of the radiative transfer problem for polarized radiation, taking partial frequency redistribution (PRD) effects into account. A widely used approximation for RIII is to consider its expression under the assumption of complete frequency redistribution (CRD) in the observer frame (RIII CRD). The adequacy of this approximation for modeling the intensity profiles has been firmly established. By contrast, its suitability for modeling scattering polarization signals has only been analyzed in a few studies, considering simplified settings. In this work, we aim at quantitatively assessing the impact and the range of validity of the RIII CRD approximation in the modeling of scattering polarization. Methods. We first present an analytic comparison between RIII and RIII CRD. We then compare the results of radiative transfer calculations, out of local thermodynamic equilibrium, performed with RIII and RIII CRD in realistic 1D atmospheric models. We focus on the chromospheric Ca i line at 4227 A and on the photospheric Sr i line at 4607 A.