STATISTICAL METHODS FOR BRAIN IMAGING AND GENOMIC DATA ANALYSIS

Modern technologies for imaging brain activity, such as functional MRI, are very useful in studying mechanisms for human brain. In this thesis, statistical methods and computational techniques are developed to investigate brain function through fMRI. In particular, we are interested in the activation of human brain networks and learning patterns. In the first component of the work, we developed a new group ICA approach, Homotopic Group ICA (“H-gICA”), which seeks to identify networks of correlated regions across subjects and measures the degree of synchrony in spontaneous activity between geometrically corresponding interhemispheric brain regions. H-gICA is able to increase the potential for network discovery and facilitate the investigation of functional homotopy via ICA based networks. In the second part of the work, we develop methodology for an investigation of motor learning using activation distributions. We investigate tests of dimension for detect- ing learning-based changes, particularly motor learning. Our investigation includes a large scale simulation study of brain activation maps, motivated by a study of motor learning in healthy adults. In the third part of the work, we devise an approach to phenotype classification from gene expression profiling. We propose a new high dimensional discriminant analysis method called group Nearest Shrunken Centroids (gNSC), which enables us to use gene pathway information. We also apply our method on a novel context analysis of association between pathways and certain medical words to improve the power of feature selection

Zika Virus Non-structural Protein 4A Blocks the RLR-MAVS Signaling

Flaviviruses have evolved complex mechanisms to evade the mammalian host immune systems including the RIG-I (retinoic acid-inducible gene I) like receptor (RLR) signaling. Zika virus (ZIKV) is a re-emerging flavivirus that is associated with severe neonatal microcephaly and adult Guillain-Barre syndrome. However, the molecular mechanisms underlying ZIKV pathogenesis remain poorly defined. Here we report that ZIKV non-structural protein 4A (NS4A) impairs the RLR-mitochondrial antiviral-signaling protein (MAVS) interaction and subsequent induction of antiviral immune responses. In human trophoblasts, both RIG-I and melanoma differentiation-associated protein 5 (MDA5) contribute to type I interferon (IFN) induction and control ZIKV replication. Type I IFN induction by ZIKV is almost completely abolished in MAVS-/- cells. NS4A represses RLR-, but not Toll-like receptor-mediated immune responses. NS4A specifically binds the N-terminal caspase activation and recruitment domain (CARD) of MAVS and thus blocks its accessibility by RLRs. Our study provides in-depth understanding of the molecular mechanisms of immune evasion by ZIKV and its pathogenesis

Context aware group nearest shrunken centroids in large-scale genomic studies

Recent genomic studies have identified genes related to specific phenotypes. In addition to marginal association analysis for individual genes, analyzing gene pathways (functionally related sets of genes) may yield additional valuable insights. We have devised an approach to phenotype classification from gene expression profiling. Our method named “group Nearest Shrunken Centroids (gNSC)” is an enhancement of the Nearest Shrunken Centroids (NSC) which is a popular and scalable method to analyze big data. While fully utilizing the variable structure of gene pathways, gNSC shares comparable computational speed as NSC if the group size is small. Comparing with NSC, gNSC improves the power of classification by utilizing the gene pathway information. In practice, we investigate the performance of gNSC on one of the largest microarray datasets aggregated from the internet. We show the effectiveness of our method by comparing the misclassification rate of gNSC with that of NSC. Additionally, we present a novel application of NSC/gNSC on context analysis of association between pathways and certain medical words. Some newest biological findings are rediscovered

Synthesis of Ag-La0.8Sr0.2MnO3 (LSM-Ag) Composite Powder and Its Application in Magnesium Air Battery

La0.8Sr0.2MnO3 (LSM) catalyst is prepared via a sol-gel method and modified via a typical silver mirror reaction. Silver ammonia solution is reduced in a polyvinylpyrrolidone (PVP)-containing solution to obtain silver nanoparticles and sodium dodecyl sulfate (SDS) is added as a surfactant. The microstructure and morphology of the LSM-Ag composite powder are characterized. According to the results, the Ag particles precipitate on the LSM surface in elemental form and the grain size is about one hundred nanometers. The analysis of electrocatalytic performance of LSM-Ag cathodes with different amounts of silver loading reveals that the number of electrons transferred during the oxygen reduction reaction (ORR) of the cathode with an Ag content of 14% by weight reached 3.9, which is very close to that of commercial Pt/C catalysts. Similarly, the maximum power density of the air battery made of LSM-14%Ag is 73 mW/cm2, which exceeds that of 63 mW/cm2, found for the LSM battery. Finally, increasing the amount of silver loading allows one to improve the electrochemical performance of LSM catalysts. The best effect is achieved when the Ag loading exceeds 14%

Effects of intermetallic phases on electrochemical properties of powder metallurgy Mg-6%Al-5%Pb anode alloy used for seawater activated battery

The changes in intermetallic phases of Mg-6%Al-5%Pb (Mg-Al-Pb) alloy prepared by powder metallurgy and their effects on electrochemical properties were studied. Experimental results showed that coarse Mg _17 Al _12 phases (with size ranges from 20 μ m to 70 μ m) and fine Mg _2 Pb phases (with the size of 100 nm scale) formed in the mixed Al, Pb and Mg powder during the hot press sintering procedure. Fine Mg _2 Pb phases exhibit strong diffusional ability to diffuse into Mg _17 Al _12 phases. Extruding further promotes the diffusion of Mg _2 Pb phases into Mg _17 Al _12 phases. Solution treatment produced a mixed microstructure which is Mg _17 Al _12 phase containing Mg _2 Pb phases inside and made other Mg _2 Pb phases homogeneously distributed in Mg matrix. Mg _17 Al _12 phases and the gathered Mg _2 Pb phases will accumulate the Mg(OH) _2 corrosion products, which impedes the subsequent discharge behavior. Homogeneously distributed Mg _2 Pb phases will fall off during discharge, which makes the discharge curve more stable. The mixed microstructure has positive effect on corrosion resistance and discharge potential. Therefore, solution-treated alloy shows the highest negative potential and the smoothest curve during the galvanostatic discharge test. Compared with the commercial AZ61 sheet, solution-treated alloy exhibit much higher anode properties in Mg/PbCl _2 battery test. Thus, the solution-treated alloy could serve as an excellent anode in seawater-activated batteries

The polymorphisms of LCR, E6, and E7 of HPV-58 isolates in Yunnan, Southwest China

Abstract Backgroud Variations in HPV LCR/E6/E7 have been shown to be associated with the viral persistence and cervical cancer development. So far, there are few reports about the polymorphisms of the HPV-58 LCR/E6/E7 sequences in Southwest China. This study aims to characterize the gene polymorphisms of the HPV-58 LCR/E6/E7 sequences in women of Southwest China, and assess the effects of variations on the immune recognition of viral E6 and E7 antigens. Methods Twelve LCR/E6/E7 of the HPV-58 isolates were amplified and sequenced. A neighbor-joining phylogenetic tree was constructed by MEGA 7.0, followed by the secondary structure prediction of the related proteins using PSIPRED v3.3. The selection pressure acting on the HPV-58 E6 and E7 coding regions was estimated by Bayes empirical Bayes analysis of PAML 4.8. Meanwhile, the MHC class-I and II binding peptides were predicted by the ProPred-I server and ProPred server. The transcription factor binding sites in the HPV-58 LCR were analyzed using the JASPAR database. Results Twenty nine SNPs (20 in the LCR, 3 in the E6, 6 in the E7) were identified at 27 nucleotide sites across the HPV-58 LCR/E6/E7. From the most variable to the least variable, the nucleotide variations were LCR > E7 > E6. The combinations of all the SNPs resulted in 11 unique sequences, which were clustered into the A lineage (7 belong to A1, 2 belong to A2, and 2 belong to A3). An insertion (TGTCAGTTTCCT) was found between the nucleotide sites 7280 and 7281 in 2 variants, and a deletion (TTTAT) was found between 7429 and 7433 in 1 variant. The most common non-synonymous substitution V77A in the E7 was observed in the sequences encoding the α-helix. 63G in the E7 was determined to be the only one positively selected site in the HPV-58 E6/E7 sequences. Six non-synonymous amino acid substitutions (including S71F and K93 N in the E6, and T20I, G41R, G63S/D, and V77A in the E7) were affecting multiple putative epitopes for both CD4+ and CD8+ T-cells. In the LCR, C7265G and C7266T were the most variable sites and were the potential binding sites for the transcription factor SOX10. Conclusion These results provide an insight into the intrinsic geographical relatedness and biological differences of the HPV-58 variants, and contribute to further research on the HPV-58 epidemiology, carcinogenesis, and therapeutic vaccine development