Application of chemometrics to analysis of soil pollutants

This overview focuses on the application of chemometrics techniques for the investigation of soils contaminated by polycyclic aromatic hydrocarbons (PAHs) and metals because these two important and very diverse groups of pollutants are ubiquitous in soils. The salient features of various studies carried out in the micro- and recreational environments of humans, are highlighted in the context of the various multivariate statistical techniques available across discipline boundaries that have been effectively used in soil studies. Particular attention is paid to techniques employed in the geosciences that may be effectively utilized for environmental soil studies; classical multivariate approaches that may be used in isolation or as complementary methods to these are also discussed. Chemometrics techniques widely applied in atmospheric studies for identifying sources of pollutants or for determining the importance of contaminant source contributions to a particular site, have seen little use in soil studies, but may be effectively employed in such investigations. Suitable programs are also available for suggesting mitigating measures in cases of soil contamination, and these are also considered. Specific techniques reviewed include pattern recognition techniques such as Principal Components Analysis (PCA), Fuzzy Clustering (FC) and Cluster Analysis (CA); geostatistical tools include variograms, Geographical Information Systems (GIS), contour mapping and kriging; source identification and contribution estimation methods reviewed include Positive Matrix Factorisation (PMF), and Principal Component Analysis on Absolute Principal Component Scores (PCA/APCS). Mitigating measures to limit or eliminate pollutant sources may be suggested through the use of ranking analysis and multi criteria decision making methods (MCDM). These methods are mainly represented in this review by studies employing the Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and its associated graphic output, Geometrical Analysis for Interactive Aid (GAIA).

Ovine bone and marrow derived progenitor cells : isolation, characterization, and osteogenic potential

Recently, research has focused on bone marrow derived multipotent mesenchymal precursor cells (MPC) for their potential clinical use in bone engineering. Prior to clinical application, MPC-based treatment concepts need to be evaluated in preclinical, immunocompetent, large animal models. Sheep in particular are considered a valid model for orthopaedic and trauma related research. However, ovine MPC and their osteogenic potential remain poorly characterized. In the present study, ex vivo expanded MPC isolated from ovine bone marrow proliferated at a higher rate than osteoblasts (OB) derived from tibial compact bone as assessed using standard 2D culture. MPC expressed the respective phenotypic profile typical for different mesenchymal cell populations (CD14-/CD31-/CD45- /CD29+/CD44+/CD166+) and showed a multilineage differentiation potential. When compared to OB, MPC had a higher mineralization potential under standard osteogenic culture conditions and expressed typical markers such as osteocalcin, osteonectin and type I collagen at the mRNA and protein level. After 4 weeks in 3D culture, MPC constructs demonstrated higher cell density and mineralization, whilst cell viability on the scaffolds was assessed >90%. Cells displayed a spindle-like morphology and formed an interconnected network. Implanted subcutaneously into NOD/SCID mice on type I collagen coated polycaprolactone-tricalciumphosphate (mPCL-TCP) scaffolds, MPC presented a higher developmental potential than osteoblasts. In summary, this study provides a detailed in vitro characterisation of ovine MPC from a bone engineering perspective and suggests that MPC provide promising means for future bone disease related treatment applications.

