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Article ; Online: An unusual cause of a bronchopleural fistula

Dongyoon Keum / Mincheol Chae / Ilseon Hwang / Hyun Jung Kim

The Korean Journal of Internal Medicine, Vol 38, Iss 4, Pp 574-

2023 Volume 575

Keywords	Medicine ; R
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	The Korean Association of Internal Medicine
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An unusual cause of a bronchopleural fistula.

Keum, Dongyoon / Chae, Mincheol / Hwang, Ilseon / Kim, Hyun Jung

The Korean journal of internal medicine

2023 Volume 38, Issue 4, Page(s) 574–575

MeSH term(s)	Humans ; Bronchial Fistula/diagnostic imaging ; Bronchial Fistula/etiology ; Bronchial Fistula/surgery ; Pleural Diseases/diagnostic imaging ; Pleural Diseases/etiology ; Pneumonectomy/adverse effects ; Postoperative Complications/etiology
Language	English
Publishing date	2023-03-27
Publishing country	Korea (South)
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	639023-7
ISSN	2005-6648 ; 1226-3303
ISSN (online)	2005-6648
ISSN	1226-3303
DOI	10.3904/kjim.2023.060
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Article ; Online: Anisotropic lens-shaped mesoporous carbon from interfacially perpendicular self-assembly for potassium-ion batteries.

Woo, Dongyoon / Ban, Minkyeong / Lee, Jisung / Park, Cheol-Young / Kim, Jinuk / Kim, Seongseop / Lee, Jinwoo

Chemical communications (Cambridge, England)

2024 Volume 60, Issue 5, Page(s) 590–593

Abstract: Anisotropic lens-shaped nitrogen-doped carbon (Lens-NMC) with unidirectionally aligned mesopores was ... ...

Abstract	Anisotropic lens-shaped nitrogen-doped carbon (Lens-NMC) with unidirectionally aligned mesopores was achieved
Language	English
Publishing date	2024-01-11
Publishing country	England
Document type	Journal Article
ZDB-ID	1472881-3
ISSN	1364-548X ; 1359-7345 ; 0009-241X
ISSN (online)	1364-548X
ISSN	1359-7345 ; 0009-241X
DOI	10.1039/d3cc04344d
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Spinodal Decomposition-Driven Structural Hierarchy of Mesoporous Inorganic Materials for Energy Applications.

Ban, Minkyeong / Woo, Dongyoon / Hwang, Jongkook / Kim, Seongseop / Lee, Jinwoo

Accounts of chemical research

2023 Volume 56, Issue 23, Page(s) 3428–3440

Abstract: ConspectusMesoporous inorganic materials (MIMs) directed by block copolymers (BCPs) have attracted tremendous attention due to their high surface area, large pore volume, and tunable pore size. The structural hierarchy of inorganic materials with ... ...

Abstract	ConspectusMesoporous inorganic materials (MIMs) directed by block copolymers (BCPs) have attracted tremendous attention due to their high surface area, large pore volume, and tunable pore size. The structural hierarchy of inorganic materials with designed meso- and macrostructures combines the benefits of mesoporosity and tailored macrostructures in which macropores have increased ion/mass transfer and large capacity to carry guest material and have a macroscale particle morphology that permits close packing and a low surface energy. Existing methods for hierarchically structured MIMs require complicated multistep procedures including preparation of sacrificial macrotemplates (e.g., foams and colloidal spheres). Despite considerable efforts to control the macrostructures of mesoporous materials, major challenges remain in the formation of a structural hierarchy with ordered mesoporosity.In polymer science, spinodal decomposition (SD) is a physical phenomenon that spontaneously produces a wide variety of macroscale heterostructures from interconnected networks to isolated droplets. Exploitation of SD is a promising method to achieve precise control of the macrostructure (e.g., macropore, particle morphology) and mesostructure (e.g., pore size and structure, composition) of inorganic materials. However, this approach for tailoring the structural hierarchy of MIMs is unexplored due to the lack of effective systems that can control the complex thermodynamic interactions of inorganic precursor/polymer blends and the phase-separation kinetics.In this Account, we present our recent research progress on the development of synthesis systems that combine unique SD behaviors and BCP self-assembly in polymer blends. To generate macropores in MIMs, we have exploited interconnected macrostructures of SD induced by designed quench conditions of multicomponent blends containing BCP. These strategies enable control of the size of the macropores of the nanostructures independently and can be extended to various compositions (e.g., carbon, SiO
Language	English
Publishing date	2023-11-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	1483291-4
ISSN	1520-4898 ; 0001-4842
ISSN (online)	1520-4898
ISSN	0001-4842
DOI	10.1021/acs.accounts.3c00524
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: TL-ADA: Transferable Loss-based Active Domain Adaptation.

Han, Kyeongtak / Kim, Youngeun / Han, Dongyoon / Lee, Hojun / Hong, Sungeun

Neural networks : the official journal of the International Neural Network Society

2023 Volume 161, Page(s) 670–681

Abstract: The field of Active Domain Adaptation (ADA) has been investigating ways to close the performance gap between supervised and unsupervised learning settings. Previous ADA research has primarily focused on query selection, but there has been little ... ...

