Colonizing while migrating : how do individual enteric neural crest cells behave?

Background Directed cell migration is essential for normal development. In most of the migratory cell populations that have been analysed in detail to date, all of the cells migrate as a collective from one location to another. However, there are also migratory cell populations that must populate the areas through which they migrate, and thus some cells get left behind while others advance. Very little is known about how individual cells behave to achieve concomitant directional migration and population of the migratory route. We examined the behavior of enteric neural crest-derived cells (ENCCs), which must both advance caudally to reach the anal end and populate each gut region. Results The behaviour of individual ENCCs was examined using live imaging and mice in which ENCCs express a photoconvertible protein. We show that individual ENCCs exhibit very variable directionalities and speed; as the migratory wavefront of ENCCs advances caudally, each gut region is populated primarily by some ENCCs migrating non-directionally. After populating each region, ENCCs remain migratory for at least 24 hours. Endothelin receptor type B (EDNRB) signaling is known to be essential for the normal advance of the ENCC population. We now show that perturbation of EDNRB principally affects individual ENCC speed rather than directionality. The trajectories of solitary ENCCs, which occur transiently at the wavefront, were consistent with an unbiased random walk and so cell-cell contact is essential for directional migration. ENCCs migrate in close association with neurites. We showed that although ENCCs often use neurites as substrates, ENCCs lead the way, neurites are not required for chain formation and neurite growth is more directional than the migration of ENCCs as a whole. Conclusions Each gut region is initially populated by sub-populations of ENCCs migrating non-directionally, rather than stopping. This might provide a mechanism for ensuring a uniform density of ENCCs along the growing gut.

Differentiation of complex lipid isomers by radical-directed dissociation mass spectrometry

Contemporary lipidomics protocols are dependent on conventional tandem mass spectrometry for lipid identification. This approach is extremely powerful for determining lipid class and identifying the number of carbons and the degree of unsaturation of any acyl-chain substituents. Such analyses are however, blind to isomeric variants arising from different carbon carbon bonding motifs within these chains including double bond position, chain branching, and cyclic structures. This limitation arises from the fact that conventional, low energy collision-induced dissociation of even-electron lipid ions does not give rise to product ions from intrachain fragmentation of the fatty acyl moieties. To overcome this limitation, we have applied radical-directed dissociation (RDD) to the study of lipids for the first time. In this approach, bifunctional molecules that contain a photocaged radical initiator and a lipid-adducting group, such as 4-iodoaniline and 4-iodobenzoic acid, are used to form noncovalent complexes (i.e., adduct ions) with a lipid during electrospray ionization. Laser irradiation of these complexes at UV wavelengths (266 nm) cleaves the carbon iodine bond to liberate a highly reactive phenyl radical. Subsequent activation of the nascent radical ions results in RDD with significant intrachain fragmentation of acyl moieties. This approach provides diagnostic fragments that are associated with the double bond position and the positions of chain branching in glycerophospholipids, sphingomyelins and triacylglycerols and thus can be used to differentiate isomeric lipids differing only in such motifs. RDD is demonstrated for well-defined lipid standards and also reveals lipid structural diversity in olive oil and human very-low density lipoprotein.

THE quest for alpha : can artificial neural networks help?

The application of artificial neural networks (ANN) in finance is relatively new area of research. We employed ANNs that used both fundamental and technical inputs to predict future prices of widely held Australian stocks and used these predicted prices for stock portfolio selection over a 10-year period (2001-2011). We found that the ANNs generally do well in predicting the direction of stock price movements. The stock portfolios selected by the ANNs with median accuracy are able to generate positive alpha over the 10-year period. More importantly, we found that a portfolio based on randomly selected network configuration had zero chance of resulting in a significantly negative alpha but a 27% chance of yielding a significantly positive alpha. This is in stark contrast to the findings of the research on mutual fund performance where active fund managers with negative alphas outnumber those with positive alphas.

Predicting freeway pavement construction cost using a back-propagation neural network : a case study in Henan, China

The objective of this research was to develop a model to estimate future freeway pavement construction costs in Henan Province, China. A comprehensive set of factors contributing to the cost of freeway pavement construction were included in the model formulation. These factors comprehensively reflect the characteristics of region and topography and altitude variation, the cost of labour, material, and equipment, and time-related variables such as index numbers of labour prices, material prices and equipment prices. An Artificial Neural Network model using the Back-Propagation learning algorithm was developed to estimate the cost of freeway pavement construction. A total of 88 valid freeway cases were obtained from freeway construction projects let by the Henan Transportation Department during the period 1994−2007. Data from a random selection of 81 freeway cases were used to train the Neural Network model and the remaining data were used to test the performance of the Neural Network model. The tested model was used to predict freeway pavement construction costs in 2010 based on predictions of input values. In addition, this paper provides a suggested correction for the prediction of the value for the future freeway pavement construction costs. Since the change in future freeway pavement construction cost is affected by many factors, the predictions obtained by the proposed method, and therefore the model, will need to be tested once actual data are obtained.