Mesenchymal stem cells

Cell based therapies as they apply to tissue engineering and regenerative medicine, require cells capable of self renewal and differentiation, and a prerequisite is to be able to prepare an effective dose of ex vivo expanded cells for autologous transplants. The in vivo identification of a source of physiologically relevant cell types suitable for cell therapies therefore figures as an integral part of tissue engineering. Stem cells serve as a reserve for biological repair, having the potential to differentiate into a number of specialised cell types within the body; they therefore represent the most useful candidates for cell based therapies. The primary goal of stem cell research is to produce cells that are both patient specific, as well as having properties suitable for the specific conditions for which they are intended to remedy. From a purely scientific perspective, stem cells allow scientists to gain a deeper understanding of developmental biology and regenerative therapies. Stem cells have acquired a number of uses for applications in regenerative medicine, immunotherapy, gene therapy, but it is in the area of tissue engineering that they generate most excitement, primarily as a result of their capacity for self-renewal and pluripotency. A unique feature of stem cells is their ability to maintain an uncommitted quiescent state in vivo and then, once triggered by conditions such as disease, injury or natural wear or tear, serve as a reservoir and natural support system to replenish lost cells. Although these cells retain the plasticity to differentiate into various tissues, being able to control this differentiation process is still one of the biggest challenges facing stem cell research. In an effort to harness the potential of these cells a number of studies have been conducted using both embryonic/foetal and adult stem cells. The use of embryonic stem cells (ESC) have been hampered by strong ethical and political concerns, this despite their perceived versatility due to their pluripotency. Ethical issues aside, other concerns raised with ESCs relates to the possibility of tumorigenesis, immune rejection and complications with immunosuppressive therapies, all of which adds layers of complications to the application ESC in research and which has led to the search for alternative sources for stem cells. The adult tissues in higher organisms harbours cells, termed adult stem cells, and these cells are reminiscent of unprogrammed stem cells. A number of sources of adult stem cells have been described. Bone marrow is by far the most accessible source of two potent populations of adult stem cells, namely haematopoietic stem cells (HSCs) and bone marrow mesenchymal stem cells (BMSCs). Autologously harvested adult stem cells can, in contrast to embryonic stem cells, readily be used in autografts, since immune rejection is not an issue; and their use in scientific research has not attracted the ethical concerns which have been the case with embryonic stem cells. The major limitation to their use, however, is the fact that adult stem cells are exceedingly rare in most tissues. This fact makes identifying and isolating these cells problematic; bone marrow being perhaps the only notable exception. Unlike the case of HSCs, there are as yet no rigorous criteria for characterizing MSCs. Changing acuity about the pluripotency of MSCs in recent studies has expanded their potential application; however, the underlying molecular pathways which impart the features distinctive to MSCs remain elusive. Furthermore, the sparse in vivo distribution of these cells imposes a clear limitation to their study in vitro. Also, when MSCs are cultured in vitro, there is a loss of the in vivo microenvironment, resulting in a progressive decline in proliferation potential and multipotentiality. This is further exacerbated with increased passage numbers in culture, characterized by the onset of senescence related changes. As a consequence, it is necessary to establish protocols for generating large numbers of MSCs but without affecting their differentiation potential. MSCs are capable of differentiating into mesenchymal tissue lineages, including bone, cartilage, fat, tendon, muscle, and marrow stroma. Recent findings indicate that adult bone marrow may also contain cells that can differentiate into the mature, nonhematopoietic cells of a number of tissues, including cells of the liver, kidney, lung, skin, gastrointestinal tract, and myocytes of heart and skeletal muscle. MSCs can readily be expanded in vitro and can be genetically modified by viral vectors and be induced to differentiate into specific cell lineages by changing the microenvironment–properties which makes these cells ideal vehicles for cellular gene therapy. MSCs can also exert profound immunosuppressive effects via modulation of both cellular and innate immune pathways, and this property allows them to overcome the issue of immune rejection. Despite the many attractive features associated with MSCs, there are still many hurdles to overcome before these cells are readily available for use in clinical applications. The main concern relates to in vivo characterization and identification of MSCs. The lack of a universal biomarker, sparse in vivo distribution, and a steady age related decline in their numbers, makes it an obvious need to decipher the reprogramming pathways and critical molecular players which govern the characteristics unique to MSCs. This book presents a comprehensive insight into the biology of adult stem cells and their utility in current regeneration therapies. The adult stem cell populations reviewed in this book include bone marrow derived MSCs, adipose derived stem cells (ASCs), umbilical cord blood stem cells, and placental stem cells. The features such as MSC circulation and trafficking, neuroprotective properties, and the nurturing roles and differentiation potential of multiple lineages have been discussed in details. In terms of therapeutic applications, the strengths of MSCs have been presented and their roles in disease treatments such as osteoarthritis, Huntington’s disease, periodontal regeneration, and pancreatic islet transplantation have been discussed. An analysis comparing osteoblast differentiation of umbilical cord blood stem cells and MSCs has been reviewed, as has a comparison of human placental stem cells and ASCs, in terms of isolation, identification and therapeutic applications of ASC in bone, cartilage regeneration, as well as myocardial regeneration. It is my sincere hope that this book will update the reader as to the research progress of MSC biology and potential use of these cells in clinical applications. It will be the best reward to all contributors of this book, if their efforts herein may in some way help the readers in any part of their study, research, and career development.

