• Korean journal of applied entomology
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• v.61 no.1
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• pp.249-254
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• 2022

Silkworms, which have for long been used as an insect resource for industrialization, have recently attracted attention as potential bio-factories for the production of novel biomaterials. In this regard, material production is typically achieved based on transformation technology, mediated via microinjection, in which a target gene is inserted into eggs containing an embryo. However, an essential step in the microinjection procedure is egg fixation, which can be a time-consuming and laborious task. Therefore, in this study, using the 3DCADian program, we adopted a 3D printing approach to model egg liners and glue drawers, which can contribute to facilitating egg alignment and fixation, thereby enhancing transformation efficiency by reducing time consumption and fatigue. After rendering using Fusion 360, the two supplementary tools were produced by printing with nylon resin (PA12) and Sinterit Lisa Pro. Subsequent analysis of the time required to fix eggs on glass slides using the two manufactured tools, revealed that the processing time was reduced by approximately 18.6% when the two tools were used compared with when these tools were not used. These innovations not only reduced fatigue but also contributed to more effective use of the microscope and manipulator for microinjection. Consequently, we believe that with additional research and refinement, the egg liner and glue drawer developed in this study could be used to enhance silkworm transformation efficiency and study similar transformation systems in other industrial insects.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.99-132
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• 2022

The purpose of this study is to propose AET (Augmented and Extended Topics), a novel method of synthesizing both LDA and BERTopic results, and to analyze the recently published LIS articles as an experimental approach. To achieve the purpose of this study, 55,442 abstracts from 85 LIS journals within the WoS database, which spans from January 2001 to October 2021, were analyzed. AET first constructs a WORD2VEC-based cosine similarity matrix between LDA and BERTopic results, extracts AT (Augmented Topics) by repeating the matrix reordering and segmentation procedures as long as their semantic relations are still valid, and finally determines ET (Extended Topics) by removing any LDA related residual subtopics from the matrix and ordering the rest of them by F₁ (BERTopic topic size rank, Inverse cosine similarity rank). AET, by comparing with the baseline LDA result, shows that AT has effectively concretized the original LDA topic model and ET has discovered new meaningful topics that LDA didn't. When it comes to the qualitative performance evaluation, AT performs better than LDA while ET shows similar performances except in a few cases.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.133-153
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• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.31-49
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• 2023

With the growth of the food-catering industry, consumer preferences and the number of dine-in restaurants are gradually increasing. Thus, personalized recommendation services are required to select a restaurant suitable for consumer preferences. Previous studies have used questionnaires and star-rating approaches, which do not effectively depict consumer preferences. Online reviews are the most essential sources of information in this regard. However, previous studies have aggregated online reviews into long documents, and traditional machine-learning methods have been applied to these to extract semantic representations; however, such approaches fail to consider the surrounding word or context. Therefore, this study proposes a novel review textual-based restaurant recommendation model (RT-RRM) that uses deep learning to effectively extract consumer preferences from online reviews. The proposed model concatenates consumer-restaurant interactions with the extracted high-level semantic representations and predicts consumer preferences accurately and effectively. Experiments on real-world datasets show that the proposed model exhibits excellent recommendation performance compared with several baseline models.

• Biomolecules & Therapeutics
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• v.32 no.1
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• pp.123-135
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• 2024

Although gemcitabine-based regimens are widely used as an effective treatment for pancreatic cancer, acquired resistance to gemcitabine has become an increasingly common problem. Therefore, a novel therapeutic strategy to treat gemcitabine-resistant pancreatic cancer is urgently required. Piceamycin has been reported to exhibit antiproliferative activity against various cancer cells; however, its underlying molecular mechanism for anticancer activity in pancreatic cancer cells remains unexplored. Therefore, the present study evaluated the antiproliferation activity of piceamycin in a gemcitabine-resistant pancreatic cancer cell line and patient-derived pancreatic cancer organoids. Piceamycin effectively inhibited the proliferation and suppressed the expression of alpha-actinin-4, a gene that plays a pivotal role in tumorigenesis and metastasis of various cancers, in gemcitabine-resistant cells. Long-term exposure to piceamycin induced cell cycle arrest at the G₀/G₁ phase and caused apoptosis. Piceamycin also inhibited the invasion and migration of gemcitabine-resistant cells by modulating focal adhesion and epithelial-mesenchymal transition biomarkers. Moreover, the combination of piceamycin and gemcitabine exhibited a synergistic antiproliferative activity in gemcitabine-resistant cells. Piceamycin also effectively inhibited patient-derived pancreatic cancer organoid growth and induced apoptosis in the organoids. Taken together, these findings demonstrate that piceamycin may be an effective agent for overcoming gemcitabine resistance in pancreatic cancer.

