Effect of poly(acrylic acid) end-group functionality on inhibition of calcium oxalate crystal growth

A number of series of poly(acrylic acids) (PAA) of differing end-groups and molecular weights prepared using atom transfer radical polymerization were used as inhibitors for the crystallization of calcium oxalate at 23 and 80°C. As measured by turbidimetry and conductivity and as expected from previous reports, all PAA series were most effective for inhibition of crystallization at molecular weights of 1500–4000. However, the extent of inhibition was in general strongly dependent on the hydrophobicity and molecular weight of the end-group. These results may be explicable in terms of adsorption/desorption of PAA to growth sites on crystallites. The overall effectiveness of the series didn't follow a simple trend with end-group hydrophobicity, suggesting self-assembly behavior or a balance between adsorption and desorption rates to crystallite surfaces may be critical in the mechanism of inhibition of calcium oxalate crystallization.

Effect of poly(acrylic acid) molecular mass and end-group functionality on calcium oxalate crystal morphology and growth

A number of series of poly(acrylic acids) (PAA) of differing end-groups and molecular mass were used to study the inhibition of calcium oxalate crystallization. The effects of the end-group on crystal speciation and morphology were significant and dramatic, with hexyl-isobutyrate end groups giving preferential formation of calcium oxalate dihydrate (COD) rather than the more stable calcium oxalate monohydrate (COM), while both more hydrophobic end-groups and less-hydrophobic end groups led predominantly to formation of the least thermodynamically stable form of calcium oxalate, calcium oxalate trihydrate. Conversely, molecular mass had little impact on calcium oxalate speciation or crystal morphology. It is probable that the observed effects are related to the rate of desorption of the PAA moiety from the crystal (lite) surfaces and that the results point to a major role for end-group as well as molecular mass in controlling desorption rate.

Formation of thermodynamically unstable calcium oxalate dihydrate in sugar mill evaporators

Calcium oxalate (CaOX) is the most intractable scale component to remove in sugar mill evaporators by either mechanical or chemical means. The operating conditions of sugar mill evaporators should preferentially favour the formation of the thermodynamically stable calcium oxalate monohydrate (COM), yet analysis of scale deposit from different sugar factories have shown that calcium oxalate dihydrate (COD) is usually the predominant phase, and in some cases is the only hydrate formed. The effects of trans-aconitic, succinic and acetic acids, all of which are present in sugarcane juice, and ethylenediamine tetraacetic acid disodium salt (EDTA) on the growth of CaOX crystals have been examined by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray powder diffraction (XRD) and thermogravimetric analysis (TGA). trans-Aconitic acid, which constitutes two-thirds of the organic acid component in sugarcane juice, in the presence of sugar resulted in the formation of COD and COM in a 3:1 ratio. EDTA was the most effective acid to promote the formation of COD followed by trans-aconitic acid, then acetic acid and lastly succinic acid.

The effect of friction on indenter force and pile-up in numerical simulations of bone nanoindentation

Nanoindentation is a useful technique for probing the mechanical properties of bone, and finite element (FE) modeling of the indentation allows inverse determination of elasto-plastic constitutive properties. However, FE simulations to date have assumed frictionless contact between indenter and bone. The aim of this study was to explore the effect of friction in simulations of bone nanoindentation. Two dimensional axisymmetric FE simulations were performed using a spheroconical indenter of tip radius 0.6m and angle 90°. The coefficient of friction between indenter and bone was varied between 0.0 (frictionless) and 0.3. Isotropic linear elasticity was used in all simulations, with bone elastic modulus E=13.56GPa and Poisson’s ratio =0.3. Plasticity was incorporated using both Drucker-Prager and von Mises yield surfaces. Friction had a modest effect on the predicted force-indentation curve for both von Mises and Drucker-Prager plasticity, reducing maximum indenter displacement by 10% and 20% respectively as friction coefficient was increased from zero to 0.3 (at a maximum indenter force of 5mN). However, friction has a much greater effect on predicted pile-up after indentation, reducing predicted pile-up from 0.27m to 0.11m with a von Mises model, and from 0.09m to 0.02m with Drucker-Prager plasticity. We conclude that it is important to include friction in nanoindentation simulations of bone.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Molecular markers of obesity and diabetes

