A TMA De-Arraying Method for High Throughput Biomarker Discovery in Tissue Research

Background: Tissue MicroArrays (TMAs) represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide) is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide.

Methodology: This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap.

Conclusion: This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores), 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores) with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.

Simple method for the rapid simultaneous screening of photocatalytic activity over multiple positions of self-cleaning films

An intelligent ink, previously shown to be capable of rapidly assessing photocatalytic activity, was simply applied via a felt-pen onto a commercially available piece of Activ (TM) self-cleaning glass. The ink, comprising of redox dye resazurin and the sacrificial electron donor glycerol within an aqueous hydroxy ethyl cellulose (HEC) polymer media, was photocatalytically degraded in a two-step process. The key initial stage was the photo-reductive conversion of resazurin to resorufin, whereby a colour change from blue to pink occurred. The latter stage was the subsequent photo-reduction of the resorufin, where a slower change from pink to colourless was seen. Red and green components of red-green-blue colour extracted from flat-bed scanner digital images of resazurin ink coated photocatalytic films at intervals during the photocatalysis reaction were inversely proportional to the changes seen via UV-visible absorption spectroscopy and indicative of reaction kinetics. A 3 x 3 grid of intelligent ink was drawn onto a piece of Activ (TM) and a glass blank. The photocatalysis reaction was monitored solely by flat-bed digital scanning. Red-green-blue values of respective positions on the grid were extracted using a custom-built program entitled RGB Extractor (c). The program was capable of extracting a number of 5 x 5 pixel averages of red-green-blue components simultaneously. Allocation of merely three coordinates allowed for the automatic generation of a grid, with scroll-bars controlling the number of positions to be extracted on the grid formed. No significant change in red and green components for any position on the glass blank was observed; however, the Activ (TM) film displayed a homogenous photo-reduction of the dye, reaching maxima in red and minima in green components in 23 +/- 3 and 14 +/- 2 min, respectively. A compositionally graded N-doped titania film synthesised in house via a combinatorial APCVD reaction was also photocatalytically tested by this method where 247 positions on a 13 x 19 grid were simultaneously analysed. The dramatic variation in photocatalysis observed was rapidly quantified for all positions (2-3 hours) allowing for correlations to be made between thicknesses and N : Ti% compositions attained from Swanepoel and WDX analysis, respectively. N incorporation within this system was found to be detrimental to film activity for the photocatalysis reaction of intelligent ink under 365 nm light.

Hand-related rather than goal-related source of gaze-dependent errors in memory-guided reaching

Mechanisms for visuospatial cognition are often inferred directly from errors in behavioral reports of remembered target direction. For example, gaze-centered target representations for reach were first inferred from reach overshoots of target location relative to gaze. Here, we report evidence for the hypothesis that these gaze-dependent reach errors stem predominantly from misestimates of hand rather than target position, as was assumed in all previous studies. Subjects showed typical gaze-dependent overshoots in complete darkness, but these errors were entirely suppressed by continuous visual feedback of the finger. This manipulation could not affect target representations, so the suppressed gaze-dependent errors must have come from misestimates of hand position, likely arising in a gaze-dependent transformation of hand position signals into visual coordinates. This finding has broad implications for any task involving localization of visual targets relative to unseen limbs, in both healthy individuals and patient populations, and shows that response-related transformations cannot be ignored when deducing the sources of gaze-related errors.

Spatial updating across saccades during manual interception

We studied the effect of intervening saccades on the manual interception of a moving target. Previous studies suggest that stationary reach goals are coded and updated across saccades in gaze-centered coordinates, but whether this generalizes to interception is unknown. Subjects (n = 9) reached to manually intercept a moving target after it was rendered invisible. Subjects either fixated throughout the trial or made a saccade before reaching (both fixation points were in the range of -10° to 10°). Consistent with previous findings and our control experiment with stationary targets, the interception errors depended on the direction of the remembered moving goal relative to the new eye position, as if the target is coded and updated across the saccade in gaze-centered coordinates. However, our results were also more variable in that the interception errors for more than half of our subjects also depended on the goal direction relative to the initial gaze direction. This suggests that the feedforward transformations for interception differ from those for stationary targets. Our analyses show that the interception errors reflect a combination of biases in the (gaze-centered) representation of target motion and in the transformation of goal information into body-centered coordinates for action.

