Characterization of cytokines, matrix metalloproteinases and toll-like receptors in human periodontal tissue destruction

Periodontal Disease affects the supporting structures of the teeth and is initiated by a microbial biofilm called dental plaque. Severity ranges from superficial inflammation of the gingiva (gingivitis) to extensive destruction of connective tissue and bone leading to tooth loss (periodontitis). In periodontitis the destruction of tissue is caused by a cascade of microbial and host factors together with proteolytic enzymes. Matrix metalloproteinases (MMPs) are known to be central mediators of the pathologic destruction in periodontitis. Initially plaque bacteria provide pathogen-associated molecular patterns (PAMPs) which are sensed by Toll-like receptors (TLRs), and initiate intracellular signaling cascades leading to host inflammation. Our aim was to characterize TNF-α (tumor necrosis factor-alpha) and its type I and II receptors in periodontal tissues, as well as, the effects of TNF-α, IL-1β (interleukin-1beta) and IL-17 on the production and/or activation of MMP-3, MMP-8 and MMP-9. Furthermore we mapped the TLRs in periodontal tissues and assessed how some of the PAMPs binding to the key TLRs found in periodontal tissues affect production of TNF-α and IL-1β by gingival epithelial cells with or without combination of IL-17. TNF-α and its receptors were detected in pericoronitis. Furthermore, increased expression of interleukin-1β and vascular cell adhesion molecule-1 was found as a biological indicator of TNF-α ligand-receptor interaction. MMP-3, -8, and 9 were investigated in periodontitis affected human gingival crevicular fluid and gingival fibroblasts produced pro-MMP-3. Following that, the effect of IL-17 was studied on MMP and pro-inflammatory cytokine production. IL-17 was increased in periodontitis and up-regulated IL-1β, TNF-α, MMP-1 and MMP-3. We continued by demonstrating TLRs in gingival tissues, in which significant differences between patients with periodontitis and healthy controls were found. Finally, enzyme-linked immunosorbent assays were performed to show that the gingival cells response to inflammatory responses in a TLR-dependent manner. Briefly, this thesis demonstrates that TLRs are present in periodontal tissues and present differences in periodontitis compared to healthy controls. The cells of gingival tissues respond to inflammatory process in a TLR-dependent manner by producing pro-inflammatory cytokines. During the destruction of periodontal tissues, the release (IL-1β and TNF-α) and co-operation with other pro-inflammatory cytokines (IL-17), which in turn increase the inflammation and thus be more harmful to the host with the increased presence of MMPs (MMP-1, MMP-3, MMP-8, MMP-9) in diseased over healthy sites.

Jump Reorientation of Water Molecules Confined in Narrow Carbon Nanotubes

We used molecular dynamics (MD) simulations to study the reorientational dynamics of water molecules confined inside narrow carbon nanotubes immersed in a bath of water. Our simulations show that the confined water molecules exhibit bistability in their reorientational relaxation, which proceeds by angular jumps between the two stable states. The angular jump of a water molecule in the bulk involves the breaking of a hydrogen bond with one of its neighbors and the formation of a hydrogen bond with a different neighbor. In contrast, the angular jump of a confined water molecule corresponds to an interchange of the two hydrogen atoms that can form a hydrogen bond with the same neighbor. The free energy barrier between these two states is a few k(B)T. The analytic solution of a simplified two-state jump model that qualitatively explains the reorientational behavior observed in simulations is also presented.

Methanotrophs from natural ecosystems for ruminant methane mitigation

Enteric fermentation of methane by ruminant animals represents a major source of anthropogenic methane production. Methane produced in this manner is released to the atmosphere where it is highly efficient at absorbing thermal radiation, which consequently increases the global surface temperature. Although many different strategies to control ruminant methane emissions have been considered, few are currently considered viable. Obligate and acultative methane oxidising bacteria (MOB) and anaerobic methane oxidising archaea (ANME) play a fundamental role in the carbon cycle by metabolising methane before it is released into the atmosphere. Because of this, methanotrophic microorganisms represent a novel biological control agent in mitigating ruminant methane emissions. This project aims to characterise methanotrophic microorganisms from a range of environments, and to subsequently determine the metabolic activity of these microorganisms under in vitro rumen-like conditions.

Maximising spent litter fertiliser returns through nutrient and carbon management

Develop a superior fertiliser product (compared to conventional spent litter and current palletised forms) formulated from poultry litter.

Oxides supported carbon air-electrodes for alkaline solution power devices

Porous carbon oxygen-reducing electrodes incorporated with perovskite oxide catalysts are reported. It has been possible to fabricate high-performance oxygen-reducing electrodes by introducing La0.5Sr0.5CoO3 and La0.99Sr0.01NiO3 with the activated coconut-shell charcoal; these electrodes could sustain load currents as high as 1 A cm−2 without serious degradation. A model to explain oxygen-reducing activity of these oxides has been proposed.

Best management options for onion thrips in onions

Best management options for onion thrips.

Electroconductance in single-wall carbon nanotubes

A comparative study of the electric-field induced hopping transport probes the effective dimensionality (D) in bulk and ultrathin films of single-wall carbon nanotubes (SWNTs). The values of the scaling function exponents for the electroconductance are found to be consistent with that in three-dimensional and two-dimensional systems. The significant difference in threshold voltage in these two types of SWNTs is a consequence of the variation in the number of energetically favorable sites available for charge carriers to hop by using the energy from the field. Furthermore, a modification to the magnetotransport is observed under high electric-fields.

