Publications by authors named "Taeyong Park"

18 Publications

  • Page 1 of 1

Preoperative nutritional risk index and postoperative one-year skeletal muscle loss can predict the prognosis of patients with gastric adenocarcinoma: a registry-based study.

BMC Cancer 2021 Feb 12;21(1):157. Epub 2021 Feb 12.

Department of Surgery, Gastric Cancer Center, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.

Background: Patients with gastric cancer have an increased nutritional risk and experience a significant skeletal muscle loss after surgery. We aimed to determine whether muscle loss during the first postoperative year and preoperative nutritional status are indicators for predicting prognosis.

Methods: From a gastric cancer registry, a total of 958 patients who received curative gastrectomy followed by chemotherapy for stage 2 and 3 gastric cancer and survived longer than 1 year were investigated. Clinical and laboratory data were collected. Skeletal muscle index (SMI) was assessed based on the muscle area at the L3 level on abdominal computed tomography.

Results: Preoperative nutritional risk index (NRI) and postoperative decrement of SMI (dSMI) were significantly associated with overall survival (hazards ratio: 0.976 [95% CI: 0.962-0.991] and 1.060 [95% CI: 1.035-1.085], respectively) in a multivariate Cox regression analysis. Recurrence, tumor stage, comorbidity index were also significant prognostic indicators. Kaplan-Meier analyses exhibited that patients with higher NRI had a significantly longer survival than those with lower NRI (5-year overall survival: 75.8% vs. 63.0%, P <  0.001). In addition, a significantly better prognosis was observed in a patient group with less decrease of SMI (5-year overall survival: 75.7% vs. 66.2%, P = 0.009). A logistic regression analysis demonstrated that the performance of preoperative NRI and dSMI in mortality prediction was quite significant (AUC: 0.63, P <  0.001) and the combination of clinical factors enhanced the predictive accuracy to the AUC of 0.90 (P <  0.001). This prognostic relevance of NRI and dSMI was maintained in patients experiencing tumor recurrence and highlighted in those with stage 3 gastric adenocarcinoma.

Conclusions: Preoperative NRI is a predictor of overall survival in stage 2 or 3 gastric cancer patients and skeletal muscle loss during the first postoperative year was significantly associated with the prognosis regardless of relapse in stage 3 tumors. These factors could be valuable adjuncts for accurate prediction of prognosis in gastric cancer patients.
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http://dx.doi.org/10.1186/s12885-021-07885-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881577PMC
February 2021

Reliability of Skeletal Muscle Area Measurement on CT with Different Parameters: A Phantom Study.

Korean J Radiol 2021 Jan 19. Epub 2021 Jan 19.

Health Screening & Promotion Center, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.

Objective: To evaluate the reliability of CT measurements of muscle quantity and quality using variable CT parameters.

Materials And Methods: A phantom, simulating the L2-4 vertebral levels, was used for this study. CT images were repeatedly acquired with modulation of tube voltage, tube current, slice thickness, and the image reconstruction algorithm. Reference standard muscle compartments were obtained from the reference maps of the phantom. Cross-sectional area based on the Hounsfield unit (HU) thresholds of muscle and its components, and the mean density of the reference standard muscle compartment, were used to measure the muscle quantity and quality using different CT protocols. Signal-to-noise ratios (SNRs) were calculated in the images acquired with different settings.

Results: The skeletal muscle area (threshold, -29 to 150 HU) was constant, regardless of the protocol, occupying at least 91.7% of the reference standard muscle compartment. Conversely, normal attenuation muscle area (30-150 HU) was not constant in the different protocols, varying between 59.7% and 81.7% of the reference standard muscle compartment. The mean density was lower than the target density stated by the manufacturer (45 HU) in all cases (range, 39.0-44.9 HU). The SNR decreased with low tube voltage, low tube current, and in sections with thin slices, whereas it increased when the iterative reconstruction algorithm was used.