Exceptional Behavior over the Whole Adsorption-Storage-Delivery Cycle for NO in Porous Metal Organic Frameworks

Two porous metal organic frameworks (MOFs), [M-2(C8H2O6)(H2O)(2)] center dot 8H(2)O (M = Co, Ni), perform exceptionally well for the adsorption, storage, and water-triggered delivery of the biologically important gas nitric oxide. Adsorption and powder X-ray diffraction studies indicate that each coordinatively unsaturated metal atom in the structure coordinates to one NO molecule. All of the stored gas is available for delivery even after the material has been stored for several months. The combination of extremely high adsorption capacity (similar to 7 mmol of NO/g of MOF) and good storage stability is ideal for the preparation of NO storage solids. However, most important is that the entire reservoir of stored gas is recoverable on contact with a simple trigger (moisture). The activity of the NO storage materials is proved in myography experiments showing that the NO-releasing MOFs cause relaxation of porcine arterial tissue.

Demonstrating the Transferability and the Descriptive Power of Sketch-Map

Increasingly, it is recognized that new automated forms of analysis are required to understand the high-dimensional output obtained from atomistic simulations. Recently, we introduced a new dimensionality reduction algorithm, sketch-map, that was designed specifically to work with data from molecular dynamics trajectories. In what follows, we provide more details on how this algorithm works and on how to set its parameters. We also test it on two well-studied Lennard-Jones clusters and show that the coordinates we extract using this algorithm are extremely robust. In particular, we demonstrate that the coordinates constructed for one particular Lennard-Jones cluster can be used to describe the configurations adopted by a second, different cluster and even to tell apart different phases of bulk Lennard-Jonesium.

A self-learning algorithm for biased molecular dynamics

A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias potential in terms of a patchwork of one-dimensional, locally valid collective coordinates. These collective coordinates are obtained from trajectory analyses so that they adapt to any new features encountered during the simulation. We show how this methodology can be used to enhance sampling in real chemical systems citing examples both from the physics of clusters and from the biological sciences.

The Origin of Phragmoplast Asymmetry

The phragmoplast coordinates cytokinesis in plants [1]. It directs vesicles to the midzone, the site where they coalesce to form the new cell plate. Failure in phragmoplast function results in aborted or incomplete cytokinesis leading to embryo lethality, morphological defects, or multinucleate cells [2, 3]. The asymmetry of vesicular traffic is regulated by microtubules [1, 4, 5, 6], and the current model suggests that this asymmetry is established and maintained through treadmilling of parallel microtubules. However, we have analyzed the behavior of microtubules in the phragmoplast using live-cell imaging coupled with mathematical modeling and dynamic simulations and report that microtubules initiate randomly in the phragmoplast and that the majority exhibit dynamic instability with higher turnover rates nearer to the midzone. The directional transport of vesicles is possible because the majority of the microtubules polymerize toward the midzone. Here, we propose the first inclusive model where microtubule dynamics and phragmoplast asymmetry are consistent with the localization and activity of proteins known to regulate microtubule assembly and disassembly.

