Browsing by Author "Xu, Yong"
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Item An Investigation into the Role of 27-Hydroxycholesterol and Estrogen Receptors in Adipose Tissue, Obesity, and Breast Cancer(2021-05) Asghari Khonakdari, Arvand; Umetani, Michihisa; Xu, Yong; Zhang, Yang; Dauwalder, Brigitte; Chung, Sang-HyukObesity is an emerging health crisis all over the world. With obesity comes several other health disorders such as type-2 diabetes, cardiovascular diseases, and cancers. Hence, understanding the underlying reasons for obesity is of paramount importance as it can guide us in developing new therapeutic approaches for preventing or decreasing the obesity rates. Breast cancer is the second cause of cancer-related deaths among women worldwide. Endocrine resistance in breast cancer which occurs after endocrine therapies, causes the tumors to relapse after years of dormancy. While estrogen receptors (ERs) mutations and malfunctions of other signaling pathways (e.g., MAPK signaling) are some of the underlying reasons for endocrine resistance in breast cancer, the underlying causes of 60% of endocrine resistance cases remain completely unknown. Estrogen and estrogen receptors play important roles in both obesity and breast cancer. 27-Hydroxycholesterol (27HC), the first identified endogenous selective estrogen receptor modulator, can modulate the activity of estrogen receptors in different tissues and thus can be one of the important factors in regulating the functions of ERs in the context of obesity and breast cancer. In this dissertation, I first showed that 27HC mostly works as an antagonist for ERs activity in different tissues. Next, I investigated the effects of 27HC on adipose tissues and obesity. My research showed that 27HC increases body weight gain in the presence of a high-fat, high- cholesterol diet in an ER-dependent manner. Moreover, 27HC increases body fat percentage regardless of the diet and affects adipose tissue gene expression and induces inflammation in the adipose tissue. I also showed that 27HC alters the morphology and function of brown adipose tissue. In regard to endocrine resistance in breast cancer, I showed that 27HC increases the growth rate of the endocrine-resistant breast cancer cells, and I also found a novel group of genes that can be the underlying reasons for the endocrine development and progression. All in all, the research presented in this dissertation confirms the importance of 27HC in obesity and breast cancer and opens new doors toward the development of potential therapeutics to decrease the obesity rates, as well as treatment of endocrine-resistant breast cancer.Item Damage detection of fiber reinforced polymer plate repaired steel structure using percussion and machine learning(2022-05-12) Xu, Yong; Song, Gangbing; Chen, Zheng; Chen, XueminThe recent collapse of the Fern Hollow Bridge in Pittsburgh, Pennsylvania, brings attention to the structurally deficient infrastructure. The fiber reinforced polymer (FRP) has been proven to be a cost-effective, efficient, and reliable method for structure rehabilitation or reinforcement. Damage detection is an important measure to ensure the integrity and performance of such repairs. A novel method of using percussion and machine learning to detect the damage of FRP plate repaired steel structure was developed and discussed in this work. A steel beam with bonded carbon fiber reinforced polymer (CFRP) and known bonding defects was used as a test specimen. Then, different locations with different bonding conditions on the beam were tapped to generate the percussion sound, which was recorded by an iPhone. The mel-frequency cepstral coefficient (MFCC) algorithm was employed to extract features from percussion sound. The support vector machine (SVM) and recurrent neural network (RNN) method were implemented to learn the training samples and achieved high accuracy when predicting the healthy status of new test samples. The SVM used a new way of feature transformation, which is based on mean and standard deviation of MFCC. The high accuracy of 98.5% demonstrated the new feature transformation method is effective for SVM in percussion application. Then, the unsupervised clustering algorithms, k-means and Gaussian mixture model (GMM), were implemented on the sample data. The accuracy of k-means algorithm varies in a wide range from 51.5% to 70.4%, while the GMM clustering uses transformed MFCC and manually selected features, achieves an accuracy of 93.8%, The results of this work have demonstrated that the novel method of percussion and machine learning is reliable for damage detection of the FRP repaired steel structure. Compared with the conventional method, the proposed method does not require installation of sensors or implementing data acquisition systems or test instruments. The damage detection using percussion and machine