Effects of conjugated linoleic acid on myogenic and inflammatory responses in a human primary muscle and tumor coculture model

The antiproliferative and anti-inflammatory properties of conjugated linoleic acid (CLA) make it a potentially novel treatment in chronic inflammatory muscle wasting disease, particularly cancer cachexia. Human primary muscle cells were grown in coculture with MIA PaCa-2 pancreatic tumor cells and exposed to varying concentrations of c9,t11 and t10,c12 CLA. Expression of myogenic (Myf5, MyoD, myogenin, and myostatin) and inflammatory genes (CCL-2, COX-2, IL-8, and TNF-) were measured by real-time PCR. The t10,c12 CLA isomer, but not the c9,t11 isomer, significantly decreased MIA PaCa-2 proliferation by between 15% and 19%. There was a marked decrease in muscle MyoD and myogenin expression (78% and 62%, respectively), but no change in either Myf5 or myostatin, in myotubes grown in coculture with MIA PaCa-2 cells. CLA had limited influence on these responses. A similar pattern of myogenic gene expression changes was observed in myotubes treated with TNF- alone. Several-fold significant increases in CCL-2, COX-2, IL-8, and TNF- expression in myotubes were observed with MIA PaCa-2 coculture. The c9,t11 CLA isomer significantly decreased basal expression of TNF- in myotubes and could ameliorate its tumor-induced rise. The study provides insight into the anti-inflammatory and antiproliferative actions of CLA and its application as a therapeutic agent in inflammatory disease states.

Identifying the predictors of employee health and satisfaction in an NPM environment : testing a comprehensive and non-linear demand-control-support model

The Demand-Control-Support (DCS) model is investigated in the context of police officers working within an organization that has relatively widespread uptake of New Public Management (NPM) practices. A survey of 479 police officers from two geographic regions was undertaken and the results indicate that the DCS offers a simple, yet powerful, framework for identifying the conditions to be managed in an NPM-oriented environment. Job control and work-based support predict all four target variables, strengthening the view that decision-making latitude and support from supervisors and colleagues represent critical resources for promoting the well-being, satisfaction and commitment of public sector employees.

An empirical examination of feedback : user control and performance in a hapto-audio-visual training environment

Utilising advanced technologies, such as virtual environments (VEs), is of importance to training and education. The need to develop and effectively apply interactive, immersive 3D VEs continues to grow. As with any emerging technology, user acceptance of new software and hardware devices is often difficult to measure and guidelines to introduce and ensure adequate and correct usage of such technologies are lacking. It is therefore imperative to obtain a solid understanding of the important elements that play a role in effective learning through VEs. In particular, 3D VEs may present unusual and varied interaction and adoption considerations. The major contribution of this study is to investigate a complex set of interrelated factors in the relatively new sphere of VEs for training and education. Although many of the factors appears to be important from past research, researcher have not explicitly studied a comprehensive set of inter-dependant, empirically validated factors in order to understand how VEs aid complex procedural knowledge and motor skill learning. By integrating theory from research on training, human computer interaction (HCI), ergonomics and cognitive psychology, this research proposes and validates a model that contributes to application-specific VE efficacy formation. The findings of this study show visual feedback has a significant effect on performance. For tactile/force feedback and auditory feedback, no significant effect were found. For satisfaction, user control is salient for performance. Other factors such as interactivity and system comfort, as well as level of task difficulty, also showed effects on performance.

Research on human embryos and cloning : difficulties of legislating in a changing environment and model approaches to regulation

It is difficult to regulate rapidly changing fields of science. New technologies are not anticipated and legislation becomes inadequate. Legislative definitions are also problematic. This article begins with consideration of such difficulties in the context of research on human embryos and cloning. It considers problems with past legislative definitions in Australia, the new regulatory regime, and whether that regime now sets clear boundaries. It is found that problems still exist – some terms are not adequately defined and boundaries for research prove unclear. Three regulatory approaches are therefore discussed. Legislation based on strict definitions is compared to a legislative model that leaves terms undefined. The third model – which combines framework legislation with the oversight of a regulatory authority – is seen as most suitable. However, problems with this model are recognised and suggestions made regarding how to ensure the “framework” remains workable and effective.

A full body musculoskeletal model based on flexible multibody simulation approach utilised in bone strain analysis during human locomotion

Load-induced strains applied to bone can stimulate its development and adaptation. In order to quantify the incident strains within the skeleton, in vivo implementation of strain gauges on the surfaces of bone is typically used. However, in vivo strain measurements require invasive methodology that is challenging and limited to certain regions of superficial bones only such as the anterior surface of the tibia. Based on our previous study [Al Nazer et al. (2008) J Biomech. 41:1036–1043], an alternative numerical approach to analyse in vivo strains based on the flexible multibody simulation approach was proposed. The purpose of this study was to extend the idea of using the flexible multibody approach in the analysis of bone strains during physical activity through integrating the magnetic resonance imaging (MRI) technique within the framework. In order to investigate the reliability and validity of the proposed approach, a three-dimensional full body musculoskeletal model with a flexible tibia was used as a demonstration example. The model was used in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model was developed using the actual geometry of human tibia, which was obtained from three-dimensional reconstruction of MRI. Motion capture data obtained from walking at constant velocity were used to drive the model during the inverse dynamics simulation in order to teach the muscles to reproduce the motion in the forward dynamics simulation. Based on the agreement between the literature-based in vivo strain measurements and the simulated strain results, it can be concluded that the flexible multibody approach enables reasonable predictions of bone strain in response to dynamic loading. The information obtained from the present approach can be useful in clinical applications including devising exercises to prevent bone fragility or to accelerate fracture healing.

Human action recognition based on 3D SIFT and LDA model

How to recognize human action from videos captured by modern cameras efficiently and effectively is a challenge in real applications. Traditional methods which need professional analysts are facing a bottleneck because of their shortcomings. To cope with the disadvantage, methods based on computer vision techniques, without or with only a few human interventions, have been proposed to analyse human actions in videos automatically. This paper provides a method combining the three dimensional Scale Invariant Feature Transform (SIFT) detector and the Latent Dirichlet Allocation (LDA) model for human motion analysis. To represent videos effectively and robustly, we extract the 3D SIFT descriptor around each interest point, which is sampled densely from 3D Space-time video volumes. After obtaining the representation of each video frame, the LDA model is adopted to discover the underlying structure-the categorization of human actions in the collection of videos. Public available standard datasets are used to test our method. The concluding part discusses the research challenges and future directions.