Conclusion: Measurement of muscle quantity using HU threshold was reliable, regardless of the CT protocol used. Conversely, the measurement of muscle quality using the mean density and narrow HU thresholds were inconsistent and inaccurate across different CT protocols. Therefore, further studies are warranted in future to determine the optimal CT protocols for reliable measurements of muscle quality.
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http://dx.doi.org/10.3348/kjr.2020.0914DOI Listing
January 2021

Sclerostin inhibits Wnt signaling through tandem interaction with two LRP6 ectodomains.

Nat Commun 2020 10 23;11(1):5357. Epub 2020 Oct 23.

Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea.

Low-density lipoprotein receptor-related protein 6 (LRP6) is a coreceptor of the β-catenin-dependent Wnt signaling pathway. The LRP6 ectodomain binds Wnt proteins, as well as Wnt inhibitors such as sclerostin (SOST), which negatively regulates Wnt signaling in osteocytes. Although LRP6 ectodomain 1 (E1) is known to interact with SOST, several unresolved questions remain, such as the reason why SOST binds to LRP6 E1E2 with higher affinity than to the E1 domain alone. Here, we present the crystal structure of the LRP6 E1E2-SOST complex with two interaction sites in tandem. The unexpected additional binding site was identified between the C-terminus of SOST and the LRP6 E2 domain. This interaction was confirmed by in vitro binding and cell-based signaling assays. Its functional significance was further demonstrated in vivo using Xenopus laevis embryos. Our results provide insights into the inhibitory mechanism of SOST on Wnt signaling.
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http://dx.doi.org/10.1038/s41467-020-19155-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585440PMC
October 2020

Assessment of Myosteatosis on Computed Tomography by Automatic Generation of a Muscle Quality Map Using a Web-Based Toolkit: Feasibility Study.

JMIR Med Inform 2020 Oct 19;8(10):e23049. Epub 2020 Oct 19.

Biomedical Research Center, Asan Medical Center, Seoul, Republic of Korea.

Background: Muscle quality is associated with fatty degeneration or infiltration of the muscle, which may be associated with decreased muscle function and increased disability.

Objective: The aim of this study is to evaluate the feasibility of automated quantitative measurements of the skeletal muscle on computed tomography (CT) images to assess normal-attenuation muscle and myosteatosis.

Methods: We developed a web-based toolkit to generate a muscle quality map by categorizing muscle components. First, automatic segmentation of the total abdominal muscle area (TAMA), visceral fat area, and subcutaneous fat area was performed using a predeveloped deep learning model on a single axial CT image at the L3 vertebral level. Second, the Hounsfield unit of each pixel in the TAMA was measured and categorized into 3 components: normal-attenuation muscle area (NAMA), low-attenuation muscle area (LAMA), and inter/intramuscular adipose tissue (IMAT) area. The myosteatosis area was derived by adding the LAMA and IMAT area. We tested the feasibility of the toolkit using randomly selected healthy participants, comprising 6 different age groups (20 to 79 years). With stratification by sex, these indices were compared between age groups using 1-way analysis of variance (ANOVA). Correlations between the myosteatosis area or muscle densities and fat areas were analyzed using Pearson correlation coefficient r.

Results: A total of 240 healthy participants (135 men and 105 women) with 40 participants per age group were included in the study. In the 1-way ANOVA, the NAMA, LAMA, and IMAT were significantly different between the age groups in both male and female participants (P≤.004), whereas the TAMA showed a significant difference only in male participants (male, P<.001; female, P=.88). The myosteatosis area had a strong negative correlation with muscle densities (r=-0.833 to -0.894), a moderate positive correlation with visceral fat areas (r=0.607 to 0.669), and a weak positive correlation with the subcutaneous fat areas (r=0.305 to 0.441).