learning brings great potential contribution to restoration of the deteriorated structure.Item Improving CNS Delivery of Genistein for the Treatment of Sanfilippo Syndrome(2017-12) Gupte, Manas Pravin; Hu, Ming; Chow, Diana Shu-Lian; Cuny, Gregory D.; Sardiello, Marco; Xu, YongStatement of the Problem: Sanfilippo syndrome or mucopolysaccharidosis type III (MPS III), a type of lysosomal storage disease, is a rare genetic disorder inherited in an autosomal recessive manner. Individuals affected by this disease lack the ability to produce one of the four enzymes responsible for the lysosomal degradation of heparan sulfate (HS). Heparan sulfate is thus accumulated in virtually every cell of the body leading to their progressive damage. The central nervous system, in particular, is affected by the accumulation of heparan sulfate, causing severe neurological impairments such as neurodegeneration and neuroinflammation. Currently, no effective therapy is available for treating MPS III. Genistein, a dietary soy isoflavone, has been observed to effectively reduce the production and reduce or prevent further accumulation of heparan sulfate in lysosomes in vitro as well as in vivo. However, in vivo reduction of heparan sulfate was seen only in the peripheral tissues but not observed in the CNS of MPS III mouse model. Low oral bioavailability, extensive metabolism, enterohepatic recycling and efflux transporters are few factors that are thought to be responsible for poor penetration of genistein into the brain. We aim to develop strategies to increase genistein concentration in the CNS, decrease the level of heparan sulfate in the CNS and thus effectively treat MPS III. Towards our goals, two major specific aims were proposed: (1) To improve accumulation of genistein in brain and (2) To evaluate the efficacy of genistein formulation. Methods: Genistein nanosuspensions were prepared by wet milling technique and characterized in order to select the most stable and uniform formulation with minimal particle size. Transcellular transport studies were carried out using Caco-2 monolayer to compare transport and permeability of unformulated genistein with genistein nanosuspension at a concentration of 200 M. Pharmacokinetic studies were carried out on 5 groups of FVB mice (N=4) for different oral doses of unformulated genistein (5 and 50 mg/kg) and genistein nanosuspension (5, 50 and 200 mg/kg). Blood samples were analyzed using a previously validated LC-MS/MS method. Single oral dose and multiple oral dose brain distribution studies were carried out in 4 groups of FVB mice and 3 groups of C57BL mice, respectively, at 200 mg/kg. Genistein concentration in brain samples were quantified by our developed and validated LC-MS/MS assay. A highly specific, sensitive and reproducible UHPLC-MS/MS method for rapid detection and analysis of heparan sulfate in murine brain tissue was also developed with successful ability to quantify HS levels in MPS IIIB mice. Results: We were able to prepare a stable and uniform genistein nanosuspension, which was able to enhance the oral absorption and increase the brain uptake of genistein. The brain distribution of the formulation was evaluated using the UPLC-MS/MS method we developed and validated for quantification of genistein in mouse brain matrix. Consecutive once a day dosing of nanosuspension resulted in higher distribution of genistein in mouse brain. The heparan sulfate polysaccharide was chemically derivatized to its disaccharide form which was quantified using UPLC-MS/MS. The measurements of HS were normalized to a spiked deuterated HS internal standard. Chromatographic separation of the derivatized products were achieved on a Biphenyl column using 10 mM ammonium acetate in water and 10 mM ammonium acetate in 100% methanol as mobile phases with a gradient elution. The assay was determined to be linear over a concentration range of 9.765625 - 625 g/mL with 9.765625 g/mL as the LLOQ. The intra- and inter-day accuracy and precision were determined to be within 20% in brain homogenate. HS was also tested for stability under various storage conditions such as bench-top stability (at 25C for 4 hours), three freeze-thaw cycles stability and auto-sampler stability (at 10C for 24 hours) with stability values within 20% range of nominal concentrations. Conclusions: We believe that our genistein formulation would be effective in treating Sanfilippo syndrome. Additionally, our strategy would find application in enhancing the CNS delivery of drugs which can be used to treat other CNS conditions whose potential has been hampered by the blood brain barrier. A straightforward, highly specific, sensitive and effective UPLC-MS/MS method for quantifying heparan sulfate in the brain matrix was devised. The validated assay was further applied for comparison and quantification of HS in brain tissues of wild type and MPS IIIB mice.