23 resultados para Model of curriculum development


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Mood stabilising drugs such as lithium (LiCl) and valproic acid (VPA) are the first line agents for treating conditions such as Bipolar disorder and Epilepsy. However, these drugs have potential developmental effects that are not fully understood. This study explores the use of a simple human neurosphere-based in vitro model to characterise the pharmacological and toxicological effects of LiCl and VPA using gene expression changes linked to phenotypic alterations in cells. Treatment with VPA and LiCl resulted in the differential expression of 331 and 164 genes respectively. In the subset of VPA targeted genes, 114 were downregulated whilst 217 genes were upregulated. In the subset of LiCl targeted genes, 73 were downregulated and 91 were upregulated. Gene ontology (GO) term enrichment analysis was used to highlight the most relevant GO terms associated with a given gene list following toxin exposure. In addition, in order to phenotypically anchor the gene expression data, changes in the heterogeneity of cell subtype populations and cell cycle phase were monitored using flow cytometry. Whilst LiCl exposure did not significantly alter the proportion of cells expressing markers for stem cells/undifferentiated cells (Oct4, SSEA4), neurons (Neurofilament M), astrocytes (GFAP) or cell cycle phase, the drug caused a 1.4-fold increase in total cell number. In contrast, exposure to VPA resulted in significant upregulation of Oct4, SSEA, Neurofilament M and GFAP with significant decreases in both G2/M phase cells and cell number. This neurosphere model might provide the basis of a human-based cellular approach for the regulatory exploration of developmental impact of potential toxic chemicals.

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The technique of growing human leukaemic cells in diffusion chambers was developed to enable chemicals to be assessed for their ability to induce terminal differentiation. HL-60 promyelocytic leukaemia cell growth, in a lucite chamber with a Millipore filter, was optimised by use of a lateral incision site. Chambers were constructed using 0.45um filters and contained 150ul of serum-free HL-60 cells at a density of 1x106 cells/ml. The chambers were implanted into CBA/Ca mice and spontaneous terminal differentiation of the cells to granulocytes was prevented by the use of serum-free medium. Under these conditions there was an initial growth lag of 72 hours and a logarithmic phase of growth for 96 hours; the cell number reached a plateau after 168 hours of culture in vivo. The amount of drug in the plasma of the animal and in chambers that had been implanted for 5 days, was determined after a single ip injection of equitoxic doses of N-methylformamide, N-ethylformamide, tetramethylurea, N-dibutylformamide, N-tetramethylbutylformamide and hexamethylenebisacetamide. Concentrations of both TMU and HMBA were obtained in the plasma and in the chamber which were pharmacologically effective for the induction of differentiation of HL-60 cells in vitro, that is 12mM TMU and 5mM HMBA. A 4 day regime of treatment of animals implanted with chambers demonstrated that TMU and HMBA induced terminal differentiation of 50% and 35%, respectively, of the implanted HL-60 cells to granulocyte-like cells, assessed by measurement of functional and biochemical markers of maturity. None of the other agents attained concentrations in the plasma that were pharmacologically effective for the induction of differentiation of the cells in vitro and were unable to induce the terminal differentiation of the cells in vivo.

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The soil-plant-moisture subsystem is an important component of the hydrological cycle. Over the last 20 or so years a number of computer models of varying complexity have represented this subsystem with differing degrees of success. The aim of this present work has been to improve and extend an existing model. The new model is less site specific thus allowing for the simulation of a wide range of soil types and profiles. Several processes, not included in the original model, are simulated by the inclusion of new algorithms, including: macropore flow; hysteresis and plant growth. Changes have also been made to the infiltration, water uptake and water flow algorithms. Using field data from various sources, regression equations have been derived which relate parameters in the suction-conductivity-moisture content relationships to easily measured soil properties such as particle-size distribution data. Independent tests have been performed on laboratory data produced by Hedges (1989). The parameters found by regression for the suction relationships were then used in equations describing the infiltration and macropore processes. An extensive literature review produced a new model for calculating plant growth from actual transpiration, which was itself partly determined by the root densities and leaf area indices derived by the plant growth model. The new infiltration model uses intensity/duration curves to disaggregate daily rainfall inputs into hourly amounts. The final model has been calibrated and tested against field data, and its performance compared to that of the original model. Simulations have also been carried out to investigate the effects of various parameters on infiltration, macropore flow, actual transpiration and plant growth. Qualitatively comparisons have been made between these results and data given in the literature.

