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Role of NADPH oxidase and its therapeutic intervention in TGF-β-mediated EMT progression: an in vitro analysis on HeLa cervical cancer cells

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Applied Biological Chemistry 2020年第1期63卷 1-8页

作者： Muthuramalingam, Karthika Cho, Moonjae Kim, Youngmee Department of Biochemistry School of Medicine Jeju National University Jeju Republic of Korea Institute of Medical Science Jeju National University Jeju Republic of Korea Interdisciplinary Graduate Program in Advanced Convergence Technology & Science Jeju National University Jeju Republic of Korea

Epithelial to mesenchymal transition (EMT) is a complex biological event, wherein polarized epithelial cells lose their integrity resulting in a mesenchymal phenotype with enhanced motility, a phenomenon known as metastasis. However, the underlying mechanisms of EMT are still poorly understood in cervical carcinomas. In this study, we investigated the molecular signalling events responsible for the effect of TGF-β, a potent inducer of EMT, on HeLa cervical cancer cells. We observed that TGF-β treatment (5 ng/mL) upregulates the expression of EMT-associated transcription factors such as Snail and Slug and downregulates the expression of epithelial markers such as ZO-1 and E-cadherin. Furthermore, treatment with TGF-β activates both Smad-dependent and Smad-independent signaling pathways, which subsides upon addition of Diphenyleneiodonium (DPI), a potent ROS inhibitor that inhibits NADPH oxidase (NOX). TGF-β treatment enhanced cellular migration and invasion ability was diminished in the presence of ROS inhibitors. In addition, we also observed that ROS-mediated, TGF-β-induced EMT progression was inhibited using therapeutic candidates that target the key signal transduction mediators, including PI3K/AKT, ERK, and P38/MAPK. Accordingly, we demonstrated the involvement of redox biology (NOX2 and NOX4 mediate migration and invasion) in TGF-β-mediated EMT advancement and explored suitable therapeutic interventions.

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PixelSteganalysis: Pixel-wise Hidden Information Removal with Low Visual Degradation

arXiv

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arXiv 2019年

作者： Jung, Dahuin Bae, Ho Choi, Hyun-Soo Yoon, Sungroh The Dept. of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Dept. of Cyber Security Ewha Womans University Seoul03760 Korea Republic of Dept. of Computer Science & Engineering Interdisciplinary Graduate Program in Medical Bigdata Convergence Kangwon National University Chuncheon 24341 Korea Republic of Ziovision Chuncheon24341 Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul08826 Korea Republic of

Recently, the field of steganography has experienced rapid developments based on deep learning (DL). DL based steganography distributes secret information over all the available bits of the cover image, thereby posing difficulties in using conventional steganalysis methods to detect, extract or remove hidden secret images. However, our proposed framework is the first to effectively disable covert communications and transactions that use DL based steganography. We propose a DL based steganalysis technique that effectively removes secret images by restoring the distribution of the original images. We formulate a problem and address it by exploiting sophisticated pixel distributions and an edge distribution of images by using a deep neural network. Based on the given information, we remove the hidden secret information at the pixel level. We evaluate our technique by comparing it with conventional steganalysis methods using three public benchmarks. As the decoding method of DL based steganography is approximate (lossy) and is different from the decoding method of conventional steganography, we also introduce a new quantitative metric called the destruction rate (DT). The experimental results demonstrate performance improvements of 10-20% in both the decoded rate and the DT. Copyright © 2019, The Authors. All rights reserved.

关键词： Steganography

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Application of CT simulation technique for virtual ultra-low-dose trial in CT colonography

Application of CT simulation technique for virtual ultra-low...

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4th International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with the 15th International Conference on medical Image Computing and Computer-Assisted Intervention, MICCAI 2012

作者： Kim, Chang Won Kim, Jong Hyo Interdisciplinary Program of Bioengineering Seoul National University College of Engineering San 56-1 Sillim-dong Gwanak-gu Seoul 151-742 Korea Republic of Department of Radiology Seoul National University College of Medicine Seoul 110-744 Korea Republic of Interdisciplinary Program in Radiation Applied Life Science Seoul National University College of Medicine Seoul 110-744 Korea Republic of Institute of Radiation Medicine Seoul National University Medical Research Center 101 Daehangno Jongno-gu Seoul 110-744 Korea Republic of Department of Intelligent Convergence Systems Graduate School of Convergence Science and Technology Seoul National University 864-1 Iui-dong Yeongtong-gu Suwon-si Gyeonggi-do 443-270 Korea Republic of

