Efficient, Unbiased Quality Assurance Of Automated Tissue Analysis Applicable To Daily Pathology Practice

Introduction/ Background Quantification of tissue biomarkers is increasingly demanded for diagnosis and is commonly performed by expert pathologists using microscopy of stained tissue at high magnification. This manual scoring is a reasonably fast, supervised procedure, but it suffers from inter- and intra-observer differences due to a) differences in selection of regions of interest, b) differences in quantity estimation, c) intra-tissue variability of biomarker expression. Computers and whole slide microscopy scanners have made it feasible to perform high-capacity analysis of high resolution images of tissue. Image analysis (IA) enables better reproducibility, but conversely, the unsupervised analysis introduces challenges regarding accuracy. Furthermore, borderline cases will always have to be rigorously inspected by pathologists. Many IA evaluation methods exist, but for pathology, a supervised comparison of experimental segmentation to an appropriately obtained standard criterion is the optimal strategy. The production of standard criterion necessitates evaluation of whole slide images to eliminate any possible region sampling bias while inter- and intra- observer bias can only be minimized by replacing any manual estimates by objective measurements. A logical step is thus to change the task of the pathologist from quantity estimation to verifying the output an automated procedure reports. Still, verification of entire tissue slides is in daily pathology practice too time-consuming. To minimize the workload pathology is turning to stereological methods which aim to efficiently quantify matter unbiasedly and have been proved useful for supervised validation of automated analysis for Ki67 scoring of breast cancer. However, the workload still needs to be reduced to a level comparable to the manual scoring procedure. Aims We aim to enable high accuracy, objective evaluation of automated image analysis with a workload and workflow feasible for daily pathology practice. This regards both production of reference data for image analysis tool calibration and continuous quality control inspection of borderline cases. Methods This study investigates proportionate sampling, a very efficient stereological sampling scheme utilizing weighted sampling of regions of automated image analysis for manual evaluation of automated IA. The sampling of regions to be inspected by a pathologist draws upon the IA to assign probability weights to all regions. This results in a highly efficient, unbiased sampling and quality assurance estimate for the automated image analysis. Results Presented here is proof-of-concept of an efficient, unbiased image analysis evaluation methodology. The task of the pathologist is changed from quantity estimation to instead annotate discrepancies between the output from the IA and the tissue in a few sampled regions. From the annotations an unbiased quality assurance estimate of the IA can be estimated including levels of accuracy obtainable and expected workloads. This confirms that the stereological proportionate sampling enables manual verification of automated whole slide image analysis for unbiased reference dataset creation and quality control inspection in borderline cases. Furthermore, the methodology is easily integrated into both image analysis platforms for production of reference data sets and laboratory information systems for daily pathology practices.

Formation of Composite Endothelial Cell–Mesenchymal Stem Cell Islets: A Novel Approach to Promote Islet Revascularization

OBJECTIVE—Mesenchymal stem cells (MSCs) contribute to endothelial cell (EC) migration by producing proteases, thereby paving the way into the tissues for ECs. MSCs were added to our previously described composite EC islets as a potential means to improve their capacity for islet angiogenesis

Registration of ‘Quest’ spring malting barley with improved resistance to Fusarium head blight

‘Quest’ (Reg No. CV-348, PI 663183) is a spring, six-rowed, malting barley (Hordeum vulgare L.) released by the Minnesota Agricultural Experiment Station in January 2010 on the basis of its improved resistance to Fusarium head blight [FHB; caused by Fusarium graminearum Schwabe; teleomorph Gibberella zeae (Schwein) Petch]. Quest was developed over three breeding cycles of selection for yield, malting quality, and FHB resistance. Disease resistance traces to the Midwest cultivar MNBrite and the two-rowed accession from China Zhedar1. Quest has about half the level of disease and about 40% less of the associated mycotoxin, deoxynivalenol, compared to the historically important cultivar in the region ‘Robust’. Quest is similar in yield to the current dominant varieties in the region and was approved as a malting variety by the American Malting Barley Association

Impact of Mechanical Unloading on Microvasculature and Associated Central Remodeling Features of the Failing Human Heart

ObjectivesThis study investigates alterations in myocardial microvasculature, fibrosis, and hypertrophy before and after mechanical unloading of the failing human heart.BackgroundRecent studies demonstrated the pathophysiologic importance and significant mechanistic links among microvasculature, fibrosis, and hypertrophy during the cardiac remodeling process. The effect of left ventricular assist device (LVAD) unloading on cardiac endothelium and microvasculature is unknown, and its influence on fibrosis and hypertrophy regression to the point of atrophy is controversial.MethodsHemodynamic data and left ventricular tissue were collected from patients with chronic heart failure at LVAD implant and explant (n = 15) and from normal donors (n = 8). New advances in digital microscopy provided a unique opportunity for comprehensive whole-field, endocardium-to-epicardium evaluation for microvascular density, fibrosis, cardiomyocyte size, and glycogen content. Ultrastructural assessment was done with electron microscopy.ResultsHemodynamic data revealed significant pressure unloading with LVAD. This was accompanied by a 33% increase in microvascular density (p = 0.001) and a 36% decrease in microvascular lumen area (p = 0.028). We also identified, in agreement with these findings, ultrastructural and immunohistochemical evidence of endothelial cell activation. In addition, LVAD unloading significantly increased interstitial and total collagen content without any associated structural, ultrastructural, or metabolic cardiomyocyte changes suggestive of hypertrophy regression to the point of atrophy and degeneration.ConclusionsThe LVAD unloading resulted in increased microvascular density accompanied by increased fibrosis and no evidence of cardiomyocyte atrophy. These new insights into the effects of LVAD unloading on microvasculature and associated key remodeling features might guide future studies of unloading-induced reverse remodeling of the failing human heart

Membranes with the Same Ion Channel Populations but Different Excitabilities

Electrical signaling allows communication within and between different tissues and is necessary for the survival of multicellular organisms. The ionic transport that underlies transmembrane currents in cells is mediated by transporters and channels. Fast ionic transport through channels is typically modeled with a conductance-based formulation that describes current in terms of electrical drift without diffusion. In contrast, currents written in terms of drift and diffusion are not as widely used in the literature in spite of being more realistic and capable of displaying experimentally observable phenomena that conductance-based models cannot reproduce (e.g. rectification). The two formulations are mathematically related: conductance-based currents are linear approximations of drift-diffusion currents. However, conductance-based models of membrane potential are not first-order approximations of drift-diffusion models. Bifurcation analysis and numerical simulations show that the two approaches predict qualitatively and quantitatively different behaviors in the dynamics of membrane potential. For instance, two neuronal membrane models with identical populations of ion channels, one written with conductance-based currents, the other with drift-diffusion currents, undergo transitions into and out of repetitive oscillations through different mechanisms and for different levels of stimulation. These differences in excitability are observed in response to excitatory synaptic input, and across different levels of ion channel expression. In general, the electrophysiological profiles of membranes modeled with drift-diffusion and conductance-based models having identical ion channel populations are different, potentially causing the input-output and computational properties of networks constructed with these models to be different as well. The drift-diffusion formulation is thus proposed as a theoretical improvement over conductance-based models that may lead to more accurate predictions and interpretations of experimental data at the single cell and network levels