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Cystic fibrosis (CF) is the most common lethal inherited disease among Caucasians and arises due to mutations in a chloride channel, called cystic fibrosis transmembrane conductance regulator. A hallmark of this disease is the chronic bacterial infection of the airways, which is usually, associated with pathogens such as Pseudomonas aeruginosa, S. aureus and recently becoming more prominent, B. cepacia. The excessive inflammatory response, which leads to irreversible lung damage, will in the long term lead to mortality of the patient at around the age of 40 years. Understanding the pathogenesis of CF currently relies on animal models, such as those employing genetically-modified mice, and on single cell culture models, which are grown either as polarised or non-polarised epithelium in vitro. Whilst these approaches partially enable the study of disease progression in CF, both types of models have inherent limitations. The overall aim of this thesis was to establish a multicellular co-culture model of normal and CF human airways in vitro, which helps to partially overcome these limitations and permits analysis of cell-to-cell communication in the airways. These models could then be used to examine the co-ordinated response of the airways to infection with relevant pathogens in order to validate this approach over animals/single cell models. Therefore epithelial cell lines of non-CF and CF background were employed in a co-culture model together with human pulmonary fibroblasts. Co-cultures were grown on collagen-coated permeable supports at air-liquid interface to promote epithelial cell differentiation. The models were characterised and essential features for investigating CF infections and inflammatory responses were investigated and analysed. A pseudostratified like epithelial cell layer was established at air liquid interface (ALI) of mono-and co-cultures and cell layer integrity was verified by tight junction (TJ) staining and transepithelial resistance measurements (TER). Mono- and co-cultures were also found to secrete the airway mucin MUC5AC. Influence of bacterial infections was found to be most challenging when intact S. aureus, B. cepacia and P. aeruginosa were used. CF mono- and co-cultures were found to mimic the hyperinflammatory state found in CF, which was confirmed by analysing IL-8 secretions of these models. These co-culture models will help to elucidate the role fibroblasts play in the inflammatory response to bacteria and will provide a useful testing platform to further investigate the dysregulated airway responses seen in CF.

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The airway epithelium is the first point of contact in the lung for inhaled material, including infectious pathogens and particulate matter, and protects against toxicity from these substances by trapping and clearance via the mucociliary escalator, presence of a protective barrier with tight junctions and initiation of a local inflammatory response. The inflammatory response involves recruitment of phagocytic cells to neutralise and remove and invading materials and is oftern modelled using rodents. However, development of valid in vitro airway epithelial models is of great importance due to the restrictions on animal studies for cosmetic compound testing implicit in the 7th amendment to the European Union Cosmetics Directive. Further, rodent innate immune responses have fundamental differences to human. Pulmonary endothelial cells and leukocytes are also involved in the innate response initiated during pulmonary inflammation. Co-culture models of the airways, in particular where epithelial cells are cultured at air liquid interface with the presence of tight junctions and differentiated mucociliary cells, offer a solution to this problem. Ideally validated models will allow for detection of early biomarkers of response to exposure and investigation into inflammatory response during exposure. This thesis describes the approaches taken towards developing an in vitro epithelial/endothelial cell model of the human airways and identification biomarkers of response to exposure to xenobiotics. The model comprised normal human primary microvascular endothelial cells and the bronchial epithelial cell line BEAS-2B or normal human bronchial epithelial cells. BEAS-2B were chosen as their characterisation at air liquid interface is limited but they are robust in culture, thereby predicted to provide a more reliable test system. Proteomics analysis was undertaken on challenged cells to investigate biomarkers of exposure. BEAS-2B morphology was characterised at air liquid interface compared with normal human bronchial epithelial cells. The results indicate that BEAS-2B cells at an air liquid interface form tight junctions as shown by expression of the tight junction protein zonula occludens-1. To this author’s knowledge this is the first time this result has been reported. The inflammatory response of BEAS-2B (measured as secretion of the inflammatory mediators interleukin-8 and -6) air liquid interface mono-cultures to Escherichia coli lipopolysaccharide or particulate matter (fine and ultrafine titanium dioxide) was comparable to published data for epithelial cells. Cells were also exposed to polymers of “commercial interest” which were in the nanoparticle range (and referred to particles hereafter). BEAS-2B mono-cultures showed an increased secretion of inflammatory mediators after challenge. Inclusion of microvascular endothelial cells resulted in protection against LPS- and particle- induced epithelial toxicity, measured as cell viability and inflammatory response, indicating the importance of co-cultures for investigations into toxicity. Two-dimensional proteomic analysis of lysates from particle-challenged cells failed to identify biomarkers of toxicity due to assay interference and experimental variability. Separately, decreased plasma concentrations of serine protease inhibitors, and the negative acute phase proteins transthyretin, histidine-rich glycoprotein and alpha2-HS glycoprotein were identified as potential biomarkers of methyl methacrylate/ethyl methacrylate/butylacrylate treatment in rats.

