Defining the E-Cadherin repressor interactome in epithelial-mesenchymal transition : the PMC42 model as a case study

Epithelial-mesenchymal transition (EMT) is a feature of migratory cellular processes in all stages of life, including embryonic development and wound healing. Importantly, EMT features cluster with disease states such as chronic fibrosis and cancer. The dissolution of the E-cadherin-mediated adherens junction (AJ) is a key preliminary step in EMT and may occur early or late in the growing epithelial tumour. This is a first step for tumour cells towards stromal invasion, intravasation, extravasation and distant metastasis. The AJ may be inactivated in EMT by directed E-cadherin cleavage; however, it is increasingly evident that the majority of AJ changes are transcriptional and mediated by an expanding group of transcription factors acting directly or indirectly to repress E-cadherin expression. A review of the current literature has revealed that these factors may regulate each other in a hierarchical pattern where Snail1 (formerly Snail) and Snail2 (formerly Slug) are initially induced, leading to the activation of Zeb family members, TCF3, TCF4, Twist, Goosecoid and FOXC2. Within this general pathway, many inter-regulatory relationships have been defined which may be important in maintaining the EMT phenotype. This may be important given the short half-life of Snail1 protein. We have investigated these inter-regulatory relationships in the mesenchymal breast carcinoma cell line PMC42 (also known as PMC42ET) and its epithelial derivative, PMC42LA. This review also discusses several newly described regulators of E-cadherin repressors including oestrogen receptor-α and new discoveries in hypoxia- and growth factor-induced EMT. Finally, we evaluated how these findings may influence approaches to current cancer treatment.

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

Plasma-enabled, catalyst-free growth of carbon nanotubes on mechanically-written Si features with arbitrary shape

Simple, rapid, catalyst-free synthesis of complex patterns of long, vertically aligned multiwalled carbon nanotubes, strictly confined within mechanically-written features on a Si(1 0 0) surface is reported. It is shown that dense arrays of the nanotubes can nucleate and fully fill the features when the low-temperature microwave plasma is in a direct contact with the surface. This eliminates additional nanofabrication steps and inevitable contact losses in applications associated with carbon nanotube patterns. Using metal catalyst has long been considered essential for the nucleation and growth of surface-supported carbon nanotubes (CNTs) [1] and [2]. Only very recently, the possibility of CNT growth using non-metallic (e.g., oxide [3] and SiC [4]) catalysts or artificially created carbon-enriched surface layers [5] has been demonstrated. However, successful integration of carbon nanostructures into Si-based nanodevice platforms requires catalyst-free growth, as the catalyst nanoparticles introduce contact losses, and their catalytic activity is very difficult to control during the growth [6]. Furthermore, in many applications in microfluidics, biological and molecular filters, electronic, sensor, and energy conversion nanodevices, the CNTs need to be arranged in specific complex patterns [7] and [8]. These patterns need to contain the basic features (e.g., lines and dots) written using simple procedures and fully filled with dense arrays of high-quality, straight, yet separated nanotubes. In this paper, we report on a completely metal or oxide catalyst-free plasma-based approach for the direct and rapid growth of dense arrays of long vertically-aligned multi-walled carbon nanotubes arranged into complex patterns made of various combinations of basic features on a Si(1 0 0) surface written using simple mechanical techniques. The process was conducted in a plasma environment [9] and [10] produced by a microwave discharge which typically generates the low-temperature plasmas at the discharge power below 1 kW [11]. Our process starts from mechanical writing (scribing) a pattern of arbitrary features on pre-treated Si(1 0 0) wafers. Before and after the mechanical feature writing, the Si(1 0 0) substrates were cleaned in an aqueous solution of hydrofluoric acid for 2 min to remove any possible contaminations (such as oil traces which could decompose to free carbon at elevated temperatures) from the substrate surface. A piece of another silicon wafer cleaned in the same way as the substrate, or a diamond scriber were used to produce the growth patterns by a simple arbitrary mechanical writing, i.e., by making linear scratches or dot punctures on the Si wafer surface. The results were the same in both cases, i.e., when scratching the surface by Si or a diamond scriber. The procedure for preparation of the substrates did not involve any possibility of external metallic contaminations on the substrate surface. After the preparation, the substrates were loaded into an ASTeX model 5200 chemical vapour deposition (CVD) reactor, which was very carefully conditioned to remove any residue contamination. The samples were heated to at least 800 °C to remove any oxide that could have formed during the sample loading [12]. After loading the substrates into the reactor chamber, N2 gas was supplied into the chamber at the pressure of 7 Torr to ignite and sustain the discharge at the total power of 200 W. Then, a mixture of CH4 and 60% of N2 gases were supplied at 20 Torr, and the discharge power was increased to 700 W (power density of approximately 1.49 W/cm3). During the process, the microwave plasma was in a direct contact with the substrate. During the plasma exposure, no external heating source was used, and the substrate temperature (∼850 °C) was maintained merely due to the plasma heating. The features were exposed to a microwave plasma for 3–5 min. A photograph of the reactor and the plasma discharge is shown in Fig. 1a and b.