Sustaining the ecological, social and economic values of the forests of Southern Tasmania

This thesis articulates a methodology that can be applied to the analysis and design of underlying organisational structures and processes that will consistently and effectively address ‘wicked problems’ (the most difficult class of problems that we can conceptualise: problems which consist of ‘clusters’ of problems; problems within these clusters cannot be solved in isolation from one another, and include sociopolitical and moral-spiritual issues (Rittel and Webber 1973)) in forestry. This transdisciplinary methodology has been developed from the perspective of institutional economics synthesised with perspectives from ecological economics and system dynamics. The institutionalist policymaking framework provides an approach for the explicit development of holistic policy. An illustrative application of this framework has been applied to the wicked problem of forestry in southern Tasmania as an example of the applicability of the approach in the Australian context. To date all attempts to seek solutions to that prevailing wicked problem set have relied on non-reflexive, partial and highly reductionist thinking. A formal assessment of prevailing governance and process arrangements applying to that particular forestry industry has been undertaken using the social fabric matrix. This methodology lies at the heart of the institutionalist policymaking framework, and allows for the systematic exploration of elaborately complex causal links and relationships, such as are present in southern Tasmania. Some possible attributes of an alternative approach to forest management that sustains ecological, social and economic values of forests have been articulated as indicative of the alternative policy and management outcomes that real-world application of this transdisciplinary, discursive and reflexive framework may crystallise. Substantive and lasting solutions to wicked problems need to be formed endogenously, that is, from within the system. The institutionalist policymaking framework is a vehicle through which this endogenous creation of solutions to wicked problems may be realised.

Cell density alters matrix accumulation in two distinct fractions and the mechanical integrity of alginate-chondrocyte constructs

Chondrocyte density in articular cartilage is known to change with the development and growth of the tissue and may play an important role in the formation of a functional extracellular matrix (ECM). The objective of this study was to determine how initial chondrocyte density in an alginate hydrogel affects the matrix composition, its distribution between the cell-associated (CM) and further removed matrix (FRM) fractions, and the tensile mechanical properties of the developing engineered cartilage. Alginate constructs containing primary bovine chondrocytes at densities of 0, 4, 16, and 64 million cells/ml were fabricated and cultured for 1 or 2 weeks, at which time structural, biochemical, and mechanical properties were analyzed. Both matrix content and distribution varied with the initial cell density. Increasing cell density resulted in an increasing content of collagen and sulfated-glycosaminoglycan (GAG) and an increasing proportion of these molecules localized in the CM. While the equilibrium tensile modulus of cell-free alginate did not change with time in culture, the constructs with highest cell density were 116% stiffer than cell-free controls after 2 weeks of culture. The equilibrium tensile modulus was positively correlated with total collagen (r2 = 0.47, p < 0.001) and GAG content (r2 = 0.68, p < 0.001), and these relationships were enhanced when analyzing only those matrix molecules in the CM fraction (r2 = 0.60 and 0.72 for collagen and GAG, respectively, each p < 0.001). Overall, the results of this study indicate that initial cell density has a considerable effect on the developing composition, structure, and function of alginate–chondrocyte constructs.

Modulation of depth-dependent properties in tissue-engineered cartilage with a semi-permeable membrane and perfusion : a continuum model of matrix metabolism and transport

The functional properties of cartilaginous tissues are determined predominantly by the content, distribution, and organization of proteoglycan and collagen in the extracellular matrix. Extracellular matrix accumulates in tissue-engineered cartilage constructs by metabolism and transport of matrix molecules, processes that are modulated by physical and chemical factors. Constructs incubated under free-swelling conditions with freely permeable or highly permeable membranes exhibit symmetric surface regions of soft tissue. The variation in tissue properties with depth from the surfaces suggests the hypothesis that the transport processes mediated by the boundary conditions govern the distribution of proteoglycan in such constructs. A continuum model (DiMicco and Sah in Transport Porus Med 50:57-73, 2003) was extended to test the effects of membrane permeability and perfusion on proteoglycan accumulation in tissue-engineered cartilage. The concentrations of soluble, bound, and degraded proteoglycan were analyzed as functions of time, space, and non-dimensional parameters for several experimental configurations. The results of the model suggest that the boundary condition at the membrane surface and the rate of perfusion, described by non-dimensional parameters, are important determinants of the pattern of proteoglycan accumulation. With perfusion, the proteoglycan profile is skewed, and decreases or increases in magnitude depending on the level of flow-based stimulation. Utilization of a semi-permeable membrane with or without unidirectional flow may lead to tissues with depth-increasing proteoglycan content, resembling native articular cartilage.

