Topology of Luminous Red Galaxies from the Sloan Digital Sky Survey

We present measurements of the genus topology of luminous red galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS) Data Release 7 catalog, with unprecedented statistical significance. To estimate the uncertainties in the measured genus, we construct 81 mock SDSS LRG surveys along the past light cone from the Horizon Run 3, one of the largest N-body simulations to date that evolved 7210^3 particles in a 10815 Mpc/h size box. After carefully modeling and removing all known systematic effects due to finite pixel size, survey boundary, radial and angular selection functions, shot noise and galaxy biasing, we find the observed genus amplitude to reach 272 at 22 Mpc/h smoothing scale with an uncertainty of 4.2%; the estimated error fully incorporates cosmic variance. This is the most accurate constraint of the genus amplitude to date, which significantly improves on our previous results. In particular, the shape of the genus curve agrees very well with the mean topology of the SDSS LRG mock surveys in the LCDM universe. However, comparison with simulations also shows small deviations of the observed genus curve from the theoretical expectation for Gaussian initial conditions. While these discrepancies are mainly driven by known systematic effects such as those of shot noise and redshift-space distortions, they do contain important cosmological information on the physical effects connected with galaxy formation, gravitational evolution and primordial non-Gaussianity. We address here the key role played by systematics on the genus curve, and show how to accurately correct for their effects to recover the topology of the underlying matter. In a forthcoming paper, we provide an interpretation of those deviations in the context of the local model of non-Gaussianity.Comment: 23 pages, 18 figures. APJ Supplement Series 201

Meaning of Wearing Faux Fur

The purpose of this study is to Understand meanings of consuming faux fur from the perspective of consumer culture theory

Anatomy of Scientific Evolution

The quest for historically impactful science and technology provides invaluable insight into the innovation dynamics of human society, yet many studies are limited to qualitative and small-scale approaches. Here, we investigate scientific evolution through systematic analysis of a massive corpus of digitized English texts between 1800 and 2008. Our analysis reveals great predictability for long-prevailing scientific concepts based on the levels of their prior usage. Interestingly, once a threshold of early adoption rates is passed even slightly, scientific concepts can exhibit sudden leaps in their eventual lifetimes. We developed a mechanistic model to account for such results, indicating that slowly-but-commonly adopted science and technology surprisingly tend to have higher innate strength than fast-and-commonly adopted ones. The model prediction for disciplines other than science was also well verified. Our approach sheds light on unbiased and quantitative analysis of scientific evolution in society, and may provide a useful basis for policy-making.Comment: Supplementary material attache

Phosphorylation of α-syntrophin is responsible for its subcellular localization and interaction with dystrophin in muscle cells

79-85Syntrophin is a well-known adaptor protein that links intracellular proteins with the dystrophin-glycoprotein complex (DGC) at the sarcolemma. However, little is known about the underlying mechanism that regulates the intracellular localization of α-syntrophin and its interaction with dystrophin. In this study, we demonstrate that α-syntrophin phosphorylation determines its intracellular localization and interaction with dystrophin in muscle cells. α-Syntrophin, a predominant isoform in skeletal muscles, directly interacts with ion channels, enzymes, receptors, and DGC proteins. Despite α-syntrophin being a potential signaling molecule, most studies focus on its function as a dystrophin-associated protein. However, we previously reported that α-syntrophin has a variety of DGC-independent functions to modulate cell migration, differentiation, survival, and protein stability. According to the results of the in vitro phosphorylation assays using subcellular fractions, the phosphorylated α-syntrophin accumulated only at the plasma membrane, and this event occurred regardless of dystrophin expression. However, the α-syntrophin interacting with dystrophin at the membrane was not in a phosphorylated state. We also identified that protein kinase C (PKC) was involved in the phosphorylation of α-syntrophin, which restricted α-syntrophin to interact with dystrophin. In conclusion, we demonstrate that the phosphorylation of α-syntrophin by PKC regulates its intracellular localization and interaction with dystrophin

Phosphorylation of α-syntrophin is responsible for its subcellular localization and interaction with dystrophin in muscle cells

