Assessment of DNA methylation was performed on human skeletal muscle and blood using reduced representation bisulfite sequencing (RRBS) for high-throughput identification and pyrosequencing for site-specific confirmation. Sorbin and SH3 homology domain 3 (SORBS3) was identified in skeletal muscle to be increased in methylation (+5.0 to +24.4 %) in the promoter and 5’untranslated region (UTR) in the obese participants (n= 10) compared to lean (n=12), and this finding corresponded with a decrease in gene expression (fold change: -1.9, P=0.0001). Furthermore, SORBS3 was demonstrated in a separate cohort of morbidly obese participants (n=7) undergoing weight-loss induced by surgery, to decrease in methylation (-5.6 to -24.2%) and increase in gene expression (fold change: +1.7; P=0.05) post-surgery. Moreover, SORBS3 promoter methylation was demonstrated in vitro to inhibit transcriptional activity (P=0.000003). The methylation and transcriptional changes for SORBS3 were significantly (P≤0.05) correlated with obesity measures and fasting insulin levels. SORBS3 was not identified in the blood methylation analysis of lean (n=10) and obese (n=10) participants suggesting that it is a muscle specific marker. However, solute carrier family 19 member 1 (SLC19A1) was identified in blood and skeletal muscle to have decreased 5’UTR methylation in obese participants, and this was significantly (P≤0.05) predicted by insulin sensitivity.
These findings suggest SLC19A1 as a potential blood-based biomarker for obese, insulin resistant states. The collective findings of SORBS3 DNA methylation and gene expression present an exciting novel target in skeletal muscle for further understanding obesity and its underlying insulin resistance. Moreover, the dynamic changes to SORBS3 in response to metabolic improvements and weight-loss induced by surgery.
Various deposition methods, both physical and chemical, were used to functionalize the ZnO NWs with metal or alloy nanoparticles (NPs) for catalytic transformations of important molecules which are relevant to energy and environment. Cu and PdZn NPs were epitaxially grown on ZnO NWs to make them resistant to sintering at elevated temperatures and thus improved the stability of such catalytic systems for methanol steam reforming (MSR) to produce hydrogen. A series of Pd/ZnO catalysts with different Pd loadings were synthesized and tested for MSR reaction. The CO selectivity was found to be strongly dependent on the size of the Pd: Both PdZn alloy and single Pd atoms yield low CO selectivity while Pd clusters give the highest CO selectivity.
By dispersing single Pd atoms onto ZnO NWs, Pd1/ZnO single-atom catalysts (SACs) was synthesized and their catalytic performance was evaluated for selected catalytic reactions. The experimental results show that the Pd1/ZnO SAC is active for CO oxidation and MSR but is not desirable other reactions. We further synthesized ZnO NWs supported noble metal (M1/ZnO; M=Rh, Pd, Pt, Ir) SACs and studied their catalytic performances for CO oxidation. The catalytic test data shows that all the fabricated noble metal SACs are active for CO oxidation but their activity are significantly different. Structure-performance relationships were investigated.
This dissertation proposes two PageRank-based analytical methods, Pathways of Topological Rank Analysis (PoTRA) and miR2Pathway, discussed in Chapter 1 and Chapter 2, respectively. PoTRA focuses on detecting pathways with an altered number of hub genes in corresponding pathways between two phenotypes. The basis for PoTRA is that the loss of connectivity is a common topological trait of cancer networks, as well as the prior knowledge that a normal biological network is a scale-free network whose degree distribution follows a power law where a small number of nodes are hubs and a large number of nodes are non-hubs. However, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the scale-free structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal samples. Hence, it is hypothesized that if the number of hub genes is different in a pathway between normal and cancer, this pathway might be involved in cancer. MiR2Pathway focuses on quantifying the differential effects of miRNAs on the activity of a biological pathway when miRNA-mRNA connections are altered from normal to disease and rank disease risk of rewired miRNA-mediated biological pathways. This dissertation explores how rewired gene-gene interactions and rewired miRNA-mRNA interactions lead to aberrant activity of biological pathways, and rank pathways for their disease risk. The two methods proposed here can be used to complement existing genomics analysis methods to facilitate the study of biological mechanisms behind disease at the systems-level.
designing personalized treatments and improving clinical outcomes of cancers. Such
investigations require accurate delineation of the subclonal composition of a tumor, which
to date can only be reliably inferred from deep-sequencing data (>300x depth). The
resulting algorithm from the work presented here, incorporates an adaptive error model
into statistical decomposition of mixed populations, which corrects the mean-variance
dependency of sequencing data at the subclonal level and enables accurate subclonal
discovery in tumors sequenced at standard depths (30-50x). Tested on extensive computer
simulations and real-world data, this new method, named model-based adaptive grouping
of subclones (MAGOS), consistently outperforms existing methods on minimum
sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports
subclone analysis using single nucleotide variants and copy number variants from one or
more samples of an individual tumor. GUST algorithm, on the other hand is a novel method
in detecting the cancer type specific driver genes. Combination of MAGOS and GUST
results can provide insights into cancer progression. Applications of MAGOS and GUST
to whole-exome sequencing data of 33 different cancer types’ samples discovered a
significant association between subclonal diversity and their drivers and patient overall
survival.
