Absence of branches from xylan in Arabidopsis gux mutants reveals potential for simplification of lignocellulosic biomass.

As one of the most abundant polysaccharides on Earth, xylan will provide more than a third of the sugars for lignocellulosic biofuel production when using grass or hardwood feedstocks. Xylan is characterized by a linear β(1,4)-linked backbone of xylosyl residues substituted by glucuronic acid, 4-O-methylglucuronic acid or arabinose, depending on plant species and cell types. The biological role of these decorations is unclear, but they have a major influence on the properties of the polysaccharide. Despite the recent isolation of several mutants with reduced backbone, the mechanisms of xylan synthesis and substitution are unclear. We identified two Golgi-localized putative glycosyltransferases, GlucUronic acid substitution of Xylan (GUX)-1 and GUX2 that are required for the addition of both glucuronic acid and 4-O-methylglucuronic acid branches to xylan in Arabidopsis stem cell walls. The gux1 gux2 double mutants show loss of xylan glucuronyltransferase activity and lack almost all detectable xylan substitution. Unexpectedly, they show no change in xylan backbone quantity, indicating that backbone synthesis and substitution can be uncoupled. Although the stems are weakened, the xylem vessels are not collapsed, and the plants grow to normal size. The xylan in these plants shows improved extractability from the cell wall, is composed of a single monosaccharide, and requires fewer enzymes for complete hydrolysis. These findings have implications for our understanding of the synthesis and function of xylan in plants. The results also demonstrate the potential for manipulating and simplifying the structure of xylan to improve the properties of lignocellulose for bioenergy and other uses.

Real-time marker prediction and CoR estimation in optical motion capture

Optical motion capture systems suffer from marker occlusions resulting in loss of useful information. This paper addresses the problem of real-time joint localisation of legged skeletons in the presence of such missing data. The data is assumed to be labelled 3d marker positions from a motion capture system. An integrated framework is presented which predicts the occluded marker positions using a Variable Turn Model within an Unscented Kalman filter. Inferred information from neighbouring markers is used as observation states; these constraints are efficient, simple, and real-time implementable. This work also takes advantage of the common case that missing markers are still visible to a single camera, by combining predictions with under-determined positions, resulting in more accurate predictions. An Inverse Kinematics technique is then applied ensuring that the bone lengths remain constant over time; the system can thereby maintain a continuous data-flow. The marker and Centre of Rotation (CoR) positions can be calculated with high accuracy even in cases where markers are occluded for a long period of time. Our methodology is tested against some of the most popular methods for marker prediction and the results confirm that our approach outperforms these methods in estimating both marker and CoR positions. © 2012 Springer-Verlag.