• Asian Pacific Journal of Cancer Prevention
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• 제14권5호
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• pp.3223-3228
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• 2013

Gene expression profiling (GEP) has identified several molecular subtypes of breast cancer, with different clinico-pathologic features and exhibiting different responses to chemotherapy. However, GEP is expensive and not available in the developing countries where the majority of patients present at advanced stage. The St Gallen Consensus in 2011 proposed use of a simplified, four immunohistochemical (IHC) biomarker panel (ER, PR, HER2, Ki67/Tumor Grade) for molecular classification. The present study was conducted in 75 newly diagnosed patients of breast cancer with large (>5cm) tumors to evaluate the association of IHC surrogate molecular subtype with the clinical response to presurgical chemotherapy, evaluated by the WHO criteria, 3 weeks after the third cycle of 5 flourouracil, adriamycin, cyclophosphamide (FAC regimen). The subtypes of luminal, basal-like and HER2 enriched were found to account for 36.0 % (27/75), 34.7 % (26/75) and 29.3% (22/75) of patients respectively. Ten were luminal A and 14 luminal B (8 HER2 negative and 6HER2 positive). The triple negative breast cancer (TNBC) was most sensitive to chemotherapy with 19% achieving clinical-complete-response (cCR) followed by HER2 enriched (2/22 (9%) cCR), luminal B (1/6 (7%) cCR) and luminal A (0/10 (0%) cCR). Heterogeneity was observed within each subgroup, being most marked in the TNBC although the most responding tumors, 8% developing clinical-progressive-disease. The study supports association of molecular subtypes with response to chemotherapy in patients with advanced breast cancer and the existence of further heterogeneity within subtypes.

• 한국정보통신학회논문지
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• 제25권8호
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• pp.1046-1052
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• 2021

4차 산업의 발전과 고성능의 컴퓨팅 환경 구축으로 다양한 산업분야에서 인공지능이 적용되고 있다. 의료분야에서는 X-Ray, MRI, PET 등의 의료 영상 및 임상 자료를 이용하여 암, COVID-19, 골 연령 측정 등의 딥 러닝 학습이 진행되었다. 또한 스마트 의료기기, IoT 디바이스와 딥 러닝 알고리즘을 적용하여 ICT 의료 융합 기술 등이 연구되고 있다. 이러한 기술 중 의료 영상 기반 딥 러닝 학습은 의료 영상의 바이오마커를 정확히 찾아내고, 최소한의 손실률과 높은 정확도가 필요하다. 따라서 본 논문은 흉부 X-Ray 이미지 기반 딥 러닝 학습 과정에서 손실률을 도출하는 손실 함수 중 영상분류 알고리즘에서 사용되는 Cross-Entropy 함수들의 성능을 비교·분석하고자 한다.

• 대한의용생체공학회:의공학회지
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• 제44권1호
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• pp.25-32
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• 2023

Recognizing the size and location of prostate cancer is critical for prostate cancer diagnosis, treatment, and predicting prognosis. This paper proposes a model to classify the tumor region and normal tissue with cross-sectional visual images of prostatectomy tissue. We used specimen images of 44 prostate cancer patients who received prostatectomy at Gachon University Gil Hospital. A total of 289 prostate slice images consist of 200 slices including tumor region and 89 slices not including tumor region. Images were divided based on the presence or absence of tumor, and a total of 93 features from each slice image were extracted using Radiomics: 18 first order, 24 GLCM, 16 GLRLM, 16 GLSZM, 5 NGTDM, and 14 GLDM. We compared feature selection techniques such as LASSO, ANOVA, SFS, Ridge and RF, LR, SVM classifiers for the model's high performances. We evaluated the model's performance with AUC of the ROC curve. The results showed that the combination of feature selection techniques LASSO, Ridge, and classifier RF could be best with an AUC of 0.99±0.005.

• 대한의용생체공학회:의공학회지
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• 제43권4호
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• pp.185-192
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• 2022

Early detection of mild cognitive impairment can help prevent the progression of dementia. The purpose of this study was to design and validate a machine learning model that automatically differential diagnosed patients with mild cognitive impairment and identified cognitive decline characteristics compared to a control group with normal cognition using resting-state quantitative electroencephalogram (qEEG) with eyes closed. In the first step, a rectified signal was obtained through a preprocessing process that receives a quantitative EEG signal as an input and removes noise through a filter and independent component analysis (ICA). Frequency analysis and non-linear features were extracted from the rectified signal, and the 3067 extracted features were used as input of a linear support vector machine (SVM), a representative algorithm among machine learning algorithms, and classified into mild cognitive impairment patients and normal cognitive adults. As a result of classification analysis of 58 normal cognitive group and 80 patients in mild cognitive impairment, the accuracy of SVM was 86.2%. In patients with mild cognitive impairment, alpha band power was decreased in the frontal lobe, and high beta band power was increased in the frontal lobe compared to the normal cognitive group. Also, the gamma band power of the occipital-parietal lobe was decreased in mild cognitive impairment. These results represented that quantitative EEG can be used as a meaningful biomarker to discriminate cognitive decline.