• IMMUNE NETWORK
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• v.24 no.2
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• pp.3.1-3.23
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• 2024

Cigarette smoke extract (CSE)-treated mouse airway epithelial cells (MAECs)-derived exosomes accelerate the progression of chronic obstructive pulmonary disease (COPD) by upregulating triggering receptor expressed on myeloid cells 1 (TREM-1); however, the specific mechanism remains unclear. We aimed to explore the potential mechanisms of CSE-treated MAECs-derived exosomes on M1 macrophage polarization and pyroptosis in COPD. In vitro, exosomes were extracted from CSE-treated MAECs, followed by co-culture with macrophages. In vivo, mice exposed to cigarette smoke (CS) to induce COPD, followed by injection or/and intranasal instillation with oe-TREM-1 lentivirus. Lung function and pathological changes were evaluated. CD68⁺ cell number and the levels of iNOS, TNF-α, IL-1β (M1 macrophage marker), and pyroptosis-related proteins (NOD-like receptor family pyrin domain containing 3, apoptosis-associated speck-like protein containing a caspase-1 recruitment domain, caspase-1, cleaved-caspase-1, gasdermin D [GSDMD], and GSDMD-N) were examined. The expression of maternally expressed gene 3 (MEG3), spleen focus forming virus proviral integration oncogene (SPI1), methyltransferase 3 (METTL3), and TREM-1 was detected and the binding relationships among them were verified. MEG3 increased N6-methyladenosine methylation of TREM-1 by recruiting SPI1 to activate METTL3. Overexpression of TREM-1 or METTL3 negated the alleviative effects of MEG3 inhibition on M1 polarization and pyroptosis. In mice exposed to CS, EXO^-CSE further aggravated lung injury, M1 polarization, and pyroptosis, which were reversed by MEG3 inhibition. TREM-1 overexpression negated the palliative effects of MEG3 inhibition on COPD mouse lung injury. Collectively, CSE-treated MAECs-derived exosomal long non-coding RNA MEG3 may expedite M1 macrophage polarization and pyroptosis in COPD via the SPI1/METTL3/TREM-1 axis.

• Information Systems Review
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• v.19 no.2
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• pp.115-136
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• 2017

Online communities have become substantial aspects of people's daily lives. However, only a few communities succeed and attract the majority of users, whereas the vast majority struggle for survival. When various communities coexist, important factors should be identified and examined to maintain attraction and achieve success. The concept of coexistence as been extensively explored in organizational ecology literature. However, given the similarities and differences between online communities and traditional organizations, the direct application of organizational theories to online contexts should be cautiously explored. In this study, we follow the roadmap proposed by Davis et al. (2007) in conducting agent-based modeling and simulation study to develop a novel theory based on the previous literature. In the case of two coexisting communities, we find that community size and participation costs can significantly affect the development of a community. A large community can attract a high number of active members who frequently log in. By contrast, low participation costs can encourage the reading and posting behaviors of members. We also observe the important influence of the distribution of interests on the topic trends of communities. A community composed of a population that focuses on only one topic can quickly converge on the topic regardless of whether the initial topic is broad or focused. This simulation model provides theoretical implications to literature and practical guidance to operators of online communities.

