Automated tumor analysis for molecular profiling in lung cancer

The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics.

Self-consistent modelling of line-driven hot-star winds with Monte Carlo radiation hydrodynamics

Radiative pressure exerted by line interactions is a prominent driver of outflows in astrophysical systems, being at work in the outflows emerging from hot stars or from the accretion discs of cataclysmic variables, massive young stars and active galactic nuclei. In this work, a new radiation hydrodynamical approach to model line-driven hot-star winds is presented. By coupling a Monte Carlo radiative transfer scheme with a finite volume fluid dynamical method, line-driven mass outflows may be modelled self-consistently, benefiting from the advantages of Monte Carlo techniques in treating multiline effects, such as multiple scatterings, and in dealing with arbitrary multidimensional configurations. In this work, we introduce our approach in detail by highlighting the key numerical techniques and verifying their operation in a number of simplified applications, specifically in a series of self-consistent, one-dimensional, Sobolev-type, hot-star wind calculations. The utility and accuracy of our approach are demonstrated by comparing the obtained results with the predictions of various formulations of the so-called CAK theory and by confronting the calculations with modern sophisticated techniques of predicting the wind structure. Using these calculations, we also point out some useful diagnostic capabilities our approach provides. Finally, we discuss some of the current limitations of our method, some possible extensions and potential future applications.

Gamma-ray diagnostics of Type Ia supernovae. Predictions of observables from three-dimensional modeling

Context. Although the question of progenitor systems and detailed explosion mechanisms still remains a matter of discussion, it is commonly believed that Type Ia supernovae (SNe Ia) are production sites of large amounts of radioactive nuclei. Even though the gamma-ray emission due to radioactive decays is responsible for powering the light curves of SNe Ia, gamma rays themselves are of particular interest as a diagnostic tool because they directly lead to deeper insight into the nucleosynthesis and the kinematics of these explosion events. Aims: We study the evolution of gamma-ray line and continuum emission of SNe Ia with the objective of analyzing the relevance of observations in this energy range. We seek to investigate the chances for the success of future MeV missions regarding their capabilities for constraining the intrinsic properties and the physical processes of SNe Ia. Methods: Focusing on two of the most broadly discussed SN Ia progenitor scenarios - a delayed detonation in a Chandrasekhar-mass white dwarf (WD) and a violent merger of two WDs - we used three-dimensional explosion models and performed radiative transfer simulations to obtain synthetic gamma-ray spectra. Both chosen models produce the same mass of 56Ni and have similar optical properties that are in reasonable agreement with the recently observed supernova SN 2011fe. We examine the gamma-ray spectra with respect to their distinct features and draw connections to certain characteristics of the explosion models. Applying diagnostics, such as line and hardness ratios, the detection prospects for future gamma-ray missions with higher sensitivities in the MeV energy range are discussed. Results: In contrast to the optical regime, the gamma-ray emission of our two chosen models proves to be quite different. The almost direct connection of the emission of gamma rays to fundamental physical processes occurring in SNe Ia permits additional constraints concerning several explosion model properties that are not easily accessible within other wavelength ranges. Proposed future MeV missions such as GRIPS will resolve all spectral details only for nearby SNe Ia, but hardness ratio and light curve measurements still allow for a distinction of the two different models at 10 Mpc and 16 Mpc for an exposure time of 106 s. The possibility of detecting the strongest line features up to the Virgo distance will offer the opportunity to build up a first sample of SN Ia detections in the gamma-ray energy range and underlines the importance of future space observatories for MeV gamma rays.

Abnormal Glycogen Storage by Retinal Neurons in Diabetes

PURPOSE: It is widely held that neurons of the central nervous system do not store glycogen and that accumulation of the polysaccharide may cause neurodegeneration. Since primary neural injury occurs in diabetic retinopathy, we examined neuronal glycogen status in the retina of streptozotocin-induced diabetic and control rats.

METHODS: Glycogen was localized in eyes of streptozotocin-induced diabetic and control rats using light microscopic histochemistry and electron microscopy, and correlated with immunohistochemical staining for glycogen phosphorylase and phosphorylated glycogen synthase (pGS).

RESULTS: Electron microscopy of 2-month-old diabetic rats (n = 6) showed massive accumulations of glycogen in the perinuclear cytoplasm of many amacrine neurons. In 4-month-old diabetic rats (n = 11), quantification of glycogen-engorged amacrine cells showed a mean of 26 cells/mm of central retina (SD ± 5), compared to 0.5 (SD ± 0.2) in controls (n = 8). Immunohistochemical staining for glycogen phosphorylase revealed strong expression in amacrine and ganglion cells of control retina, and increased staining in cell processes of the inner plexiform layer in diabetic retina. In control retina, the inactive pGS was consistently sequestered within the cell nuclei of all retinal neurons and the retinal pigment epithelium (RPE), but in diabetics nuclear pGS was reduced or lost in all classes of retinal cell except the ganglion cells and cone photoreceptors.

CONCLUSIONS: The present study identifies a large population of retinal neurons that normally utilize glycogen metabolism but show pathologic storage of the polysaccharide during uncontrolled diabetes.

Control of ionization and dissociation of H2+ by elliptically polarized ultra-short VUV laser pulses

Resonance-enhanced multiphoton ionization of H₂ ⁺ exposed to elliptically polarized VUV laser pulses is investigated. Differential cross sections for nuclei and electron are obtained using numerical solutions of the time-dependent Schrödinger equation. In this work in progress, we explore the dependence of the dissociative ionization observables with the polarization of the light.