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This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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Central nervous system (CNS) drug disposition is dictated by a drug’s physicochemical properties and its ability to permeate physiological barriers. The blood–brain barrier (BBB), blood-cerebrospinal fluid barrier and centrally located drug transporter proteins influence drug disposition within the central nervous system. Attainment of adequate brain-to-plasma and cerebrospinal fluid-to-plasma partitioning is important in determining the efficacy of centrally acting therapeutics. We have developed a physiologically-based pharmacokinetic model of the rat CNS which incorporates brain interstitial fluid (ISF), choroidal epithelial and total cerebrospinal fluid (CSF) compartments and accurately predicts CNS pharmacokinetics. The model yielded reasonable predictions of unbound brain-to-plasma partition ratio (Kpuu,brain) and CSF:plasma ratio (CSF:Plasmau) using a series of in vitro permeability and unbound fraction parameters. When using in vitro permeability data obtained from L-mdr1a cells to estimate rat in vivo permeability, the model successfully predicted, to within 4-fold, Kpuu,brain and CSF:Plasmau for 81.5% of compounds simulated. The model presented allows for simultaneous simulation and analysis of both brain biophase and CSF to accurately predict CNS pharmacokinetics from preclinical drug parameters routinely available during discovery and development pathways.

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The extant literature on workplace coaching is characterised by a lack of theoretical and empirical understanding regarding the effectiveness of coaching as a learning and development tool; the types of outcomes one can expect from coaching; the tools that can be used to measure coaching outcomes; the underlying processes that explain why and how coaching works and the factors that may impact on coaching effectiveness. This thesis sought to address these substantial gaps in the literature with three linked studies. Firstly, a meta-analysis of workplace coaching effectiveness (k = 17), synthesizing the existing research was presented. A framework of coaching outcomes was developed and utilised to code the studies. Analysis indicated that coaching had positive effects on all outcomes. Next, the framework of outcomes was utilised as the deductive start-point to the development of the scale measuring perceived coaching effectiveness. Utilising a multi-stage approach (n = 201), the analysis indicated that perceived coaching effectiveness may be organised into a six factor structure: career clarity; team performance; work well-being; performance; planning and organizing and personal effectiveness and adaptability. The final study was a longitudinal field experiment to test a theoretical model of individual differences and coaching effectiveness developed in this thesis. An organizational sample of 84 employees each participated in a coaching intervention, completed self-report surveys, and had their job performance rated by peers, direct reports and supervisors (a total of 352 employees provided data on participant performance). The results demonstrate that compared to a control group, the coaching intervention generated a number of positive outcomes. The analysis indicated that coachees’ enthusiasm, intellect and orderliness influenced the impact of coaching on outcomes. Mediation analysis suggested that mastery goal orientation, performance goal orientation and approach motivation in the form of behavioural activation system (BAS) drive, were significant mediators between personality and outcomes. Overall, the findings of this thesis make an original contribution to the understanding of the types of outcomes that can be expected from coaching, and the magnitude of impact coaching has on outcomes. The thesis also provides a tool for reliably measuring coaching effectiveness and a theoretical model to understand the influence of coachee individual differences on coaching outcomes.