Out of their minds: legal theory in neural networks

This paper examines the use of connectionism (neural networks) in modelling legal reasoning. I discuss how the implementations of neural networks have failed to account for legal theoretical perspectives on adjudication. I criticise the use of neural networks in law, not because connectionism is inherently unsuitable in law, but rather because it has been done so poorly to date. The paper reviews a number of legal theories which provide a grounding for the use of neural networks in law. It then examines some implementations undertaken in law and criticises their legal theoretical naïvete. It then presents a lessons from the implementations which researchers must bear in mind if they wish to build neural networks which are justified by legal theories.

Correlates of female sexual functioning : adult attachment and differentiation of self

Introduction Female sexual functioning is affected by a range of factors including motivation, psychological well-being, and relationship issues. In understanding female sexual dysfunction (FSD), there has been a tendency to privilege diagnostic and medical over relationship issues. Aim To investigate the association between women’s experience of intimacy in close relationships - operationalized in terms of attachment and degree of differentiation of self - and FSD. Methods Two hundred and thirty sexually active Australian women responded to an invitation to complete a set of validated scales to assess potential correlates of sexual functioning. Main Outcome Measures The Female Sexuality Function Index, the Experiences in Close Relationships Scale, the Differentiation of Self Inventory, as well as a set of study-specific questions were subject to hierarchical multiple regression analyses Results Relational variables of attachment avoidance and to a lesser degree, attachment anxiety were associated with FSD. Participants with lower levels of differentiation of self were more likely to report sexual difficulties. The inability to maintain a sense of self in the presence of intimate others was the strongest predictors of sexual problems. A history of sexual abuse in adulthood and higher levels of psychological distress were also associated with sexual difficulties. Conclusions The findings provide support for a relational understanding of female sexual functioning. Attachment avoidance, attachment anxiety, and degree of differentiation of self are shown to be associated with sexual difficulties. The findings support the need to focus on relational and psychological factors in women’s experience of sex.

Differentiation state and invasiveness of human breast cancer cell lines

Eighteen breast cancer cell lines were examined for expression of markers of epithelial and fibroblastic differentiation: E-cadherin, desmoplakins, ZO- 1, vimentin, keratin and β1 and β4 integrins. The cell lines were distributed along a spectrum of differentiation from epithelial to fibroblastic phenotypes. The most well-differentiated, epithelioid cell lines contained proteins characteristic of desmosomal, adherens and tight junctions, were adherent to one another on plastic and in the basement membrane matrix Matrigel and were keratin-positive and vimentin-negative. These cell lines were all weakly invasive in an in vitro chemoinvasion assay. The most poorly-differentiated, fibroblastic cell lines were E-cadherin-, desmoplakin- and ZO-1-negative and formed branching structures in Matrigel. They were vimentin-positive, contained only low levels of keratins and were highly invasive in the in vitro chemoinvasion assay. Of all of the markers analyzed, vimentin expression correlated best with in vitro invasive ability and fibroblastic differentiation. In a cell line with unstable expression of vimentin, T47D(CO), the cells that were invasive were of the fibroblastic type. The differentiation markers described here may be useful for analysis of clinical specimens and could potentially provide a more precise measure of differentiation grade yielding more power for predicting prognosis.

Modulation of breast cancer progression and differentiation by the gp30/neregulin

In the last decade we have come to understand that the growth of cancer cells in general and of breast cancer in particular depends, in many cases, upon growth factors that will bind to and activate their receptors. One of these growth factor receptors is the erbB-2 protein which plays an important role in the prognosis of breast cancer and is overexpressed in nearly 30% of human breast cancer patients. While evidence accumulates to support the relationship between erbB-2 overexpression and poor overall survival in breast cancer, understanding of the biological consequence(s) of erbB-2 overexpression remains elusive. Our recent discovery of the gp30 has allowed us to identify a number of related but distinct biological endpoints which appear responsive to signal transduction through the erbB-2 receptor. These endpoints of growth, invasiveness, and differentiation have clear implications for the emergence, maintenance and/or control of malignancy, and represent established endpoints in the assessment of malignant progression in breast cancer. We have shown that gp30 induces a biphasic growth effect on cells with erbB-2 over-expression. We have recently determined the protein sequence of gp30 and cloned its full length cDNA sequence. We have also cloned two additional forms to the ligand, that are believed to be different isoforms. We are currently expressing the different forms in order to determine their biological effects. To elucidate the cellular mechanisms underlying cell growth inhibition by gp30, we tested the effect of this ligand on cell growth and differentiation of the human breast cancer cells which overexpress erbB-2 and cells which express low levels of this protooncogene. High concentrations of ligand induced differentiation of cells overexpressing erbB-2, as measured by inhibition of cell growth, and increased synthesis of milk components, and modulation of E-cadherin and up- regulation of c-jun and c-fos. These findings indicate that ligand-induced growth inhibition in cells overexpressing erbB-2 is associated with an apparent induction of differentiation. The availability of gp30 derived synthetic peptides and its full cDNAs provides tools necessary to acquire a better understanding of the mechanism of action of the this ligands and the erbB-2 receptor in breast cancer.

