Prediction of nutrient digestibility and energy concentrations in fresh grass using nutrient composition

Improved nutrient utilization efficiency is strongly related to enhanced economic performance and reduced environmental footprint of dairy farms. Pasture-based systems are widely used for dairy production in certain areas of the world, but prediction equations of fresh grass nutritive value (nutrient digestibility and energy concentrations) are limited. Equations to predict digestible energy (DE) and metabolizable energy (ME) used for grazing cattle have been either developed with cattle fed conserved forage and concentrate diets or sheep fed previously frozen grass, and the majority of them require measurements less commonly available to producers, such as nutrient digestibility. The aim of the present study was therefore to develop prediction equations more suitable to grazing cattle for nutrient digestibility and energy concentrations, which are routinely available at farm level by using grass nutrient contents as predictors. A study with 33 nonpregnant, nonlactating cows fed solely fresh-cut grass at maintenance energy level for 50 wk was carried out over 3 consecutive grazing seasons. Freshly harvested grass of 3 cuts (primary growth and first and second regrowth), 9 fertilizer input levels, and contrasting stage of maturity (3 to 9 wk after harvest) was used, thus ensuring a wide representation of nutritional quality. As a result, a large variation existed in digestibility of dry matter (0.642-0.900) and digestible organic matter in dry matter (0.636-0.851) and in concentrations of DE (11.8-16.7 MJ/kg of dry matter) and ME (9.0-14.1 MJ/kg of dry matter). Nutrient digestibilities and DE and ME concentrations were negatively related to grass neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents but positively related to nitrogen (N), gross energy, and ether extract (EE) contents. For each predicted variable (nutrient digestibilities or energy concentrations), different combinations of predictors (grass chemical composition) were found to be significant and increase the explained variation. For example, relatively higher R(2) values were found for prediction of N digestibility using N and EE as predictors; gross-energy digestibility using EE, NDF, ADF, and ash; NDF, ADF, and organic matter digestibilities using N, water-soluble carbohydrates, EE, and NDF; digestible organic matter in dry matter using water-soluble carbohydrates, EE, NDF, and ADF; DE concentration using gross energy, EE, NDF, ADF, and ash; and ME concentration using N, EE, ADF, and ash. Equations presented may allow a relatively quick and easy prediction of grass quality and, hence, better grazing utilization on commercial and research farms, where nutrient composition falls within the range assessed in the current study.

Smart tool for force measurements during knee arthroscopy: in vivo human study

This paper describes the magnitude and patterns of forces obtained by using a probe, equipped with a six-axis force torque sensor, in knee arthroscopy. The probe was used by orthopaedic surgeons and trainees, who performed 11 different tasks in 10 standard knee arthroscopies. The force magnitude and patterns generated are presented; which can support the development of virtual arthroscopy systems with realistic haptic feedback. The results were compared across both groups of surgeons. A difference in the force patterns generated by senior versus junior surgeons was noted which can aid in the development of an objective assessment system for arthroscopy skills. The results could potentially be useful to assess future performance in real arthroscopy.

Virtual reality simulator for vitreoretinal surgery

AIM

To develop computer simulation of steps in vitreoretinal surgery using virtual reality technology.

MATERIAL AND METHODS

A workstation with three-dimensional position tracking stylus was attached to a Pentium II desktop PC with a graphic accelerator. Computer algorithms were developed using Open GL and Microsoft Visual C++ languages to control the interaction and update the visual feedback tracking the instruments. Soft tissue computer modelling was carried out to mimic the removal of a vitreous opacity. Lens touch with the instruments was also detected. Mathematical modelling to allow for lens distortion was taken into account.

RESULTS

A virtual reality computer model has been developed that can simulate initial steps of vitreoretinal surgery. Soft tissue modelling of the vitreous opacity and its removal by the vitrector was successfully simulated. The movements of the active and passive instruments in the dummy eye corresponded to the movements on the computer screen. On evaluation of the system, there was a minimal but discernable time lag between the stylus movement and the visual feedback. There was no tactile feedback when the lens touch was simulated. No further complex vitreoretinal surgery simulation was possible at this stage.

Molecular structure of the human asparagine synthetase gene

The human gene for asparagine synthetase has been isolated and the molecular organization has been determined by mapping and DNA sequencing of intron-exon boundaries. The gene spans 35 kb and contains 13 exons. The structure of the human gene has a high degree of similarity to that of the hamster asparagine synthetase gene, with identical positions for all but one of the intron regions. The 5' upstream region of this gene, like other housekeeping genes, lacks conventional TATA and CAAT boxes. Comparisons of the 5' upstream sequences of the human and hamster genes show limited similarity; however, both have a very high G + C content which may play a role in expression through DNA methylation.