• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.111-126
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• 2022

Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.

• Korean Journal of Organic Agriculture
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• v.29 no.1
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• pp.85-96
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• 2021

Reflux esophagitis (RE) is a common gastrointestinal disease observed at all ages, which seriously affects the quality of life. In this study, we investigated the anti-inflammatory effects of Pomacea canaliculata extract (PCE) using the experimental RE rat model. RE was induced by a surgical procedure. The rats were randomly divided into 4 groups: normal group, RE group, PCE group (RE treated with PCE, 100 mg/kg), positive control group (RE treated with ranitidine, 40 mg/kg). We performed the histological examination and measured the expression of tight junction complex and inflammatory mediators using western blot analysis. The phenotypes of RE were attenuated by PCE treatment. PCE administration significantly reduced esophageal mucosal damage and protected tight junction confirmed by claudin-5. Furthermore, PCE treatment reduced inflammatory reaction by inhibiting the expression of COX-2 and TNF-α. PCE treatment, also, reduced translocation of NF-κB into nuclear and IκB-α phosphorylation at the same time. Our findings indicate that PCE has the potential as a novel therapeutic agent to inhibit RE by protecting mucosal damage and regulating inflammatory reactions mediated by NF-κB signaling.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.36 no.1
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• pp.1-20
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• 2023

Objectives : The purpose of this study was to evaluate the anti-inflammatory effect of Tanghwajitongsan(THJTS) through inhibition of NF-κB and MAPK. Methods : We evaluated cell survival rate by MTT assay, NO production by nitrite content in the culture medium. We quantified TNF-α, IL-1β, IL-6 and PGE₂ of the cultured supernatant by ELISA. And we evaluated the effect of THJTS on protein expression of NF-κB, MAPK, iNOS and COX-2 by Western blot analysis. THJTS ameliorates LPS-activated alterations in protein expression of NF-κB, p-38, iNOS and COX-2 and production of NO, pro-inflammatory cytokines and PGE₂. Also, THJTS ameliorates LOX, PGN and FLA-activated alterations in protein expression of NO, iNOS. THJTS ameliorates only PGN-activated alterations in protein expression of COX-2. Results : THJTS ameliorates LPS-activated alterations in protein expression of NF-κB, p-38, iNOS and COX-2 and production of NO, pro-inflammatory cytokines and PGE₂. Also, THJTS ameliorates LOX, PGN and FLA-activated alterations in protein expression of NO, iNOS. THJTS ameliorates only PGN-activated alterations in protein expression of COX-2. Conclusions : This study can provide scientific evidence for the anti-inflammatory effects and underlying mechanisms of THJTS.

• Journal of Periodontal and Implant Science
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• v.52 no.2
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• pp.127-140
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• 2022

Purpose: In dental avulsion, delayed replantation usually has an uncertain prognosis. After tooth replantation, complex inflammatory responses promote a return to periodontal tissue homeostasis. Various types of cytokines are produced in the inflammatory microenvironment, and these cytokines determine the periodontal tissue response. This study aimed to identify the gene expression profiles of replanted teeth and evaluate the functional differences between immediate and delayed replantation. Methods: Maxillary molars from Sprague-Dawley rats were extracted, exposed to a dry environment, and then replanted. The animals were divided into 2 groups according to the extra-oral time: immediate replantation (dry for 5 minutes) and delayed replantation (dry for 60 minutes). Either 3 or 7 days after replantation, the animals were sacrificed. Periodontal soft tissues were harvested for mRNA sequencing. Hallmark gene set enrichment analysis was performed to predict the function of gene-gene interactions. The normalized enrichment score (NES) was calculated to determine functional differences. Results: The hallmark gene sets enriched in delayed replantation at 3 days were oxidative phosphorylation (NES=2.82, Q<0.001) and tumor necrosis factor-alpha (TNF-α) signaling via the nuclear factor kappa light chain enhancer of activated B cells (NF-κB) pathway (NES=1.52, Q=0.034). At 7 days after delayed replantation, TNF-α signaling via the NF-κB pathway (NES=-1.82, Q=0.002), angiogenesis (NES=-1.66, Q=0.01), and the transforming growth factor-beta signaling pathway (NES=-1.46, Q=0.051) were negatively highlighted. Conclusions: Differentially expressed gene profiles were significantly different between immediate and delayed replantation. TNF-α signaling via the NF-κB pathway was marked during the healing process. However, the enrichment score of this pathway changed in a time-dependent manner between immediate and delayed replantation.

