Insulin-like growth factor-i : vitronectin complex-induced changes in gene expression effect breast cell survival and migration

Recent studies have demonstrated that IGF-I associates with VN through IGF-binding proteins (IGFBP) which in turn modulate IGF-stimulated biological functions such as cell proliferation, attachment and migration. Since IGFs play important roles in transformation and progression of breast tumours, we aimed to describe the effects of IGF-I:IGFBP:VN complexes on breast cell function and to dissect mechanisms underlying these responses. In this study we demonstrate that substrate-bound IGF-I:IGFBP:VN complexes are potent stimulators of MCF-7 breast cell survival, which is mediated by a transient activation of ERK/MAPK and sustained activation of PI3-K/AKT pathways. Furthermore, use of pharmacological inhibitors of the MAPK and PI3-K pathways confirms that both pathways are involved in IGF-I:IGFBP:VN complex-mediated increased cell survival. Microarray analysis of cells stimulated to migrate in response to IGF-I:IGFBP:VN complexes identified differential expression of genes with previously reported roles in migration, invasion and survival (Ephrin-B2, Sharp-2, Tissue-factor, Stratifin, PAI-1, IRS-1). These changes were not detected when the IGF-I analogue (\[L24]\[A31]-IGF-I), which fails to bind to the IGF-I receptor, was substituted; confirming the IGF-I-dependent differential expression of genes associated with enhanced cell migration. Taken together, these studies have established that IGF-I:IGFBP:VN complexes enhance breast cell migration and survival, processes central to facilitating metastasis. This study highlights the interdependence of ECM and growth factor interactions in biological functions critical for metastasis and identifies potential novel therapeutic targets directed at preventing breast cancer progression.

Concept combination and the origins of complex cognition

At the core of our uniquely human cognitive abilities is the capacity to see things from different perspectives, or to place them in a new context. We propose that this was made possible by two cognitive transitions. First, the large brain of Homo erectus facilitated the onset of recursive recall: the ability to string thoughts together into a stream of potentially abstract or imaginative thought. This hypothesis is sup-ported by a set of computational models where an artificial society of agents evolved to generate more diverse and valuable cultural outputs under conditions of recursive recall. We propose that the capacity to see things in context arose much later, following the appearance of anatomically modern humans. This second transition was brought on by the onset of contextual focus: the capacity to shift between a minimally contextual analytic mode of thought, and a highly contextual associative mode of thought, conducive to combining concepts in new ways and ‘breaking out of a rut’. When contextual focus is implemented in an art-generating computer program, the resulting artworks are seen as more creative and appealing. We summarize how both transitions can be modeled using a theory of concepts which high-lights the manner in which different contexts can lead to modern humans attributing very different meanings to the interpretation of one concept.

Sensitivity of the NMR density matrix to pulse sequence parameters : a simplified analytic approach

We present a formalism for the analysis of sensitivity of nuclear magnetic resonance pulse sequences to variations of pulse sequence parameters, such as radiofrequency pulses, gradient pulses or evolution delays. The formalism enables the calculation of compact, analytic expressions for the derivatives of the density matrix and the observed signal with respect to the parameters varied. The analysis is based on two constructs computed in the course of modified density-matrix simulations: the error interrogation operators and error commutators. The approach presented is consequently named the Error Commutator Formalism (ECF). It is used to evaluate the sensitivity of the density matrix to parameter variation based on the simulations carried out for the ideal parameters, obviating the need for finite-difference calculations of signal errors. The ECF analysis therefore carries a computational cost comparable to a single density-matrix or product-operator simulation. Its application is illustrated using a number of examples from basic NMR spectroscopy. We show that the strength of the ECF is its ability to provide analytic insights into the propagation of errors through pulse sequences and the behaviour of signal errors under phase cycling. Furthermore, the approach is algorithmic and easily amenable to implementation in the form of a programming code. It is envisaged that it could be incorporated into standard NMR product-operator simulation packages.

