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Article ; Online: A Spike-like Self-Assembly of Polyaspartamide Integrated with Functionalized Nanoparticles.

Han, Sa Ra / Ahn, Yujin / Cho, Sungwoo / Jeong, Hyewon / Ji, Yoonsook / Jung, Woonggyu / Jeong, Jae Hyun

2024 Volume 16, Issue 2

Abstract: The integration of nanoparticles (NPs) into molecular self-assemblies has been extensively studied with the aim of building well-defined, ordered structures which exhibit advanced properties and performances. This study demonstrates a novel strategy for ... ...

Abstract	The integration of nanoparticles (NPs) into molecular self-assemblies has been extensively studied with the aim of building well-defined, ordered structures which exhibit advanced properties and performances. This study demonstrates a novel strategy for the preparation of a spike-like self-assembly designed to enhance UV blocking. Poly(2-hydroxyethyl aspartamide) (PHEA) substituted with octadecyl chains and menthyl anthranilate (C
Language	English
Publishing date	2024-01-15
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym16020234
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Regulated Self-Folding in Multi-Layered Hydrogels Considered with an Interfacial Layer.

Lim, Jun Woo / Kim, Sang Jin / Jeong, Jimin / Shin, Sung Gyu / Woo, Chaewon / Jung, Woonggyu / Jeong, Jae Hyun

Gels (Basel, Switzerland)

2024 Volume 10, Issue 1

Abstract: Multi-layered hydrogels consisting of bi- or tri-layers with different swelling ratios are designed to soft hydrogel actuators by self-folding. The successful use of multi-layered hydrogels in this application greatly relies on the precise design and ... ...

Abstract	Multi-layered hydrogels consisting of bi- or tri-layers with different swelling ratios are designed to soft hydrogel actuators by self-folding. The successful use of multi-layered hydrogels in this application greatly relies on the precise design and fabrication of the curvature of self-folding. In general, however, the self-folding often results in an undesired mismatch with the expecting value. To address this issue, this study introduces an interfacial layer formed between each layered hydrogel, and this layer is evaluated to enhance the design and fabrication precision. By considering the interfacial layer, which forms through diffusion, as an additional layer in the multi-layered hydrogel, the degree of mismatch in the self-folding is significantly reduced. Experimental results show that as the thickness of the interfacial layer increases, the multi-layered hydrogel exhibits a 3.5-fold increase in its radius of curvature during the self-folding. In addition, the diffusion layer is crucial for creating robust systems by preventing the separation of layers in the muti-layered hydrogel during actuation, thereby ensuring the integrity of the system in operation. This new strategy for designing multi-layered hydrogels including an interfacial layer would greatly serve to fabricate precise and robust soft hydrogel actuators.
Language	English
Publishing date	2024-01-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2813982-3
ISSN	2310-2861 ; 2310-2861
ISSN (online)	2310-2861
ISSN	2310-2861
DOI	10.3390/gels10010048
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Article ; Online: Implementation of a portable diffraction phase microscope for digital histopathology.

Aimakov, Nurbolat / Min, Eunjung / Ban, Sungbea / Lee, Sangjin / Bae, Jung Kweon / You, Joon S / Jung, Woonggyu

Journal of biophotonics

2024 Volume 17, Issue 3, Page(s) e202300496

Abstract: Quantitative phase imaging (QPI) has a significant advantage in histopathology as it helps in differentiating biological tissue structures and cells without the need for staining. To make this capability more accessible, it is crucial to develop compact ... ...

Abstract	Quantitative phase imaging (QPI) has a significant advantage in histopathology as it helps in differentiating biological tissue structures and cells without the need for staining. To make this capability more accessible, it is crucial to develop compact and portable systems. In this study, we introduce a portable diffraction phase microscopy (DPM) system that allows the acquisition of phase map images from various organs in mice using a low-NA objective lens. Our findings indicate that the cell and tissue structures observed in portable DPM images are similar to those seen in conventional histology microscope images. We confirmed that the developed system's performance is comparable to the benchtop DPM system. Additionally, we investigate the potential utility of digital histopathology by applying deep learning technology to create virtual staining of DPM images.
MeSH term(s)	Animals ; Mice ; Microscopy/methods ; Histological Techniques
Language	English
Publishing date	2024-02-15
Publishing country	Germany
Document type	Letter
ZDB-ID	2390063-5
ISSN	1864-0648 ; 1864-063X
ISSN (online)	1864-0648
ISSN	1864-063X
DOI	10.1002/jbio.202300496
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Zs.A 6723: Show issues

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Article ; Online: A novel optical coherence tomography-based in vitro method of anti-aging skin analysis using 3D skin wrinkle mimics.

