• Asian-Australasian Journal of Animal Sciences
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• 제27권10호
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• pp.1493-1498
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• 2014

Epigenetic factors, such as DNA methylation status, may regulate adipogenesis and lipogenesis, thus affecting intramuscular fat (IMF) deposition in longissimus dorsi muscle (LM) of beef cattle. In Korean cattle steers, the LM consists mainly of muscle tissue. However, the LM tissue also contains IMF. We compared the gene expression levels between the IMF and muscle portions of the LM after tissue separation. Real-time polymerase chain reaction analysis showed that the mRNA levels of both adipogenic peroxisome proliferator-activated receptor gamma isoform 1 (PPARG1) and lipogenic fatty acid binding protein 4 (FABP4) were higher (p<0.01) in the IMF than in the muscle portion of the LM. We determined DNA methylation levels of regulatory regions of the PPARG1 and FABP4 genes by pyrosequencing of genomic DNA. DNA methylation levels of two of three CpG sites in the PPARG1 gene promoter region were lower (p<0.05) in the IMF than in the muscle portion of the LM. DNA methylation levels of all five CpG sites from the FABP4 gene promoter region were also lower (p<0.001) in the IMF than in the muscle portion. Thus, mRNA levels of both PPARG1 and FABP4 genes were inversely correlated with DNA methylation levels in regulatory regions of CpG sites of the corresponding gene. Our findings suggest that DNA methylation status regulates tissue-specific expression of adipogenic and lipogenic genes in the IMF and muscle portions of LM tissue in Korean cattle.

• 상하수도학회지
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• 제30권1호
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• pp.19-31
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• 2016

The Saemangeum watershed is required to manage water pollution effectively but the effect of liquid manure (LM) on soil and water quality in the basin is not clearly identified as yet. This study aims at assessing the effect on soil of a rice field and water quality of water bodies near the rice field during rice-crop time period to find out the effect of LM, the effect of rainfall, and the effect of rice-crop environment on soil and water quality by analyzing data of nitrogen components. As a result of the LM distribution, $NO_3-N$ was much higher than other N components in the entire soil layers and it was accelerated by rainfall right after the LM distribution. Compared to chemical fertilizer (CF), LM was slightly affected but still influenced on the surface water quality. During weak rainfall, low nitrogen concentration in topsoil was resulted as NH3-N decreased and Org-N and $NO_3-N$ increased. $NO_3-N$ concentration in the water of irrigation canals increased with time. During intensive rainfall, $NO_3-N$ and Org-N of the soil were measured highly in the submerged condition, while the water quality of the rice field was lower due to flooding into the irrigation canal as well as the growth of the rice plants. Also, total nitrogen was increased more than 7 times and it showed serious water quality deterioration due to LM and excessive fertilizer distribution, and rainfall during all rice-crop processes. The effect of LM on water quality should be studied consistently to provide critical data while considering weather condition, cropping conditions, soil characteristics, and so on.

• 전자공학회논문지CI
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• 제47권3호
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• pp.76-82
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• 2010

본 논문은 수치적인 입출력데이터로부터 언어적인 규칙을 생성시키기 위한 체계적인 접근방법으로써 정보입자(information granules)에 근거한 언어적인 모델(LM: Linguistic Model)을 발전시킨다. Pedrycz에 의해 소개된 언어적인 모델은 컨텍스트 기반 퍼지 클러스터링(CFC: Context-based Fuzzy Clustering)으로부터 얻어지는 퍼지 정보입자에 의해 수행되어지며, 이는 입력과 출력공간과 연관된 클러스터 된 데이터들의 동질성을 보존하도록 클러스터를 추정한다. 언어적인 모델의 효능성은 이전 연구에서 이미 증명되었음에도 불구하고 성능 측면에서 개선시킬 필요성이 있다. 따라서, 본 논문에서는 기존 언어적인 모델의 근사화와 일반화 성능을 모두 향상시키기 위해 언어적인 컨텍스트의 자동적인 생성, 바이어스항의 추가, 결론부 파라미터의 변형된 구조를 통해 이루어진다. 실험결과는 자동차 연료소비량 예측문제와 보스턴 housing 데이터를 통해 제안된 방법이 언어적인 모델뿐만 아니라 기존 방법들보다 우수함을 증명한다.

• 전자공학회논문지
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• 제51권11호
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• pp.73-82
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• 2014

LM 알고리즘은 비선형 시스템의 least square problem을 풀기위해 사용되는 것으로, 다양한 분야에서 활용되고 있는 중요한 알고리즘이다. 하지만 응용 분야의 목적 함수가 복잡하고 고차원인 경우, 목적 함수의 연산 횟수가 많아지고, 내부에서 연산되는 행렬 및 벡터 연산에 시간이 많이 소요되어, 임베디드 환경에서의 실시간 동작을 위해서는 하드웨어 가속기 설계가 불가피하다. 본 논문에서는 LM 알고리즘을 하드웨어로 설계하였으며, 반복되는 목적 함수 연산을 파이프라인 처리 하고, 행렬 및 벡터 연산은 데이터 입력 주기를 줄여 속도를 향상시켰다. 설계한 LM 알고리즘의 하드웨어 성능을 측정하기 위해, 응용분야로 3D reconstruction의 한 부분인 refining fundamental matrix(RFM)를 적용하였다. 실험 결과 소프트웨어와 비슷한 정확도를 가지면서, 최대 74.3배의 속도 향상을 볼 수 있었다.