Carbon saturation of arrays of Ni catalyst nanoparticles of different size and pattern uniformity on a silicon substrate

The kinetics of saturation of Ni catalyst nanoparticle patterns of the three different degrees of order, used as a model for the growth of carbon nanotips on Si, is investigated numerically using a complex model that involves surface diffusion and ion motion equations. It is revealed that Ni catalyst patterns of different degrees of order, with Ni nanoparticle sizes up to 12.5 nm, exhibit different kinetics of saturation with carbon on the Si surface. It is shown that in the cases examined (surface coverage in the range of 1-50%, highly disordered Ni patterns) the relative pattern saturation factor calculated as the ratio of average incubation times for the processes conducted in the neutral and ionized gas environments reaches 14 and 3.4 for Ni nanoparticles of 2.5 and 12.5 nm, respectively. In the highly ordered Ni patterns, the relative pattern saturation factor reaches 3 for nanoparticles of 2.5 nm and 2.1 for nanoparticles of 12.5 nm. Thus, more simultaneous saturation of Ni catalyst nanoparticles of sizes in the range up to 12.5 nm, deposited on the Si substrate, can be achieved in the low-temperature plasma environment than with the neutral gas-based process.

A hierarchical model of goal directed navigation selects trajectories in a visual environment

We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model’s flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat’s point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond.

Refining a teaching pattern: Reflection around artefacts

This book is about understanding the nature and application of reflection in higher education. It provides a theoretical model to guide the implementation of reflective learning and reflective practice across multiple disciplines and international contexts in higher education. The book presents research into the ways in which reflection is both considered and implemented in different ways across different professional disciplines, while maintaining a common purpose to transform and improve learning and/or practice. Chapter 13 'Refining a Teaching Pattern: Reflection Around Artefacts' explores reflective practices of an artefact, in this case fashion design garment samples.

A computational model for BMP movement in sea urchin embryos

Bone morphogen proteins (BMPs) are distributed along a dorsal-ventral (DV) gradient in many developing embryos. The spatial distribution of this signaling ligand is critical for correct DV axis specification. In various species, BMP expression is spatially localized, and BMP gradient formation relies on BMP transport, which in turn requires interactions with the extracellular proteins Short gastrulation/Chordin (Chd) and Twisted gastrulation (Tsg). These binding interactions promote BMP movement and concomitantly inhibit BMP signaling. The protease Tolloid (Tld) cleaves Chd, which releases BMP from the complex and permits it to bind the BMP receptor and signal. In sea urchin embryos, BMP is produced in the ventral ectoderm, but signals in the dorsal ectoderm. The transport of BMP from the ventral ectoderm to the dorsal ectoderm in sea urchin embryos is not understood. Therefore, using information from a series of experiments, we adapt the mathematical model of Mizutani et al. (2005) and embed it as the reaction part of a one-dimensional reaction–diffusion model. We use it to study aspects of this transport process in sea urchin embryos. We demonstrate that the receptor-bound BMP concentration exhibits dorsally centered peaks of the same type as those observed experimentally when the ternary transport complex (Chd-Tsg-BMP) forms relatively quickly and BMP receptor binding is relatively slow. Similarly, dorsally centered peaks are created when the diffusivities of BMP, Chd, and Chd-Tsg are relatively low and that of Chd-Tsg-BMP is relatively high, and the model dynamics also suggest that Tld is a principal regulator of the system. At the end of this paper, we briefly compare the observed dynamics in the sea urchin model to a version that applies to the fly embryo, and we find that the same conditions can account for BMP transport in the two types of embryos only if Tld levels are reduced in sea urchin compared to fly.