Carbon in Condamine Catchment

Education and support to imporve soil carbon in the Condamine catchment.

Carbon grazing: Managing carbon flows for resilient pasture in variable climate

Work with consultants to help graziers understand implications of carbon in their pastures.

A hybrid clustering procedure for concentric and chain-like clusters

K-means algorithm is a well known nonhierarchical method for clustering data. The most important limitations of this algorithm are that: (1) it gives final clusters on the basis of the cluster centroids or the seed points chosen initially, and (2) it is appropriate for data sets having fairly isotropic clusters. But this algorithm has the advantage of low computation and storage requirements. On the other hand, hierarchical agglomerative clustering algorithm, which can cluster nonisotropic (chain-like and concentric) clusters, requires high storage and computation requirements. This paper suggests a new method for selecting the initial seed points, so that theK-means algorithm gives the same results for any input data order. This paper also describes a hybrid clustering algorithm, based on the concepts of multilevel theory, which is nonhierarchical at the first level and hierarchical from second level onwards, to cluster data sets having (i) chain-like clusters and (ii) concentric clusters. It is observed that this hybrid clustering algorithm gives the same results as the hierarchical clustering algorithm, with less computation and storage requirements.

Soil carbon stock in the tropical rangelands of Australia: Effects of soil type and grazing pressure, and determination of sampling requirement.

On-going, high-profile public debate about climate change has focussed attention on how to monitor the soil organic carbon stock (C(s)) of rangelands (savannas). Unfortunately, optimal sampling of the rangelands for baseline C(s) - the critical first step towards efficient monitoring - has received relatively little attention to date. Moreover, in the rangelands of tropical Australia relatively little is known about how C(s) is influenced by the practice of cattle grazing. To address these issues we used linear mixed models to: (i) unravel how grazing pressure (over a 12-year period) and soil type have affected C(s) and the stable carbon isotope ratio of soil organic carbon (delta(13)C) (a measure of the relative contributions of C(3) and C(4) vegetation to C(s)); (ii) examine the spatial covariation of C(s) and delta(13)C; and, (iii) explore the amount of soil sampling required to adequately determine baseline C(s). Modelling was done in the context of the material coordinate system for the soil profile, therefore the depths reported, while conventional, are only nominal. Linear mixed models revealed that soil type and grazing pressure interacted to influence C(s) to a depth of 0.3 m in the profile. At a depth of 0.5 m there was no effect of grazing on C(s), but the soil type effect on C(s) was significant. Soil type influenced delta(13)C to a soil depth of 0.5 m but there was no effect of grazing at any depth examined. The linear mixed model also revealed the strong negative correlation of C(s) with delta(13)C, particularly to a depth of 0.1 m in the soil profile. This suggested that increased C(s) at the study site was associated with increased input of C from C(3) trees and shrubs relative to the C(4) perennial grasses; as the latter form the bulk of the cattle diet, we contend that C sequestration may be negatively correlated with forage production. Our baseline C(s) sampling recommendation for cattle-grazing properties of the tropical rangelands of Australia is to: (i) divide the property into units of apparently uniform soil type and grazing management; (ii) use stratified simple random sampling to spread at least 25 soil sampling locations about each unit, with at least two samples collected per stratum. This will be adequate to accurately estimate baseline mean C(s) to within 20% of the true mean, to a nominal depth of 0.3 m in the profile.

Soil carbon modelling as a tool for carbon balance studies in forestry

Soils represent a remarkable stock of carbon, and forest soils are estimated to hold half of the global stock of soil carbon. Topical concern about the effects of climate change and forest management on soil carbon as well as practical reporting requirements set by climate conventions have created a need to assess soil carbon stock changes reliably and transparently. The large spatial variability of soil carbon commensurate with relatively slow changes in stocks hinders the assessment of soil carbon stocks and their changes by direct measurements. Models therefore widely serve to estimate carbon stocks and stock changes in soils. This dissertation aimed to develop the soil carbon model YASSO for upland forest soils. The model was aimed to take into account the most important processes controlling the decomposition in soils, yet remain simple enough to ensure its practical applicability in different applications. The model structure and assumptions were presented and the model parameters were defined with empirical measurements. The model was evaluated by studying the sensitivities of the model results to parameter values, by estimating the precision of the results with an uncertainty analysis, and by assessing the accuracy of the model by comparing the predictions against measured data and to the results of an alternative model. The model was applied to study the effects of intensified biomass extraction on the forest carbon balance and to estimate the effects of soil carbon deficit on net greenhouse gas emissions of energy use of forest residues. The model was also applied in an inventory based method to assess the national scale forest carbon balance for Finland’s forests from 1922 to 2004. YASSO managed to describe sufficiently the effects of both the variable litter and climatic conditions on decomposition. When combined with the stand models or other systems providing litter information, the dynamic approach of the model proved to be powerful for estimating changes in soil carbon stocks on different scales. The climate dependency of the model, the effects of nitrogen on decomposition and forest growth as well as the effects of soil texture on soil carbon stock dynamics are areas for development when considering the applicability of the model to different research questions, different land use types and wider geographic regions. Intensified biomass extraction affects soil carbon stocks, and these changes in stocks should be taken into account when considering the net effects of forest residue utilisation as energy. On a national scale, soil carbon stocks play an important role in forest carbon balances.