• Microbiology and Biotechnology Letters
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• v.45 no.1
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• pp.63-70
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• 2017

A functional screen of 60,672 fosmid metagenomic clones amplified from marine sediment obtained from the Dokdo islets in Korea identified the gene EstES1, whose product, EstES1, displayed lipolytic properties on tributyrin-supplemented media. EstES1 is a 576 amino acid protein with a predicted molecular weight of 59.4 kDa including 37 N-terminal leader amino acids. EstES1 exhibited the highest sequence similarity (44%) to a carboxylesterase found in Haliangium ochraceum DSM14365. Phylogenetic analysis indicated that EstES1 belongs to a currently uncharacterized family of lipases. Within the conserved domain, EstES1 retains the catalytic triad that consists of the consensus penta-peptide motif, GESAG. EstES1 demonstrated a broad substrate specificity toward the long acyl group of ethyl esters (C2-C12), and its optimal activity was recorded toward p-Nitrophenyl butyrate (C4) at pH 9.0 and $40^{\circ}C$ (specific activity of 255.4 U/mg). The enzyme remained stable in the ranges of $60-65^{\circ}C$ and pH 9.0-10.5 and in the presence of methanol, ethanol, isopropanol, and dimethyl sulfoxide. Therefore, EstES1 has potential for use in industrial applications involving high temperature, organic solvents, and/or alkaline conditions.

• Journal of Animal Environmental Science
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• v.15 no.2
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• pp.171-182
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• 2009

Conventionally, many pig producers have utilized a continual sow managements system that the matings, farrowings and weanings are done weekly basis. But this transitional method is not able to cut the cycle of diseases and fully apply all-in/all-out system because of the continuous flow of sows and pigs. Conventional weekly management system is currently limiting in small farm to work efficiently both for workers and pigs. Therefore, pig producers have found novel management methods for applying all-in/all-out system, improving pig health, leading to better growth, lowering mortality and reducing medication costs nowadays. Moreover, all-in/all-out pig management system has known as a strategy for improving productivity in swine farm. The batch system is one of the best management methods to adopt all-in/all-out pig management system that prevent spreading diseases in pig and remove cycle of diseases. Batch farrowing system is a concept for providing a group of sows that delivery within a specific farrowing interval and inducing a large enough scale of piglets to fill the weaner facilities. There are different types of batch farrowing system with batch size and interval of farrowing when several factors at the swine farm are considered such as total number of sows, available facilities in the farm, and the efficiency of workforce. Sow managements such as farrowing, weaning and breeding, every 3 weeks rather than weekly, 2 or 5-week interval have advantages for workers and reproductive cycle of sows as well as pig flow. Because there are several pros and cons both in weekly and batch management system, various factors should be considered to apply the most suitable management system in each individual farm. To improve poor swine productivity in Korea compared to ED, batch system for sows will be an alternative choice which is able to prevent high incidence of diseases in swine farm such as PMWS, PRRS, PRDC and PED because all-in/all-out pig management can be also applied automatically by using this management system.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.21 no.1
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• pp.15-21
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• 2021

Purpose: Urea cycle disorder (UCD) is an inherited inborn error of metabolism, acting on each step of urea cycle that cause various phenotypes. The purpose of the study was to investigate the long-term clinical consequences in different groups of UCD to characterize it. Methods: Twenty-two patients with UCD genetically confirmed were enrolled at Pusan National University Children's hospital and reviewed clinical features, biochemical and genetic features retrospectively. Results: UCD diagnosed in the present study included ornithine transcarbamylase deficiency (OTCD) (n=10, 45.5%), argininosuccinate synthase 1 deficiency (ASSD) (n=6, 27.3%), carbamoyl-phosphate synthetase 1 deficiency (CPS1D) (n=3, 13.6%), hyperornithinemia-hyperammonemia-homocitrullinuria syndrome (HHHS) (n=2, 9.1%), and arginase-1 deficiency (ARG1D) (n=1, 4.5%). The age at the diagnosis was 32.7±66.2 months old (range 0.1 to 228.0 months). Eight (36.4%) patients with UCD displayed short stature. Neurologic sequelae were observed in eleven (50%) patients with UCD. Molecular analysis identified 37 different mutation types (14 missense, 6 nonsense, 6 deletion, 6 splicing, 3 delins, 1 insertion, and 1 duplication) including 14 novel variants. Progressive growth impairment and poor neurological outcomes were associated with plasma isoleucine and leucine concentrations, respectively. Conclusion: Although combinations of treatments such as nutritional restriction of proteins and use of alternative pathways for discarding excessive nitrogen are extensively employed, the prognosis of UCD remains unsatisfactory. Prospective clinical trials are necessary to evaluate whether supplementation with BCAAs might improve growth or neurological outcomes and decrease metabolic crisis episodes in patients with UCD.