COPPER BINDING PROTEINS IN BREAST CANCER : CELLULAR AND MOLECULAR MECHANISMS

Cancer is one of the leading causes of human death. However, the mechanisms governing cancer are still not fully understood. Elevated levels of copper (Cu) have been observed in both cancerous tissues and the serum of cancer patients. Cu ions play a crucial role in supporting cancer by activating Cu-dependent enzymes, which promote cancer cell proliferation, angiogenesis, and metastasis. Cu ions can undergo redox reactions, switching between the +1 and +2 oxidation states. Free Cu ions can therefore catalyze the production of reactive oxygen species (ROS), which may damage biomolecules. To avoid such reactions, Cu ions are controlled and transported by dedicated Cu transport proteins in cells. This thesis focuses on two Cu-binding proteins, antioxidant 1 Cu chaperone (Atox1) and mediator of cell motility 1 (Memo1). Previous studies have shown that Atox1 is upregulated in breast cancer cells and patients. The results of Paper I indicate that Atox1 knockdown significantly reduces the velocity and directionality of breast cancer cell migration. Data in Paper I also show close proximity between Atox1 and the Cu-dependent enzyme lysyl oxidase (LOX) in cells. These results imply that Cu transport in the Atox1-ATP7A-LOX axis is crucial for cancer cell migration. I also investigated the role of an Atox1 homolog, CUC-1, in Caenorhabditis elegans (C. elegans) cell migration during development (Paper II). CUC-1 knock-out worms have more developmental defects, implying that Atox1-like proteins contribute to cell migration during development.Memo1, connected to many oncogenic signaling pathways, was recently suggested to bind oxidized Cu ions and promote ROS generation. In contrast, my work shows that Memo1 binds the reduced form of Cu and protects against Cu-induced ROS generation in vitro and in breast cancer cells (Paper III and IV). Memo1 knockdown and external Cu addition significantly decrease cell viability and increase ROS levels in breast cancer cells. This Memo1 functionality may serve as a protective mechanism, allowing cancer cells to handle the increased demand of Cu ions in cancer-related processes.In conclusion, my research provides important new discoveries for the Cu-binding proteins Atox1 and Memo1 that may be relevant for future cancer treatments

Impact of Biological Wastewater Treatment on the Reactivity of N-Nitrosodimethylamine (NDMA) Precursors