ISBN: (纸本)9783642336119

A low-dose CT simulation technique is presented which might allow for a virtual ultra-low-dose trial in CT colonography without requiring raw sinogram data. A virtual sinogram is generated by performing the line integral of the CT number-based attenuation value with use of the CT scan parameters available in the DICOM header and in the literature. A separate noise sinogram is generated with use of a noise model, which incorporates the X-ray photon flux depending on the mAs, system electronic noise, and virtual sinogram. A synthetic noise CT image is generated by application of the filtered back projection of the noise sinogram with use of an appropriate filter that depends on the reconstruction kernel of the original CT. Finally, a simulated low-dose CT image is generated by addition of the CT data for the synthetic noise to the original CT data. Clinical CT colonography images with and without fecal tagging were used as simulation input and 50%, 25%, and 12.5% dose images were generated and evaluated. Our results suggest that the proposed CT simulation technique has potential for application in virtual ultra-low-dose trial in CT colonography in which an unlimited number of scan protocols could be performed without repetition of the real CT exposure to the patients. © 2012 Springer-Verlag.

关键词： Computerized tomography

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Real-Time Detection of Cattle Behavior Using YOLOv9 with AutoAugment and Mixup Data Augmentation Techniques

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Transactions of the Korean Institute of Electrical Engineers 2024年第12期73卷 2326-2332页

作者： Lee, Su-Bin Park, Jae-Beom Cho, Hyun-Chong Dept. of Electronics Engineering Dept. of Data Science Kangwon National University Korea Republic of Dept. of Data Science Kangwon National University Korea Republic of Dept. of Interdisciplinary Graduate Program for BIT Medical Convergence Kangwon National University Korea Republic of

As the number of livestock farms in Korea decreases, the scale of individual farms has grown, necessitating advanced methods for efficient livestock management. Recent studies have increasingly applied computer vision and deep learning to monitor livestock behavior, health, and disease, aiming to enhance productivity and animal welfare. This study introduces a real-time cattle behavior detection system utilizing YOLOv9, a state-of-the-art object detection algorithm known for its high accuracy and efficiency. The YOLOv9-s model, optimized for real-time detection with minimal computational overhead, was employed. To further enhance detection accuracy, we incorporated AutoAugment, a data augmentation technique that automatically selects the optimal augmentation policies, and mixup, a method that improves model generalization by creating new training samples through linear interpolation of existing ones. The application of AutoAugment improved the mean Average Precision (mAP) from 0.926 to 0.941, while the addition of mixup raised the mAP to 0.947, representing a 2.1% performance increase. These results confirm the system's capability for accurate and efficient real-time detection of cattle behavior. Copyright © The Korean Institute of Electrical Engineers.

关键词： Livestock

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Silicone breast implant modification review: Overcoming capsular contracture

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Biomaterials Research 2018年第1期22卷 1-9页

作者： Shin, Byung Ho Kim, Byung Hwi Kim, Sujin Lee, Kangwon Choy, Young Bin Heo, Chan Yeong Seoul National University College of Medicine Department of Biomedical Engineering Seoul 03080 South Korea Seoul National University Department of Transdisciplinary Studies Graduate School of Convergence Science and Technology Seoul 08826 South Korea Seoul National University Interdisciplinary Program for Bioengineering College of Engineering Seoul 08826 South Korea Seoul National University Department of Plastic and Reconstructive Surgery College of Medicine Seoul 03080 South Korea Seoul National University Bundang Hospital Department of Plastic and Reconstructive Surgery Seongnam 13620 South Korea Seoul National University Institute of Medical and Biological Engineering Medical Research Center Seoul 03080 South Korea Advanced Institutes of Convergence Technology Suwon Gyeonggi-do 16229 South Korea

Background: Silicone implants are biomaterials that are frequently used in the medical industry due to their physiological inertness and low toxicity. However, capsular contracture remains a concern in long-term transplantation. To date, several studies have been conducted to overcome this problem. This review summarizes and explores these trends. Main body: First, we examined the overall foreign body response from initial inflammation to fibrosis capsule formation in detail and introduced various studies to overcome capsular contracture. Secondly, we introduced that the main research approaches are to inhibit fibrosis with anti-inflammatory drugs or antibiotics, to control the topography of the surface of silicone implants, and to administer plasma treatment. Each study examined aspects of the various mechanisms by which capsular contracture could occur, and addressed the effects of inhibiting fibrosis. Conclusion: This review introduces various silicone surface modification methods to date and examines their limitations. This review will help identify new directions in inhibiting the fibrosis of silicone implants. © 2018 The Author(s).

