• Journal of the Korean Society of Radiology
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• v.82 no.3
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• pp.654-669
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• 2021

Purpose To evaluate the accuracy of MRI in predicting the pathological complete response (pCR) and the residual tumor size of breast cancer after neoadjucant chemotherapy (NAC), and to determine the factors affecting the accuarcy. Materials and Methods Eighty-eight breast cancer patients who underwent surgery after NAC at our center between 2010 and 2017 were included in this study. pCR was defined as the absence of invasive cancer on pathological evaluation. The maximum diameter of the residual tumor on post-NAC MRI was compared with the tumor size of the surgical specimen measured pathologically. Statistical analysis was performed to elucidate the factors affecting pCR and the residual tumor size-discrepancy between the MRI and the pathological measurements. Results The pCR rate was 10%. The diagnostic accuracy of MRI and the area under the curve for predicting pCR were 90.91% and 0.8017, respectively. The residual tumor sizes obtained using MRI and pathological measurements showed a strong correlation (r = 0.9, p < 0.001), especially in patients with a single mass lesion (p = 0.047). The size discrepancy between MRI and the pathological measurements was significantly greater in patients with the luminal type (p = 0.023) and multifocal tumors/non-mass enhancement on pre-NAC MRI (p = 0.047). Conclusion MRI is an accurate tool for evaluating pCR and residual tumor size in breast cancer patients who receive NAC. Tumor subtype and initial MRI features affect the accuracy of MRI.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.807-820
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• 2023

Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. Materials and Methods: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1-7 according to acquisition conditions. CT images in groups 2-7 were converted into the target CT style (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. Results: Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2-7 improved after CT conversion (original vs. converted: 0.63 vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists' scores were significantly higher (P < 0.001) and less variable on converted CT. Conclusion: CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.

• Korean Journal of Radiology
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• v.23 no.2
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• pp.226-236
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• 2022

Objective: This study aimed to explore the myelin volume change in patients with mild traumatic brain injury (mTBI) with post-concussion syndrome (PCS) using a multidynamic multiecho (MDME) sequence and automatic whole-brain segmentation. Materials and Methods: Forty-one consecutive mTBI patients with PCS and 29 controls, who had undergone MRI including the MDME sequence between October 2016 and April 2018, were included. Myelin volume fraction (MVF) maps were derived from the MDME sequence. After three dimensional T1-based brain segmentation, the average MVF was analyzed at the bilateral cerebral white matter (WM), bilateral cerebral gray matter (GM), corpus callosum, and brainstem. The Mann-Whitney U-test was performed to compare MVF and myelin volume between patients with mTBI and controls. Myelin volume was correlated with neuropsychological test scores using the Spearman rank correlation test. Results: The average MVF at the bilateral cerebral WM was lower in mTBI patients with PCS (median [interquartile range], 25.2% [22.6%-26.4%]) than that in controls (26.8% [25.6%-27.8%]) (p = 0.004). The region-of-interest myelin volume was lower in mTBI patients with PCS than that in controls at the corpus callosum (1.87 cm³ [1.70-2.05 cm³] vs. 2.21 cm³ [1.86-3.46 cm³]; p = 0.003) and brainstem (9.98 cm³ [9.45-11.00 cm³] vs. 11.05 cm³ [10.10-11.53 cm³]; p = 0.015). The total myelin volume was lower in mTBI patients with PCS than that in controls at the corpus callosum (0.45 cm³ [0.39-0.48 cm³] vs. 0.48 cm³ [0.45-0.54 cm³]; p = 0.004) and brainstem (1.45 cm³ [1.28-1.59 cm³] vs. 1.54 cm³ [1.42-1.67 cm³]; p = 0.042). No significant correlation was observed between myelin volume parameters and neuropsychological test scores, except for the total myelin volume at the bilateral cerebral WM and verbal learning test (delayed recall) (r = 0.425; p = 0.048). Conclusion: MVF quantified from the MDME sequence was decreased at the bilateral cerebral WM in mTBI patients with PCS. The total myelin volumes at the corpus callosum and brainstem were decreased in mTBI patients with PCS due to atrophic changes.