An evaluation of alternative media for pebble matrix filtration using clay balls and recycled crushed glass

Protecting slow sand filters (SSFs) from high-turbidity waters by pretreatment using pebble matrix filtration (PMF) has previously been studied in the laboratory at University College London, followed by pilot field trials in Papua New Guinea and Serbia. The first full-scale PMF plant was completed at a water-treatment plant in Sri Lanka in 2008, and during its construction, problems were encountered in sourcing the required size of pebbles and sand as filter media. Because sourcing of uniform-sized pebbles may be problematic in many countries, the performance of alternative media has been investigated for the sustainability of the PMF system. Hand-formed clay balls made at a 100-yearold brick factory in the United Kingdom appear to have satisfied the role of pebbles, and a laboratory filter column was operated by using these clay balls together with recycled crushed glass as an alternative to sand media in the PMF. Results showed that in countries where uniform-sized pebbles are difficult to obtain, clay balls are an effective and feasible alternative to natural pebbles. Also, recycled crushed glass performed as well as or better than silica sand as an alternative fine media in the clarification process, although cleaning by drainage was more effective with sand media. In the tested filtration velocity range of ð0:72–1:33Þ m=h and inlet turbidity range of (78–589) NTU, both sand and glass produced above 95% removal efficiencies. The head loss development during clogging was about 30% higher in sand than in glass media.

Learning the kernel matrix with semidefinite programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.

Matrix regularization techniques for online multitask learning

In this paper we examine the problem of prediction with expert advice in a setup where the learner is presented with a sequence of examples coming from different tasks. In order for the learner to be able to benefit from performing multiple tasks simultaneously, we make assumptions of task relatedness by constraining the comparator to use a lesser number of best experts than the number of tasks. We show how this corresponds naturally to learning under spectral or structural matrix constraints, and propose regularization techniques to enforce the constraints. The regularization techniques proposed here are interesting in their own right and multitask learning is just one application for the ideas. A theoretical analysis of one such regularizer is performed, and a regret bound that shows benefits of this setup is reported.

Learning the Kernel Matrix with Semi-Definite Programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

Extracellular matrix of the human cyclic corpus luteum

Extracellular matrix regulates many cellular processes likely to be important for development and regression of corpora lutea. Therefore, we identified the types and components of the extracellular matrix of the human corpus luteum at different stages of the menstrual cycle. Two different types of extracellular matrix were identified by electron microscopy; subendothelial basal laminas and an interstitial matrix located as aggregates at irregular intervals between the non-vascular cells. No basal laminas were associated with luteal cells. At all stages, collagen type IV α1 and laminins α5, β2 and γ1 were localized by immunohistochemistry to subendothelial basal laminas, and collagen type IV α1 and laminins α2, α5, β1 and β2 localized in the interstitial matrix. Laminin α4 and β1 chains occurred in the subendothelial basal lamina from mid-luteal stage to regression; at earlier stages, a punctate pattern of staining was observed. Therefore, human luteal subendothelial basal laminas potentially contain laminin 11 during early luteal development and, additionally, laminins 8, 9 and 10 at the mid-luteal phase. Laminin α1 and α3 chains were not detected in corpora lutea. Versican localized to the connective tissue extremities of the corpus luteum. Thus, during the formation of the human corpus luteum, remodelling of extracellular matrix does not result in basal laminas as present in the adrenal cortex or ovarian follicle. Instead, novel aggregates of interstitial matrix of collagen and laminin are deposited within the luteal parenchyma, and it remains to be seen whether this matrix is important for maintaining the luteal cell phenotype.