Developmental Pathways in Microcerotermes turneri (Termitidae: Termitinae): Biometric Descriptors of Worker Caste and Instar

The foraging process of location and exploitation of food in complex termite societies is in part reliant upon unequal division of specific tasks amongst its members (polyethism). To conduct studies assessing the role of individuals in foraging activities it is necessary to have descriptors of worker caste and instar. Here we provide biometric descriptors of specific caste and instar for worker caste and instars of Microcerotermes turneri (Froggatt) (Termitidae: Termitinae) for the worker castes (male and female) for the identification of individuals in laboratory assays applicable across multiple nests. The use of head width for determining sex of workers was successful across multiple nests. The length of the first three flagellum segments of the antenna and tibia three could be used to determine worker instar.

What does the animal model teach us about the effects of physical activity on growing bone?

Experiments to design physical activity programs that optimize their osteogenic potential are difficult to accomplish in humans. The aim of this article is to review the contributions that animal studies have made to knowledge of the loading conditions that are osteogenic to the skeleton during growth, as well as to consider to what extent animal studies fail to provide valid models of physical activity and skeletal maturation. Controlled loading studies demonstrate that static loads are ineffective, and that bone formation is threshold driven and dependent on strain rate, amplitude, and duration of loading. Only a few loading cycles per session are required, and distributed bouts are more osteogenic than sessions of long duration. Finally, animal models fail to inform us of the most appropriate ways to account for the variations in biological maturation that occur in our studies of children and adolescents, requiring the use of techniques for studying human growth and development.

Cyclic pneumatic soft-tissue compression accelerates the union of distal radial osteomoties in an ovine model

The aim of this randomised, controlled in vivo study in an ovine model was to investigate the effect of cylic pneumatic pressure on fracture healing. We performed a transverse osteotomy of the right radius in 37 sheep. They were randomised to a control group or a treatment group where they received cyclic loading of the osteotomy by the application of a pressure cuff around the muscles of the proximal forelimb. Sheep from both groups were killed at four or six weeks. Radiography, ultrasonography, biomechanical testing and histomorphometry were used to assess the differences between the groups. The area of periosteal callus, peak torsional strength, fracture stiffness, energy absorbed over the first 10° of torsion and histomorphometric analysis all showed that the osteotomies treated with the cyclic pneumatic pressure at four weeks were not significantly different from the control osteotomies at six weeks.

3D statistical shape models to embed spatial relationship information

This paper presents the creation of 3D statistical shape models of the knee bones and their use to embed information into a segmentation system for MRIs of the knee. We propose utilising the strong spatial relationship between the cartilages and the bones in the knee by embedding this information into the created models. This information can then be used to automate the initialisation of segmentation algorithms for the cartilages. The approach used to automatically generate the 3D statistical shape models of the bones is based on the point distribution model optimisation framework of Davies. Our implementation of this scheme uses a parameterized surface extraction algorithm, which is used as the basis for the optimisation scheme that automatically creates the 3D statistical shape models. The current approach is illustrated by generating 3D statistical shape models of the patella, tibia and femoral bones from a segmented database of the knee. The use of these models to embed spatial relationship information to aid in the automation of segmentation algorithms for the cartilages is then illustrated.