Conclusions: The automated web-based toolkit is feasible and enables quantitative CT assessment of myosteatosis, which can be a potential quantitative biomarker for evaluating structural and functional changes brought on by aging in the skeletal muscle.
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http://dx.doi.org/10.2196/23049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605976PMC
October 2020

Modeling Protein Homo-Oligomer Structures with GalaxyHomomer Web Server.

Methods Mol Biol 2020 ;2165:127-137

Department of Chemistry, Seoul National University, Seoul, Republic of Korea.

Cellular processes, such as metabolism, signal transduction, or immunity, often depend on the homo-oligomerization of proteins. Detailed structural knowledge of the homo-oligomer structure is therefore crucial for molecular-level understanding of protein functions and their regulation. In this chapter, we introduce the GalaxyHomomer server, which supports easy-to-use web interfaces for general users. It is freely accessible at http://galaxy.seoklab.org/homomer . GalaxyHomomer carries out template-based modeling, ab initio docking or both depending on the availability of proper oligomer templates. It also incorporates recently developed model refinement methods that can consistently improve model quality by performing symmetric loop modeling and overall structure refinement. Moreover, the server provides additional options that can be chosen by the user depending on the availability of information on the monomer structure, oligomeric state, and locations of unreliable/flexible loops or termini.
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http://dx.doi.org/10.1007/978-1-0716-0708-4_7DOI Listing
January 2020

Developing a Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein Model in a Viral Membrane.

J Phys Chem B 2020 08 6;124(33):7128-7137. Epub 2020 Jul 6.

Departments of Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States.

This technical study describes all-atom modeling and simulation of a fully glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB: 6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19) so that researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.
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http://dx.doi.org/10.1021/acs.jpcb.0c04553DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341691PMC
August 2020

Retrograde pyelography before radical nephroureterectomy for upper tract urothelial carcinoma is associated with intravesical tumor recurrence.

Int Braz J Urol 2020 Sep-Oct;46(5):778-785

Department of Urology, College of Medicine, Yeungnam University, Daegu, Republic of Korea.

Purpose: To investigate the association between preoperative retrograde pyelography (RGP), conducted to evaluate upper tract urothelial carcinoma (UTUC), and intravesical recurrence (IVR) after radical nephroureterectomy (RNU).

Materials And Methods: Of 114 patients that underwent RNU, 72 patients without preoperative ureteroscopy and a history of bladder tumor were selectively enrolled. Variables associated with IVR were identified.

Results: RGP was performed at a mean duration of 24.9 days prior to RNU in 41 (56.1%) of study subjects. During the mean follow-up period of 64.5 months, IVRs were identified in 32 (44.4%) patients at 22.3±18.8 (mean±SD) months after RNU. Despite similar tumor characteristics in the RGP and non-RGP groups, the incidence of IVR was considerably higher in the RGP group (63.4%) than in the non-RGP group (19.4%, p <0.001). The following variables differed significantly between the IVR and non-IVR groups: age (64.6±8.51 vs. 59.6±9.65 years), tumor location (lower or upper; 53.1% vs. 20%), tumor invasiveness (> pT2; 53.1% vs. 17.5%), preoperative hemoglobin (12.8±1.36 vs. 13.9±1.65), preoperative creatinine (1.29±0.32 vs. 1.11±0.22), and preoperative RGP (81.3% vs. 37.5%), respectively. Multivariate Cox regression model showed that tumor location (p=0.020, HR=2.742), preoperative creatinine level (p=0.004, HR=6.351), and preoperative RGP (p=0.045, HR=3.134) independently predicted IVR.

Conclusion: Given the limitations of retrospective single-center series, performance of RGP before RNU was shown to have a negative effect on IVR after surgery.
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http://dx.doi.org/10.1590/S1677-5538.IBJU.2019.0503DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822386PMC
December 2020

Modeling and Simulation of a Fully-glycosylated Full-length SARS-CoV-2 Spike Protein in a Viral Membrane.

bioRxiv 2020 May 21. Epub 2020 May 21.

Departments of Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, USA.