Syntrophin is a well-known adaptor protein that links intracellular proteins with the dystrophin-glycoprotein complex (DGC) at the sarcolemma. However, little is known about the underlying mechanism that regulates the intracellular localization of α-syntrophin and its interaction with dystrophin. In this study, we demonstrate that α-syntrophin phosphorylation determines its intracellular localization and interaction with dystrophin in muscle cells. α-Syntrophin, a predominant isoform in skeletal muscles, directly interacts with ion channels, enzymes, receptors, and DGC proteins. Despite α-syntrophin being a potential signaling molecule, most studies focus on its function as a dystrophin-associated protein. However, we previously reported that α-syntrophin has a variety of DGC-independent functions to modulate cell migration, differentiation, survival, and protein stability. According to the results of the in vitro phosphorylation assays using subcellular fractions, the phosphorylated α-syntrophin accumulated only at the plasma membrane, and this event occurred regardless of dystrophin expression. However, the α-syntrophin interacting with dystrophin at the membrane was not in a phosphorylated state. We also identified that protein kinase C (PKC) was involved in the phosphorylation of α-syntrophin, which restricted α-syntrophin to interact with dystrophin. In conclusion, we demonstrate that the phosphorylation of α-syntrophin by PKC regulates its intracellular localization and interaction with dystrophin

비침습적 디지털 방식을 이용한 건강한 치주조직의 계측 및 평가

학위논문 (박사)-- 서울대학교 대학원 : 치의과학과, 2017. 2. 구영.Objectives. The aim of this study was to measure and determine the relationship between labial alveolar bone and gingival thicknesses using a non-invasive and relatively accurate digital registration method. In addition, the correlation of different morphometric parameters with the thickness of the labial gingiva and alveolar bone at different apico-coronal levels was evaluated. Methods. In 20 periodontally healthy subjects, cone-beam computed tomography (CB-CT) images and intraoral scanned files were obtained. Measurements of labial alveolar bone and gingival thickness at the central incisors, lateral incisors, and canines were performed at 0–5 mm points from the alveolar crest on the superimposed images. Clinical parameters including the crown width/crown length ratio (CW/CL), gingival width (GW), gingival scallop (SC), and transparency of the periodontal probe through the gingival sulcus (TRAN) were examined. Results. The mean labial alveolar bone thicknesses at the central incisors, lateral incisors, and canines were 0.86, 0.83, and 0.9 mm, respectively. Likewise, the mean gingival thicknesses at the central incisors, lateral incisors, and canines were 0.92, 0.83, and 0.81 mm, respectively. Significant differences in gingival thickness were observed at the alveolar crest level (G0) between the central incisors and the canines (p=0.001), and between the central incisors and the lateral incisors (p=0.001). At the G1 level (gingival thickness at 1 mm inferior to the alveolar crest), there was also a difference between the central incisors and the canines (p=0.002), and between the central incisors and the lateral incisors (p=0.004). Gingival thickness at the alveolar crest level was positively correlated with the thickness of the alveolar bone plate (p<0.05). The correlation analyses revealed no significant correlation between the clinical parameters and the hard and soft tissue thicknesses. Conclusions. Despite the morphologic variations of the periodontium, the gingival and labial alveolar bone thicknesses of the anterior maxillary teeth were found to be relatively thin (<1 mm) overall. An analysis of the mean thickness at each level showed that gingival thickness tended to increase and that alveolar bone thickness tended to decrease toward the root apex. With respect to the tooth types, a significant difference in gingival thickness at the alveolar crest level was observed. The gingival thickness at the alveolar crest level also revealed a positive correlation with labial alveolar bone thickness, although this correlation at identical depth levels was not significant. However, the measurement of gingival thickness at, or under the alveolar crest level, was not associated with the clinical parameters of the gingival features, such as the crown form and the gingival scallop, or the keratinized gingival width. Therefore, it is recommended that, in future studies, accurate measuring methods of the supracrestal gingival area should be developed, and the predictive potential of clinical parameters on tissue thickness should be verified.1. Introduction 1 2. Materials and Methods 4 3. Results 9 4. Discussion 12 5. Conclusions 19 6. References 20 Table and Figures 24 Abstract (in Korean) 35Docto