关键词： Capsular contracture Fibrosis Foreign body reaction Inflammation Modification Silicone implant

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SU-C-BRB-06: Utilizing 3D Scanner and Printer for Dummy Eye-Shield: Artifact-Free CT Images of Tungsten Eye-Shield for Accurate Dose Calculation

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medical Physics 2015年第6PART2期42卷 3194-3195页

作者： J Park J Lee H Kim I Kim S Ye Program in Biomedical Radiation Sciences Department of Transdisciplinary Studies Graduate School of Convergence Science and Technology Seoul National University Seoul Korea Institute of Radiation Medicine Seoul National University Medical Research Center Seoul Korea Department of Radiation Oncology Seoul National University Hospital Seoul Korea Interdisciplinary Program in Radiation Applied Life Science Seoul National University College of Medicine Seoul Korea Advanced Institutes of Convergence Technology Seoul National University Suwon Korea

Purpose: To evaluate the effect of a tungsten eye-shield on the dose distribution of a patient. Methods: A 3D scanner was used to extract the dimension and shape of a tungsten eye-shield in the STL format. Scanned data was transferred into a 3D printer. A dummy eye shield was then produced using bio-resin (3D systems, VisiJet M3 Proplast). For a patient with mucinous carcinoma, the planning CT was obtained with the dummy eye-shield placed on the patient's right eye. Field shaping of 6 MeV was performed using a patient-specific cerrobend block on the 15 × 15 cm 2 applicator. The gantry angle was 330° to cover the planning target volume near by the lens. EGS4/BEAMnrc was commissioned from our measurement data from a Varian 21EX. For the CT-based dose calculation using EGS4/DOSXYZnrc, the CT images were converted to a phantom file through the ctcreate program. The phantom file had the same resolution as the planning CT images. By assigning the CT numbers of the dummy eye-shield region to 17000, the real dose distributions below the tungsten eye-shield were calculated in EGS4/DOSXYZnrc. In the TPS, the CT number of the dummy eye-shield region was assigned to the maximum allowable CT number (3000). Results: As compared to the maximum dose, the MC dose on the right lens or below the eye shield area was less than 2%, while the corresponding RTP calculated dose was an unrealistic value of approximately 50%. Conclusion: Utilizing a 3D scanner and a 3D printer, a dummy eye-shield for electron treatment can be easily produced. The artifact-free CT images were successfully incorporated into the CT-based Monte Carlo simulations. The developed method was useful in predicting the realistic dose distributions around the lens blocked with the tungsten shield.

关键词： Computed tomography Tungsten 3D printing Image scanners Three dimensional image processing Monte Carlo methods medical image artifacts Cancer Field shaping

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Machine learning based gastric cancer computer-aided diagnosis system using feature selection

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Transactions of the Korean Institute of Electrical Engineers 2020年第1期69卷 170-176页

作者： Kim, Yun-Ji Lee, Sin-Ae Kim, Dong-Hyun Chae, Jung-Woo Ham, Hyun-Sik Cho, Hyun Chin Cho, Hyun-Chong Dept. of Electronics Engineering Interdisciplinary Graduate Program for BIT Medical Convergence Kangwon National University Korea Republic of Dept. of Electronics Engineering Kangwon National University Korea Republic of Dept. of Internal Medicine Institute of Health Sciences Gyeongsang National University School of Medicine and Gyeongsang Korea Republic of

Gastric cancer is a kind of cancer that is difficult to detect at an early stage because it has almost no symptoms at the beginning. In this study, we propose a Computer-aided Diagnosis(CADx) system that detects gastric cancer from the endoscopy. The data set we used consist of 93 normal images and 93 gastric images. We extracted 6 features in 449 dimensions from the gastric endoscopy images and reduced them to 10 dimensions through feature selection algorithms. Algorithms that we use to dimension reduction are Pearson Correlation, Chi-Squared Test, Recursive Feature Elimination, and Model-based Feature Selection, which are provided by the Sci-kit Learn library. A method was also used to select the top 10 features with a higher number of times selected by these four algorithms. Normal images and gastric cancer images were classified using support vector machine(SVM). Recursive feature elimination algorithm has the highest performance among the five feature selection algorithms, with an accuracy of 0.92. © 2020 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Support vector machines

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3D Super Resolution for Non-Isotropic medical Image Through Multi-Input 3D ResUnet

3D Super Resolution for Non-Isotropic Medical Image Through ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Youjin Seo ByeongChang Jeong Yeji Yoon Daegyeom Kim JuHong Min Cheol E. Han Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong Sejong Republic of Korea Dept. of Electronics and Information Engineering Korea University Sejong Sejong Republic of Korea Dept. of Neurology Samsung Medical Center Sungkyunkwan University Seoul Republic of Korea

Fluid-attenuated inversion recovery imaging (FLAIR) is a magnetic resonance (MR) method that is frequently utilized to diagnose brain lesions. However, it usually provides transverse section imaging in high resolution but with very low resolution in the other axis. This non-isotropy huddles its wide utilization in research including machine learning. In this study, we applied a deep-learning based super resolution (SR) technique to convert non-isotropic FLAIR images into isotropic one. We proposed a multi-input 3D ResUnet that uses both FLAIR and T1-weighted MR images as its inputs. As a result, our proposed model successfully reconstructed isotropic FLAIR images (SSIM: 0.9947 $\pm 0.0009)$ , and out-performed the FLAIR only single-input 3D ResUnet.