The Role of Arg228 in the phosphorylation of galactokinase: The mechanism of GHMP kinases by QM/MM studies

GHMP kinases are a group of structurally-related small molecule kinases. They have been found in all kingdoms of life and are mostly responsible for catalysing the ATP-dependent phosphorylation of intermediary metabolites. Although the GHMP kinases are of clinical, pharmaceutical and biotechnological importance, the mechanism of GHMP-kinases is controversial. A catalytic base mechanism was suggested for mevalonate kinase that has a structural feature of the ?-phosphate of ATP close to an aspartate residue; however, for one GHMP member, homoserine kinase, where the residue acting as general base is absent, a direct phosphorylation mechanism was suggested. Furthermore, it has been proposed by some authors that all the GHMP kinases function via the direct phosphorylation mechanism. This controversy in mechanism has limited our ability to exploit these enzymes as drug targets and in biotechnology. Here the phosphorylation reaction mechanism of the human galactokinase, a member of GHMP kinase was investigated using molecular dynamics simulations and density functional theory-based QM/MM calculations (B3LYP-D/AMBER99). The reaction coordinates were localized by potential energy scan using adiabatic mapping method. Our results indicate that a highly conserved Glu174 captures Arg105 to the proximity of the a-phosphate of ATP forming a H-bond network, therefore the mobility of ATP in the large oxyanion hole is restricted. Arg228 functions to stabilize the negative charge developed at the ß,?-bridging oxygen of the ATP during bond cleavage. The reaction occurs via direct phosphorylation mechanism and the Asp186 in proximity of ATP does not directly participate in the reaction pathway. Since Arg228 is not conserved among GHMP kinases, reagents which form interactions with Arg228, and therefore can interrupt its function in phosphorylation may be developed into potential selective inhibitors for galactokinase.

Orphan receptor IL-17RD tunes IL-17A signalling and is required for neutrophilia

Interleukin-17A, the prototypical member of the interleukin-17 cytokine family, coordinates local tissue inflammation by recruiting neutrophils to sites of infection. Dysregulation of interleukin-17 signalling has been linked to the pathogenesis of inflammatory diseases and autoimmunity. The interleukin-17 receptor family members (A-E) have a broad range of functional effects in immune signalling yet no known role has been described for the remaining orphan receptor, interleukin-17 receptor D, in regulating interleukin-17A-induced signalling pathways. Here we demonstrate that interleukin-17 receptor D can differentially regulate the various pathways employed by interleukin-17A. Neutrophil recruitment, in response to in vivo administration of interleukin-17A, is abolished in interleukin-17 receptor D-deficient mice, correlating with reduced interleukin-17A-induced activation of p38 mitogen-activated protein kinase and expression of the neutrophil chemokine MIP-2. In contrast, interleukin-17 receptor D deficiency results in enhanced interleukin-17A-induced activation of nuclear factor-kappa B and interleukin-6 and keratinocyte chemoattractant expression. Interleukin-17 receptor D disrupts the interaction of Act1 and TRAF6 causing differential regulation of nuclear factor-kappa B and p38 mitogen-activated protein kinase signalling pathways. © 2012 Macmillan Publishers Limited. All rights reserved.

The nucleus of Comet 67P/Churyumov-Gerasimenko. A new shape model and thermophysical analysis