Artificial neural networks to predict activity type and energy expenditure in youth

Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

Adipose differentiation of bone marrow-derived mesenchymal stem cells using Pluronic F-127 hydrogel in vitro

Due to increasing clinical demand for adipose tissue, a suitable scaffold for engineering adipose tissue constructs is needed. In this study, we have developed a three-dimensional (3-D) culture system using bone marrow-derived mesenchymal stem cells (BM-MSC) and a Pluronic F-127 hydrogel scaffold as a step towards the in vitro tissue engineering of fat. BM-MSC were dispersed into a Pluronic F-127 hydrogel with or without type I collagen added. The adipogenic differentiation of the BM-MSC was assessed by cellular morphology and further confirmed by Oil Red O staining. The BM-MSC differentiated into adipocytes in Pluronic F-127 in the presence of adipogenic stimuli over a period of 2 weeks, with some differentiation present even in absence of such stimuli. The addition of type I collagen to the Pluronic F-127 caused the BM-MSC to aggregate into clumps, thereby generating an uneven adipogenic response, which was not desirable.

Lithium release from ß-tricalcium phosphate inducing cementogenic and osteogenic differentiation for both hPDLCs and hBMSCs

It is accepted that the accelerated differentiation of tissue cells on bioactive materials is of great importance to regenerate the lost tissues. It was previously reported that lithium (Li) ions could enhance the in vitro proliferation and differentiation of retinoblastoma cells and endometrium epithelia by activating the Wnt canonical signalling pathway. It is interesting to incorporate Li ions into bioactive ceramics, such as β-tricalcium phosphate (Li-β-TCP), in order to stimulate both osteogenic and cementogenic differentiation of different stem cells for the regeneration of bone/periodontal tissues. Therefore, the aim of this study was to investigate the interactions of human periodontal ligament cells (hPDLCs) and human bone marrow stromal cells (hBMSCs) with Li-β-TCP bioceramic bulks and their ionic extracts, and further explore the osteogenic and cementogenic stimulation of Li-β-TCP bioceramics and the possible molecular mechanisms. The results showed that Li-β-TCP bioceramic disks supported the cell attachment and proliferation, and significantly enhanced bone/cementum-related gene expression, Wnt canonical signalling pathway activation for both hPDLCs and hBMSCs, compared to conventional β-TCP bioceramic disks without Li. The release of Li from Li-β-TCP powders could significantly promote the bone/cementum-related gene expression for both hPDLCs and hBMSCs compared to pure β-TCP extracts without Li release. Our results suggest that the combination of Li with β-TCP bioceramics may be a promising method to enhance bone/cementum regeneration as Li-β-TCP possesses excellent in vitro osteogenic and cementogenic stimulation properties by inducing bone/cementum-related gene expression in both hPDLCs and hBMSCs.

Dopamine transporter genotype predicts behavioural and neural measures of response inhibition

The ability to inhibit unwanted actions is a heritable executive function that may confer risk to disorders such as attention deficit hyperactivity disorder (ADHD). Converging evidence from pharmacology and cognitive neuroscience suggests that response inhibition is instantiated within frontostriatal circuits of the brain with patterns of activity that are modulated by the catecholamines dopamine and noradrenaline. A total of 405 healthy adult participants performed the stop-signal task, a paradigmatic measure of response inhibition that yields an index of the latency of inhibition, termed the stop-signal reaction time (SSRT). Using this phenotype, we tested for genetic association, performing high-density single-nucleotide polymorphism mapping across the full range of autosomal catecholamine genes. Fifty participants also underwent functional magnetic resonance imaging to establish the impact of associated alleles on brain and behaviour. Allelic variation in polymorphisms of the dopamine transporter gene (SLC6A3: rs37020; rs460000) predicted individual differences in SSRT, after corrections for multiple comparisons. Furthermore, activity in frontal regions (anterior frontal, superior frontal and superior medial gyri) and caudate varied additively with the T-allele of rs37020. The influence of genetic variation in SLC6A3 on the development of frontostriatal inhibition networks may represent a key risk mechanism for disorders of behavioural inhibition.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.