A constitutive model for mechanical response characterization of pumpkin peel and flesh tissues under tensile and compressive loadings

Enhancing quality of food products and reducing volume of waste during mechanical operations of food industry requires a comprehensive knowledge of material response under loadings. While research has focused on mechanical response of food material, the volume of waste after harvesting and during processing stages is still considerably high in both developing and developed countries. This research aims to develop and evaluate a constitutive model of mechanical response of tough skinned vegetables under postharvest and processing operations. The model focuses on both tensile and compressive properties of pumpkin flesh and peel tissues where the behaviours of these tissues vary depending on various factors such as rheological response and cellular structure. Both elastic and plastic response of tissue were considered in the modelling process and finite elasticity combined with pseudo elasticity theory was applied to generate the model. The outcomes were then validated using the published results of experimental work on pumpkin flesh and peel under uniaxial tensile and compression. The constitutive coefficients for peel under tensile test was α = 25.66 and β = −18.48 Mpa and for flesh α = −5.29 and β = 5.27 Mpa. under compression the constitutive coefficients were α = 4.74 and β = −1.71 Mpa for peel and α = 0.76 and β = −1.86 Mpa for flesh samples. Constitutive curves predicted the values of force precisely and close to the experimental values. The curves were fit for whole stress versus strain curve as well as a section of curve up to bio yield point. The modelling outputs had presented good agreement with the empirical values and the constructive curves exhibited a very similar pattern to the experimental curves. The presented constitutive model can be applied next to other agricultural materials under loading in future.

Decision making in social neurobiological systems modeled as transitions in dynamic pattern formation

Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V(x)=−k1x+k2ax2/2−bx4/4+x6/6, where k1 and k2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise εt, leading to the motion equation dx/dt = −dV/dx+Q0.5εt, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.

A model for reflection in the pedagogic field of higher education

This chapter provides an introduction to the use of pedagogical patterns in capturing and sharing educational design experience. In higher education, helping students to learn to engage in productive reflection presents a complex set of challenges. Delicate balances must be found: too little structure and support for students’ reflective work can leave them floundering; too much, and some will remain dependent. Moreover, this is a dynamic teaching problem – scaffolding needs to be adjusted as students develop confidence and capability, which they will do at different rates. The model presented in this chapter embraces the three main elements that teachers can legitimately design, or help set in place, to support their students’ reflective activity: good tasks, the right tools, and appropriate divisions of labour. It delineates a complex, shifting architecture of tasks, tools and people, activities and outcomes associated with reflective learning. It shows how the designable elements of this complex mix can be described in patterns and pattern languages, which then become design resources for teachers’ own action, reflection and professional development.

Differential susceptibility to performance degradation across categories of facial emotion - a model confirmation

Patients with a number of psychiatric and neuropathological conditions demonstrate problems in recognising facial expressions of emotion. Research indicating that patients with schizophrenia perform more poorly in the recognition of negative valence facial stimuli than positive valence stimuli has been interpreted as evidence of a negative emotion specific deficit. An alternate explanation rests in the psychometric properties of the stimulus materials. This model suggests that the pattern of impairment observed in schizophrenia may reflect initial discrepancies in task difficulty between stimulus categories, which are not apparent in healthy subjects because of ceiling effects. This hypothesis is tested, by examining the performance of healthy subjects in a facial emotion categorisation task with three levels of stimulus resolution. Results confirm the predictions of the model, showing that performance degrades differentially across emotion categories, with the greatest deterioration to negative valence stimuli. In the light of these results, a possible methodology for detecting emotion specific deficits in clinical samples is discussed.