This technical study describes all-atom modeling and simulation of a fully-glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB:6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently-determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully-glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19), so researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.
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http://dx.doi.org/10.1101/2020.05.20.103325DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263518PMC
May 2020

Lifestyle Modification Leads to Spatially Variable Reduction in Hepatic Steatosis in Potential Living Liver Donors.

Liver Transpl 2020 04;26(4):487-497

Division of Liver Transplantation and Hepatobiliary Surgery, Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.

The spatial variability of hepatic fat reduction in potential living liver donors with hepatic steatosis (HS) who undergo lifestyle modification has not been investigated. Here, we aimed to examine the intrasegmental and intersegmental variability of changes in liver attenuation on computed tomography (CT) in potential living liver donors with HS after diet modification and exercise. A total of 87 living liver donor candidates (30.5 ± 7.0 years; 74 males) with biopsy-proven macrovesicular fat (MaF) ≥10% were included. All underwent diet modification and exercise to improve HS, baseline and follow-up unenhanced CT scans, and liver biopsies. Attenuation and its variability (mean and standard deviation, respectively, in Hounsfield units) in segmental, lobar, superficial, deep, and whole areas of the liver were measured across 32 different regions of interest on both baseline and follow-up CT. At baseline, the right lobe and superficial areas of liver showed significantly lower and more variable attenuation than left lobe and deep areas. Greater variability was noted in patients with more severe HS. Mean interval changes in liver attenuation and variability before and after diet modification and exercise were 13.7 (range, -10.6 to 46.2) and 4.7 (1.6-10.6), respectively. The mean interval change in liver attenuation was significantly higher in the right lobe than in the left (14.7 versus 12.7; P < 0.001), and in superficial areas than in deep areas (14.0 versus 13.4; P = 0.02). Greater variability and larger interval changes in liver attenuation were noted in those who responded (≥20% decrease in MaF) to diet modification and exercise than in those who did not. In conclusion, potential living liver donors with HS show significant intrasegmental and intersegmental variability in hepatic fat reduction on CT before and after diet modification and exercise.
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http://dx.doi.org/10.1002/lt.25733DOI Listing
April 2020

Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography.

Korean J Radiol 2020 01;21(1):88-100

Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.

Objective: We aimed to develop and validate a deep learning system for fully automated segmentation of abdominal muscle and fat areas on computed tomography (CT) images.

Materials And Methods: A fully convolutional network-based segmentation system was developed using a training dataset of 883 CT scans from 467 subjects. Axial CT images obtained at the inferior endplate level of the 3rd lumbar vertebra were used for the analysis. Manually drawn segmentation maps of the skeletal muscle, visceral fat, and subcutaneous fat were created to serve as ground truth data. The performance of the fully convolutional network-based segmentation system was evaluated using the Dice similarity coefficient and cross-sectional area error, for both a separate internal validation dataset (426 CT scans from 308 subjects) and an external validation dataset (171 CT scans from 171 subjects from two outside hospitals).

Results: The mean Dice similarity coefficients for muscle, subcutaneous fat, and visceral fat were high for both the internal (0.96, 0.97, and 0.97, respectively) and external (0.97, 0.97, and 0.97, respectively) validation datasets, while the mean cross-sectional area errors for muscle, subcutaneous fat, and visceral fat were low for both internal (2.1%, 3.8%, and 1.8%, respectively) and external (2.7%, 4.6%, and 2.3%, respectively) validation datasets.

Conclusion: The fully convolutional network-based segmentation system exhibited high performance and accuracy in the automatic segmentation of abdominal muscle and fat on CT images.
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http://dx.doi.org/10.3348/kjr.2019.0470DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960305PMC
January 2020

Structure prediction of biological assemblies using GALAXY in CAPRI rounds 38-45.

Proteins 2020 08 10;88(8):1009-1017. Epub 2019 Dec 10.

Department of Chemistry, Seoul National University, Seoul, Republic of Korea.

