modelling of aortic valve implants - predicting in vitro performance using finite element analysis.

The competing structural and hemodynamic considerations in valve design generally require a large amount of hydrodynamic and durability testing during development, often resulting in inefficient "trial-and-error" prototyping. While in silico modelling through finite element analysis (FEA) has been widely used to inform valve design by optimising structural performance, few studies have exploited the potential insight FEA could provide into critical hemodynamic performance characteristics of the valve. The objective of this study is to demonstrate the potential of FEA to predict the hydrodynamic performance of tri-leaflet aortic valve implants obtained during development through testing.

Human mesenchymal stromal cells broadly modulate high glucose-induced inflammatory responses of renal proximal tubular cell monolayers.

Background: Renal proximal tubular epithelial cells (RPTEC) are dysfunctional in diabetic kidney disease (DKD). Mesenchymal stromal cells (MSC) may modulate DKD pathogenesis through anti-inflammatory mediators. This study aimed to investigate the pro-inflammatory effect of extended exposure to high glucose (HG) concentration on stable RPTEC monolayers and the influence of MSC on this response.

Understanding the role of parasites in food webs using the group model.

Parasites are ubiquitous and have been shown to influence macroscopic measures of ecological network structure, such as connectance and robustness, as well as local structure, such as subgraph frequencies. Nevertheless, they are often under-represented in ecological studies due to their small size and often complex life cycles. We consider whether or not parasites play structurally unique roles in ecological networks; that is, can we distinguish parasites from other species using network structure alone? We partition the species in a community statistically using the group model, and we test whether or not parasites tend to cluster in their own groups, using a measure of "imbalance.

Ecological Network Inference From Long-Term Presence-Absence Data.

Ecological communities are characterized by complex networks of trophic and nontrophic interactions, which shape the dy-namics of the community. Machine learning and correlational methods are increasingly popular for inferring networks from co-occurrence and time series data, particularly in microbial systems. In this study, we test the suitability of these methods for inferring ecological interactions by constructing networks using Dynamic Bayesian Networks, Lasso regression, and Pear-son's correlation coefficient, then comparing the model networks to empirical trophic and nontrophic webs in two ecological systems.

Life Space Assessment in Spinal Cord Injury.

To examine the Life Space Assessment (LSA) in persons with spinal cord injury (SCI), exploring its psychometric properties, differences between persons with cervical versus thoracolumbar injuries, and cutoff score differentiating a restricted from an unrestricted life space. : We conducted a test-retest reliability study in a community setting involving 50 persons with SCI (25 injured above C7, 25 injured below T1). Data were collected in 2 phone interviews approximately 9 days apart using the LSA.

What Can Interaction Webs Tell Us About Species Roles?

The group model is a useful tool to understand broad-scale patterns of interaction in a network, but it has previously been limited in use to food webs, which contain only predator-prey interactions. Natural populations interact with each other in a variety of ways and, although most published ecological networks only include information about a single interaction type (e.g.

Stability and feedback levels in food web models.

Neutel & Thorne (Ecology Letters, 17:651-661, June 2014) provide an approximation for the leading eigenvalue of a food web community matrix involving coefficients of its characteristic polynomial. Though valuably incorporating three-way species interactions, two critical problems emerge when one considers the dimensions of the system, calling the approach's accuracy and precision into question.