• 대한예방한의학회지
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• 제27권2호
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• pp.35-48
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• 2023

Objective : We studied prognostic biomarkers discovery for lung cancer based on the pattern identification for the personalized Korean medicine. Methods : Using 30 tissue samples, we performed a whole exome sequencing to examine the genetic differences among three groups. Results : The exome sequencing identified among 23,490 SNPs germline variants, 12 variants showed significant frequency differences between Xu and Stasis groups (P<0.0005). As similar, 18 and 10 variants were identified in analysis for Xu vs. Gentleness group and Stasis vs. Gentleness group, respectively (P<0.001). Our exome sequencing also found 8,792 lung cancer specific variants and among the groups identified 6, 34, and 12 variants which showed significant allele frequency differences in the comparison groups; Xu vs. Stasis, Xu vs. Gentleness group, and Stasis vs. Gentleness group. As a result of PCA analysis, in germline data set, Xu group was divided from other groups. Analysis using somatic variants also showed similar result. And in gene ontology analysis using pattern identification variants, we found genes like as FUT3, MYCBPAP, and ST5 were related to tumorigenicity, and tumor metastasis in comparison between Xu and Stasis. Other significant SNPs for two were responsible for eye morphogenesis and olfactory receptor activity. Classification of somatic pattern identification variants showed close relationship in multicellular organism reproduction, anion-anion antiporter activity, and GTPase regulator activity. Conclusions : Taken together, our study identified 40 variants in 29 genes in association with germline difference of pattern identification groups and 52 variants in 47 genes in somatic cancer tissues.

• Asian Pacific Journal of Cancer Prevention
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• 제16권7호
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• pp.2819-2826
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• 2015

Combinations of multiple biomarkers representing distinct aspects of metastasis may have better prognostic value for breast cancer patients, especially those in late stages. In this study, we evaluated the protein levels of N-${\alpha}$-acetyltransferase 10 protein (Naa10p), synuclein-${\gamma}$ (SNCG), and phosphatase of regenerating liver-3 (PRL-3) in 365 patients with breast cancer by immunohistochemistry. Distinct prognostic subgroups of breast cancer were identified by combination of the three biomarkers. The Naa10p+SNCG-PRL-3-subgroup showed best prognosis with a median distant metastasis-free survival (DMFS) of 140 months, while the Naa10p-SNCG+PRL-3+subgroup had the worst prognosis with a median DMFS of 60.5 months. Multivariate analysis indicated Naa10p, SNCG, PRL-3, and the TNM classification were all independent prognostic factors for both DMFS and overall survival (OS). The three biomarker combination of Naa10p, SNCG and PRL-3 performed better in patients with lymph node metastasis, especially those with more advanced tumors than other subgroups. In conclusion, the combined expression profile of Naa10p, SNCG and PRL-3, alone or in combination with the TNM classification system, may provide a precise estimate of prognosis of breast cancer patients.

• Journal of Gastric Cancer
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• 제18권2호
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• pp.142-151
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• 2018

Purpose: The modification of the cancer classification system aimed to improve the classical anatomy-based tumor, node, metastasis (TNM) staging by considering tumor biology, which is associated with patient prognosis, because such information provides additional precision and flexibility. Materials and Methods: We previously developed an mRNA expression-based single patient classifier (SPC) algorithm that could predict the prognosis of patients with stage II/III gastric cancer. We also validated its utilization in clinical settings. The prognostic single patient classifier (pSPC) differentiates based on 3 prognostic groups (low-, intermediate-, and high-risk), and these groups were considered as independent prognostic factors along with TNM stages. We evaluated whether the modified TNM staging system based on the pSPC has a better prognostic performance than the TNM 8th edition staging system. The data of 652 patients who underwent gastrectomy with curative intent for gastric cancer between 2000 and 2004 were evaluated. Furthermore, 2 other cohorts (n=307 and 625) from a previous study were assessed. Thus, 1,584 patients were included in the analysis. To modify the TNM staging system, one-grade down-staging was applied to low-risk patients according to the pSPC in the TNM 8th edition staging system; for intermediate- and high-risk groups, the modified TNM and TNM 8th edition staging systems were identical. Results: Among the 1,584 patients, 187 (11.8%), 664 (41.9%), and 733 (46.3%) were classified into the low-, intermediate-, and high-risk groups, respectively, according to the pSPC. pSPC prognoses and survival curves of the overall population were well stratified, and the TNM stage-adjusted hazard ratios of the intermediate- and high-risk groups were 1.96 (95% confidence interval [CI], 1.41-2.72; P<0.001) and 2.54 (95% CI, 1.84-3.50; P<0.001), respectively. Using Harrell's C-index, the prognostic performance of the modified TNM system was evaluated, and the results showed that its prognostic performance was better than that of the TNM 8th edition staging system in terms of overall survival (0.635 vs. 0.620, P<0.001). Conclusions: The pSPC-modified TNM staging is an alternative staging system for stage II/III gastric cancer.