The proposed thermal model is then applied to a novel $\Pi$-gate architecture which has been suggested to reduce hot electron generation in the device, compared to the conventional T-gate. Additionally, small signal ac simulations are performed for the determination of cutoff frequencies using the thermal model as well.
Finally, further extensions of the CMC algorithm used in this work are discussed, including 1) higher-order moments of the phonon BTE, 2) coupling to phonon Monte Carlo simulations, and 3) application to other large-bandgap, and therefore high-power, materials such as diamond.
The relation between flux and fluctuation is fundamental to complex physical systems that support and transport flows. A recently obtained law predicts monotonous enhancement of fluctuation as the average flux is increased, which in principle is valid but only for large systems. For realistic complex systems of small sizes, this law breaks down when both the average flux and fluctuation become large. Here we demonstrate the failure of this law in small systems using real data and model complex networked systems, derive analytically a modified flux-fluctuation law, and validate it through computations of a large number of complex networked systems. Our law is more general in that its predictions agree with numerics and it reduces naturally to the previous law in the limit of large system size, leading to new insights into the flow dynamics in small-size complex systems with significant implications for the statistical and scaling behaviors of small systems, a topic of great recent interest.
Novel hydride chemistries are employed to deposit light-emitting Ge1-y Snyalloys with y ≤ 0.1 by Ultra-High Vacuum Chemical Vapor Deposition (UHV-CVD) on Ge-buffered Si wafers. The properties of the resultant materials are systematically compared with similar alloys grown directly on Si wafers. The fundamental difference between the two systems is a fivefold (and higher) decrease in lattice mismatch between film and virtual substrate, allowing direct integration of bulk-like crystals with planar surfaces and relatively low dislocation densities. For y ≤ 0.06, the CVD precursors used were digermane Ge2H6 and deuterated stannane SnD4. For y ≥ 0.06, the Ge precursor was changed to trigermane Ge3H8, whose higher reactivity enabled the fabrication of supersaturated samples with the target film parameters. In all cases, the Ge wafers were produced using tetragermane Ge4H10 as the Ge source. The photoluminescence intensity from Ge1-y Sny /Ge films is expected to increase relative to Ge1-y Sny /Si due to the less defected interface with the virtual substrate. However, while Ge1-y Sny /Si films are largely relaxed, a significant amount of compressive strain may be present in the Ge1-y Sny /Ge case. This compressive strain can reduce the emission intensity by increasing the separation between the direct and indirect edges. In this context, it is shown here that the proposed CVD approach to Ge1-y Sny /Ge makes it possible to approach film thicknesses of about 1 μm, for which the strain is mostly relaxed and the photoluminescence intensity increases by one order of magnitude relative to Ge1-y Sny /Si films. The observed strain relaxation is shown to be consistent with predictions from strain-relaxation models first developed for the Si1-x Gex /Si system. The defect structure and atomic distributions in the films are studied in detail using advanced electron-microscopy techniques, including aberration corrected STEM imaging and EELS mapping of the average diamond–cubic lattice.
An outstanding and fundamental problem in contemporary physics is to include and probe the many-body effect in the study of relativistic quantum manifestations of classical chaos. We address this problem using graphene systems described by the Hubbard Hamiltonian in the setting of resonant tunneling. Such a system consists of two symmetric potential wells separated by a potential barrier, and the geometric shape of the whole domain can be chosen to generate integrable or chaotic dynamics in the classical limit. Employing a standard mean-field approach to calculating a large number of eigenenergies and eigenstates, we uncover a class of localized states with near-zero tunneling in the integrable systems. These states are not the edge states typically seen in graphene systems, and as such they are the consequence of many-body interactions. The physical origin of the non-edge-state type of localized states can be understood by the one-dimensional relativistic quantum tunneling dynamics through the solutions of the Dirac equation with appropriate boundary conditions. We demonstrate that, when the geometry of the system is modified to one with chaos, the localized states are effectively removed, implying that in realistic situations where many-body interactions are present, classical chaos is capable of facilitating greatly quantum tunneling. This result, besides its fundamental importance, can be useful for the development of nanoscale devices such as graphene-based resonant-tunneling diodes.