Explorations into the nature of insulin binding to oxidized dextran : this thesis was presented in partial fulfillment of the requirements for the degree of Master of Science in Chemistry at Massey University

The results reported in this thesis comprise an investigation into the conjugation of insulin to oxidized dextran, various release studies from the conjugates, and an attempt to interpret the binding nature of the conjugates. A model system involving the sustained release from insulin-dextran conjugates has been employed in this study. For insulin, up to 3 potential sites only (A1-Gly. B1-Phe and B29-Lys) were expected to bind to oxidized dextran. The rate of release and the maintenance of activity of the released protein are vital to such systems. Success in the interpretation of the binding nature of the conjugate will allow us to investigate its relationship to the rate of release. The desired rate of release for the sustained release of protein could then be achieved, once the projected binding could be obtained. Activation of dextran was achieved by periodate oxidation to give levels of 8%, 16% and 27% oxidized dextran. Insulin was chosen for its relatively 'uncomplicated' structure and few possible sites available for binding with activated dextran. Insulin was bound to the dextran through imine bonds. Complex formation was examined under a wide range of conditions. Initial studies were begun with the determination of a desirable basic molar ratio. A molar ratio of insulin to 8% activated dextran of 10 : 1 arose from this set of experiments. Insulin was bound to 27% activated dextran at pH 7.4, pH 9 and pH 10. In the cases of pH 9 and pH 10, many more lower MW complexes were formed than at pH 7.4. It seemed that the higher the pH of formation, the more crosslinks occurred between an insulin molecule and dextran molecules in the lower MW range. Approximate physiological pHs (pH 7.1-7.8) were used for complex formation in all subsequent experiments. Release studies were carried out under approximate physiological conditions (pH 7.4, 37°C). Immediate release was observed upon isolation by size exclusion chromatography. The greatest release occurred in the first 24 hours for all three activation levels. The higher the activation level of dextran, the lower the level of release. An equilibrium was established after several days' release and studies at 37°C produced the expected result: greater release relative to ambient. A number of studies were carried out with complex after sodium cyanoborohydride had been used to reduce the imine bonds. The first set of experiments on the reduced complexes was enzymatic cleavage studies, which employed trypsin and α-chvmotrypsin. The results for trypsin digestion of the reduced insulin-27% oxidized dextran complex indicated partial binding had occurred at B29-Lys, in combination with full binding at B1 and/or Al. Amino acid analysis results of the isolated complex after trypsin digestion indicated about 90% binding occurred at B29-Lys for the complex, which formed at pH 7.1. The results of α-chymotrypsin digestion study were shown questionable due to its incomplete cleavage. The reduced complexes were analyzed by amino acid analysis. The insulin-27% activated dextran complexes formed at pH 7.4, pH 9 and pH 10 showed similar extents of binding at B1-Phe, indicating B1 might be the prime binding site. There was more binding at B29 and A1 for the pH 9 than at pH 7.4 case. At pH 10 abnormal values arose. The studies for the complexes of insulin with 16% and 27% activated dextran indicated the more highly activated the dextran, the greater the binding at B29 and A1. Trials with the 2, 4-dinitrophenyl-derivativatization method proved to be a useful way to examine the degree of B1 and B29 binding from the amino acid analysis results of complex. The insulin-16% activated dextran complex formed at pH 7.1 was found to be about 100% binding at B1, 60% at A1 and 50% at B29. Oxidative and reductive cleavage studies of A and B chains of insulin and the complex were carried out to investigate the level of A1 binding. After chemical cleavage of the three disulfide bonds in insulin and subsequent chromatography, the amino acid analysis results for the treated complexes indicated a significant proportion of A chain had bound to dextran, i.e. at A1. An estimation of 60-70% of A1 binding was achieved for this study. This exploratory study has shown that varied complex formation conditions such as the level of activation of dextran, pH, and temperature could alter the extent of binding between insulin and dextran molecules. Amino acid analysis of the reduced complex was a useful method to interpret the binding

Land Development in Emerging Markets

One of the most important issues in emerging markets is the timing and intensity of land development decisions and how these decisions affect property values. In these markets, newly developed office space and residential units often account for a substantial proportion of the aggregate supply of similar types of developed properties. In this article I use a real option model to study the land development problem faced by a central planner. The optimal capital intensity, the value of land and the post-development rents and property values in these markets are strikingly lower than the corresponding values in the markets where the demand is perfectly elastic. Furthermore, the optimal capital intensity and the value of land are most sensitive to the market demand conditions in the emerging markets experiencing the fastest growth or greatest uncertainty, or at times when interest rates or construction costs are lowest.Land value, Capital intensity, Equilibrium, Emerging markets

The Predictability of REIT Returns and Market Segmentatio

Recent research suggests that real estate returns are more predictable than the returns of other assets and that the real estate market is segmented from the general stock market. This study examines these two issues empirically using a multifactor asset pricing model that allows for time-varying risk premiums. The results indicate that, in a general two-factor asset pricing framework, the REIT market is integrated with the general stock market. Furthermore, no evidence can be found that REIT returns are more predictable than the returns of other stocks.