• 한국식품과학회지
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• 제31권6호
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• pp.1628-1634
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• 1999

Listeria monocytogenes의 식품 속에서 신속하고 특이적인 검출을 위하여, listeriolysin O gene에 의한 primer, LM 1과 LM 2를 선택하여 PCR을 수행하였다. L. monocytogenes의 DNA 추출이나 cell lysis 없이 intact whole cell을 직접 이용하여 PCR을 하였으며 $10^{2-6}$ CFU 수준의 균체 배양액으로부터 L. monocytogenes에 특이적인 702 bp의 PCR 증폭 산물을 확인하였다. 우유, 닭고기, 김치 등의 식품에 L. monocytogenes를 접종하여 증균배양 전후 균의 PCR에 대한 감도와 생균수를 비교한 결과, 실험된 식품 속에서의 L. monocytogenes의 검출 감도는 순수 배양액에서의 경우에 비해 약 1/10로 둔화되었으나 역시 특이적인 검출이 가능하였다. Primer LM 1과 2를 이용한 본 실험조건에서의 L. monocytogenes의 PCR에 의한 검출은 약 4시간으로 확인이 가능하였으며, 기존의 배양 방법에 비해, 특이성이나 검출 속도 면에서 식품위생 실무에 적용하기 위한 높은 잠재력을 보여 주었다.

• Brain Tumor Research and Treatment
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• 제6권2호
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• pp.54-59
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• 2018

Background Leptomeningeal metastasis (LM) is an uncommon, but devastating complication of advanced cancer and has no standard treatment. Herein, we analyzed the clinical characteristics and outcomes of patients with solid tumors who were diagnosed with LM. Methods Between January 2007 and December 2017, we retrospectively analyzed the medical records of patients with solid tumors who were diagnosed with LM. Results A total of 58 patients were enrolled in this study. The median age of patients was 51 years (range, 27-72 years), and 62.1% had a poor Eastern Cooperative Oncology Group (ECOG) performance status (PS) (>2). The common types of primary tumor were breast cancer (39.7%), gastric cancer (25.9%), and non-small cell lung cancer (20.7%). Forty-two patients (72.4%) were diagnosed with LM by MRI of the brain and/or spine and cerebrospinal fluid (CSF) analysis, 14 were diagnosed by CSF analysis alone, and 2 were diagnosed by MRI alone. Treatments for LM were performed in 53 patients (91.4%), and best supportive care was provided for 5 patients (8.6%). Intrathecal chemotherapy, radiotherapy, and systemic chemotherapy were administered in 43 (74.1%), 17 (29.3%), and 24 (41.4%) patients, respectively. The median overall survival of the entire cohort was 2.4 months (95% confidence interval, 1.0-3.7). In the analysis of prognostic factors for survival, a good ECOG PS (${\leq}2$), administration of systemic chemotherapy after LM diagnosis, and a prior history of brain radiation were associated with prolonged survival. Conclusion Although the prognosis of LM in patients with solid tumors is poor, systemic chemotherapy might improve survival in selected patients with a good PS.

• Journal of Chest Surgery
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• 제55권5호
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• pp.397-404
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• 2022

Background: Distant recurrence of esophageal cancer (EC), even after radical resection, is common, and the most frequent site of EC metastasis is the liver. However, a multidisciplinary treatment strategy for postoperative liver metastasis (LM) from EC has yet to be established; in particular, the role of liver-directed therapy (LDT) remains uncertain. We investigated the clinicopathological features and outcomes of patients undergoing post-esophagectomy LM with versus without LDT to explore its therapeutic implications. Methods: Among 624 consecutive patients undergoing R0/R1 esophagectomy for EC, 30 were identified in whom LM had developed as the initial recurrence. Their characteristics were retrospectively reviewed. Results: Six of the 30 subjects underwent LDT for metachronous LM. Five of those 6 also received systemic chemotherapy. A comparison between the 6 LDT and 24 non-LDT cases revealed no significant differences in major clinicopathological and operative factors, except for concurrent metastasis to extrahepatic organs (1/6 vs. 15/24, p=0.044). Twenty-nine of the 30 patients died during the study period, whereas 1 who had received multimodal treatment with LDT remained alive more than 200 months after multiple LM had been detected. Kaplan-Meier analysis for survival after LM demonstrated significantly prolonged survival in LDT cases compared to non-LDT cases treated with systemic chemotherapy alone (p=0.014). Even when the analysis was limited to patients without extrahepatic metastasis, this significant prognostic advantage of LDT was maintained (p=0.047). Conclusion: Multimodal treatment combined with LDT might be beneficial for patients with metachronous LM from EC and should therefore be considered a potential treatment option.