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Corrigendum to "Long-term outcome and predictors of vagus nerve stimulation for drug-resistant epilepsy: Real-world evidence from the Korean National Hospital Consortium" [Epilepsy Res. 210 (2025) 107511 0920-1211]

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Epilepsy research 2025年 211卷 107522页

作者： Seo-Young Lee Hyesung Lee Jae-Wook Cho Kyung Wook Kang Jong-Geun Seo Jon Soo Kim Joon-Won Kang Daeyoung Kim Young-Soo Kim Sun Ah Choi Jeonghoon Park Ji Hoon Phi Sang Ook Nam Won Seop Kim Jae-Moon Kim Ki Joong Kim Department of Neurology Kangwon National University Hospital Chuncheon Republic of Korea Interdisciplinary Graduate Program in Medical Bigdata Convergence Kangwon National University Chuncheon Republic of Korea. Department of Biohealth Regulatory Science Sungkyunkwan University Suwon Republic of Korea. Department of Neurology Pusan National University Yangsan Hospital Yangsan Republic of Korea Research Institute for Convergence of Biomedical Science and Technology Pusan National University School of Medicine Yangsan Republic of Korea. Department of Neurology Chonnam National University Hospital Kwangju Republic of Korea. Department of Neurology School of Medicine Kyungpook National University Daegu Republic of Korea. Department of Pediatrics Chungbuk National University Hospital Cheongju Republic of Korea. Department of Pediatrics Chungnam National University Hospital Daejeon Republic of Korea. Department of Neurology Chungnam National University Hospital Daejeon Republic of Korea. Department of Neurology Gyeongsang National University Hospital Jinju Republic of Korea. Department of Pediatrics Ewha Womans University College of Medicine Seoul Republic of Korea. Department of Neurology Kangwon National University Hospital Chuncheon Republic of Korea. Division of Pediatric Neurosurgery Seoul National University Children's Hospital Seoul National University College of Medicine Seoul Republic of Korea. Electronic address: phijh@snu.ac.kr. Department of Pediatrics Pusan National University School of Medicine Pusan Republic of Korea. Electronic address: neuroped@***. Department of Pediatrics Seoul National University College of Medicine Seoul Republic of Korea.

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Application of CT simulation technique for virtual fecal tagging in CTC

Application of CT simulation technique for virtual fecal tag...

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作者： Yang, Zepa Jin, Hyeong-Min Kim, Jong Hyo Department of Biomedical Sciences Seoul National University College of Medicine Seoul 110-744 Korea Republic of Department of Radiology Seoul National University College of Medicine Seoul 110-744 Korea Republic of Interdisciplinary Program in Radiation Applied Life Science Seoul National University College of Medicine Seoul 110-744 Korea Republic of Institute of Radiation Medicine Seoul National University Medical Research Center 101 Daehangno Jongno-gu Seoul 110-744 Korea Republic of Department of Intelligent Convergence Systems Graduate School of Convergence Science and Technology Seoul National University 864-1 Iui-dong Yeongtong-gu Suwon-si Gyeonggi-do 443-270 Korea Republic of

ISBN: (纸本)9783642336119

An integrative CT simulation technique is presented that creates realistic CT images of virtual fecal-tagged material that was added to given clinical DICOM CT images. The energy spectrum of the CT X-ray source, the energy-dependent attenuation, and the scattering properties of the soft tissue and tagging material were incorporated in the generation technique for the DICOM image-based virtual sinograms, followed by CT reconstruction reflecting the vendor-specific filtering kernels. Dark band artifacts were generated by appropriate combining of beam-hardening and -scattering effects into the generation procedure for the virtual sinograms. We used a set of simple numerical phantoms to assess the basic behavior of artifact production. A reference set of CTC images with and without tagging material and artifacts was used for evaluation of the realism of the simulated results. The level of realism was evaluated in terms of the artifact strength and patterns around the added tagging material, compared to real tagging images. The results showed that our CT simulation technique provides sufficient realism for virtual fecal-tagged images that reflect a chain of physical and numerical processes, including beam hardening, scattering, and vendor-specific kernel filtered backprojection. The technique presented has the potential to be used as a tool for investigating the effect of tagging materials on image quality and to gauge how well the electronic cleansing technique performs. © 2012 Springer-Verlag.

关键词： Hardening

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