Recently it has been shown that the consumption of a diet high in saturated fat is associated with impaired insulin sensitivity and increased incidence of type 2 diabetes. In contrast, diets that are high in monounsaturated fatty acids (MUFAs) or polyunsaturated fatty acids (PUFAs), especially very long chain n-3 fatty acids (FAs), are protective against disease. However, the molecular mechanisms by which saturated FAs induce the insulin resistance and hyperglycaemia associated with metabolic syndrome and type 2 diabetes are not clearly defined. It is possible that saturated FAs may act through alternative mechanisms compared to MUFA and PUFA to regulate of hepatic gene expression and metabolism. It is proposed that, like MUFA and PUFA, saturated FAs regulate the transcription of target genes. To test this hypothesis, hepatic gene expression analysis was undertaken in a human hepatoma cell line, Huh-7, after exposure to the saturated FA, palmitate. These experiments showed that palmitate is an effective regulator of gene expression for a wide variety of genes. A total of 162 genes were differentially expressed in response to palmitate. These changes not only affected the expression of genes related to nutrient transport and metabolism, they also extend to other cellular functions including, cytoskeletal architecture, cell growth, protein synthesis and oxidative stress response. In addition, this thesis has shown that palmitate exposure altered the expression patterns of several genes that have previously been identified in the literature as markers of risk of disease development, including CVD, hypertension, obesity and type 2 diabetes. The altered gene expression patterns associated with an increased risk of disease include apolipoprotein-B100 (apo-B100), apo-CIII, plasminogen activator inhibitor 1, insulin-like growth factor-I and insulin-like growth factor binding protein 3. This thesis reports the first observation that palmitate directly signals in cultured human hepatocytes to regulate expression of genes involved in energy metabolism as well as other important genes. Prolonged exposure to long-chain saturated FAs reduces glucose phosphorylation and glycogen synthesis in the liver. Decreased glucose metabolism leads to elevated rates of lipolysis, resulting in increased release of free FAs. Free FAs have a negative effect on insulin action on the liver, which in turn results in increased gluconeogenesis and systemic dyslipidaemia. It has been postulated that disruption of glucose transport and insulin secretion by prolonged excessive FA availability might be a non-genetic factor that has contributed to the staggering rise in prevalence of type 2 diabetes. As glucokinase (GK) is a key regulatory enzyme of hepatic glucose metabolism, changes in its activity may alter flux through the glycolytic and de novo lipogenic pathways and result in hyperglycaemia and ultimately insulin resistance. This thesis investigated the effects of saturated FA on the promoter activity of the glycolytic enzyme, GK, and various transcription factors that may influence the regulation of GK gene expression. These experiments have shown that the saturated FA, palmitate, is capable of decreasing GK promoter activity. In addition, quantitative real-time PCR has shown that palmitate incubation may also regulate GK gene expression through a known FA sensitive transcription factor, sterol regulatory element binding protein-1c (SREBP-1c), which upregulates GK transcription. To parallel the investigations into the mechanisms of FA molecular signalling, further studies of the effect of FAs on metabolic pathway flux were performed. Although certain FAs reduce SREBP-1c transcription in vitro, it is unclear whether this will result in decreased GK activity in vivo where positive effectors of SREBP-1c such as insulin are also present. Under these conditions, it is uncertain if the inhibitory effects of FAs would be overcome by insulin. The effects of a combination of FAs, insulin and glucose on glucose phosphorylation and metabolism in cultured primary rat hepatocytes at concentrations that mimic those in the portal circulation after a meal was examined. It was found that total GK activity was unaffected by an increased concentration of insulin, but palmitate and eicosapentaenoic acid significantly lowered total GK activity in the presence of insulin. Despite the fact that total GK enzyme activity was reduced in response to FA incubation, GK enzyme translocation from the inactive, nuclear bound, to active, cytoplasmic state was unaffected. Interestingly, none of the FAs tested inhibited glucose phosphorylation or the rate of glycolysis when insulin is present. These results suggest that in the presence of insulin the levels of the active, unbound cytoplasmic GK are sufficient to buffer a slight decrease in GK enzyme activity and decreased promoter activity caused by FA exposure. Although a high fat diet has been associated with impaired hepatic glucose metabolism, there is no evidence from this thesis that FAs themselves directly modulate flux through the glycolytic pathway in isolated primary hepatocytes when insulin is also present. Therefore, although FA affected expression of a wide range of genes, including GK, this did not affect glycolytic flux in the presence of insulin. However, it may be possible that a saturated FA-induced decrease in GK enzyme activity when combined with the onset of insulin resistance may promote the dys-regulation of glucose homeostasis and the subsequent development of hyperglycaemia, metabolic syndrome and type 2 diabetes.

