Integrated glycomics, proteomics, and glycoproteomics of human leukocytes and glioblastoma tissue microarrays

This thesis includes studies on N-, mucin type O-, and glycosaminoglycan (GAG)-linked glycosylation in human biospecimens. Glycosylation plays a central role in biological processes, including protein folding, immune surveillance, and regulation of cell growth. The structures of GAG are regulated in a tissue-specific manner. Heparan sulfate (HS) and chondroitin sulfate (CS) are the two types of GAGs targeted in this thesis. Human leukocytes express both CS and HS GAGs with CS being the more abundant type; however, little is known regarding the properties and structures of GAG chains, their ranges of variability among normal subjects, and changes in structure associated with disease conditions. We measured the relative and absolute disaccharides abundances of HS and CS for purified B, T, NK cells, monocytes, and polymorphonuclear leukocytes (PMNs) using size exclusion chromatography-mass spectrometry (SEC-MS). We found that all leukocytes express HS chains with levels of sulfation more similar to heparin than to organ-derived HS. In addition, CS abundances varied considerably in a leukocyte cell type specific manner. Therefore, our results established the ranges of GAG structures expressed on normal leukocytes as well as necessary for subsequent inquiry into disease conditions. Glioblastoma (GBM) accounts for 30% of human primary brain tumors. It is deadly and highly invasive. In past decades, most GBM research focused on pathophysiological changes in genome. There remains a dearth of knowledge regarding alterations in glycomics, glycoproteomics, and proteomics during GBM tumorigenesis. Therefore, we developed a comprehensive platform for high-throughput sample preparation with surface digestion for tissue microarrays, LC-MS/MS data dependent acquisition, and semi-automated data analysis to integrate glycomics, glycoproteomics, and proteomics for different grade of tumor and different subtypes of GBM. By analyzing GBM tissue microarrays, we found tumor grade and subtype specific changes to the expression of biomolecules. We also identified approximately 100 site-specific N- and mucin type O-glycosylations, the majority of which were previously unreported. Overall, our results improved the fundamental understandings about GBM pathogenesis.2018-11-02T00:00:00

Null geodesics and gravitational lensing in a nonsingular spacetime

In this paper, the null geodesics and gravitational lensing in a nonsingular spacetime are investigated. According to the nature of the null geodesics, the spacetime is divided into several cases. In the weak deflection limit, we find the influence of the nonsingularity parameter $q$ on the positions and magnifications of the images is negligible. In the strong deflection limit, the coefficients and observables for the gravitational lensing in a nonsingular black hole background and a weakly nonsingular spacetime are obtained. Comparing these results, we find that, in a weakly nonsingular spacetime, the relativistic images have smaller angular position and relative magnification, but larger angular separation than that of a nonsingular black hole. These results might offer a way to probe the spacetime nonsingularity parameter and put a bound on it by the astronomical instruments in the near future.Comment: 15 pages, 5 figures, 1 tabl

Gravity Localization and Effective Newtonian Potential for Bent Thick Branes

In this letter, we first investigate the gravity localization and mass spectrum of gravity KK modes on de Sitter and Anti-de Sitter thick branes. Then, the effective Newtonian gravitational potentials for these bent branes are discussed by the two typical examples. The corrections of the Newtonian potential turns out to be $\Delta U(r)\sim 1/r^{2}$ at small $r$ for both cases. These corrections are very different from that of the Randall-Sundrum brane model $\Delta U(r)\sim 1/r^{3}$.Comment: 6 pages, 2 figure

Online Unsupervised Multi-view Feature Selection

In the era of big data, it is becoming common to have data with multiple modalities or coming from multiple sources, known as "multi-view data". Multi-view data are usually unlabeled and come from high-dimensional spaces (such as language vocabularies), unsupervised multi-view feature selection is crucial to many applications. However, it is nontrivial due to the following challenges. First, there are too many instances or the feature dimensionality is too large. Thus, the data may not fit in memory. How to select useful features with limited memory space? Second, how to select features from streaming data and handles the concept drift? Third, how to leverage the consistent and complementary information from different views to improve the feature selection in the situation when the data are too big or come in as streams? To the best of our knowledge, none of the previous works can solve all the challenges simultaneously. In this paper, we propose an Online unsupervised Multi-View Feature Selection, OMVFS, which deals with large-scale/streaming multi-view data in an online fashion. OMVFS embeds unsupervised feature selection into a clustering algorithm via NMF with sparse learning. It further incorporates the graph regularization to preserve the local structure information and help select discriminative features. Instead of storing all the historical data, OMVFS processes the multi-view data chunk by chunk and aggregates all the necessary information into several small matrices. By using the buffering technique, the proposed OMVFS can reduce the computational and storage cost while taking advantage of the structure information. Furthermore, OMVFS can capture the concept drifts in the data streams. Extensive experiments on four real-world datasets show the effectiveness and efficiency of the proposed OMVFS method. More importantly, OMVFS is about 100 times faster than the off-line methods

Type 1 2HDM as effective theory of supersymmetry

It is generally believed that the low energy effective theory of the minimal supersymmetric standard model is the type 2 two Higgs doublet model. We will show that the type 1 two Higgs doublet model can also as the effective of supersymmetry in a specific case with high scale supersymmetry breaking and gauge mediation. If the other electroweak doublet obtain the vacuum expectation value after the electroweak symmetry breaking, the Higgs spectrum is quite different. A remarkable feature is that the physical Higgs boson mass can 125 GeV unlike in the ordinary models with high scale supersymmetry in which the Higgs mass is generally around 140 GeV.Comment: 11 pages, 3 figures, Published in Commun.Theor.Phy

Geometric curvatures of plane symmetry black hole

In this paper, we study the properties and thermodynamic stability of the plane symmetry black hole from the viewpoint of geometry. Weinhold metric and Ruppeiner metric are obtained, respectively. The Weinhold curvature gives phase transition points, which correspond to the first-order phase transition only at N=1, where $N$ is a parameter in the plane symmetry black hole. While the Ruppeiner one shows first-order phase transition points for arbitrary $N\neq 1$. Both of which give no any information about the second-order phase transition. Considering the Legendre invariant proposed by Quevedo et. al., we obtain a unified geometry metric, which gives a correctly the behavior of the thermodynamic interactions and phase transitions. The geometry is also found to be curved and the scalar curvature goes to negative infinity at the Davies' phase transition points when the logarithmic correction is included.Comment: 16 pages, 6 figure