Min, Daejin / Ahn, Yujin / Lee, Hae Kwang / Jung, Woonggyu / Kim, Hyoung-June

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)

2023 Volume 29, Issue 6, Page(s) e13354

Abstract: Background: Wrinkles represent a characteristic symptom of skin aging. In recent years, various studies have focused on their prevention and/or cure. However, clinical tests are still the only method available to directly detect and evaluate the anti- ... ...

Abstract	Background: Wrinkles represent a characteristic symptom of skin aging. In recent years, various studies have focused on their prevention and/or cure. However, clinical tests are still the only method available to directly detect and evaluate the anti-wrinkle efficacy of various substances. Moreover, no in vitro strategy for such anti-aging skin analysis has been reported. Therefore, in this study, we aimed to develop a novel technology to overcome these limitations. Materials and methods: Full-thickness (FT) skin wrinkle mimics with various widths and depths were fabricated using a collagen stamping method. These were analyzed and compared using 2D and 3D Swept Source-Optical Coherence Tomography (SS-OCT) imaging technologies. Results: SS-OCT demonstrated superficial and cross-sectional images of the wrinkle mimics, and the size of the wrinkles was validated using image analysis. Retinoic acid treatment significantly decreased both the depth and width of wrinkles formed in the FT skin wrinkle mimics. Conclusions: Using 3D tissue engineering and SS-OCT imaging technologies, we developed a novel in vitro technique that can directly detect skin wrinkles. This significantly efficient method could lead to an alternative strategy for animal experiments and preclinical anti-aging research on the skin.
MeSH term(s)	Tomography, Optical Coherence/methods ; Skin Aging ; Skin/diagnostic imaging ; Imaging, Three-Dimensional/methods
Language	English
Publishing date	2023-06-23
Publishing country	England
Document type	Journal Article
ZDB-ID	1229160-2
ISSN	1600-0846 ; 0909-752X ; 1397-1344
ISSN (online)	1600-0846
ISSN	0909-752X ; 1397-1344
DOI	10.1111/srt.13354
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Zs.A 4278: Show issues

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Article: Deep Learning-Based Glaucoma Screening Using Regional RNFL Thickness in Fundus Photography.

Yang, Hyunmo / Ahn, Yujin / Askaruly, Sanzhar / You, Joon S / Kim, Sang Woo / Jung, Woonggyu

Diagnostics (Basel, Switzerland)

2022 Volume 12, Issue 11

Abstract: Since glaucoma is a progressive and irreversible optic neuropathy, accurate screening and/or early diagnosis is critical in preventing permanent vision loss. Recently, optical coherence tomography (OCT) has become an accurate diagnostic tool to observe ... ...

Abstract	Since glaucoma is a progressive and irreversible optic neuropathy, accurate screening and/or early diagnosis is critical in preventing permanent vision loss. Recently, optical coherence tomography (OCT) has become an accurate diagnostic tool to observe and extract the thickness of the retinal nerve fiber layer (RNFL), which closely reflects the nerve damage caused by glaucoma. However, OCT is less accessible than fundus photography due to higher cost and expertise required for operation. Though widely used, fundus photography is effective for early glaucoma detection only when used by experts with extensive training. Here, we introduce a deep learning-based approach to predict the RNFL thickness around optic disc regions in fundus photography for glaucoma screening. The proposed deep learning model is based on a convolutional neural network (CNN) and utilizes images taken with fundus photography and with RNFL thickness measured with OCT for model training and validation. Using a dataset acquired from normal tension glaucoma (NTG) patients, the trained model can estimate RNFL thicknesses in 12 optic disc regions from fundus photos. Using intuitive thickness labels to identify localized damage of the optic nerve head and then estimating regional RNFL thicknesses from fundus images, we determine that screening for glaucoma could achieve 92% sensitivity and 86.9% specificity. Receiver operating characteristic (ROC) analysis results for specificity of 80% demonstrate that use of the localized mean over superior and inferior regions reaches 90.7% sensitivity, whereas 71.2% sensitivity is reached using the global RNFL thicknesses for specificity at 80%. This demonstrates that the new approach of using regional RNFL thicknesses in fundus images holds good promise as a potential screening technique for early stage of glaucoma.
Language	English
Publishing date	2022-11-21
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics12112894
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Article: Encoder-Weighted W-Net for Unsupervised Segmentation of Cervix Region in Colposcopy Images.

Park, Jinhee / Yang, Hyunmo / Roh, Hyun-Jin / Jung, Woonggyu / Jang, Gil-Jin

Cancers

2022 Volume 14, Issue 14

Abstract: Cervical cancer can be prevented and treated better if it is diagnosed early. Colposcopy, a way of clinically looking at the cervix region, is an efficient method for cervical cancer screening and its early detection. The cervix region segmentation ... ...

