An insertion sequence unique to Frankia strain ArI5

At the genetic level, understanding of symbiotic nitrogen fixation by Frankia is limited to nif functions that are highly conserved among all organisms. The genetics and biochemistry of nodulation are largely unexplored because of a complete lack of genetic tools. In other bacteria, mobile genetic elements such as insertion sequences (IS) and transposons are commonly used to create mutations and insert new genetic material. We have characterized a 4 kbp segment of DNA from Frankia strain ArI5 that has the hallmarks of a mobile genetic element, inverted repeats flanking a gene encoding a transposase. There are at least six copies of this element in strain ArI5 but none in either strain CcI3 or CpI1. The inverted repeats are 17 nt long and separated by 2156 bp. Within that region are two, overlapping ORFs that each encode a transposase. RT-PCR analysis of RNA from Frankia ArI5 cells conclusively demonstrates the expression of one transposase gene and suggests that both may be transcribed. Numerous attempts to clone the intact IS in E. coli were unsuccessful suggesting that the element may be unstable in this context. A clone containing the complete IS was constructed in E. coli then modified by insertion of the kanamycin (KAN) resistance gene from Tn5. A fragment of DNA including the inverted repeats, transposase genes and KAN gene, was transferred to the suicide vector pJBSD1. The construct, pFRISK, was transformed into E. coli to search for transposition events.     

The contribution of the glenoid labrum to glenohumeral stability under physiological joint loading using finite element analysis

The labrum contributes to passive glenohumeral joint stability. Cadaveric studies have demonstrated that this has position and load dependency, which has not been quantified under physiological loads. This study aims to validate subject-specific finite element (FE) models against in vitro measurements of joint stability and to utilise the FE models to predict joint stability under physiological loads. The predicted stability values were within ± one standard deviation of experimental data and the FE models showed a reduction in stability of 10–15% with high, physiological, loads. The developed regression equations provide the first representation of passive glenohumeral stability and will aid surgical decision-making.