Abstract	The field of Active Domain Adaptation (ADA) has been investigating ways to close the performance gap between supervised and unsupervised learning settings. Previous ADA research has primarily focused on query selection, but there has been little examination of how to effectively train newly labeled target samples using both labeled source samples and unlabeled target samples. In this study, we present a novel Transferable Loss-based ADA (TL-ADA) framework. Our approach is inspired by loss-based query selection, which has shown promising results in active learning. However, directly applying loss-based query selection to the ADA scenario leads to a buildup of high-loss samples that do not contribute to the model due to transferability issues and low diversity. To address these challenges, we propose a transferable doubly nested loss, which incorporates target pseudo labels and a domain adversarial loss. Our TL-ADA framework trains the model sequentially, considering both the domain type (source/target) and the availability of labels (labeled/unlabeled). Additionally, we encourage the pseudo labels to have low self-entropy and diverse class distributions to improve their reliability. Experiments on several benchmark datasets demonstrate that our TL-ADA model outperforms previous ADA methods, and in-depth analysis supports the effectiveness of our proposed approach.
MeSH term(s)	Reproducibility of Results ; Benchmarking ; Entropy
Language	English
Publishing date	2023-02-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	740542-x
ISSN	1879-2782 ; 0893-6080
ISSN (online)	1879-2782
ISSN	0893-6080
DOI	10.1016/j.neunet.2023.02.004
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Article ; Online: Lipid nanoparticle-mediated CRISPR/Cas9 gene editing and metabolic engineering for anticancer immunotherapy.

Ju, Hyemin / Kim, Dongyoon / Oh, Yu-Kyoung

Asian journal of pharmaceutical sciences

2022 Volume 17, Issue 5, Page(s) 641–652

Abstract: Metabolic engineering of the tumor microenvironment has emerged as a new strategy. Lactate dehydrogenase A (LDHA) is a prominent target for metabolic engineering. Here, we designed a cationic lipid nanoparticle formulation for LDHA gene editing. The ... ...

Abstract	Metabolic engineering of the tumor microenvironment has emerged as a new strategy. Lactate dehydrogenase A (LDHA) is a prominent target for metabolic engineering. Here, we designed a cationic lipid nanoparticle formulation for LDHA gene editing. The plasmid DNA delivery efficiency of our lipid nanoparticle formulations was screened by testing the fluorescence of lipid nanoparticles complexed to plasmid DNA encoding green fluorescence protein (GFP). The delivery efficiency was affected by the ratios of three components: a cationic lipid, cholesterol or its derivative, and a fusogenic lipid. The lipid nanoparticle designated formulation F3 was complexed to plasmid DNA co-encoding CRISPR-associated protein 9 and LDHA-specific sgRNA, yielding the lipoplex, pCas9-sgLDHA/F3. The lipoplex including GFP-encoding plasmid DNA provided gene editing in HeLa-GFP cells. Treatment of B16F10 tumor cells with pCas9-sgLDHA/F3 yielded editing of the LDHA gene and increased the pH of the culture medium. pCas9-sgLDHA/F3 treatment activated the interferon-gamma and granzyme production of T cells in culture.
Language	English
Publishing date	2022-08-22
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2650931-3
ISSN	2221-285X ; 1818-0876 ; 2221-285X
ISSN (online)	2221-285X
ISSN	1818-0876 ; 2221-285X
DOI	10.1016/j.ajps.2022.07.005
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Book ; Online: Masked Autoencoder for Unsupervised Video Summarization

Shim, Minho / Kim, Taeoh / Kim, Jinhyung / Wee, Dongyoon

2023

Abstract: Summarizing a video requires a diverse understanding of the video, ranging from recognizing scenes to evaluating how much each frame is essential enough to be selected as a summary. Self-supervised learning (SSL) is acknowledged for its robustness and ... ...

Abstract	Summarizing a video requires a diverse understanding of the video, ranging from recognizing scenes to evaluating how much each frame is essential enough to be selected as a summary. Self-supervised learning (SSL) is acknowledged for its robustness and flexibility to multiple downstream tasks, but the video SSL has not shown its value for dense understanding tasks like video summarization. We claim an unsupervised autoencoder with sufficient self-supervised learning does not need any extra downstream architecture design or fine-tuning weights to be utilized as a video summarization model. The proposed method to evaluate the importance score of each frame takes advantage of the reconstruction score of the autoencoder's decoder. We evaluate the method in major unsupervised video summarization benchmarks to show its effectiveness under various experimental settings.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Publishing date	2023-06-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: On-demand delivery of protein drug from 3D-printed implants.

Kim, Dongyoon / Wu, Yina / Oh, Yu-Kyoung

Journal of controlled release : official journal of the Controlled Release Society

2022 Volume 349, Page(s) 133–142

Abstract: Here, we constructed 3D-printed multiunit implants to enable remote light-controlled protein drug delivery in a spatiotemporal manner. Multiunit implants were designed to be 3D printed using polycaprolactone, lauric acid, and melanin as a matrix, and a ... ...