Abstract	Cervical cancer can be prevented and treated better if it is diagnosed early. Colposcopy, a way of clinically looking at the cervix region, is an efficient method for cervical cancer screening and its early detection. The cervix region segmentation significantly affects the performance of computer-aided diagnostics using a colposcopy, particularly cervical intraepithelial neoplasia (CIN) classification. However, there are few studies of cervix segmentation in colposcopy, and no studies of fully unsupervised cervix region detection without image pre- and post-processing. In this study, we propose a deep learning-based unsupervised method to identify cervix regions without pre- and post-processing. A new loss function and a novel scheduling scheme for the baseline W-Net are proposed for fully unsupervised cervix region segmentation in colposcopy. The experimental results showed that the proposed method achieved the best performance in the cervix segmentation with a Dice coefficient of 0.71 with less computational cost. The proposed method produced cervix segmentation masks with more reduction in outliers and can be applied before CIN detection or other diagnoses to improve diagnostic performance. Our results demonstrate that the proposed method not only assists medical specialists in diagnosis in practical situations but also shows the potential of an unsupervised segmentation approach in colposcopy.
Language	English
Publishing date	2022-07-13
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527080-1
ISSN	2072-6694
ISSN	2072-6694
DOI	10.3390/cancers14143400
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Article: Quantification and visualization of metastatic lung tumors in mice.

Lee, Ha Neul / Kim, Seyl / Park, Sooah / Jung, Woonggyu / Kang, Jin Seok

Toxicological research

2022 Volume 38, Issue 4, Page(s) 503–510

Abstract: Histopathological examination is important for the diagnosis of various diseases. Conventional histopathology provides a two-dimensional view of the tissues, and requires the tissue to be extracted, fixed, and processed using histotechnology techniques. ... ...

Abstract	Histopathological examination is important for the diagnosis of various diseases. Conventional histopathology provides a two-dimensional view of the tissues, and requires the tissue to be extracted, fixed, and processed using histotechnology techniques. However, there is an increasing need for three-dimensional (3D) images of structures in biomedical research. The objective of this study was to develop reliable, objective tools for visualizing and quantifying metastatic tumors in mouse lung using micro-computed tomography (micro-CT), optical coherence tomography (OCT), and field emission-scanning electron microscopy (FE-SEM). Melanoma cells were intravenously injected into the tail vein of 8-week-old C57BL/6 mice. The mice were euthanized at 2 or 4 weeks after injection. Lungs were fixed and examined by micro-CT, OCT, FE-SEM, and histopathological observation. Micro-CT clearly distinguished between tumor and normal cells in surface and deep lesions, thereby allowing 3D quantification of the tumor volume. OCT showed a clear difference between the tumor and surrounding normal tissues. FE-SEM clearly showed round tumor cells, mainly located in the alveolar wall and growing inside the alveoli. Therefore, whole-tumor 3D imaging successfully visualized the metastatic tumor and quantified its volume. This promising approach will allow for fast and label-free 3D phenotyping of diverse tissue structures.
Language	English
Publishing date	2022-04-27
Publishing country	Singapore
Document type	Journal Article
ZDB-ID	2727978-9
ISSN	2234-2753 ; 1976-8257
ISSN (online)	2234-2753
ISSN	1976-8257
DOI	10.1007/s43188-022-00134-4
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Article: Multi-contrast digital histopathology of mouse organs using quantitative phase imaging and virtual staining.

Min, Eunjung / Aimakov, Nurbolat / Lee, Sangjin / Ban, Sungbea / Yang, Hyunmo / Ahn, Yujin / You, Joon S / Jung, Woonggyu

Biomedical optics express

2023 Volume 14, Issue 5, Page(s) 2068–2079

Abstract: Quantitative phase imaging (QPI) has emerged as a new digital histopathologic tool as it provides structural information of conventional slide without staining process. It is also capable of imaging biological tissue sections with sub-nanometer ... ...

Abstract	Quantitative phase imaging (QPI) has emerged as a new digital histopathologic tool as it provides structural information of conventional slide without staining process. It is also capable of imaging biological tissue sections with sub-nanometer sensitivity and classifying them using light scattering properties. Here we extend its capability further by using optical scattering properties as imaging contrast in a wide-field QPI. In our first step towards validation, QPI images of 10 major organs of a wild-type mouse have been obtained followed by H&E-stained images of the corresponding tissue sections. Furthermore, we utilized deep learning model based on generative adversarial network (GAN) architecture for virtual staining of phase delay images to a H&E-equivalent brightfield (BF) image analogues. Using the structural similarity index, we demonstrate similarities between virtually stained and H&E histology images. Whereas the scattering-based maps look rather similar to QPI phase maps in the kidney, the brain images show significant improvement over QPI with clear demarcation of features across all regions. Since our technology provides not only structural information but also unique optical property maps, it could potentially become a fast and contrast-enriched histopathology technique.
Language	English
Publishing date	2023-04-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	2572216-5
ISSN	2156-7085
ISSN	2156-7085
DOI	10.1364/BOE.484516
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Article: The synergistic effect of biomimetic electrical stimulation and extracellular-matrix-mimetic nanopattern for upregulating cell activities

