Role of dentin matrix protein 1 in cartilage redifferentiation and osteoarthritis

Objective The aim of this study was to test the possible involvement, relevance and significance of dentin matrix protein 1 (DMP1) in chondrocyte redifferentiation and OA. Methods To examine the function of DMP1 in vitro, bone marrow stromal cells (BMSCs) and articular chondrocytes (ACs) were isolated and differentiated in micromasses in the presence or absence of DMP1 small interfering RNA and analysed for chondrogenic phenotype. The association of DMP1 expression with OA progression was analysed time dependently in the OA menisectomy rat model and in grade-specific OA human samples. Results It was found that DMP1 was strongly related to chondrogenesis, which was evidenced by the strong expression of DMP1 in the 14.5-day mouse embryonic cartilage development stage and in femoral heads of post-natal days 0 and 4. In vitro chondrogenesis in BMSCs and ACs was accompanied by a gradual increase in DMP1 expression at both the gene and protein levels. In addition, knockdown of DMP1 expression led to decreased chondrocyte marker genes, such as COL2A1, ACAN and SOX9, and an increase in the expression of COL10A and MMP13 in ACs. Moreover, treatment with IL-1β, a well-known catabolic culprit of proteoglycan matrix loss, significantly reduced the expression of DMP1. Furthermore, we also observed the suppression of DMP1 protein in a grade-specific manner in knee joint samples from patients with OA. In the menisectomy-induced OA model, an increase in the Mankin score was accompanied by the gradual loss of DMP1 expression. Conclusion Observations from this study suggest that DMP1 may play an important role in maintaining the chondrogenic phenotype and its possible involvement in altered cartilage matrix remodelling and degradation in disease conditions like OA.

Genetic evidence for the vital function of osterix in cementogenesis

To date, attempts to regenerate a complete tooth, including the critical periodontal tissues associated with the tooth root, have not been successful. Controversy still exists regarding the origin of the cell source for cellular cementum (epithelial or mesenchymal). This disagreement may be partially due to a lack of understanding of the events leading to the initiation and development of the tooth roots and supportive tissues, such as the cementum. Osterix (OSX) is a transcriptional factor essential for osteogenesis, but its role in cementogenesis has not been addressed. In the present study, we first documented a close relationship between the temporal- and spatial-expression pattern of OSX and the formation of cellular cementum. We then generated 3.6 Col 1-OSX transgenic mice, which displayed accelerated cementum formation vs. WT controls. Importantly, the conditional deletion of OSX in the mesenchymal cells with two different Cre systems (the 2.3 kb Col 1 and an inducible CAG-CreER) led to a sharp reduction in cellular cementum formation (including the cementum mass and mineral deposition rate) and gene expression of dentin matrix protein 1 (DMP1) by cementocytes. However, the deletion of the OSX gene after cellular cementum formed did not alter the properties of the mature cementum as evaluated by backscattered SEM and resin-cast SEM. Transient transfection of Osx in the cementoblasts in vitro significantly inhibited cell proliferation and increased cell differentiation and mineralization. Taken together, these data support 1) the mesenchymal origin of cellular cementum (from PDL progenitor cells); 2) the vital role of OSX in controlling the formation of cellular cementum; and 3) the limited remodeling of cellular cementum in adult mice.

Growth-hormone-stimulated dentinogenesis in Lewis dwarf rat molars

In dentinogenesis, certain growth factors, matrix proteoglycans, and proteins are directly or indirectly dependent on growth hormone. The hypothesis that growth hormone up-regulates the expression of enzymes, sialoproteins, and other extracellular matrix proteins implicated in the formation and mineralization of tooth and bone matrices was tested by the treatment of Lewis dwarf rats with growth hormone over 5 days. The molar teeth were processed for immunohistochemical demonstration of bone-alkaline phosphatase, bone morphogenetic proteins-2 and -4, osteocalcin, osteopontin, bone sialoprotein, and E11 protein. Odontoblasts responded to growth hormone by more cells expressing bone morphogenetic protein, alkaline phosphatase, osteocalcin, and osteopontin. No changes were found in bone sialoprotein or E11 protein expression. Thus, growth hormone may stimulate odontoblasts to express several growth factors and matrix proteins associated with dentin matrix biosynthesis in mature rat molars.