• Journal of Food Hygiene and Safety
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• v.39 no.1
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• pp.44-53
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• 2024

Global interest in natural functional materials to strengthen human immunity is increasing due to the increase in immune-related diseases associated with COVID-19 and the aging population. In this study, we determined the potential therapeutic effect of Eleutherococcus senticosus stems on immune enhancement according to the cultivation region. The contents of eleutheroside B and E, which are chemical components of E. senticosus stems, were analyzed. We showed that the eleutheroside B content of E. senticosus stems in different cultivation regions ranged from 2.96±0.11 to 6.24±0.05 mg/g and from 1.11±0.05 to 2.11±0.03 mg/g in 70% ethanol and hot water extracts, respectively. The eleutheroside E content ranged from 4.93±0.20 to 10.79±0.03 mg/g and 1.75±0.14 to 3.64±0.05 mg/g in 70% ethanol and hot water extracts, respectively. In addition, the immunomodulatory effect of E. senticosus stems was evaluated using RAW 264.7 macrophages. The 70% ethanol extract of E. senticosus stems showed no cytotoxicity up to 200 ㎍/mL, and the hot water extract showed no cytotoxicity up to 500 ㎍/mL. Additionally, the E. senticosus stem extract significantly increased the production of nitric oxide and cytokines (TNF-α, IL-6, and IL-1β) compared to their production in the control group. These results suggest that E. senticosus stem extracts are a potential functional food material and ingredient to enhance the immune response.

• Journal of Food Hygiene and Safety
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• v.39 no.1
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• pp.9-15
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• 2024

This study was performed to survey the distribution of Listeria spp. in fresh agricultural products in the Busan area, the Republic of Korea, from January to November 2022. We investigated the pathogenicity and epidemiological relationships by tracing isolated strains using polymerase chain reaction and pulsed-field gel electro-phoresis (PFGE) methods. Forty cases of Listeria spp. were detected in the 210 samples of fresh agricultural products analyzed. Four species, Listeria rocourtiae, L. innocua, L. grayi, and L. monocytogenes were detected only in green vegetables (lettuce, perilla leaps) and the others (L. innocua, L. monocytogenes, and L. grayi) were detected in enoki and oyster mushrooms. L. innocua was detected in 22 samples and L. grayi in six samples. L. monocytogenes, which causes foodborne diseases, was only detected in enoki mushrooms and the strains that were isolated had genes responsible for the pathogenicity of listeriosis (iap, prfA, inlA, inlC, inlJ, and hly). To investigate the genetic similarity and contamination route of L. monocytogenes, serotyping and PFGE were conducted for 12 strains isolated from fresh agricultural (10 strains) and poultry (2 strains) products distributed at a market in the Busan area. Two serotypes (1/2a, 1/2b) were detected in strains isolated from the agricultural and poultry products, but serotype 1/2b was only detected in strains isolated from agricultural products. PFGE analysis showed index of similarity values of 45.7 to 100% and the same patterns were represented in isolates from some enoki mushrooms. These isolates had the same serotypes and showed significant epidemiological relationships.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2094-2123
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• 2021

Incidental thyroid nodules are commonly detected on ultrasonography (US). This has contributed to the rapidly rising incidence of low-risk papillary thyroid carcinoma over the last 20 years. The appropriate diagnosis and management of these patients is based on the risk factors related to the patients as well as the thyroid nodules. The Korean Society of Thyroid Radiology (KSThR) published consensus recommendations for US-based management of thyroid nodules in 2011 and revised them in 2016. These guidelines have been used as the standard guidelines in Korea. However, recent advances in the diagnosis and management of thyroid nodules have necessitated the revision of the original recommendations. The task force of the KSThR has revised the Korean Thyroid Imaging Reporting and Data System and recommendations for US lexicon, biopsy criteria, US criteria of extrathyroidal extension, optimal thyroid computed tomography protocol, and US follow-up of thyroid nodules before and after biopsy. The biopsy criteria were revised to reduce unnecessary biopsies for benign nodules while maintaining an appropriate sensitivity for the detection of malignant tumors in small (1-2 cm) thyroid nodules. The goal of these recommendations is to provide the optimal scientific evidence and expert opinion consensus regarding US-based diagnosis and management of thyroid nodules.