• Animal Bioscience
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• v.35 no.6
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• pp.927-937
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• 2022

Objective: Frankfurters are emulsion-type sausages that are widely consumed worldwide. However, some concerns regarding negative health effects have been raised because of the high fat content and the type of fat. This study aimed to evaluate the effects of duck fat and κ-carrageenan as replacements for beef fat and pork backfat in frankfurters. Methods: The different formulations for the frankfurters were as follows: 20% beef fat (BF), 20% pork backfat (PBF), 20% duck fat (DF), 20% soybean oil (SO), 20% duck fat/1% κ-carrageenan (DFC), and 20% soybean oil/1% κ-carrageenan (SOC). Physicochemical (fatty acid profile, color, rheological properties, cooking loss, water holding capacity, emulsion stability, and texture profile analysis), oxidative stability and sensory properties of frankfurters were evaluated. Results: Duck fat and κ-carrageenan improved rheological properties of meat batter, and physicochemical properties (emulsion stability, cooking loss, and hardness) of frankfurters. Moreover, duck fat added-frankfurters (DF and DFC) had higher oxidative stability than that of soybean-added frankfurters (SO and SOC) during refrigerated storage for 28 days. In sensory evaluation, flavor, texture, and overall acceptability of DFC were acceptable to untrained panelists. Conclusion: Our data suggest that duck fat and κ-carrageenan can replace beef fat and pork backfat in frankfurters. Duck fat and κ-carrageenan contributed to improve the physicochemical properties and oxidative stability while maintaining sensory properties. Therefore, the use of duck fat and κ-carrageenan may be a suitable alternative for replacing beef fat or pork backfat in frankfurters.

• Restorative Dentistry and Endodontics
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• v.48 no.2
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• pp.16.1-16.11
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• 2023

Objectives: The aim of this study was to evaluate the influence of peak kilovoltage (kVp) and a metal artifact reduction (MAR) tool on image quality and the diagnosis of vertical root fracture (VRF) in cone-beam computed tomography (CBCT). Materials and Methods: Twenty single-rooted human teeth filled with an intracanal metal post were divided into 2 groups: control (n = 10) and VRF (n = 10). Each tooth was placed into the socket of a dry mandible, and CBCT scans were acquired using a Picasso Trio varying the kVp (70, 80, 90, or 99), and the use of MAR (with or without). The examinations were assessed by 5 examiners for the diagnosis of VRF using a 5-point scale. A subjective evaluation of the expression of artifacts was done by comparing random axial images of the studied protocols. The results of the diagnoses were analyzed using 2-way analysis of variance and the Tukey post hoc test, the subjective evaluations were compared using the Friedman test, and intra-examiner reproducibility was evaluated using the weighted kappa test (α = 5%). Results: The kVp and MAR did not influence the diagnosis of VRF (p > 0.05). According to the subjective classification, the 99 kVp protocol with MAR demonstrated the least expression of artifacts, while the 70 kVp protocol without MAR led to the most artifacts. Conclusions: Protocols with higher kVp combined with MAR improved the image quality of CBCT examinations. However, those factors did not lead to an improvement in the diagnosis of VRF.

• Journal of Animal Science and Technology
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• v.65 no.1
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• pp.183-196
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• 2023

