Development and synthesis of innovative approaches to the surgical assessment of articular cartilage degeneration

This research has established, through ultrasound, near infrared spectroscopy and biomechanics experiments, parameters and parametric relationships that can form the framework for quantifying the integrity of the articular cartilage-on-bone laminate, and objectively distinguish between normal/healthy and abnormal/degenerated joint tissue, with a focus on articular cartilage. This has been achieved by: 1. using traditional experimental methods to produce new parameters for cartilage assessment; 2. using novel methodologies to develop new parameters; and 3. investigating the interrelationships between mechanical, structural and molec- ular properties to identify and select those parameters and methodologies that can be used in a future arthroscopic probe based on points 1 and 2. By combining the molecular, micro- and macro-structural characteristics of the tissue with its mechanical properties, we arrive at a set of critical benchmarking parameters for viable and early-stage non-viable cartilage. The interrelationships between these characteristics, examined using a multivariate analysis based on principal components analysis, multiple linear regression and general linear modeling, could then to deter- mine those parameters and relationships which have the potential to be developed into a future clinical device. Specifically, this research has found that the ultrasound and near infrared techniques can subsume the mechanical parameters and combine to characterise the tissue at the molecular, structural and mechanical levels over the full depth of the cartilage matrix. It is the opinion in this thesis that by enabling the determination of the precise area of in uence of a focal defect or disease in the joint, demarcating the boundaries of articular cartilage with dierent levels of degeneration around a focal defect, better surgical decisions that will advance the processes of joint management and treatment will be achieved. Providing the basis for a surgical tool, this research will contribute to the enhancement and quanti�cation of arthroscopic procedures, extending to post- treatment monitoring and as a research tool, will enable a robust method for evaluating developing (particularly focalised) treatments.

Controlled carbon nanotube synthesis from germanium nanoparticles

Controlled syntheses of carbon nanotubes (CNTs) are highly desirable for nanoelectronic applications. To date, metallic catalyst particles have usually been deemed unavoidable for the nucleation and growth of any kind of CNTs. However, the presence of metal species mixed with the CNTs represents a shortcoming for most electronic applications, as metal particles are incompatible with silicon semiconductor technology. Recently it has been shown that it is possible to create nanotubes without the presence of metallic catalysts, by using SIO2, Ge and other non-metallic nanoparticles. Here we report on a metal-catalyst-free synthesis of CNTs, obtained through Ge nano-particles assembled on silicon surfaces previously patterned by Focused Ion Beam and nanoindentation.

N2O emissions from agricultural lands: a synthesis of simulation approaches

Nitrous oxide (N2O) is primarily produced by the microbially-mediated nitrification and denitrification processes in soils. It is influenced by a suite of climate (i.e. temperature and rainfall) and soil (physical and chemical) variables, interacting soil and plant nitrogen (N) transformations (either competing or supplying substrates) as well as land management practices. It is not surprising that N2O emissions are highly variable both spatially and temporally. Computer simulation models, which can integrate all of these variables, are required for the complex task of providing quantitative determinations of N2O emissions. Numerous simulation models have been developed to predict N2O production. Each model has its own philosophy in constructing simulation components as well as performance strengths. The models range from those that attempt to comprehensively simulate all soil processes to more empirical approaches requiring minimal input data. These N2O simulation models can be classified into three categories: laboratory, field and regional/global levels. Process-based field-scale N2O simulation models, which simulate whole agroecosystems and can be used to develop N2O mitigation measures, are the most widely used. The current challenge is how to scale up the relatively more robust field-scale model to catchment, regional and national scales. This paper reviews the development history, main construction components, strengths, limitations and applications of N2O emissions models, which have been published in the literature. The three scale levels are considered and the current knowledge gaps and challenges in modelling N2O emissions from soils are discussed.

Patterns of substrate utilization during long-term incubations at different temperatures

Microorganisms play key roles in biogeochemical cycling by facilitating the release of nutrients from organic compounds. In doing so, microbial communities use different organic substrates that yield different amounts of energy for maintenance and growth of the community. Carbon utilization efficiency (CUE) is a measure of the efficiency with which substrate carbon is metabolized versus mineralized by the microbial biomass. In the face of global change, we wanted to know how temperature affected the efficiency by which the soil microbial community utilized an added labile substrate, and to determine the effect of labile soil carbon depletion (through increasing duration of incubation) on the community's ability to respond to an added substrate. Cellobiose was added to soil samples as a model compound at several times over the course of a long-term incubation experiment to measure the amount of carbon assimilated or lost as CO2 respiration. Results indicated that in all cases, the time required for the microbial community to take up the added substrate increased as incubation time prior to substrate addition increased. However, the CUE was not affected by incubation time. Increased temperature generally decreased CUE, thus the microbial community was more efficient at 15 degrees C than at 25 degrees C. These results indicate that at warmer temperatures microbial communities may release more CO2 per unit of assimilated carbon. Current climate-carbon models have a fixed CUE to predict how much CO2 will be released as soil organic matter is decomposed. Based on our findings, this assumption may be incorrect due to variation of CUE with changing temperature. (c) 2008 Elsevier Ltd. All rights reserved.