Signal transduction mechanisms underlying growth hormone receptor action

Our understanding of the mechanisms of action of GH and its receptor, the GHR, has advanced significantly in the last decade and has provided some important surprises. It is now clear that the GH-GHR axis activates a number of inter-related signalling pathways, not all of which are dependent on the intracellular tyrosine kinase, JAK2 as originally postulated. JAK2-independent pathways, mediated via the Src family kinases, together with a number of negative regulators of GH signalling and emerging cross-talk mechanisms with other growth factor receptors, provide a complex array of mechanisms that are capable of fine-tuning responses to GH in a cell context dependent manner. Additionally, it is also now clear that GH and the GHR can translocate to the nucleus of target cells and initiate, as yet not well defined, nuclear responses. Continued emphasis on elucidation of these complex mechanisms is critical to provide further insights into the diverse physiological and pathophysiological effects of GH.

Genomic evidence for the parallel evolution of coastal forms in the Senecio lautus complex

Instances of parallel ecotypic divergence where adaptation to similar conditions repeatedly cause similar phenotypic changes in closely related organisms are useful for studying the role of ecological selection in speciation. Here we used a combination of traditional and next generation genotyping techniques to test for the parallel divergence of plants from the Senecio lautus complex, a phenotypically variable groundsel that has adapted to disparate environments in the South Pacific. Phylogenetic analysis of a broad selection of Senecio species showed that members of the S. lautus complex form a distinct lineage that has diversified recently in Australasia. An inspection of thousands of polymorphisms in the genome of 27 natural populations from the S. lautus complex in Australia revealed a signal of strong genetic structure independent of habitat and phenotype. Additionally, genetic differentiation between populations was correlated with the geographical distance separating them, and the genetic diversity of populations strongly depended on geographical location. Importantly, coastal forms appeared in several independent phylogenetic clades, a pattern that is consistent with the parallel evolution of these forms. Analyses of the patterns of genomic differentiation between populations further revealed that adjacent populations displayed greater genomic heterogeneity than allopatric populations and are differentiated according to variation in soil composition. These results are consistent with a process of parallel ecotypic divergence in face of gene flow.

MMP-9 and the epidermal growth factor signal pathway in non-small cell lung cancer

Background Matrix metalloproteinase (MMP)-9 is an endopeptidase that digests basement membrane type-IV collagen. Enhanced expression has been related to tumour progression in a number of systems. The control of MMP expression is complex, but recently epidermal growth actor receptor (EGFR) activity has been implicated in up-regulation of MMP-9 in tumour cells in vitro. Aims To evaluate interrelations between MMP-9 and EGFR expression in non-small cell lung cancer (NSCLC) and to assess the impact of expression on survival. Methods This is a retrospective study of 152 patients who underwent resection for stage I-IIIa NSCLC with a post-operative survival >60 days. Minimum follow-up was 2 years. Standard ABC immunohistochemistry was performed on 4μm paraffin-embedded sections from the tumour periphery using monoclonal antibodies to MMP-9 and EGFR. Results: MMP-9 was expressed in the tumour cells of 79/152 (52%) cases. EGFR expression was found in 86/152 (57%) cases [membranous 51/152 (34%), cytoplasmic 35/152 (23%)]. MMP-9 expression was associated with poor outcome (p=0.04). Membranous, cytoplasmic and overall EGFR expression were not associated with outcome (p=0.29, p=0.85 and p=0.41 respectively). There was a strong correlation between MMP-9 expression and EGFR expression (p=0.001) and EGFR membranous expression (p=0.01) but not with cytoplasmic EGFR expression (p=0.28). Co-expression of MMP-9 and EGFR (36%) conferred a worse prognosis (p=0.003). Subset analysis revealed only MMP-9 and membranous EGFR co-expression (22%) was associated with poor outcome (p=0.008). Conclusions Our results show that MMP-9 and EGFR are co-expressed in NSCLC. This finding suggests the EGFR signalling pathway may play an important role in the invasive behaviour of NSCLC via specific upregulation of MMP-9. The co-expression of these markers also confers a poor prognosis.