Interferon-alpha inducible protein 6 (IFI6) is an interferon-stimulated gene (ISG), belonging to the FAM14 family of proteins and is localized in the mitochondrial membrane, where it plays a role in apoptosis. Transcriptional regulation of this gene is poorly understood in the context of inflammation by intracellular nucleic acid-sensing receptors and pathological conditions caused by viral infection. In this study, chicken IFI6 (chIFI6) was identified and studied for its molecular features and transcriptional regulation in chicken cells and tissues, i.e., lungs, spleens, and tracheas from highly pathogenic avian influenza virus (HPAIV)-infected chickens. The chIFI6-coding sequences contained 1638 nucleotides encoding 107 amino acids in three exons, whereas the duck IFI6-coding sequences contained 495 nucleotides encoding 107 amino acids. IFI6 proteins from chickens, ducks, and quail contain an IF6/IF27-like superfamily domain. Expression of chIFI6 was higher in HPAIV-infected White Leghorn chicken lungs, spleens, and tracheas than in mock-infected controls. TLR3 signals regulate the transcription of chIFI6 in chicken DF-1 cells via the NF-κB and JNK signaling pathways, indicating that multiple signaling pathways differentially contribute to the transcription of chIFI6. Further research is needed to unravel the molecular mechanisms underlying IFI6 transcription, as well as the involvement of chIFI6 in the pathogenesis of HPAIV in chickens.

• Journal of Veterinary Science
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• v.24 no.3
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• pp.23.1-23.16
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• 2023

Background: Irritable bowel syndrome (IBS) is a functional bowel disorder (FBD). Objectives: To assess the therapeutic effects of paeoniflorin (PF) on IBS in rats. Method: Sixty male Sprague-Dawley rats were randomly divided into normal, model, positive drug, low-dose PF, medium-dose PF and high-dose PF groups (n = 10). After gavage for 2 consecutive weeks, the effect of PF on abdominal pain symptoms was assessed based on the abdominal withdrawal reflex (AWR) score, fecal water content and pathological changes in colon tissues. D-lactate, interleukin-1β (IL-1β), transforming growth factor-β (TGF-β) and tumor necrosis factor-α (TNF-α) were detected by enzyme-linked immunosorbent assay, and phosphorylated nuclear factor kappa B (p-NF-κB) p65 was detected by Western blotting. The abundance and diversity changes of intestinal flora were explored using 16S ribosomal RNA sequencing. Result: In PF groups, the mucosal morphology of colon tissues was intact, and the glands were arranged neatly and structured clearly, without obvious inflammatory cell infiltration. Compared with the model group, PF groups had significantly elevated pain threshold, and mRNA and protein levels of zonula occludens-1 (ZO-1) and occludin, decreased AWR score at 20 mmHg pressure, fecal water content, mRNA levels of IL-1β, TGF-β, and TNF-α, protein level of p-NF-κB p65 and level of serum D-lactate, and reduced levels of serum IL-1β, TGF-β, and TNF-α (p < 0.05, p < 0.01). PF groups had higher abundance of Lactobacillus, Akkermansia, Alistipes, and Bacteroides, but lower abundance of Desulfovibrio, Parasutterella, and Enterococcus than those of the model group. Conclusions: PF exerts therapeutic effects on IBS in rats probably by regulating the intestinal flora, and then up-regulating the expressions of ZO-1 and occludin in colon tissue while down-regulating the levels of IL-1β, TGF-β, TNF-α, D-lactate and p-NF-κB p65.

• Journal of Korean Society of Rural Planning
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• v.28 no.1
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• pp.57-69
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• 2022

Crop classification is very important for estimating crop yield and figuring out accurate cultivation area. The purpose of this study is to classify crops harvested in fall in Idam-ri, Goesan-gun, Chungcheongbuk-do by using unmanned aerial vehicle (UAV) images and support vector machine (SVM) model. The study proceeded in the order of image acquisition, variable extraction, model building, and evaluation. First, RGB and multispectral image were acquired on September 13, 2021. Independent variables which were applied to Farm-Map, consisted gray level co-occurrence matrix (GLCM)-based texture characteristics by using RGB images, and multispectral reflectance data. The crop classification model was built using texture characteristics and reflectance data, and finally, accuracy evaluation was performed using the error matrix. As a result of the study, the classification model consisted of four types to compare the classification accuracy according to the combination of independent variables. The result of four types of model analysis, recursive feature elimination (RFE) model showed the highest accuracy with an overall accuracy (OA) of 88.64%, Kappa coefficient of 0.84. UAV-based RGB and multispectral images effectively classified cabbage, rice and soybean when the SVM model was applied. The results of this study provided capacity usefully in classifying crops using single-period images. These technologies are expected to improve the accuracy and efficiency of crop cultivation area surveys by supplementing additional data learning, and to provide basic data for estimating crop yields.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.