So, Jin-Young / Lee, Joohyun / Ahn, Yujin / Kang, Daeseung / Jung, Woonggyu / Bae, Won-Gyu

Biosensors & bioelectronics. 2020 Nov. 01, v. 167

2020

Abstract: Endogenous bioelectric signaling and the extracellular matrix (ECM) are factors that have a great effect on the performance of cellular functions. Presenting an experimental platform to confirm the synergy effects of an electrical stimulation, which ... ...

Abstract	Endogenous bioelectric signaling and the extracellular matrix (ECM) are factors that have a great effect on the performance of cellular functions. Presenting an experimental platform to confirm the synergy effects of an electrical stimulation, which simulates endogenous bioelectricity, and nanopatterns that can be precisely fabricated in various patterns sizes makes it possible to consider those factors effectively. Herein, we have performed a comparison of cellular response to each of general electrical stimulation and biomimetic electrical stimulation (BES) and demonstrated the synergy effects of electrical stimulation and ECM-mimetic nanopatterns. BES has provided the most remarkable proliferation among different types of electrical stimulation and upregulated the behavior of cells through synergy effects with ECM-mimetic nanopatterns. Thus, it is believed that using the synergy effects of BES and ECM-like nanopatterns has broad applications in the biomedical field, such as cell culture with electrical stimulation, induction of cell growth, tissue repair, etc.
Keywords	bioelectricity ; biomimetics ; biosensors ; cell culture ; cell growth ; electrical treatment ; extracellular matrix ; synergism ; tissue repair
Language	English
Dates of publication	2020-1101
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1011023-9
ISSN	1873-4235 ; 0956-5663
ISSN (online)	1873-4235
ISSN	0956-5663
DOI	10.1016/j.bios.2020.112470
Database	NAL-Catalogue (AGRICOLA)

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Zs.A 2275: Show issues

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Jg. 1995 - 2021: Lesesall (2.OG)
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Article ; Online: Deep-Learning-Based Algorithm for the Removal of Electromagnetic Interference Noise in Photoacoustic Endoscopic Image Processing.

Gulenko, Oleksandra / Yang, Hyunmo / Kim, KiSik / Youm, Jin Young / Kim, Minjae / Kim, Yunho / Jung, Woonggyu / Yang, Joon-Mo

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 10

Abstract: Despite all the expectations for photoacoustic endoscopy (PAE), there are still several technical issues that must be resolved before the technique can be successfully translated into clinics. Among these, electromagnetic interference (EMI) noise, in ... ...

Abstract	Despite all the expectations for photoacoustic endoscopy (PAE), there are still several technical issues that must be resolved before the technique can be successfully translated into clinics. Among these, electromagnetic interference (EMI) noise, in addition to the limited signal-to-noise ratio (SNR), have hindered the rapid development of related technologies. Unlike endoscopic ultrasound, in which the SNR can be increased by simply applying a higher pulsing voltage, there is a fundamental limitation in leveraging the SNR of PAE signals because they are mostly determined by the optical pulse energy applied, which must be within the safety limits. Moreover, a typical PAE hardware situation requires a wide separation between the ultrasonic sensor and the amplifier, meaning that it is not easy to build an ideal PAE system that would be unaffected by EMI noise. With the intention of expediting the progress of related research, in this study, we investigated the feasibility of deep-learning-based EMI noise removal involved in PAE image processing. In particular, we selected four fully convolutional neural network architectures, U-Net, Segnet, FCN-16s, and FCN-8s, and observed that a modified U-Net architecture outperformed the other architectures in the EMI noise removal. Classical filter methods were also compared to confirm the superiority of the deep-learning-based approach. Still, it was by the U-Net architecture that we were able to successfully produce a denoised 3D vasculature map that could even depict the mesh-like capillary networks distributed in the wall of a rat colorectum. As the development of a low-cost laser diode or LED-based photoacoustic tomography (PAT) system is now emerging as one of the important topics in PAT, we expect that the presented AI strategy for the removal of EMI noise could be broadly applicable to many areas of PAT, in which the ability to apply a hardware-based prevention method is limited and thus EMI noise appears more prominently due to poor SNR.
MeSH term(s)	Algorithms ; Animals ; Deep Learning ; Electromagnetic Phenomena ; Endoscopy ; Image Processing, Computer-Assisted/methods ; Rats
Language	English
Publishing date	2022-05-23
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22103961
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