Characterising an ECG signal using statistical modelling : a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

Hip and knee kinematics display complex and time-varying sagittal kinematics during repetitive stepping: Implications for design of a functional fatigue model of the knee extensors and flexors

The validity of fatigue protocols involving multi-joint movements, such as stepping, has yet to be clearly defined. Although surface electromyography can monitor the fatigue state of individual muscles, the effects of joint angle and velocity variation on signal parameters are well established. Therefore, the aims of this study were to i) describe sagittal hip and knee kinematics during repetitive stepping ii) identify periods of high inter-trial variability and iii) determine within-test reliability of hip and knee kinematic profiles. A group of healthy men (N = 15) ascended and descended from a knee-high platform wearing a weighted vest (10%BW) for 50 consecutive trials. The hip and knee underwent rapid flexion and extension during step ascent and descent. Variability of hip and knee velocity peaked between 20-40% of the ascent phase and 80-100% of the descent. Significant (p<0.05) reductions in joint range of motion and peak velocity during step ascent were observed, while peak flexion velocity increased during descent. Healthy individuals use complex hip and knee motion to negotiate a knee-high step with kinematic patterns varying across multiple repetitions. These findings have important implications for future studies intending to use repetitive stepping as a fatigue model for the knee extensors and flexors.

A hybrid quality function deployment and cybernetic analytic network process model for project manager selection

Identifying appropriate decision criteria and making optimal decisions in a structured way is a complex process. This paper presents an approach for doing this in the form of a hybrid Quality Function Deployment (QFD) and Cybernetic Analytic Network Process (CANP) model for project manager selection. This involves the use of QFD to translate the owner's project management expectations into selection criteria and the CANP to weight the expectations and selection criteria. The supermatrix approach then prioritises the candidates with respect to the overall decision-making goal. A case study is used to demonstrate the use of the model in selecting a renovation project manager. This involves the development of 18 selection criteria in response to the owner's three main expectations of time, cost and quality.

Further development of discrete computational techniques for calculation of restricted diffusion propagators in porous media

Magnetic resonance is a well-established tool for structural characterisation of porous media. Features of pore-space morphology can be inferred from NMR diffusion-diffraction plots or the time-dependence of the apparent diffusion coefficient. Diffusion NMR signal attenuation can be computed from the restricted diffusion propagator, which describes the distribution of diffusing particles for a given starting position and diffusion time. We present two techniques for efficient evaluation of restricted diffusion propagators for use in NMR porous-media characterisation. The first is the Lattice Path Count (LPC). Its physical essence is that the restricted diffusion propagator connecting points A and B in time t is proportional to the number of distinct length-t paths from A to B. By using a discrete lattice, the number of such paths can be counted exactly. The second technique is the Markov transition matrix (MTM). The matrix represents the probabilities of jumps between every pair of lattice nodes within a single timestep. The propagator for an arbitrary diffusion time can be calculated as the appropriate matrix power. For periodic geometries, the transition matrix needs to be defined only for a single unit cell. This makes MTM ideally suited for periodic systems. Both LPC and MTM are closely related to existing computational techniques: LPC, to combinatorial techniques; and MTM, to the Fokker-Planck master equation. The relationship between LPC, MTM and other computational techniques is briefly discussed in the paper. Both LPC and MTM perform favourably compared to Monte Carlo sampling, yielding highly accurate and almost noiseless restricted diffusion propagators. Initial tests indicate that their computational performance is comparable to that of finite element methods. Both LPC and MTM can be applied to complicated pore-space geometries with no analytic solution. We discuss the new methods in the context of diffusion propagator calculation in porous materials and model biological tissues.

Fractional models in space for diffusive processes in heterogeneous media with applications in cell motility and electrical signal propagation

This work addresses fundamental issues in the mathematical modelling of the diffusive motion of particles in biological and physiological settings. New mathematical results are proved and implemented in computer models for the colonisation of the embryonic gut by neural cells and the propagation of electrical waves in the heart, offering new insights into the relationships between structure and function. In particular, the thesis focuses on the use of non-local differential operators of non-integer order to capture the main features of diffusion processes occurring in complex spatial structures characterised by high levels of heterogeneity.

