Copy number variations (CNVs) identified in Korean individuals

<p>Abstract</p> <p>Background</p> <p>Copy number variations (CNVs) are deletions, insertions, duplications, and more complex variations ranging from 1 kb to sub-microscopic sizes. Recent advances in array technologies have enabled researchers to identify a number of CNVs from normal individuals. However, the identification of new CNVs has not yet reached saturation, and more CNVs from diverse populations remain to be discovered.</p> <p>Results</p> <p>We identified 65 copy number variation regions (CNVRs) in 116 normal Korean individuals by analyzing Affymetrix 250 K Nsp whole-genome SNP data. Ten of these CNVRs were novel and not present in the Database of Genomic Variants (DGV). To increase the specificity of CNV detection, three algorithms, CNAG, dChip and GEMCA, were applied to the data set, and only those regions recognized at least by two algorithms were identified as CNVs. Most CNVRs identified in the Korean population were rare (<1%), occurring just once among the 116 individuals. When CNVs from the Korean population were compared with CNVs from the three HapMap ethnic groups, African, European, and Asian; our Korean population showed the highest degree of overlap with the Asian population, as expected. However, the overlap was less than 40%, implying that more CNVs remain to be discovered from the Asian population as well as from other populations. Genes in the novel CNVRs from the Korean population were enriched for genes involved in regulation and development processes.</p> <p>Conclusion</p> <p>CNVs are recently-recognized structural variations among individuals, and more CNVs need to be identified from diverse populations. Until now, CNVs from Asian populations have been studied less than those from European or American populations. In this regard, our study of CNVs from the Korean population will contribute to the full cataloguing of structural variation among diverse human populations.</p

Super-hydration and reduction of manganese oxide minerals at shallow terrestrial depths

Manganese oxides are ubiquitous marine minerals which are redox sensitive. As major components of manganese nodules found on the ocean floor, birnessite and buserite have been known to be two distinct water-containing minerals with manganese octahedral interlayer separations of similar to 7 angstrom and similar to 10 angstrom, respectively. We show here that buserite is a super-hydrated birnessite formed near 5 km depth conditions. As one of the most hydrous minerals containing ca. 34.5 wt. % water, super-hydrated birnessite, i.e., buserite, remains stable up to ca. 70 km depth conditions, where it transforms into manganite by releasing ca. 24.3 wt. % water. Subsequent transformations to hausmannite and pyrochroite occur near 100 km and 120 km depths, respectively, concomitant with a progressive reduction of Mn4+ to Mn2+. Our work forwards an abiotic geochemical cycle of manganese minerals in subduction and/or other aqueous terrestrial environments, with implications for water storage and cycling, and the redox capacity of the region

Association between red blood cell storage duration and clinical outcome in patients undergoing off-pump coronary artery bypass surgery: a retrospective study

Background: Prolonged storage of red blood cells (RBCs) leads to fundamental changes in both the RBCs and the storage media. We retrospectively evaluated the relationship between the RBC age and in-hospital and long-term postoperative outcomes in patients undergoing off-pump coronary artery bypass. Methods: The electronic medical records of 1,072 OPCAB patients were reviewed and information on the transfused RBCs and clinical data were collected. The effects of RBCs age (mean age, oldest age of transfused RBCs, any RBCs older than 14 days) on various in-hospital postoperative complications and long-term major adverse cardiovascular and cerebral events over a mean follow-up of 31 months were investigated. Correlations between RBCs age and duration of intubation, intensive care unit, or hospital stay, and base excess at the first postoperative morning were also analyzed. Results: After adjusting for confounders, there was no relationship between the RBCs age and in-hospital and long-term clinical outcomes except for postoperative wound complications. A significant linear trend was observed between the oldest age quartiles of transfused RBCs and the postoperative wound complications (quartile 1 vs. 2, 3 and 4: OR, 8.92, 12.01 and 13.79, respectively; P for trend = 0.009). The oldest transfused RBCs showed significant relationships with a first postoperative day negative base excess (P = 0.021), postoperative wound complications (P = 0.001), and length of hospital stay (P = 0.008). Conclusions: In patients undergoing off-pump coronary artery bypass, the oldest age of transfused RBCs were associated with a postoperative negative base excess, increased wound complications, and a longer hospital stay, but not with the other in-hospital or long-term outcomes.Peer Reviewe

Electrochemical determination of the surface composition of Pd-Pt core-shell nanoparticles

Different amounts of Pt atoms were deposited onto the surface of Pd nanoparticles supported on carbon black by hydroquinone reduction method in anhydrous ethanol. Here, we surveyed electrochemical probing of surface compositions of Pd-Pt surface alloys. They were calculated from hydrogen desorption, carbon monoxide adlayer oxidation, and reduced carbon dioxide oxidation charges. The surface composition of Pt drastically increased up to Pt[0.3]/Pd/C (23.1 at.% of Pt) and then approached that of pure Pt with the moderate rate of increase. (C) 2012 Elsevier B.V. All rights reserved.1561sciescopu

Facile synthesis of highly active and stable Pt–Ir/C electrocatalysts for oxygenreduction and liquid fueloxidation reaction

A facile room temperature synthesis technique has been developed for Pt–Ir/C electrocatalysts for applications to low-temperature fuel cells. The prepared PtxIry electrocatalyst was highly stable and active toward the oxygen reduction reaction (ORR), as well as liquid fuel oxidation reaction with high CO tolerance.11Nsciescopu

Densification behavior of freeze-casted alumina with grain boundary segregation of impurities

Coble&apos;s densification theory has been adopted to investigate the densification behavior of a freeze-casted Al2O3 sample. The successful adoption of bulk theory determined the dominant densification mechanisms of the porous structure. We noted a shift of the densification mechanism from grain boundary to lattice diffusion at 1500 degrees C. Interestingly, a very low activation energy value of 72.17 kJ/mol was measured for grain boundary diffusion while a general value of 455.83 kJ/mol for lattice diffusion. This outcome was accompanied by the presence of glassy phases at the grain boundary that would facilitate densification when grain boundary diffusion dominates the overall densification kinetics. Otherwise, the concentration of oxygen vacancies was high at the grain boundaries without the glassy phases. Both resulted from the segregation of intrinsic impurities, emphasizing the need for the proper selection of dopants to determine the grain boundary characteristics and hence potential densification strategies based on sintering science

Evaluation of Scalability and Degree of Fine-Tuning of Deep Convolutional Neural Networks for COVID-19 Screening on Chest X-ray Images Using Explainable Deep-Learning Algorithm

According to recent studies, patients with COVID-19 have different feature characteristics on chest X-ray (CXR) than those with other lung diseases. This study aimed at evaluating the layer depths and degree of fine-tuning on transfer learning with a deep convolutional neural network (CNN)-based COVID-19 screening in CXR to identify efficient transfer learning strategies. The CXR images used in this study were collected from publicly available repositories, and the collected images were classified into three classes: COVID-19, pneumonia, and normal. To evaluate the effect of layer depths of the same CNN architecture, CNNs called VGG-16 and VGG-19 were used as backbone networks. Then, each backbone network was trained with different degrees of fine-tuning and comparatively evaluated. The experimental results showed the highest AUC value to be 0.950 concerning COVID-19 classification in the experimental group of a fine-tuned with only 2/5 blocks of the VGG16 backbone network. In conclusion, in the classification of medical images with a limited number of data, a deeper layer depth may not guarantee better results. In addition, even if the same pre-trained CNN architecture is used, an appropriate degree of fine-tuning can help to build an efficient deep learning model