• Investigative Magnetic Resonance Imaging
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• 제26권1호
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• pp.32-42
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• 2022

Purpose: To evaluate the clinical benefit of 2D contrast-enhanced T2 fluid-attenuated inversion recovery (CE-T2 FLAIR) image for detecting leptomeningeal metastasis (LM) in the brain metastasis work-up for lung cancer. Materials and Methods: From June 2017 to July 2019, we collected all consecutive patients with lung cancer who underwent brain magnetic resonance image (MRI), including contrast-enhanced 3D fast spin echo T1 black-blood image (CE-T1WI) and CE-T2 FLAIR; we recruited clinico-radiologically suspected LM cases. Two independent readers analyzed the images for LM in three sessions: CE-T1WI, CE-T2 FLAIR, and their combination. Results: We recruited 526 patients with suspected lung cancer who underwent brain MRI; of these, we excluded 77 (insufficient image protocol, unclear pathology, different contrast media, poor image quality). Of the 449 patients, 34 were clinico-radiologically suspected to have LM; among them, 23 were diagnosed with true LM. The calculated detection performance of CE-T1WI, CE-T2 FLAIR, and combined analysis obtained from the 34 suspected LM were highest in the combined analysis (AUC: 0.80, 0.82, and 0.89, respectively). The inter-observer agreement was also the highest in the combined analysis (0.68, 0.72, and 0.86, respectively). In quantitative analyses, CNR of CE-T2 FLAIR was significantly higher than that of CE-T1WI (Wilcoxon signed rank test, P < 0.05). Conclusion: Adding CE-T2 FLAIR might provide better detection for LM in the brain-metastasis screening for lung cancer.

• Journal of Korean Neurosurgical Society
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• 제66권4호
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• pp.465-475
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• 2023

Objective : Our objective is to analyze the occurrence, clinical course and risk factors for glioma patients with leptomeningeal metastasis (LM) according to different metastasis patterns and clinical variables. Methods : We retrospectively reviewed data from 376 World Health Organization (WHO) grade II-IV adult glioma patients who were treated in the National Cancer Center from 2001 to 2020. Patients who underwent surgery at other institutions, those without initial images or those with pathologically unconfirmed cases were excluded. LM was diagnosed based on magnetic resonance imaging (MRI) findings or cerebrospinal fluid (CSF) cytology. The metastasis pattern was categorized as nodular or linear according to the enhancement pattern. Tumor proximity to the CSF space was classified as involved or separated, whereas location of the tumor was dichotomized as midline, for tumors residing in the thalamus, basal ganglia and brainstem, or lateral, for tumors residing in the cerebral and cerebellar hemispheres. Results : A total of 138 patients were enrolled in the study. A total of 44 patients (38%) were diagnosed with LM during a median follow-up of 9 months (range, 0-60). Among the clinical variables, tumor proximity to CSF space, the location of the tumor and the WHO grade were significant factors for LM development in univariate analysis. In multivariate analysis, the midline location of the tumor and WHO grade IV gliomas were the most significant factor for LM development. The hazard ratio was 2.624 for midline located gliomas (95% confidence interval [CI], 1.384-4.974; p=0.003) and 3.008 for WHO grade IV gliomas (95% CI, 1.379-6.561; p=0.006). Conclusion : Midline location and histological grading are an important factor for LM in glioma patients. The proximity to the CSF circulation pathway is also an important factor for WHO grade IV glioma LM. Patients carrying high risks should be followed up more thoroughly.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
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• pp.448-453
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• 2023

대규모 언어 모델 (Large Language Model, LLM)을 인간의 선호도 관점에서 평가하는 것은 기존의 벤치마크 평가와는 다른 도전적인 과제이다. 이를 위해, 기존 연구들은 강력한 LLM을 평가자로 사용하여 접근하였지만, 높은 비용 문제가 부각되었다. 또한, 평가자로서 LLM이 사용하는 주관적인 점수 기준은 모호하여 평가 결과의 신뢰성을 저해하며, 단일 모델에 의한 평가 결과는 편향될 가능성이 있다. 본 논문에서는 엄격한 기준을 활용하여 편향되지 않은 평가를 수행할 수 있는 평가 프레임워크 및 평가자 모델 'FubaoLM'을 제안한다. 우리의 평가 프레임워크는 심층적인 평가 기준을 통해 다수의 강력한 한국어 LLM을 활용하여 연쇄적 사고(Chain-of-Thought) 기반 평가를 수행한다. 이러한 평가 결과를 다수결로 통합하여 편향되지 않은 평가 결과를 도출하며, 지시 조정 (instruction tuning)을 통해 FubaoLM은 다수의 LLM으로 부터 평가 지식을 증류받는다. 더 나아가 본 논문에서는 전문가 기반 평가 데이터셋을 구축하여 FubaoLM 효과성을 입증한다. 우리의 실험에서 앙상블된 FubaoLM은 GPT-3.5 대비 16% 에서 23% 향상된 절대 평가 성능을 가지며, 이항 평가에서 인간과 유사한 선호도 평가 결과를 도출한다. 이를 통해 FubaoLM은 비교적 적은 비용으로도 높은 신뢰성을 유지하며, 편향되지 않은 평가를 수행할 수 있음을 보인다.