We participated in CARPI rounds 38-45 both as a server predictor and a human predictor. These CAPRI rounds provided excellent opportunities for testing prediction methods for three classes of protein interactions, that is, protein-protein, protein-peptide, and protein-oligosaccharide interactions. Both template-based methods (GalaxyTBM for monomer protein, GalaxyHomomer for homo-oligomer protein, GalaxyPepDock for protein-peptide complex) and ab initio docking methods (GalaxyTongDock and GalaxyPPDock for protein oligomer, GalaxyPepDock-ab-initio for protein-peptide complex, GalaxyDock2 and Galaxy7TM for protein-oligosaccharide complex) have been tested. Template-based methods depend heavily on the availability of proper templates and template-target similarity, and template-target difference is responsible for inaccuracy of template-based models. Inaccurate template-based models could be improved by our structure refinement and loop modeling methods based on physics-based energy optimization (GalaxyRefineComplex and GalaxyLoop) for several CAPRI targets. Current ab initio docking methods require accurate protein structures as input. Small conformational changes from input structure could be accounted for by our docking methods, producing one of the best models for several CAPRI targets. However, predicting large conformational changes involving protein backbone is still challenging, and full exploration of physics-based methods for such problems is still to come.
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http://dx.doi.org/10.1002/prot.25859DOI Listing
August 2020

Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment.

Authors:
Marc F Lensink Guillaume Brysbaert Nurul Nadzirin Sameer Velankar Raphaël A G Chaleil Tereza Gerguri Paul A Bates Elodie Laine Alessandra Carbone Sergei Grudinin Ren Kong Ran-Ran Liu Xi-Ming Xu Hang Shi Shan Chang Miriam Eisenstein Agnieszka Karczynska Cezary Czaplewski Emilia Lubecka Agnieszka Lipska Paweł Krupa Magdalena Mozolewska Łukasz Golon Sergey Samsonov Adam Liwo Silvia Crivelli Guillaume Pagès Mikhail Karasikov Maria Kadukova Yumeng Yan Sheng-You Huang Mireia Rosell Luis A Rodríguez-Lumbreras Miguel Romero-Durana Lucía Díaz-Bueno Juan Fernandez-Recio Charles Christoffer Genki Terashi Woong-Hee Shin Tunde Aderinwale Sai Raghavendra Maddhuri Venkata Subraman Daisuke Kihara Dima Kozakov Sandor Vajda Kathryn Porter Dzmitry Padhorny Israel Desta Dmitri Beglov Mikhail Ignatov Sergey Kotelnikov Iain H Moal David W Ritchie Isaure Chauvot de Beauchêne Bernard Maigret Marie-Dominique Devignes Maria E Ruiz Echartea Didier Barradas-Bautista Zhen Cao Luigi Cavallo Romina Oliva Yue Cao Yang Shen Minkyung Baek Taeyong Park Hyeonuk Woo Chaok Seok Merav Braitbard Lirane Bitton Dina Scheidman-Duhovny Justas Dapkūnas Kliment Olechnovič Česlovas Venclovas Petras J Kundrotas Saveliy Belkin Devlina Chakravarty Varsha D Badal Ilya A Vakser Thom Vreven Sweta Vangaveti Tyler Borrman Zhiping Weng Johnathan D Guest Ragul Gowthaman Brian G Pierce Xianjin Xu Rui Duan Liming Qiu Jie Hou Benjamin Ryan Merideth Zhiwei Ma Jianlin Cheng Xiaoqin Zou Panagiotis I Koukos Jorge Roel-Touris Francesco Ambrosetti Cunliang Geng Jörg Schaarschmidt Mikael E Trellet Adrien S J Melquiond Li Xue Brian Jiménez-García Charlotte W van Noort Rodrigo V Honorato Alexandre M J J Bonvin Shoshana J Wodak

Proteins 2019 12 25;87(12):1200-1221. Epub 2019 Oct 25.

