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Krieger, Elmar,Joo, Keehyoung,Lee, Jinwoo,Lee, Jooyoung,Raman, Srivatsan,Thompson, James,Tyka, Mike,Baker, David,Karplus, Kevin Wiley Subscription Services, Inc., A Wiley Company 2009 Proteins Vol.77 No.suppl9
<P>A correct alignment is an essential requirement in homology modeling. Yet in order to bridge the structural gap between template and target, which may not only involve loop rearrangements, but also shifts of secondary structure elements and repacking of core residues, high-resolution refinement methods with full atomic details are needed. Here, we describe four approaches that address this 'last mile of the protein folding problem' and have performed well during CASP8, yielding physically realistic models: YASARA, which runs molecular dynamics simulations of models in explicit solvent, using a new partly knowledge-based all atom force field derived from Amber, whose parameters have been optimized to minimize the damage done to protein crystal structures. The LEE-SERVER, which makes extensive use of conformational space annealing to create alignments, to help Modeller build physically realistic models while satisfying input restraints from templates and CHARMM stereochemistry, and to remodel the side-chains. ROSETTA, whose high resolution refinement protocol combines a physically realistic all atom force field with Monte Carlo minimization to allow the large conformational space to be sampled quickly. And finally UNDERTAKER, which creates a pool of candidate models from various templates and then optimizes them with an adaptive genetic algorithm, using a primarily empirical cost function that does not include bond angle, bond length, or other physics-like terms.</P>
Amelioration of sepsis by TIE2 activation–induced vascular protection
Han, Sangyeul,Lee, Seung-Jun,Kim, Kyung Eun,Lee, Hyo Seon,Oh, Nuri,Park, Inwon,Ko, Eun,Oh, Seung Ja,Lee, Yoon-Sook,Kim, David,Lee, Seungjoo,Lee, Dae Hyun,Lee, Kwang-Hoon,Chae, Su Young,Lee, Jung-Hoon American Association for the Advancement of Scienc 2016 Science translational medicine Vol.8 No.335
<P>Protection of endothelial integrity has been recognized as a frontline approach to alleviating sepsis progression, yet no effective agent for preserving endothelial integrity is available. Using an unusual anti-angiopoietin 2 (ANG2) antibody, ABTAA (ANG2-binding and TIE2-activating antibody), we show that activation of the endothelial receptor TIE2 protects the vasculature from septic damage and provides survival benefit in three sepsis mouse models. Upon binding to ANG2, ABTAA triggers clustering of ANG2, assembling an ABTAA/ANG2 complex that can subsequently bind and activate TIE2. Compared with a conventional ANG2-blocking antibody, ABTAA was highly effective in augmenting survival from sepsis by strengthening the endothelial glycocalyx, reducing cytokine storms, vascular leakage, and rarefaction, and mitigating organ damage. Together, our data advance the role of TIE2 activation in ameliorating sepsis progression and open a potential therapeutic avenue for sepsis to address the lack of sepsisspecific treatment.</P>
David Hong,Sung Eun Kim,Seung Hun Lee,Seung-Jae Lee,Jong-Young Lee,Sang Min Kim,Sang Yeub Lee,Woochan Kwon,Ki Hong Choi,Taek Kyu Park,Jeong Hoon Yang,Young Bin Song,Seung-Hyuk Choi,Hyeon-Cheol Gwon,Jo 대한내과학회 2024 The Korean Journal of Internal Medicine Vol.39 No.5
Although percutaneous coronary intervention (PCI) for chronic total occlusion (CTO) has been increasing in recent years, CTO PCI is still one of the most challenging procedures with relatively higher rates of procedural complications and adverse clinical events after PCI. Due to the innate limitations of invasive coronary angiography, intravascular imaging (IVI) has been used as an adjunctive tool to complement PCI, especially in complex coronary artery disease. Considering the complexity of CTO lesions, the role of IVI is particularly important in CTO intervention. IVI has been a useful adjunctive tool in every step of CTO PCI including assisted wire crossing, confirmation of wire location within CTO segment, and stent optimization. The meticulous use of IVI has been one of the greatest contributors to recent progress of CTO PCI. Nevertheless, studies evaluating the role of IVI during CTO PCI are limited. The current review provides a comprehensive overview of the mechanistic advantages of IVI in CTO PCI, summarizes previous studies and trials, and presents future perspective of IVI in CTO PCI.
이다빛(David Lee),김재호(Jae-Ho Kim),정우혁(Woo-Hyuk Jung),이희재(Hee-Jae Lee),이상국(Sang-Goog Lee) 한국HCI학회 2014 한국HCI학회 학술대회 Vol.2014 No.2
Brain-Computer interfaces(BCIs)에서 Electroencephalogram(EEG)의 특징을 추출하는 것은 중요하다. 일반적으로 EEG의 특징 추출 방법으로는 Fast Fourier transform(FFT)과 Wavelet transform(WT)이 많이 사용되었다. 하지만 이러한 방법들은 신호가 linear하고 stationary 하다는 가정 하에 적용되었기 때문에 신호 분해시 신호의 왜곡이 생길 수 있다. 이에 본 논문은 움직임 상상 EEG 분류를 위해 Empirical Mode Decomposition(EMD)과 FFT를 이용하는 특징을 제안했다. 먼저 움직임 상상 EEG에 EMD를 적용하여 Implicit Mode Functions(IMF)를 추출 뒤, 추출된 IMFs에 FFT를 적용하여 해당 IMF의 주파수 성분을 확인하였다. 주파수 성분이 μ 대역을 포함하고 있는 IMF의 표준편차를 특징으로 사용하였다. 추출된 특징을 Support Vector Machine(SVM)의 입력으로 사용하였고 샘플의 검증을 위해 10-fold cross validation을 이용하였다. 제안하는 방법은 움직임 상상 EEG에 대해 84.50%의 분류 정확도를 보여주었다. Feature extraction of Electroencephalogram (EEG) is an important issue in brain-computer interfaces(BCIs). The most commonly used methods for feature extraction from EEGs is Fast Fourier transform(FFT) and Wavelet transform(WT). However, when signal decomposition is carried out , these methods can happens distortion of the signal because it assumes that the signal is linear and stationary. In this paper, we proposed to use Empirical Mode Decomposition(EMD) and FFT to feature for classification of movement imagery EEGs. The EMD was applied to generate Implicit Mode Functions(IMFs) from the movement imagery EEGs. The FFT was then used to identify frequency component of each IMF at generated IMFs. The standard deviation of IMF included mu rhythm was used as feature. In the classification process, we used the extracted feature as input of Support Vector Machine(SVM) and 10-fold cross-validation to verification of sample. Under the proposed method, the classification accuracy of movement imagery EEGs was found to be 84.50%.