N-Nitrosamines are a group of probable human carcinogens associated with 10-6 lifetime cancer risks at low ng/L levels in drinking water. N-nitrosamines can form via the reactions between chloramines (i.e., monochloramine, dichloramine) and organic precursors (e.g., secondary, tertiary and quaternary amines). Municipal wastewater effluents are considered one of the major sources of N-nitrosamine precursors that can impact downstream drinking water qualities. Although many studies have investigated the formation of N-nitrosamines in the influents and effluents of wastewater treatment plants (WWTPs), the major sources of N-nitrosamine precursors are still largely unknown. The first objective of this research was to evaluate the occurrences of N-nitrosamine precursors in different sewage components (i.e., blackwaters and greywaters). Results showed that urine blackwater (i.e., raw human urine diluted in tap water 250 times) showed exceptionally high NDMA formation potential (FP, \u3e10000 ng/L). The FP of the other N-nitrosamines tested were more than one magnitude lower than NDMA FP. Urine blackwater was the predominant contributor to NDMA (i.e., \u3e90%) and N-nitrosopyrrolidine (NPYR) FP (i.e., 65%) in domestic sewage, while laundry greywater was the major source of most other N-nitrosamine FP (i.e., 55%-100%). In contrast, N-nitrosamine formation under the uniform formation condition (UFC) from all sewage components was generally \u3c100 ng/L, far lower than N-nitrosamine FP. Because of the huge discrepancies between N-nitrosamine UFC and FP, the potential effects of different factors (i.e., pH, dissolved organic carbon (DOC), specific ultraviolet absorbance at 254 nm (SUVA254), Br-) on NDMA UFC and FP were examined. Under different pH conditions (i.e., pH 6.0, 6.8, 7.8 and 8.8), all model NDMA precursors tested achieved peak NDMA UFC at pH 6.8-7.8 in DDW, regardless of compounds’ pKa values (i.e., 3.8-13.6). The peak NDMA FP tended to be achieved at a relatively higher pH than NDMA UFC. In surface waters with higher DOC or SUVA254, NDMA UFC tended to be lower, while NDMA FP tended to increase with increasing DOC. The effects of Br- (i.e., 1000 µg/L) on NDMA UFC depended on pH. Linear regression analysis indicated that NDMA UFC poorly correlated (R2 = 0.04-0.06, n = 17) with NDMA FP in different surface waters. The removal of NDMA FP and removal of NDMA UFC from model NDMA precursors were then evaluated during batch activated sludge (AS) treatment tests. Among the four model compounds tested, trimethylamine (TMA) and minocycline (MNCL) were readily removed (i.e., 77%-100% removals of NDMA FP) during 24-h AS treatment, ranitidine (RNTD) was moderately removed (i.e., 34%-87% removals of NDMA FP), and sumatriptan (SMTR) was the least removable (i.e., 29%-46% removals of NDMA FP). Increasing incubation time (or hydraulic retention time (HRT)) and solids retention time (SRT) favored the removal of NDMA FP from RNTD. Biosorption was found to be the major deactivation pathway of the amine-based pharmaceuticals (i.e., RNTD, MNCL and SMTR) tested, while biodegradation was the major deactivation pathway of TMA. Adding different biostimulants (e.g., glucose, acetate, benzoate and ammonia) insignificantly affected the removal of NDMA FP from RNTD. Non-specific oxygenase (i.e., phenol 2-monooxygenase) may play an insignificant role affecting the removal of NDMA FP from RNTD, especially at extended incubation time (i.e., 5-20 d). Removal of NDMA UFC from the tested compounds was generally comparable to the removal of their NDMA FP, except for MNCL which yielded negligible NDMA UFC before and after AS treatment. Finally, removal of N-nitrosamine precursors from sewage components (i.e., blackwaters and greywaters) and WWTP influents during the AS treatment was investigated under both FP and UFC tests. Removal of N-nitrosamine FP from sewage components depended on precursor sources (i.e., blackwaters and greywaters) and N-nitrosamine species. Increasing incubation time from 6 to 24 h enhanced the removal of N-nitrosamine FP. Removal of N-nitrosamine FP from WWTP influents mainly depended on AS sources during the batch treatment tests, rather than the types of wastewater influents. Among the three AS (i.e., domestic rural, domestic urban and textile AS) tested, the rural domestic AS showed relatively higher removal of N-nitrosamine FP from biologically originated precursor sources (e.g., urine blackwater, shower greywater not containing any personal care products, and kitchen greywater containing food leachates only). On the other hand, the textile AS exhibited higher removal of N-nitrosamine FP from sewage components containing detergents or personal care products (e.g., shower greywater containing shampoo, kitchen greywater containing dishwashing detergent, and laundry greywater containing laundry detergent). Different from N-nitrosamine FP, N-nitrosamine UFC from most sewage components increased after 6 or 24-h AS treatment

NANOPARTICLE BEHAVIOR IN BIOLOGICAL GELS AND BIOFLUIDS: THE IMPACT OF INTERACTIONS WITH CHARGED BIOGELS AND THE FORMATION OF PROTEIN CORONAS ON NANOPARTICLES