• Journal of Food Hygiene and Safety
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• v.39 no.3
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• pp.288-298
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• 2024

This study aimed to investigate the amino acid content, fatty acid composition, total flavonoid and phenol contents, and antioxidant activities of Prunus yedoensis Matsum. bark extracts using various extraction solvents. Through amino acid analysis, 13 amino acids were detected in extracts obtained using hot water, 30% ethanol, and 70% ethanol. The major amino acids were identified as aspartic acid, arginine, and proline, and the total amino acid content was 0.17%, 0.16%, and 0.09%, respectively. Fatty acid analysis showed a saturated fatty acid (SFA) ratio of 62.7-66.7% in extracts obtained using hot water, 30% ethanol, and 70% ethanol, with the primary fatty acid identified as palmitic acid. The total flavonoid and polyphenol contents were 727.70-769.87 mg quercetin equivalent (QE)/ g and 309.24-348.09 mg gallic acid equivalent (GAE)/g, respectively, in extracts obtained using hot water, 30% ethanol, and 70% ethanol extracts. Measurements of antioxidant activity confirmed that extracts obtained using hot water, 30% ethanol, and 70% ethanol extracts increased the antioxidant effect in 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activity, and ferric reducing antioxidant power (FRAP) in a concentration-dependent manner. A high correlation was observed between the total flavonoid content, total polyphenol content, and antioxidant activities of the extracts. This study provides data and novel insights for the development of functional food materials using P. yedoensis Matsum. bark extracts.

• CELLMED
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• v.8 no.1
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• pp.5.1-5.4
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• 2018

Pharmacopuncture, or herbal acupuncture, is a new form of therapy derived from combinations of two traditional therapeutic methods, herbal medicine and acupuncture therapy. To compare the efficacy between loratadine-pharmacopuncture (LP) and loratadine-oral administration (LO), the effect of loratadine was investigated in murine models. Anti-anaphylactic effects of loratadine treatments were investigated in compound 48/80-induced systemic anaphylactic reaction and passive cutaneous anaphylaxis (PCA). LP treatment significantly inhibited the compound 48/80-induced systemic anaphylactic reaction and PCA. The effect between LP and LO were on a similar level. These results indicate that LP can be used as an alternative method for LO in case of emergency.

• Journal of Korean Society of Forest Science
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• v.13 no.1
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• pp.25-39
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• 1971

Recently successful induction of haploid plant by means of anther culture method has become a big topic among geneticists and plant breeders. The haploid plant can be used as a precious material for such basic researches as mutation or genetics. Once the haploid is obtained, production of homozygous plant is not a difficult problem. The method of producing homozygous plant can, also, be applied to the practical breeding works. When applied to the hybridization of self-fertilizing breeding period would be greatly shortened and in cross-fertilizing vegetables production of uniform hybrid seed would be very easily obtained. Last few years many scientists attempted anther cultures using various plant species, but it was successful only in several species. Unlike the other tissue cultures which use somatic organs or tissues as explants, anther culture seems to be very difficult because the plants or calli have to be induced from the haploid microspores or pollen grains. In the present experiment anther culture of fruit trees and ornamental shrubs of four genera and seven species was attemped. Anthers of Various stages ranging from tetrad and late microspore were cultured on the modified Murashige and Skoog's medium supplemented with various concentrations of auxins and kinetin as growth regulators. Handling of materials, sterilization, and other operations of culture were done by routine methods. The results were summarized as follows: 1. Calli were induced in the anthers of Forsythia Koreana Nak., Rhododendron mucronuratum Turcz., R. yedoense Max. var. Poukhanense Nak., and Prunus armeniaca L. var. ansu Max. No signs of callus were observed in Prunus persica Sieb. et Zucc. var. vurgaris Max., Pyrus ussuriensis var. macrostipes (Nak.), and Prunus salcina Lindley. 2. Calli were easily formed in any of the media with differing concentrations of auxins and kinetin. 3. In F. Koreana calli developed from anther surface and connective. Callus emerging out of anther locule was not observed. 4. Somatic calli arose from filament, connective, and inside of anther wall in R. mucronulatum. Many of the microspores accumulated starch grains. 5. The anther lobes located opposite the filament of R. yedoense turned easily to calli. This phenomenon was not observed in R. mucronulatum. Microspore embedded for a period in the medium became starch pollen. No callus was observed arising from microspore. 6. In P. armeniaca calli were not induced from somatic anther tissues. Instead, callus emerged out of anther locule rupturing the anther slit. Starch was not formed in the microspore. 7. In P. persica, Pyrus ussuriensis, and P. salcina, calli were not observed in the anthers examined more than 60 days after culture. Microspores of these species, however, were free of starch grains even after long period of subculture. 8. It was learned that somatic calli of the species examined arose usually from endothelium of anther wall, septum of two neighboring anther locules, parenchyma tissues of connectives, or anther lobes. 9. In the anther locule of P. armeniaca cultured long in medium, swollen microspores, polynucleate microspores, multicellular pollen grains, or callus mass were frequently observed, this indicating that the callus of this species was microspore-origin. 10. It was clarified that in P. armeniaca production of haploid plant by anther culture might be possible.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.