Influence of osteocytes in the in vitro and in vivo β-tricalcium phosphate-stimulated osteogenesis

Osteocytes, known to act as the main regulators of bone homeostasis, have become a major focus in the field of bone research. Bioactive ceramics have been widely used for bone regeneration. However, there are few studies about the interaction of osteocytes with bioceramics. The effects of osteocytes on the in vitro and in vivo osteogenesis of bioceramics are also unclear. The aim of this study was to investigate the role of osteocytes on the b-tricalcium phosphate (b-TCP) stimulated osteogenesis. It was found that osteocytes responded to the b-TCP stimulation, leading to the release of Wnt (wingless-related MMTV integration site), which enhanced osteogenic differentiation of bone marrow stromal cells via Wnt signaling pathway. Receptor activator of nuclear factor kappa B ligand, an osteoclast inducer, was also upregulated, indicating that osteocytes would also participated in activation of osteoclasts, which played a major role in the degradation process of b-TCP and new bone remodeling. In vivo studies further demonstrated that when the material was completely embedded by newly formed bone, the only cell contacting with the material was osteocyte. However, the material would eventually be degraded and replaced by the new bone, requiring the participation of osteoclasts and osteoblasts, which were demonstrated by using immunostaining in this study. As the only cell contacting with the material, osteocytes probably acted in a regulatory role to regulate the surrounding osteoclasts and osteoblasts. Osteocytes were also found to participate in the maturation of osteoblasts and the mineralization process of biomaterials, by upregulating E11 (podoplanin) and dentin matrix protein 1 expression. These findings indicated that osteocytes involved in bone biomaterial-mediated osteogenesis and biomaterial degradation, providing valuable insights into the mechanism of material-stimulated osteogenesis, and a novel strategy to optimize the evaluating system for the biological properties of biomaterials.

Dynamic matrix control on wind-induced vibration of spatial latticed structures [Chinese title = 空间网壳结构风振抑制的动态矩阵预测控制分析]

Ameliorated strategies were put forward to improve the model predictive control in reducing the wind induced vibration of spatial latticed structures. The dynamic matrix control (DMC) predictive method was used and the reference trajectory which is called the decaying functions was suggested for the analysis of spatial latticed structure (SLS) under wind loads. The wind-induced vibration control model of SLS with improved DMC model predictive control was illustrated, then the different feedback strategies were investigated and a typical SLS was taken as example to investigate the reduction of wind-induced vibration. In addition, the robustness and reliability of DMC strategy were discussed by varying the model configurations.

Decision Matrix Compared with Partnering Principles

The ideas for this CRC research project are based directly on Sidwell, Kennedy and Chan (2002). That research examined a number of case studies to identify the characteristics of successful projects. The findings were used to construct a matrix of best practice project delivery strategies. The purpose of this literature review is to test the decision matrix against established theory and best practice in the subject of construction project management.

Report on the Development and Validation of the Best Practice Decision Matrix

The Co-operative Research Centre for Construction Innovation (CRC-CI) is funding a project known as Value Alignment Process for Project Delivery. The project consists of a study of best practice project delivery and the development of a suite of products, resources and services to guide project teams towards the best procurement approach for a specific project or group of projects. These resources will be focused on promoting the principles that underlie best practice project delivery rather than simply identifying an off-the-shelf procurement system. This project builds on earlier work by Sidwell, Kennedy and Chan (2002), on re-engineering the construction delivery process, which developed a procurement framework in the form of a Decision Matrix