A simulation model of the within-host dynamics of Plasmodium vivax infection

Background The benign reputation of Plasmodium vivax is at odds with the burden and severity of the disease. This reputation, combined with restricted in vitro techniques, has slowed efforts to gain an understanding of the parasite biology and interaction with its human host. Methods A simulation model of the within-host dynamics of P. vivax infection is described, incorporating distinctive characteristics of the parasite such as the preferential invasion of reticulocytes and hypnozoite production. The developed model is fitted using digitized time-series’ from historic neurosyphilis studies, and subsequently validated against summary statistics from a larger study of the same population. The Chesson relapse pattern was used to demonstrate the impact of released hypnozoites. Results The typical pattern for dynamics of the parasite population is a rapid exponential increase in the first 10 days, followed by a gradual decline. Gametocyte counts follow a similar trend, but are approximately two orders of magnitude lower. The model predicts that, on average, an infected naïve host in the absence of treatment becomes infectious 7.9 days post patency and is infectious for a mean of 34.4 days. In the absence of treatment, the effect of hypnozoite release was not apparent as newly released parasites were obscured by the existing infection. Conclusions The results from the model provides useful insights into the dynamics of P. vivax infection in human hosts, in particular the timing of host infectiousness and the role of the hypnozoite in perpetuating infection.

Topical pattern based document modelling and relevance ranking

For traditional information filtering (IF) models, it is often assumed that the documents in one collection are only related to one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling was proposed to generate statistical models to represent multiple topics in a collection of documents, but in a topic model, topics are represented by distributions over words which are limited to distinctively represent the semantics of topics. Patterns are always thought to be more discriminative than single terms and are able to reveal the inner relations between words. This paper proposes a novel information filtering model, Significant matched Pattern-based Topic Model (SPBTM). The SPBTM represents user information needs in terms of multiple topics and each topic is represented by patterns. More importantly, the patterns are organized into groups based on their statistical and taxonomic features, from which the more representative patterns, called Significant Matched Patterns, can be identified and used to estimate the document relevance. Experiments on benchmark data sets demonstrate that the SPBTM significantly outperforms the state-of-the-art models.

An external field prior for the hidden Potts model with application to cone-beam computed tomography

In images with low contrast-to-noise ratio (CNR), the information gain from the observed pixel values can be insufficient to distinguish foreground objects. A Bayesian approach to this problem is to incorporate prior information about the objects into a statistical model. A method for representing spatial prior information as an external field in a hidden Potts model is introduced. This prior distribution over the latent pixel labels is a mixture of Gaussian fields, centred on the positions of the objects at a previous point in time. It is particularly applicable in longitudinal imaging studies, where the manual segmentation of one image can be used as a prior for automatic segmentation of subsequent images. The method is demonstrated by application to cone-beam computed tomography (CT), an imaging modality that exhibits distortions in pixel values due to X-ray scatter. The external field prior results in a substantial improvement in segmentation accuracy, reducing the mean pixel misclassification rate for an electron density phantom from 87% to 6%. The method is also applied to radiotherapy patient data, demonstrating how to derive the external field prior in a clinical context.

A model-framed evaluation of elephant effects on tree and fire dynamics in African savannas

There is a concern that high densities of elephants in southern Africa could lead to the overall reduction of other forms of biodiversity. We present a grid-based model of elephant-savanna dynamics, which differs from previous elephant-vegetation models by accounting for woody plant demographics, tree-grass interactions, stochastic environmental variables (fire and rainfall), and spatial contagion of fire and tree recruitment. The model projects changes in height structure and spatial pattern of trees over periods of centuries. The vegetation component of the model produces long-term tree-grass coexistence, and the emergent fire frequencies match those reported for southern African savannas. Including elephants in the savanna model had the expected effect of reducing woody plant cover, mainly via increased adult tree mortality, although at an elephant density of 1.0 elephant/km2, woody plants still persisted for over a century. We tested three different scenarios in addition to our default assumptions. (1) Reducing mortality of adult trees after elephant use, mimicking a more browsing-tolerant tree species, mitigated the detrimental effect of elephants on the woody population. (2) Coupling germination success (increased seedling recruitment) to elephant browsing further increased tree persistence, and (3) a faster growing woody component allowed some woody plant persistence for at least a century at a density of 3 elephants/km2. Quantitative models of the kind presented here provide a valuable tool for exploring the consequences of management decisions involving the manipulation of elephant population densities. © 2005 by the Ecological Society of America.