Fatigue and sleepiness: Complex bedfellows

Do you know how to drive a train? If you don’t you probably believe that you have a fair idea of what it’s all about. Forget what you know, or think you know. Trains are heavy and fast but they feel and handle like driving on ice so they take a long time to stop. The braking distances for a typical piece of track are unlike anything you will have experienced before. With that in mind, imagine you were driving with a bit of dew, or grease, or millipede over the track. You would lose traction and slip everywhere. To avoid this, you would need a compensatory driving strategy. You could drive more slowly, or brake sooner, or change how you brake. Your experience and intuition would lead the way. Folks, this is why it’s called “driving by the seat of your pants”...

Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

Genetic insights into common pathways and complex relationships among iImmune-mediated diseases

Shared aetiopathogenic factors among immune-mediated diseases have long been suggested by their co-familiality and co-occurrence, and molecular support has been provided by analysis of human leukocyte antigen (HLA) haplotypes and genome-wide association studies. The interrelationships can now be better appreciated following the genotyping of large immune disease sample sets on a shared SNP array: the 'Immunochip'. Here, we systematically analyse loci shared among major immune-mediated diseases. This reveals that several diseases share multiple susceptibility loci, but there are many nuances. The most associated variant at a given locus frequently differs and, even when shared, the same allele often has opposite associations. Interestingly, risk alleles conferring the largest effect sizes are usually disease-specific. These factors help to explain why early evidence of extensive 'sharing' is not always reflected in epidemiological overlap. © 2013 Macmillan Publishers Limited. All rights reserved.

External signal-activated liposomal drug delivery systems

Modern drug discovery gives rise to a great number of potential new therapeutic agents, but in some cases the efficient treatment of patient may not be achieved because the delivery of active compounds to the target site is insufficient. Thus, drug delivery is one of the major challenges in current pharmaceutical research. Numerous nanoparticle-based drug carriers, e.g. liposomes, have been developed for enhanced drug delivery and targeting. Drug targeting may enhance the efficiency of the treatment and, importantly, reduce unwanted side effects by decreasing drug distribution to non-target tissues. Liposomes are biocompatible lipid-based carriers that have been studied for drug delivery during the last 40 years. They can be functionalized with targeting ligands and sensing materials for triggered activation. In this study, various external signal-assisted liposomal delivery systems were developed. Signals can be used to modulate drug permeation or release from the liposome formulation, and they provide accurate control of time, place and rate of activation. The study involved three types of signals that were used to trigger drug permeation and release: electricity, heat and light. Electrical stimulus was utilized to enhance the permeation of liposomal DNA across the skin. Liposome/DNA complex-mediated transfections were performed in tight rat epidermal cell model. Various transfection media and current intensities were tested, and transfection efficiency was evaluated non-invasively by monitoring the concentration of secreted reporter protein in cell culture medium. Liposome/DNA complexes produced gene expression, but electrical stimulus did not enhance the transfection efficiency significantly. Heat-sensitive liposomal drug delivery system was developed by coating liposomes with biodegradable and thermosensitive poly(N-(2-hydroxypropyl) methacrylamide-mono/dilactate polymer. Temperature-triggered liposome aggregation and contents release from liposomes were evaluated. The cloud point temperature (CP) of the polymer was set to 42 °C. Polymer-coated liposome aggregation and contents release were observed above CP of the polymer, while non-coated liposomes remained intact. Polymer precipitates above its CP and interacts with liposomal bilayers. It is likely that this induces permeabilization of the liposomal membrane and contents release. Light-sensitivity was introduced to liposomes by incorporation of small (< 5 nm) gold nanoparticles. Hydrophobic and hydrophilic gold nanoparticles were embedded in thermosensitive liposomes, and contents release was investigated upon UV light exposure. UV light-induced lipid phase transitions were examined with small angle X-ray scattering, and light-triggered contents release was shown also in human retinal pigment epithelial cell line. Gold nanoparticles absorb light energy and transfer it into heat, which induces phase transitions in liposomes and triggers the contents release. In conclusion, external signal-activated liposomes offer an advanced platform for numerous applications in drug delivery, particularly in the localized drug delivery. Drug release may be localized to the target site with triggering stimulus that results in better therapeutic response and less adverse effects. Triggering signal and mechanism of activation can be selected according to a specific application.