VIB Structural Biology Research Center, VUB, Brussels, Belgium.

We present the results for CAPRI Round 46, the third joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo-oligomers and 6 heterocomplexes. Eight of the homo-oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher-order assemblies. These were more difficult to model, as their prediction mainly involved "ab-initio" docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance "gap" was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template-based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.
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http://dx.doi.org/10.1002/prot.25838DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274794PMC
December 2019

Rapid and Accurate Registration Method between Intraoperative 2D XA and Preoperative 3D CTA Images for Guidance of Percutaneous Coronary Intervention.

Comput Math Methods Med 2019 22;2019:3253605. Epub 2019 Aug 22.

Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Republic of Korea.

In this paper, we propose a rapid rigid registration method for the fusion visualization of intraoperative 2D X-ray angiogram (XA) and preoperative 3D computed tomography angiography (CTA) images. First, we perform the cardiac cycle alignment of a patient's 2D XA and 3D CTA images obtained from a different apparatus. Subsequently, we perform the initial registration through alignment of the registration space and optimal boundary box. Finally, the two images are registered where the distance between two vascular structures is minimized by using the local distance map, selective distance measure, and optimization of transformation function. To improve the accuracy and robustness of the registration process, the normalized importance value based on the anatomical information of the coronary arteries is utilized. The experimental results showed fast, robust, and accurate registration using 10 cases, each of the left coronary artery (LCA) and right coronary artery (RCA). Our method can be used as a computer-aided technology for percutaneous coronary intervention (PCI). Our method can be applied to the study of other types of vessels.
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http://dx.doi.org/10.1155/2019/3253605DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724445PMC
April 2020

Prediction of protein oligomer structures using GALAXY in CASP13.

Proteins 2019 12 9;87(12):1233-1240. Epub 2019 Oct 9.

Department of Chemistry, Seoul National University, Seoul, Republic of Korea.

Many proteins need to form oligomers to be functional, so oligomer structures provide important clues to biological roles of proteins. Prediction of oligomer structures therefore can be a useful tool in the absence of experimentally resolved structures. In this article, we describe the server and human methods that we used to predict oligomer structures in the CASP13 experiment. Performances of the methods on the 42 CASP13 oligomer targets consisting of 30 homo-oligomers and 12 hetero-oligomers are discussed. Our server method, Seok-assembly, generated models with interface contact similarity measure greater than 0.2 as model 1 for 11 homo-oligomer targets when proper templates existed in the database. Model refinement methods such as loop modeling and molecular dynamics (MD)-based overall refinement failed to improve model qualities when target proteins have domains not covered by templates or when chains have very small interfaces. In human predictions, additional experimental data such as low-resolution electron microscopy (EM) map were utilized. EM data could assist oligomer structure prediction by providing a global shape of the complex structure.
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http://dx.doi.org/10.1002/prot.25814DOI Listing
December 2019

GalaxyTongDock: Symmetric and asymmetric ab initio protein-protein docking web server with improved energy parameters.

J Comput Chem 2019 10 7;40(27):2413-2417. Epub 2019 Jun 7.

Department of Chemistry, Seoul National University, Seoul 08826, Republic of Korea.

Protein-protein docking methods are spotlighted for their roles in providing insights into protein-protein interactions in the absence of full structural information by experiment. GalaxyTongDock is an ab initio protein-protein docking web server that performs rigid-body docking just like ZDOCK but with improved energy parameters. The energy parameters were trained by iterative docking and parameter search so that more native-like structures are selected as top rankers. GalaxyTongDock performs asymmetric docking of two different proteins (GalaxyTongDock_A) and symmetric docking of homo-oligomeric proteins with C and D symmetries (GalaxyTongDock_C and GalaxyTongDock_D). Performance tests on an unbound docking benchmark set for asymmetric docking and a model docking benchmark set for symmetric docking showed that GalaxyTongDock is better or comparable to other state-of-the-art methods. Experimental and/or evolutionary information on binding interfaces can be easily incorporated by using block and interface options. GalaxyTongDock web server is freely available at http://galaxy.seoklab.org/tongdock. © 2019 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/jcc.25874DOI Listing
October 2019

Portal Vein Flow by Doppler Ultrasonography and Liver Volume by Computed Tomography in Living Donor Candidates: Correlation with Indocyanine Green Test.

