Biomaterials based on noncovalent interactions of small molecules

Unlike conventional materials that covalent bonds connecting atoms as the major force to hold the materials together, supramolecular biomaterials rely on noncovalent intermolecular interactions to assemble. The reversibility and biocompatibility of supramolecular biomaterials render them with diverse range of functions and lead to rapid development in the past two decades. This review focuses on the noncovalent and enzymatic control of supramolecular biomaterials, with the introduction to various triggering mechanism to initiate self-assembly. Representative applications of supramolecular biomaterials are highlighted in four categories: tissue engineering, cancer therapy, drug delivery, and molecular imaging. By introducing various applications, we intend to show enzymatic control and noncovalent interactions as a powerful tool for achieving spatiotemporal control of biomaterials both in vitro and in vivo for biomedicine

Investor Behaviour: An Examination of Investor Sentiment and Cognitive Dissonance

This thesis seeks to examine the roles of investor sentiment and cognitive dissonance on investor behaviour. The objectives of this thesis are: first, to investigate the impact of the interaction of investor sentiment with culture on momentum and post-earnings-announcement-drift by way of cognitive dissonance in international markets; second, using investor sentiment and analyst recommendations to examine how cognitive dissonance affects institutional herding in the U.S. financial market. The effect of investor sentiment, culture as well as cognitive dissonance is examined for the two anomalies, momentum and post-earnings-announcement-drift. The investigation is carried out both across a wide range of countries and in two distinct culture groups. We investigate these issues by building on a specific behavioural model and by bringing together arguments from psychology and the cross-culture literature in relation to investor sentiment, culture and the notion of cognitive dissonance. We propose that cognitive dissonance will be evident when private or public news contradicts investors’ sentiment. This will cause a slow diffusion of such news being incorporated into stock prices, resulting in return continuation and people in different cultures experiencing different degrees of cognitive dissonance and in different situations. The empirical findings suggest that cognitive dissonance is a key driver in explaining these two anomalies across countries and in the two distinct cultures. The interaction of investor sentiment and analyst recommendations on institutional herding is investigated by using two commonly used herding measures in the micro-level in the U.S. It suggests that cognitive dissonance is an important driver for institutional herding by taking account of the interaction between the two factors. Cognitive dissonance will be evident when analyst recommendation revisions conflict with sentiment, causing institutions to herd differently in the current and subsequent periods. The two herding measures allow us to capture different aspects of herding in the two periods and to gain better insights into spurious and intentional herding

Non-target-site resistance to ALS inhibitors in waterhemp

The acetolactate synthase (ALS) enzyme, or acetohydroxyacid synthase (AHAS) enzyme, is an essential enzyme in branched-chain amino acid biosynthesis, and is the target site of five families of herbicides referred to as ALS inhibitors. Waterhemp (Amaranthus tuberculatus) is considered one of the most problematic weeds in the Midwest cropping region. The evolution of herbicide resistance and multiple resistance mechanisms within the species is one of the major properties making it difficult to control, and ALS-resistant waterhemp populations have been found and studied considerably. A waterhemp population (designated MCR) from Illinois with resistance to HPPD and atrazine was found to segregate for both high and moderate levels of resistance to ALS inhibitors. Plants in this population with high-level resistance had the Trp574Leu ALS mutation, which is present in other waterhemp populations resistant to ALS inhibitors. Plants from the MCR population that showed only moderate levels of resistance to ALS inhibitors did not have this mutation. Thus, research was conducted to investigate the resistance mechanism in the waterhemp plants with moderate resistance to ALS-inhibitors. Plants with moderate resistance were crossed and the resulting progeny where characterized. Firstly the ALS gene of the progeny was sequenced and in vitro ALS enzyme assays were conducted, and results indicated that the plants lacked a target-site mutation. Secondly, a series of greenhouse dose-response experiments were conducted to evaluate the resistance level across different chemical families of ALS-inhibitors. Thirdly, malathion, a cytochrome P450-inhibiting pesticide, was incorporated with ALS-inhibitor application to unveil the possible mechanism of resistance. Based on the results obtained, it was concluded that both target-site-mutation-based and metabolism-based ALS resistance mediated by cytochrome P450s exist in the original MCR population

Evaluations of soybean genotypes for drought tolerance and charcoal rot resistance

Soybean is the fourth most cultivated crop worldwide and provides one of the most important sources of oil and protein. Drought stress is one of the major constraints to soybean yield in the United States. Charcoal rot of soybean, caused by Macrophomina phaseolina, is a soil-borne fungal pathogen that infects over 500 plant species worldwide and also has been known to negatively impact soybean yields. Environmental conditions, such as severe drought, have been associated with increased charcoal rot severity. Both drought tolerance and charcoal rot resistance are complex traits, and their interaction is not well understood. In Chapter 2, a collection of 41 SoyNAM parents were evaluated for their response to drought tolerance. Greenhouse gravimetric tests were conducted on the 41 SoyNAM parents and on a selection of the 41 SoyNAM parents representing the most and least drought tolerant genotypes. Another experiment tested the 41 SoyNAM parents in a growth chamber based on sudden water depletion drought stress assessed by image-based ratings. Soybean genotypes for both the greenhouse and growth chamber tests were significant (P < 0.01), and there was a positive correlation (r = 0.37, P = 0.02) between the tests. Soybean genotypes U03-100612, LG94-1906 and Skylla, demonstrated drought tolerance in both tests, and PI 404188A was drought sensitive in both tests. In Chapter 3, charcoal rot resistance of SoyNAM parents were evaluated by a cut-stem inoculation method in controlled conditions in a growth chamber. Soybean genotypes were significant (P < 0.001) for the percentage of dead plants. The parents were then tested with cutstem inoculation incorporated with and without a drought treatment. The drought treatment increased (P < 0.05) disease severity of charcoal rot for all variables measured, which indicted that drought enhances charcoal rot severity. Genotype had significant (P < 0.05) effect on disease severity in all but one variable. The evaluation at 15 days after inoculation of the two tests were positively correlated (r = 0.36, P = 0.02). Soybean genotypes Skylla had the low disease ratings among the SoyNAM parents in both tests. In Chapter 4, a genome-wide association mapping study was conducted by phenotyping a diverse soybean collection of 350 genotypes for their response to M. phaseolina inoculation. Data from the cut-stem inoculation method were associated with the SoySNP50K marker dataset to detect and map significant (P < 0.001) SNPs. Eight SNPs were associated with charcoal rot resistance located on chromosomes 3, 11, 13, 14, 18 and 20. The functions of the candidate genes located near these SNPs involve plant defense, metabolite transportation and protein synthesis

Illumination Variation Correction Using Image Synthesis For Unsupervised Domain Adaptive Person Re-Identification

Unsupervised domain adaptive (UDA) person re-identification (re-ID) aims to learn identity information from labeled images in source domains and apply it to unlabeled images in a target domain. One major issue with many unsupervised re-identification methods is that they do not perform well relative to large domain variations such as illumination, viewpoint, and occlusions. In this paper, we propose a Synthesis Model Bank (SMB) to deal with illumination variation in unsupervised person re-ID. The proposed SMB consists of several convolutional neural networks (CNN) for feature extraction and Mahalanobis matrices for distance metrics. They are trained using synthetic data with different illumination conditions such that their synergistic effect makes the SMB robust against illumination variation. To better quantify the illumination intensity and improve the quality of synthetic images, we introduce a new 3D virtual-human dataset for GAN-based image synthesis. From our experiments, the proposed SMB outperforms other synthesis methods on several re-ID benchmarks.Comment: 10 pages, 5 figures, 5 table