Context. Comet 67P/Churyumov-Gerasimenko is the target of the European Space Agency Rosetta spacecraft rendez-vous mission. Detailed physical characteristation of the comet before arrival is important for mission planning as well as providing a test bed for ground-based observing and data-analysis methods. Aims: To conduct a long-term observational programme to characterize the physical properties of the nucleus of the comet, via ground-based optical photometry, and to combine our new data with all available nucleus data from the literature. Methods: We applied aperture photometry techniques on our imaging data and combined the extracted rotational lightcurves with data from the literature. Optical lightcurve inversion techniques were applied to constrain the spin state of the nucleus and its broad shape. We performed a detailed surface thermal analysis with the shape model and optical photometry by incorporating both into the new Advanced Thermophysical Model (ATPM), along with all available Spitzer 8-24 μm thermal-IR flux measurements from the literature. Results: A convex triangular-facet shape model was determined with axial ratios b/a = 1.239 and c/a = 0.819. These values can vary by as much as 7% in each axis and still result in a statistically significant fit to the observational data. Our best spin state solution has Psid = 12.76137 ± 0.00006 h, and a rotational pole orientated at Ecliptic coordinates λ = 78°(±10°), β = + 58°(±10°). The nucleus phase darkening behaviour was measured and best characterized using the IAU HG system. Best fit parameters are: G = 0.11 ± 0.12 and HR(1,1,0) = 15.31 ± 0.07. Our shape model combined with the ATPM can satisfactorily reconcile all optical and thermal-IR data, with the fit to the Spitzer 24 μm data taken in February 2004 being exceptionally good. We derive a range of mutually-consistent physical parameters for each thermal-IR data set, including effective radius, geometric albedo, surface thermal inertia and roughness fraction. Conclusions: The overall nucleus dimensions are well constrained and strongly imply a broad nucleus shape more akin to comet 9P/Tempel 1, rather than the highly elongated or "bi-lobed" nuclei seen for comets 103P/Hartley 2 or 8P/Tuttle. The derived low thermal inertia of

Status of GPCR modeling and docking as reflected by community-wide GPCR Dock 2010 assessment

The community-wide GPCR Dock assessment is conducted to evaluate the status of molecular modeling and ligand docking for human G protein-coupled receptors. The present round of the assessment was based on the recent structures of dopamine D3 and CXCR4 chemokine receptors bound to small molecule antagonists and CXCR4 with a synthetic cyclopeptide. Thirty-five groups submitted their receptor-ligand complex structure predictions prior to the release of the crystallographic coordinates. With closely related homology modeling templates, as for dopamine D3 receptor, and with incorporation of biochemical and QSAR data, modern computational techniques predicted complex details with accuracy approaching experimental. In contrast, CXCR4 complexes that had less-characterized interactions and only distant homology to the known GPCR structures still remained very challenging. The assessment results provide guidance for modeling and crystallographic communities in method development and target selection for further expansion of the structural coverage of the GPCR universe.

Power Modeling and Capping for Heterogeneous ARM/FPGA SoCs

Low-power processors and accelerators that were originally designed for the embedded systems market are emerging as building blocks for servers. Power capping has been actively explored as a technique to reduce the energy footprint of high-performance processors. The opportunities and limitations of power capping on the new low-power processor and accelerator ecosystem are less understood. This paper presents an efficient power capping and management infrastructure for heterogeneous SoCs based on hybrid ARM/FPGA designs. The infrastructure coordinates dynamic voltage and frequency scaling with task allocation on a customised Linux system for the Xilinx Zynq SoC. We present a compiler-assisted power model to guide voltage and frequency scaling, in conjunction with workload allocation between the ARM cores and the FPGA, under given power caps. The model achieves less than 5% estimation bias to mean power consumption. In an FFT case study, the proposed power capping schemes achieve on average 97.5% of the performance of the optimal execution and match the optimal execution in 87.5% of the cases, while always meeting power constraints.

A Lagrangian approach for modeling road collisions using second-order models of traffic flow

In [M. Herty, A. Klein, S. Moutari, V. Schleper, and G. Steinaur, IMA J. Appl. Math., 78(5), 1087–1108, 2013] and [M. Herty and V. Schleper, ZAMM J. Appl. Math. Mech., 91, 763–776, 2011], a macroscopic approach, derived from fluid-dynamics models, has been introduced to infer traffic conditions prone to road traffic collisions along highways’ sections. In these studies, the governing equations are coupled within an Eulerian framework, which assumes fixed interfaces between the models. A coupling in Lagrangian coordinates would enable us to get rid of this (not very realistic) assumption. In this paper, we investigate the well-posedness and the suitability of the coupling of the governing equations within the Lagrangian framework. Further, we illustrate some features of the proposed approach through some numerical simulations.

Predicting forest attributes In southeast Alaska using artificial neural networks

Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.