Exp Clin Transplant 2019 10 14;17(5):627-631. Epub 2019 Mar 14.

From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea; and the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.

Objectives: Our goal was to investigate the correlation between indocyanine green test results and imaging parameters in living liver donor candidates.

Materials And Methods: Our study included 219 healthy donor candidates who were evaluated with Doppler ultrasonography (portal vein time average flow), computed tomography (liver volume), liver biopsy (fat fraction), and indocyanine green retention rate at 15 minutes.

Results: Portal vein time average flow (r= -0.375), fat-free liver volume/body weight ratio (r = -0.239), and portal vein time average flow × fat-free liver volume/body weight ratio (r = -0.424) showed significant correlations with indocyanine green retention rate at 15 minutes (all P < .001).

Conclusions: Imaging parameters were significantly correlated with indocyanine green retention rate at 15 minutes in living liver donor candidates.
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http://dx.doi.org/10.6002/ect.2018.0223DOI Listing
October 2019

GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure.

Nucleic Acids Res 2017 07;45(W1):W320-W324

Department of Chemistry, Seoul National University, Seoul 151-747, Korea.

Homo-oligomerization of proteins is abundant in nature, and is often intimately related with the physiological functions of proteins, such as in metabolism, signal transduction or immunity. Information on the homo-oligomer structure is therefore important to obtain a molecular-level understanding of protein functions and their regulation. Currently available web servers predict protein homo-oligomer structures either by template-based modeling using homo-oligomer templates selected from the protein structure database or by ab initio docking of monomer structures resolved by experiment or predicted by computation. The GalaxyHomomer server, freely accessible at http://galaxy.seoklab.org/homomer, carries out template-based modeling, ab initio docking or both depending on the availability of proper oligomer templates. It also incorporates recently developed model refinement methods that can consistently improve model quality. Moreover, the server provides additional options that can be chosen by the user depending on the availability of information on the monomer structure, oligomeric state and locations of unreliable/flexible loops or termini. The performance of the server was better than or comparable to that of other available methods when tested on benchmark sets and in a recent CASP performed in a blind fashion.
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http://dx.doi.org/10.1093/nar/gkx246DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570155PMC
July 2017

The effects of radio frequency plasma power on Ai2O3 films deposited at room-temperature by remote plasma atomic layer deposition.

J Nanosci Nanotechnol 2012 Jul;12(7):5494-9

Department of Nano-Scale Semiconductor Engineering, Hanyang University, Seoul 133-791, Korea.

Al2O3 films were deposited by a remote plasma atomic layer deposition (RPALD) method at room temperature (25 degrees C) in a reactor using alternating exposures of Al(CH3)3 and O2 plasma. Oxygen plasma was used as a reactant gas to decompose the trimethylaluminum [TMA, Al(CH3)3] precursor at room temperature. The RF plasma power was increased to produce enough radicals for the deposition of the Al2O3 films at room temperature. Then, changes in the interfacial and bulk properties of the deposited Al2O3 films were investigated according to increasing RF power. Al2O3 films deposited by RPALD with RF powers over 100 W showed similar bulk properties, indicating that radicals over a certain threshold did not have a decisive effect on the additional decomposition of precursors for a low impurity content in the films. An increase in RF plasma power could improve the interfacial stability due to an increase in radicals and ions in the plasma and the minimization of plasma-induced substrate damage by adopting remote plasma.
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http://dx.doi.org/10.1166/jnn.2012.6265DOI Listing
July 2012