Intertemporal Asset Pricing Without Consumption Data: Empirical Tests

In this paper I conduct tests of an intertemporal asset pricing model using variables that forecast stock returns as the risk factors. I document that the forecasting variables are priced so that expected excess returns are related to their conditional covariances with the forecasting variables. The variability in the covariance risk fails to explain the cross‐sectional and time‐series variation in expected stock returns. Evidence rejects restrictions on the prices of covariance risk imposed by the model with constant volatilities. I also find that an extended model that allows time‐varying conditional volatilities is misspecified.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108338/1/jfir00236.pd

Connecting Software Metrics across Versions to Predict Defects

Accurate software defect prediction could help software practitioners allocate test resources to defect-prone modules effectively and efficiently. In the last decades, much effort has been devoted to build accurate defect prediction models, including developing quality defect predictors and modeling techniques. However, current widely used defect predictors such as code metrics and process metrics could not well describe how software modules change over the project evolution, which we believe is important for defect prediction. In order to deal with this problem, in this paper, we propose to use the Historical Version Sequence of Metrics (HVSM) in continuous software versions as defect predictors. Furthermore, we leverage Recurrent Neural Network (RNN), a popular modeling technique, to take HVSM as the input to build software prediction models. The experimental results show that, in most cases, the proposed HVSM-based RNN model has a significantly better effort-aware ranking effectiveness than the commonly used baseline models

Deep Sketch Hashing: Fast Free-hand Sketch-Based Image Retrieval

Free-hand sketch-based image retrieval (SBIR) is a specific cross-view retrieval task, in which queries are abstract and ambiguous sketches while the retrieval database is formed with natural images. Work in this area mainly focuses on extracting representative and shared features for sketches and natural images. However, these can neither cope well with the geometric distortion between sketches and images nor be feasible for large-scale SBIR due to the heavy continuous-valued distance computation. In this paper, we speed up SBIR by introducing a novel binary coding method, named \textbf{Deep Sketch Hashing} (DSH), where a semi-heterogeneous deep architecture is proposed and incorporated into an end-to-end binary coding framework. Specifically, three convolutional neural networks are utilized to encode free-hand sketches, natural images and, especially, the auxiliary sketch-tokens which are adopted as bridges to mitigate the sketch-image geometric distortion. The learned DSH codes can effectively capture the cross-view similarities as well as the intrinsic semantic correlations between different categories. To the best of our knowledge, DSH is the first hashing work specifically designed for category-level SBIR with an end-to-end deep architecture. The proposed DSH is comprehensively evaluated on two large-scale datasets of TU-Berlin Extension and Sketchy, and the experiments consistently show DSH's superior SBIR accuracies over several state-of-the-art methods, while achieving significantly reduced retrieval time and memory footprint.Comment: This paper will appear as a spotlight paper in CVPR201

Functionalization of Carbon Nanotubes with Stimuli- Responsive Molecules and Polymers

“Smartly” functionalized carbon nanotubes (CNTs) constitute an actively pursued research topic in the fields of nanomaterials and nanotechnology. The development of highly efficient and selective methodologies for dispersing CNTs in the liquid phase has not only made efficient separation and purification of CNTs possible, but also opened the doors to many fascinating material and biological applications. Very recently, the development of CNT hybrid systems with controlled stimuli-responsiveness has achieved significant breakthroughs. This chapter outlines the state of the art within this vibrant research area, and examples from the most recent literature are selected to demonstrate progress in the preparation of CNT composites, the physical properties of which can be readily switched by various external stimuli (e.g., pH, photoirradiation, solvent, temperature, etc.)

A generalization of Dugas' construction on stable auto-equivalences for symmetric algebras

We give a unified generalization of Dugas' construction on stable auto-equivalences of Morita type from local symmetric algebras to arbitrary symmetric algebras. For group algebras $kP$ of $p$-groups in characteristic $p$, we recover all the stable auto-equivalences corresponding to endo-trivial modules over $kP$ except that $P$ is generalized quaternion of order $2^m$. Moreover, we give many examples of stable auto-equivalences of Morita type for non-local symmetric algebras