Towards a rule-based matrix for evaluating distress mechanisms in bridges

The effective management of bridge stock involves making decisions as to when to repair, remedy, or do nothing, taking into account the financial and service life implications. Such decisions require a reliable diagnosis as to the cause of distress and an understanding of the likely future degradation. Such diagnoses are based on a combination of visual inspections, laboratory tests on samples and expert opinions. In addition, the choice of appropriate laboratory tests requires an understanding of the degradation mechanisms involved. Under these circumstances, the use of expert systems or evaluation tools developed from “realtime” case studies provides a promising solution in the absence of expert knowledge. This paper addresses the issues in bridge infrastructure management in Queensland, Australia. Bridges affected by alkali silica reaction and chloride induced corrosion have been investigated and the results presented using a mind mapping tool. The analysis highights that several levels of rules are required to assess the mechanism causing distress. The systematic development of a rule based approach is presented. An example of this application to a case study bridge has been used to demonstrate that preliminary results are satisfactory.

Towards a Rule-based matrix for evaluating distress mechanisms in bridges

One of the key issues facing public asset owners is the decision of refurbishing aged built assets. This decision requires an assessment of the “remaining service life” of the key components in a building. The remaining service life is significantly dependent upon the existing condition of the asset and future degradation patterns considering durability and functional obsolescence. Recently developed methods on Residual Service Life modelling, require sophisticated data that are not readily available. Most of the data available are in the form of reports prior to undertaking major repairs or in the form of sessional audit reports. Valuable information from these available sources can serve as bench marks for estimating the reference service life. The authors have acquired similar informations from a public asset building in Melbourne. Using these informations, the residual service life of a case study building façade has been estimated in this paper based on state-of-the-art approaches. These estimations have been evaluated against expert opinion. Though the results are encouraging it is clear that the state-of-the-art methodologies can only provide meaningful estimates provided the level and quality of data are available. This investigation resulted in the development of a new framework for maintenance that integrates the condition assessment procedures and factors influencing residual service life

Inducing shades of meaning by matrix methods : a first step towards thematic analysis of opinion

This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Botanical matrix

Botanical matrix is a graphic map produced via a process involving an initial site installation (350 m contour transect), a botanical survey and photographic documentation of species. The site is a housing subdivision at Point Henry, on the SE coast of Western Australia which is a landscape which is host the most botanically diverse vegetation found worldwide - known locally as 'kwongan'. Notoriously difficult vegetation to measure and map, kwongan is a visual 'engima', for paradoxically it appears to the lay person as visually bland and highly homogenous. There is thus is a critical need for the development of new forms of representation which overcome the barriers between the perception and reality of this botanical condition. Botanical Matrix is one result of the author's research which seeks to address this important problem.

The osteogenic differentiation of adipose tissue-derived precursor cells in A 3D scaffold/matrix environment

Abstract: This paper details an in-vitro study using human adipose tissue-derived precursor/stem cells (ADSCs) in three-dimensional (3D) tissue culture systems. ADSCs from 3 donors were seeded onto NaOH-treated medical grade polycaprolactone-tricalcium phosphate (mPCL-TCP) scaffolds with two different matrix components; fibrin glue and lyophilized collagen. ADSCs within these scaffolds were then induced to differentiate along the osteogenic lineage for a 28-day period and various assays and imaging techniques were performed at Day 1, 7, 14, 21 and 28 to assess and compare the ADSC’s adhesion, viability, proliferation, metabolism and differentiation along the osteogenic lineage when cultured in the different scaffold/matrix systems. The ADSC cells were proliferative in both collagen and fibrin mPCL-TCP scaffold systems with a consistently higher cell number (by comparing DNA amounts) in the induced group over the non-induced groups for both scaffold systems. In response to osteogenic induction, these ADSCs expressed elevated osteocalcin, alkaline phosphatase and osteonectin levels. Cells were able to proliferate within the pores of the scaffolds and form dense cellular networks after 28 days of culture and induction. The successful cultivation of osteogenic by FDM process manufactured ADSCs within a 3D matrix comprising fibrin glue or collagen, immobilized within a robust synthetic scaffold is a promising technique which should enhance their potential usage in the regenerative medicine arena, such as bone tissue engineering.