With the rapid growth of nanotechnology, situations where nanomaterials will interact with biological systems will unquestionably grow. Therefore, it is increasingly understood that interactions between nanomaterials and biological environments will play an essential role in nanomedicine. Biological polymer networks, including mucus and the extracellular matrix, serve as a filter for the exchange of molecules and nanoparticles. Such polymer networks are complex and heterogeneous hydrogel environments that regulate transport processes through finely tuned particle-network interactions. In chapters 3 and 4, we investigate the role of electrostatics on the basic mechanisms governing the diffusion of charged molecules inside model polymer networks by using fluorescence correlation spectroscopy (FCS). In chapter 3, we show that particle transport of charged probe molecules in charged hydrogels is highly asymmetric and that the filtering capability of the gel is sensitive to the solution ionic strength. Brownian dynamics simulations are in quantitative agreement with our experimental result. In chapter 4, we focus on hyperbranched cationic dendrimer macromolecules (polyamidoamine, PAMAM) which differ from probes in size, charge density and chain flexibilities. Our results show PAMAM has strongly reduced mobility in like charge gels and greatly enhanced apparent diffusivity in oppositely charged gels. Further studies with salt suggest that the oppositely charged polymer network acts as a giant counterion enhancing the mobility of PAMAM by changing its conformation to a more compacted state. Due to their large surface areas, nanomaterials in biological fluids are modified by adsorption of biomolecules, mainly proteins, to form so called “protein coronas”. These coronas ultimately define the biological identity of the nanoparticles and dictate the interactions of cells with the protein-NP complex. We have studied the adsorption of human transferrin and bovine serum albumin on the surface of sulfonated polystyrene nanoparticle. In chapter 5, we show the formation of multi-layered protein coronas and compare to established adsorption models. In addition we followed for the first time the protein binding kinetics as a function of pH and salt. Through these studies, we aim to gain quantitative knowledge of the dynamic rearrangement of proteins on engineered nanomaterials

Understanding the psychology of guilt

Understanding the Psychology of Guilt Guilt is a common negative emotion, experienced frequently in everyday life. It is likely that most adults have experienced this emotion at one time or another. The present research aims to advance our understanding of the nature of guilt by comparing it with regret in different contexts, examining the relation between guilt and being self-interest, and exploring motivations of sharing guilt with others. I ground my research in behavioral experiments with diverse populations (participants from the Netherlands, the United States, and China). Together, my research integrates theoretical frameworks from different literatures (self-identity theory, communication of emotion, and decision-making theory) and rigorous methods to better understand the emotion of guilt. There are several important findings in my research. First, I found that people feel guilt and regret differently when different self-discrepancies are experienced. More specifically, it suggests that guilt is more likely to be felt when people experience “ought” self-discrepancies related failure when compared with regret. Second, I found that guilt is relationship oriented. It can motivate people to forgo self-interest even when choosing it is a morally right option. Finally, I explored the phenomenon of sharing of guilt with third parties and found that the strongest motivations for sharing guilt are venting, clarification and meaning, and advice and solution. It enriches the literature of social sharing of emotions by adding guilt. This research is an important step toward better understanding of nature of guilt. Moreover, it has important practical implications for different fields, such as consumer research, education equality, and counselling support. For example, a considerable body of literature in marketing has studied effects of (anticipated) regret or (anticipated) guilt on consumer decisions and has found that people sometimes engage in behaviors (such as buying environmentally friendly product to reduce guilt; switching service to reduce regret) to reduce those emotions. However, the result of these research is inconsistent. Some find that guilt manipulations can increase charitable behavior, while other findings suggests that guilt does not relate to changes in pro-environmental behavior. Our research can help to explain this inconsistency. It could be that some guilt manipulation also induces regret in people, and this makes people to focus on improving self instead of caring about the environment or other people

QEBA: Query-Efficient Boundary-Based Blackbox Attack

Machine learning (ML), especially deep neural networks (DNNs) have been widely used in various applications, including several safety-critical ones (e.g. autonomous driving). As a result, recent research about adversarial examples has raised great concerns. Such adversarial attacks can be achieved by adding a small magnitude of perturbation to the input to mislead model prediction. While several whitebox attacks have demonstrated their effectiveness, which assume that the attackers have full access to the machine learning models; blackbox attacks are more realistic in practice. In this paper, we propose a Query-Efficient Boundary-based blackbox Attack (QEBA) based only on model's final prediction labels. We theoretically show why previous boundary-based attack with gradient estimation on the whole gradient space is not efficient in terms of query numbers, and provide optimality analysis for our dimension reduction-based gradient estimation. On the other hand, we conducted extensive experiments on ImageNet and CelebA datasets to evaluate QEBA. We show that compared with the state-of-the-art blackbox attacks, QEBA is able to use a smaller number of queries to achieve a lower magnitude of perturbation with 100% attack success rate. We also show case studies of attacks on real-world APIs including MEGVII Face++ and Microsoft Azure.Comment: Accepted by CVPR 202