Abstract	Here, we constructed 3D-printed multiunit implants to enable remote light-controlled protein drug delivery in a spatiotemporal manner. Multiunit implants were designed to be 3D printed using polycaprolactone, lauric acid, and melanin as a matrix, and a polycaprolactone scaffold as a multiunit divider. As a model drug, insulin was loaded to each unit of the implant. The 3D printing yielded a rectangular matrix with multiunit sectors segregated by polycaprolactone lanes. Irradiation with near infrared light (NIR) triggered controlled release of insulin from the irradiated locus: Upon NIR irradiation, heat generated from the melanin melted the polycaprolactone/lauric acid matrix to release insulin from the scaffold. In the absence of melanin in the matrix, the implant did not show NIR-responsive insulin release. When lauric acid was absent from the matrix, the NIR-irradiated unit did not undergo dismantling. When the insulin-loaded multiunit implant was applied to a mouse diabetic model and irradiated with NIR, repetitive insulin release resulted in an efficient decrease of the blood glucose level over multiple days. Together, these results suggest that 3D printing technology-based multi-dosing of insulin on demand can enable convenient treatment of diabetes through external NIR irradiation, potentially avoiding the pain and discomfort of repeated insulin injections.
MeSH term(s)	Animals ; Blood Glucose ; Delayed-Action Preparations ; Drug Delivery Systems/methods ; Drug Liberation ; Insulins ; Melanins ; Mice ; Printing, Three-Dimensional
Chemical Substances	Blood Glucose ; Delayed-Action Preparations ; Insulins ; Melanins
Language	English
Publishing date	2022-07-06
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	632533-6
ISSN	1873-4995 ; 0168-3659
ISSN (online)	1873-4995
ISSN	0168-3659
DOI	10.1016/j.jconrel.2022.06.047
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Article: On-demand delivery of protein drug from 3D-printed implants

Kim, Dongyoon / Wu, Yina / Oh, Yu-Kyoung

Journal of controlled release. 2022 Sept., v. 349

2022

Abstract	Here, we constructed 3D-printed multiunit implants to enable remote light-controlled protein drug delivery in a spatiotemporal manner. Multiunit implants were designed to be 3D printed using polycaprolactone, lauric acid, and melanin as a matrix, and a polycaprolactone scaffold as a multiunit divider. As a model drug, insulin was loaded to each unit of the implant. The 3D printing yielded a rectangular matrix with multiunit sectors segregated by polycaprolactone lanes. Irradiation with near infrared light (NIR) triggered controlled release of insulin from the irradiated locus: Upon NIR irradiation, heat generated from the melanin melted the polycaprolactone/lauric acid matrix to release insulin from the scaffold. In the absence of melanin in the matrix, the implant did not show NIR-responsive insulin release. When lauric acid was absent from the matrix, the NIR-irradiated unit did not undergo dismantling. When the insulin-loaded multiunit implant was applied to a mouse diabetic model and irradiated with NIR, repetitive insulin release resulted in an efficient decrease of the blood glucose level over multiple days. Together, these results suggest that 3D printing technology-based multi-dosing of insulin on demand can enable convenient treatment of diabetes through external NIR irradiation, potentially avoiding the pain and discomfort of repeated insulin injections.
Keywords	blood glucose ; diabetes ; dodecanoic acid ; drugs ; heat ; insulin ; irradiation ; loci ; melanin ; mice ; models ; pain ; three-dimensional printing
Language	English
Dates of publication	2022-09
Size	p. 133-142.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	632533-6
ISSN	1873-4995 ; 0168-3659
ISSN (online)	1873-4995
ISSN	0168-3659
DOI	10.1016/j.jconrel.2022.06.047
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Masked Image Modeling via Dynamic Token Morphing

Kim, Taekyung / Han, Dongyoon / Heo, Byeongho

2023

Abstract: Masked Image Modeling (MIM) arises as a promising option for Vision Transformers among various self-supervised learning (SSL) methods. The essence of MIM lies in token-wise masked patch predictions, with targets patchified from images; or generated by ... ...

Abstract	Masked Image Modeling (MIM) arises as a promising option for Vision Transformers among various self-supervised learning (SSL) methods. The essence of MIM lies in token-wise masked patch predictions, with targets patchified from images; or generated by pre-trained tokenizers or models. We argue targets from the pre-trained models usually exhibit spatial inconsistency, which makes it excessively challenging for the model to follow to learn more discriminative representations. To mitigate the issue, we introduce a novel self-supervision signal based on Dynamic Token Morphing (DTM), which dynamically aggregates contextually related tokens. DTM can be generally applied to various SSL frameworks, yet we propose a simple MIM that employs DTM to effectively improve the performance barely introducing extra training costs. Our experiments on ImageNet-1K and ADE20K evidently demonstrate the superiority of our methods. Furthermore, the comparative evaluation of iNaturalist and Fine-grained Visual Classification datasets further validates the transferability of our method on various downstream tasks. Our code will be released publicly. Comment: 15 pages, 6 figures
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-12-30
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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