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Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

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Prostate cancer (CaP) patients with disseminated disease often suffer from severe cachexia, which contributes to mortality in advanced cancer. Human cachexia-associated protein (HCAP) was recently identified from a breast cancer library based on the available 20-amino acid sequence of proteolysis-inducing factor (PIF), which is a highly active cachectic factor isolated from mouse colon adenocarcinoma MAC16. Herein, we investigated the expression of HCAP in CaP and its potential involvement in CaP-associated cachexia. HCAP mRNA was detected in CaP cell lines, in primary CaP tissues and in its osseous metastases. In situ hybridization showed HCAP mRNA to be localized only in the epithelial cells in CaP tissues, in the metastatic foci in bone, liver and lymph node, but not in the stromal cells or in normal prostate tissues. HCAP protein was detected in 9 of 14 CaP metastases but not in normal prostate tissues from cadaveric donors or patients with organ-confined tumors. Our Western blot analysis revealed that HCAP was present in 9 of 19 urine specimens from cachectic CaP patients but not in 19 urine samples of noncachectic patients. HCAP mRNA and protein were also detected in LuCaP 35 and PC-3M xenografts from our cachectic animal models. Our results demonstrated that human CaP cells express HCAP and the expression of HCAP is associated with the progression of CaP and the development of CaP cachexia. © 2003 Wiley-Liss, Inc.

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The research investigates the processes of adoption and implementation, by organisations, of computer aided production management systems (CAPM). It is organised around two different theoretical perspectives. The first part is informed by the Rogers model of the diffusion, adoption and implementation of innovations, and the second part by a social constructionist approach to technology. Rogers' work is critically evaluated and a model of adoption and implementation is distilled from it and applied to a set of empirical case studies. In the light of the case study data, strengths and weaknesses of the model are identified. It is argued that the model is too rational and linear to provide an adequate explanation of adoption processes. It is useful for understanding processes of implementation but requires further development. The model is not able to adequately encompass complex computer based technologies. However, the idea of 'reinvention' is identified as Roger's key concept but it needs to be conceptually extended. Both Roger's model and definition of CAPM found in the literature from production engineering tend to treat CAPM in objectivist terms. The problems with this view are addressed through a review of the literature on the sociology of technology, and it is argued that a social constructionist approach offers a more useful framework for understanding CAPM, its nature, adoption, implementation, and use. CAPM it is argued, must be understood on terms of the ways in which it is constituted in discourse, as part of a 'struggle for meaning' on the part of academics, professional engineers, suppliers, and users.

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This thesis, set within an Action Research framework, details the development and validation of a writer-centred model of the writing process. The model was synthesised within the boundaries of a writers’ group for MA students. The initial data collected, and analysed using the principles of grounded theory, were retrospective descriptions of group members’ writing processes. After initial analysis, additional data, from group members’ writing, and from audio recordings, were used for further analysis, and to form a model of the writing process. To ascertain whether the model had value outside the specific context in which it was made, it was validated from three different perspectives. Firstly, the retrospective descriptions of other writers were collected and analysed, using the model as a framework. Secondly, the model was presented at academic conferences; comments about the model, made by members of the audience, were collected and analysed. Finally, the model was used in writing courses for PhD students. Comments from these students, along with questionnaire responses, were collected and the content analysed. Upon examination of all data sources, the model was updated to reflect additional insights arising from the analysis. Analysis of the data also indicated that the model is useable outside its original context. Potential uses for the model are 1) raising awareness of the process of writing, 2) putting writers at ease, 3) serving as a starting point for individuals or groups to design their own models of the writing process, and 4) as a tool to help writers take control of their writing processes.