Lysophosphatidic Acid Stimulates Lymphangiogenesis in Human Lymphatic Endothelial Cells

Lymphangiogenesis is the process by which new lymphatic vessels sprout and grow from existing vessels whether under developmental, immunological, or cancerous conditions. Proper lymphatic vessel formation is important in working alongside normal angiogenesis in order to help regulate the body’s tissue fluid as well as aid in immunosurveillance. Various factors regulate lymphangiogenesis such as members of the vascular endothelial growth factor family (VEGF). Another factor that has recently been identified to play a role in lymphangiogenesis is the bio-active phospholipid lysophosphatidic acid (LPA) however the molecular mechanism by which LPA regulates lymphangiogenesis has not been well characterized. In this study, human lymphatic endothelial cells (HLECs) were treated with LPA in the presence or absence of VEGF and the late stage effects of lymphangiogenesis were examined. Preliminary evidence suggests that VEGF and LPA induces proliferation in HLECs, however there is no increase in this stimulation when both factors are added together. A Matrigel tube formation assay revealed that LPA induces an increase in cellular extensions as well as in tubule length as compared to the control

Sizing the association between lifestyle behaviours and fatness in a large, heterogeneous sample of youth of multiple ethnicities from 4 countries

Background:&nbsp;The magnitude of the relationship between lifestyle risk factors for obesity and adiposity is not clear.&nbsp;The aim of this study was to clarify this in order to determine the level of importance of lifestyle factors in obesity&nbsp;aetiology.Methods: A cross-sectional analysis was carried out on data on youth who were not trying to change weight&nbsp;(n = 5714), aged 12 to 22 years and from 8 ethnic groups living in New Zealand, Australia, Fiji and Tonga.&nbsp;Demographic and lifestyle data were measured by questionnaires. Fatness was measured by body mass index (BMI),&nbsp;BMI z-score and bioimpedance analysis, which was used to estimate percent body fat and total fat mass (TFM).&nbsp;Associations between lifestyle and body composition variables were examined using linear regression and forest plots.Results: TV watching was positively related to fatness in a dose-dependent manner. Strong, dose-dependent&nbsp;associations were observed between fatness and soft drink consumption (positive relationship), breakfast consumption&nbsp;(inverse relationship) and after-school physical activity (inverse relationship). Breakfast consumption-fatness associations&nbsp;varied in size across ethnic groups. Lifestyle risk factors for obesity were associated with percentage differences in body&nbsp;composition variables that were greatest for TFM and smallest for BMI.Conclusions: Lifestyle factors were most strongly related to TFM, which suggests that studies that use BMI alone to&nbsp;quantify fatness underestimate the full effect of lifestyle on adiposity. This study clarifies the size of lifestyle-fatness&nbsp;relationships observed in previous studies.</div

Managing in conflict: How actors distribute conflict in an industrial network

IMP researchers have examined conflict as a threat to established business relationships and commercial exchanges, drawing on theories and concepts developed in organization studies. We examine cases of conflict in relationships from the oil and gas industry's service sector, focusing on conflicts of interest and resources, and conflict as experienced by actors. Through a comparative case study design, we propose an explanation of how actors manage conflict and manage in conflict given that they tend to value and maintain relationships beyond episodes of exchange. We consider conflicts in relationships from a network perspective, showing that actors experienced these while adapting to changes in their business setting, modifying their roles in that network. By identifying conflict with the organizing forms of relationship and network, we show how actors formulate conflict through pursuing and combining a number of strategies, distributing the conflict across an enlarged network

A network traffic flow model for motorway and urban highways

The research reported in this paper develops a network level traffic flow model (NTFM) which is applicable for both motorway and urban roads. It forecasts the traffic flow rates, queue propagation at the junctions and travel delays through the network. NTFM uses sub-models associated with all road and junction types which comprise the highway. The flow at any one part of the network is obviously very dependent upon the flows at all other parts of the network. To predict the two-way traffic flow in NTFM, an iterative simulation method is executed to generate the evolution of dependent traffic flows and queues. To demonstrate the capability of the model it is applied to a small case study network and a local Loughborough-Nottingham highway network. The results indicate that NTFM is capable of identifying the relationship between traffic flows and capturing traffic phenomena such as queue dynamics. By introducing a reduced flow rate on links of the network then the effects of strategies employed to carry out roadworks can be mimicked

Hot plasma in the magnetotail lobes shows characteristics consistent with closed field lines trapped in the lobes

We examine the magnetotail using data from the Hot Ion Analyzer on Cluster 1 during 2001–2009. We develop and utilise an algorithm in order to identify times during which Cluster 1 is in the magnetotail lobe but observes plasma which is hotter than our expectations of the lobe. We analyze the prevailing Interplanetary Magnetic Field (IMF) Bz conditions for our algorithm and a reference algorithm (with no particle energy criteria) and find that the periods we select are, on average, ~2 nT more towards northward IMF. Examining the temperature in the magnetotail for our periods shows that the morphology of the average temperature is consistent with the Milan et al. (2005) model of magnetotail structure during Northward IMF, in which closed field lines are prevented from convecting to the dayside, causing them and the plasma trapped on them to protrude into the magnetotail lobes. We also find evidence that ~0.5% of our identified periods may be driven by direct entry into the magnetosphere from the solar wind

Computer simulation of glioma growth and morphology

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion