Learning to Optimize Domain Specific Normalization for Domain Generalization

We propose a simple but effective multi-source domain generalization technique based on deep neural networks by incorporating optimized normalization layers that are specific to individual domains. Our approach employs multiple normalization methods while learning separate affine parameters per domain. For each domain, the activations are normalized by a weighted average of multiple normalization statistics. The normalization statistics are kept track of separately for each normalization type if necessary. Specifically, we employ batch and instance normalizations in our implementation to identify the best combination of these two normalization methods in each domain. The optimized normalization layers are effective to enhance the generalizability of the learned model. We demonstrate the state-of-the-art accuracy of our algorithm in the standard domain generalization benchmarks, as well as viability to further tasks such as multi-source domain adaptation and domain generalization in the presence of label noise

Reference-unbiased copy number variant analysis using CGH microarrays

Comparative genomic hybridization (CGH) microarrays have been used to determine copy number variations (CNVs) and their effects on complex diseases. Detection of absolute CNVs independent of genomic variants of an arbitrary reference sample has been a critical issue in CGH array experiments. Whole genome analysis using massively parallel sequencing with multiple ultra-high resolution CGH arrays provides an opportunity to catalog highly accurate genomic variants of the reference DNA (NA10851). Using information on variants, we developed a new method, the CGH array reference-free algorithm (CARA), which can determine reference-unbiased absolute CNVs from any CGH array platform. The algorithm enables the removal and rescue of false positive and false negative CNVs, respectively, which appear due to the effects of genomic variants of the reference sample in raw CGH array experiments. We found that the CARA remarkably enhanced the accuracy of CGH array in determining absolute CNVs. Our method thus provides a new approach to interpret CGH array data for personalized medicine

TIARA: a database for accurate analysis of multiple personal genomes based on cross-technology

High-throughput genomic technologies have been used to explore personal human genomes for the past few years. Although the integration of technologies is important for high-accuracy detection of personal genomic variations, no databases have been prepared to systematically archive genomes and to facilitate the comparison of personal genomic data sets prepared using a variety of experimental platforms. We describe here the Total Integrated Archive of Short-Read and Array (TIARA; http://tiara.gmi.ac.kr) database, which contains personal genomic information obtained from next generation sequencing (NGS) techniques and ultra-high-resolution comparative genomic hybridization (CGH) arrays. This database improves the accuracy of detecting personal genomic variations, such as SNPs, short indels and structural variants (SVs). At present, 36 individual genomes have been archived and may be displayed in the database. TIARA supports a user-friendly genome browser, which retrieves read-depths (RDs) and log2 ratios from NGS and CGH arrays, respectively. In addition, this database provides information on all genomic variants and the raw data, including short reads and feature-level CGH data, through anonymous file transfer protocol. More personal genomes will be archived as more individuals are analyzed by NGS or CGH array. TIARA provides a new approach to the accurate interpretation of personal genomes for genome research

Behavior of a GaSb (100) Surface in the Presence of H₂O₂ in Wet-Etching Solutions

Gallium antimonide (GaSb) has an extremely high electron mobility and an excellent lattice match with various III–V ternary and quaternary compounds. In this study, the effect of wet-etching processes on the GaSb (001) surface was investigated, with a focus on the effect of H₂O₂. Dilution with H₂O and addition of H₂O₂ in HF/H₂O₂/H₂O, NH₄OH/H₂O₂/H₂O, and HCl/H₂O₂/H₂O mixtures produced different effects on the GaSb surface. The etching rate of GaSb increased with a high dilution ratio and a small amount of H₂O₂ in the mixture of NH₄OH/H₂O₂/H₂O. The addition of H₂O₂ in H₂O decreased GaSb oxide thickness and increased the contact angle on the GaSb surface and the XPS Ga 3d and Sb 3d_3/2 peak area ratios of Ga₂O₃/GaSb and Sb₂O₃/GaSb, which strongly imply that the H₂O₂ in the wet-etching solution served as an inhibitor of surface oxidation on GaSb. On the basis of the observed etching rates of GaSb, oxidation kinetics, contact angles, and chemical states, it is suggested that concurrent oxidation of GaSb and etching of oxidized GaSb occur on the GaSb surface in the presence of H₂O₂. Furthermore, the overall kinetics is determined by the relative amount of H₂O₂, which depends on the pH of the etching solution

OGT and FLAD1 Genes Had Significant Prognostic Roles in Progressive Pathogenesis in Prostate Cancer

Purpose: This study aimed to identify metabolic genes associated with non-metastatic prostate cancer progression using The Cancer Genome Atlas (TCGA) datasets and validate their prognostic role by assessing patients’ immunohistochemical prostatectomy specimens. Materials and Methods: Several metabolic candidate genes analyzed were highly correlated with cancer progression to biochemical recurrence (BCR) and deaths in 335 patients’ genetic information from TCGA datasets. Those candidate genes and their expressions in tissue specimens were validated retrospectively by immunohistochemical analysis of radical prostatectomy specimens collected from 514 consecutive patients with non-metastatic prostate cancer between 2000 and 2015. The Cox proportional-hazards model was used to predict the prognostic role of each candidate gene expression in BCR and survival prognoses with a statistical significance of p-value <0.05. Twenty metabolic genes were identified by own developed software (Targa; https://github.com/cgab-ncc/TarGA), whose median expression levels consistently increased with cancer progression to the BCR and deaths. Results: Five metabolic genes (MAT2A, FLAD1, UGDH, OGT, and RRM2) were found to be significantly involved in the overall survival in the TCGA dataset. The immunohistochemical validation and clinicopathological data showed that OGT (hazard ratio [HR], 1.002; 95% confidence interval [CI], 1.001–1.003) and FLAD1 (HR, 1.010; 95% CI, 1.003–1.017) remained significant factors for BCR and cancer-specific survival, respectively, in the multivariate analysis even after adjusting for confounding clinicopathological parameters (p<0.05). Conclusions: OGT and FLAD1 showed significant prognostic factors of disease progression, even after adjustment for confounding clinicopathological parameters in non-metastatic prostate cancer

Investigation of the Efficacy of Benzylidene-3-methyl-2-thioxothiazolidin-4-one Analogs with Antioxidant Activities on the Inhibition of Mushroom and Mammal Tyrosinases

Based on the fact that substances with a β-phenyl-α,β-unsaturated carbonyl (PUSC) motif confer strong tyrosinase inhibitory activity, benzylidene-3-methyl-2-thioxothiazolidin-4-one (BMTTZD) analogs 1–8 were prepared as potential tyrosinase inhibitors. Four analogs (1–3 and 5) inhibited mushroom tyrosinase strongly. Especially, analog 3 showed an inhibitory effect that was 220 and 22 times more powerful than kojic acid in the presence of l-tyrosine and l-dopa, respectively. A kinetic study utilizing mushroom tyrosinase showed that analogs 1 and 3 competitively inhibited tyrosinase, whereas analogs 2 and 5 inhibited tyrosinase in a mixed manner. A docking simulation study indicated that analogs 2 and 5 could bind to both the tyrosinase active and allosteric sites with high binding affinities. In cell-based experiments using B16F10 cells, analogs 1, 3, and 5 effectively inhibited melanin production; their anti-melanogenic effects were attributed to their ability to inhibit intracellular tyrosinase activity. Moreover, analogs 1, 3, and 5 inhibited in situ B16F10 cellular tyrosinase activity. In three antioxidant experiments, analogs 2 and 3 exhibited strong antioxidant efficacy, similar to that of the positive controls. These results suggest that the BMTTZD analogs are promising tyrosinase inhibitors for the treatment of hyperpigmentation-related disorders

Discovery of common Asian copy number variants using integrated high-resolution array CGH and massively parallel DNA sequencing

Copy number variants (CNVs) account for the majority of human genomic diversity in terms of base coverage. Here, we have developed and applied a new method to combine high-resolution array comparative genomic hybridization (CGH) data with whole-genome DNA sequencing data to obtain a comprehensive catalog of common CNVs in Asian individuals. The genomes of 30 individuals from three Asian populations (Korean, Chinese and Japanese) were interrogated with an ultra-high-resolution array CGH platform containing 24 million probes. Whole-genome sequencing data from a reference genome (NA10851, with 28.3x coverage) and two Asian genomes (AK1, with 27.8x coverage and AK2, with 32.0x coverage) were used to transform the relative copy number information obtained from array CGH experiments into absolute copy number values. We discovered 5,177 CNVs, of which 3,547 were putative Asian-specific CNVs. These common CNVs in Asian populations will be a useful resource for subsequent genetic studies in these populations, and the new method of calling absolute CNVs will be essential for applying CNV data to personalized medicine.Conrad DF, 2010, NATURE, V464, P704, DOI 10.1038/nature08516Kim JI, 2009, NATURE, V460, P1011, DOI 10.1038/nature08211Horowitz RE, 2008, NEW ENGL J MED, V359, P2393Shiffman D, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0002895Kidd JM, 2008, NATURE, V453, P56, DOI 10.1038/nature06862Perry GH, 2008, AM J HUM GENET, V82, P685, DOI 10.1016/j.ajhg.2007.12.010Graham DSC, 2008, GENES IMMUN, V9, P93, DOI 10.1038/sj.gene.6364453Lohmueller KE, 2008, NATURE, V451, P994, DOI 10.1038/nature06611Korbel JO, 2007, SCIENCE, V318, P420, DOI 10.1126/science.1149504Hossain P, 2007, NEW ENGL J MED, V356, P213Larson MG, 2007, BMC MED GENET, V8, DOI 10.1186/1471-2350-8-S1-S5Redon R, 2006, NATURE, V444, P444, DOI 10.1038/nature05329Jee SH, 2006, NEW ENGL J MED, V355, P779Aitman TJ, 2006, NATURE, V439, P851, DOI 10.1038/nature04489Conrad DF, 2006, NAT GENET, V38, P75, DOI 10.1038/ng1697Wang YH, 2005, J LAB CLIN MED, V146, P321, DOI 10.1016/j.lab.2005.07.007Lindner I, 2005, MOL NUTR FOOD RES, V49, P972, DOI 10.1002/mnfr.200500087Tuzun E, 2005, NAT GENET, V37, P727, DOI 10.1038/ng1562Lee JW, 2005, ONCOGENE, V24, P1477, DOI 10.1038/sj.onc.1208304Iafrate AJ, 2004, NAT GENET, V36, P949, DOI 10.1038/ng1416Samuels Y, 2004, SCIENCE, V304, P554, DOI 10.1126/science.1096502Burchard EG, 2003, NEW ENGL J MED, V348, P1170COLIN Y, 1991, BLOOD, V78, P27474