Yonsei University

About: Yonsei University is a education organization based out in Seoul, South Korea. It is known for research contribution in the topics: Population & Cancer. The organization has 50162 authors who have published 106172 publications receiving 2279044 citations. The organization is also known as: Yonsei.

Overcoming artifacts from metallic orthopedic implants at high-field-strength MR imaging and multi-detector CT.

Abstract: At magnetic resonance (MR) imaging and multidetector computed tomography (CT), artifacts arising from metallic orthopedic hardware are an obstacle to obtaining optimal images. Although various techniques for reducing such artifacts have been developed and corroborated by previous researchers, a new era of more powerful MR imaging and multidetector CT modalities has renewed the importance of a systematic consideration of methods for artifact reduction. Knowledge of the factors that contribute to artifacts, of related theories, and of artifact reduction techniques has become mandatory for radiologists. Factors that affect artifacts on MR images include the composition of the metallic hardware, the orientation of the hardware in relation to the direction of the main magnetic field, the strength of the magnetic field, the pulse sequence type, and other MR imaging parameters (mainly voxel size, which is determined by the field of view, image matrix, section thickness, and echo train length). At multidetector CT, the factors that affect artifacts include the composition of the hardware, orientation of the hardware, acquisition parameters (peak voltage, tube charge, collimation, and acquired section thickness), and reconstruction parameters (reconstructed section thickness, reconstruction algorithm used, and whether an extended CT scale was used). A comparison of images obtained with different hardware and different acquisition and reconstruction parameters facilitates an understanding of methods for reducing or overcoming artifacts related to metallic implants.

A new approach to fuzzy modeling

Abstract: This paper proposes a new approach to fuzzy modeling. The suggested fuzzy model can express a given unknown system with a few fuzzy rules as well as Takagi and Sugeno's model (1985), because it has the same structure as that of Takagi and Sugeno's model. It is also as easy to implement as Sugeno and Yasukawa's model (1993) because its identification mimics the simple identification procedure of Sugeno and Yasukawa's model. The suggested algorithm is composed of two steps: coarse tuning and fine tuning. In coarse tuning, fuzzy C-regression model (FCRM) clustering is used, which is a modified version of fuzzy C-means (FCM). In fine tuning, gradient descent algorithm is used to precisely adjust parameters of the fuzzy model instead of nonlinear optimization methods used in other models. Finally, some examples are given to demonstrate the validity of this algorithm.

New class of microRNA targets containing simultaneous 5′-UTR and 3′-UTR interaction sites

Abstract: MicroRNAs (miRNAs) are known to post-transcriptionally regulate target mRNAs through the 3'-UTR, which interacts mainly with the 5'-end of miRNA in animals. Here we identify many endogenous motifs within human 5'-UTRs specific to the 3'-ends of miRNAs. The 3'-end of conserved miRNAs in particular has significant interaction sites in the human-enriched, less conserved 5'-UTR miRNA motifs, while human-specific miRNAs have significant interaction sites only in the conserved 5'-UTR motifs, implying both miRNA and 5'-UTR are actively evolving in response to each other. Additionally, many miRNAs with their 3'-end interaction sites in the 5'-UTRs turn out to simultaneously contain 5'-end interaction sites in the 3'-UTRs. Based on these findings we demonstrate combinatory interactions between a single miRNA and both end regions of an mRNA using model systems. We further show that genes exhibiting large-scale protein changes due to miRNA overexpression or deletion contain both UTR interaction sites predicted. We provide the predicted targets of this new miRNA target class, miBridge, as an efficient way to screen potential targets, especially for nonconserved miRNAs, since the target search space is reduced by an order of magnitude compared with the 3'-UTR alone. Efficacy is confirmed by showing SEC24D regulation with hsa-miR-605, a miRNA identified only in primate, opening the door to the study of nonconserved miRNAs. Finally, miRNAs (and associated proteins) involved in this new targeting class may prevent 40S ribosome scanning through the 5'-UTR and keep it from reaching the start-codon, preventing 60S association.