Applied batch cryptography

The material presented in this thesis may be viewed as comprising two key parts, the first part concerns batch cryptography specifically, whilst the second deals with how this form of cryptography may be applied to security related applications such as electronic cash for improving efficiency of the protocols. The objective of batch cryptography is to devise more efficient primitive cryptographic protocols. In general, these primitives make use of some property such as homomorphism to perform a computationally expensive operation on a collective input set. The idea is to amortise an expensive operation, such as modular exponentiation, over the input. Most of the research work in this field has concentrated on its employment as a batch verifier of digital signatures. It is shown that several new attacks may be launched against these published schemes as some weaknesses are exposed. Another common use of batch cryptography is the simultaneous generation of digital signatures. There is significantly less previous work on this area, and the present schemes have some limited use in practical applications. Several new batch signatures schemes are introduced that improve upon the existing techniques and some practical uses are illustrated. Electronic cash is a technology that demands complex protocols in order to furnish several security properties. These typically include anonymity, traceability of a double spender, and off-line payment features. Presently, the most efficient schemes make use of coin divisibility to withdraw one large financial amount that may be progressively spent with one or more merchants. Several new cash schemes are introduced here that make use of batch cryptography for improving the withdrawal, payment, and deposit of electronic coins. The devised schemes apply both to the batch signature and verification techniques introduced, demonstrating improved performance over the contemporary divisible based structures. The solutions also provide an alternative paradigm for the construction of electronic cash systems. Whilst electronic cash is used as the vehicle for demonstrating the relevance of batch cryptography to security related applications, the applicability of the techniques introduced extends well beyond this.

Repair of calvarial defects with customized tissue-engineered bone grafts - I. Evaluation of osteogenesis in a three-dimensional culture system

Bone generation by autogenous cell transplantation in combination with a biodegradable scaffold is one of the most promising techniques being developed in craniofacial surgery. The objective of this combined in vitro and in vivo study was to evaluate the morphology and osteogenic differentiation of bone marrow derived mesenchymal progenitor cells and calvarial osteoblasts in a two-dimensional (2-D) and three-dimensional (3-D) culture environment (Part I of this study) and their potential in combination with a biodegradable scaffold to reconstruct critical-size calvarial defects in an autologous animal model [Part II of this study; see Schantz, J.T., et al. Tissue Eng. 2003;9(Suppl. 1):S-127-S-139; this issue]. New Zealand White rabbits were used to isolate osteoblasts from calvarial bone chips and bone marrow stromal cells from iliac crest bone marrow aspirates. Multilineage differentiation potential was evaluated in a 2-D culture setting. After amplification, the cells were seeded within a fibrin matrix into a 3-D polycaprolactone (PCL) scaffold system. The constructs were cultured for up to 3 weeks in vitro and assayed for cell attachment and proliferation using phase-contrast light, confocal laser, and scanning electron microscopy and the MTS cell metabolic assay. Osteogenic differentiation was analyzed by determining the expression of alkaline phosphatase (ALP) and osteocalcin. The bone marrow-derived progenitor cells demonstrated the potential to be induced to the osteogenic, adipogenic, and chondrogenic pathways. In a 3-D environment, cell-seeded PCL scaffolds evaluated by confocal laser microscopy revealed continuous cell proliferation and homogeneous cell distribution within the PCL scaffolds. On osteogenic induction mesenchymal progenitor cells (12 U/L) produce significantly higher (p < 0.05) ALP activity than do osteoblasts (2 U/L); however, no significant differences were found in osteocalcin expression. In conclusion, this study showed that the combination of a mechanically stable synthetic framework (PCL scaffolds) and a biomimetic hydrogel (fibrin glue) provides a potential matrix for bone tissue-engineering applications. Comparison of osteogenic differentiation between the two mesenchymal cell sources revealed a similar pattern.