• 생명과학회지
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• 제31권10호
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• pp.960-968
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• 2021

미세조류 연구는 18세기 후반부터 시작된 이후 생물산업에서 가장 중요한 생물자원으로 인식되어 왔다. 특히 미세조류의 산업 활용에 초점을 맞춘 식품/사료 및 생리 활성 화합물에 대한 초기 주요 연구 분야는 현재 대체 에너지 자원, 탄소 배출 저감 및 폐수 처리를 포함한 환경 연구 분야로 더욱 확대되고 있다. 하지만 그 산업적 활용의 중요성에도 불구하고 미세조류 배양의 장기 보존과 관련된 기초 연구 분야는 많은 주목을 받지 못하고 있다. 그러나 생물학적으로 활성을 띄는 안정적인 미세조류 배양체 보존은 이러한 미세조류의 산업적 활용을 더욱 부각시킬 수 있는 핵심적인 성공요소이다. 따라서 본 총설은 조류(algae)의 분류체계에서 가장 큰 분류군을 차지하는 녹조류(Chlorophyceae)를 포함하여 현재까지 개발된 다양한 최첨단 미세조류 냉동보존기술을 조사하였다. 또한, 국내 생물자원은행 및 국제 미세조류 자원은행에 기탁된 생물학적으로 활성을 띄는 미세조류 배양체를 보존·유지하기 수행하고 있는 보존 기술과 함께 동결보존 시 온도조절 효과, 보존제 효과 등 미세조류의 성공적인 동결보존 기술과 관련된 주요 요인들을 조사하였다. 본 연구를 통해 확인된 결과를 살펴보면, 미세조류의 형태 및 생리학적 다양성으로 인해 현재로서는 범용적으로 사용할 수 있는 표준 미세조류 장기 보존 방법이 없다는 것을 확인하였다. 따라서, 이러한 문제를 극복하기 위해서는 미세조류의 분류학적 체계를 명확하기 위한 종 특이적 바이오마커의 개발과 종 특이적 동결보존 방법에 기반한 체계적인 접근을 위한 기초 연구 분야에 대해 훨씬 더 많은 노력이 필요함을 확인하였다.

• Korean Journal of Radiology
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• 제22권5호
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• pp.770-781
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• 2021

Objective: Chemical exchange-dependent saturation transfer (CEST) MRI is sensitive for detecting solid-like proteins and may detect changes in the levels of mobile proteins and peptides in tissues. The objective of this study was to evaluate the characteristics of chemical exchange proton pools using the CEST MRI technique in patients with dementia. Materials and Methods: Our institutional review board approved this cross-sectional prospective study and informed consent was obtained from all participants. This study included 41 subjects (19 with dementia and 22 without dementia). Complete CEST data of the brain were obtained using a three-dimensional gradient and spin-echo sequence to map CEST indices, such as amide, amine, hydroxyl, and magnetization transfer ratio asymmetry (MTR_asym) values, using six-pool Lorentzian fitting. Statistical analyses of CEST indices were performed to evaluate group comparisons, their correlations with gray matter volume (GMV) and Mini-Mental State Examination (MMSE) scores, and receiver operating characteristic (ROC) curves. Results: Amine signals (0.029 for non-dementia, 0.046 for dementia, p = 0.011 at hippocampus) and MTR_asym values at 3 ppm (0.748 for non-dementia, 1.138 for dementia, p = 0.022 at hippocampus), and 3.5 ppm (0.463 for non-dementia, 0.875 for dementia, p = 0.029 at hippocampus) were significantly higher in the dementia group than in the non-dementia group. Most CEST indices were not significantly correlated with GMV; however, except amide, most indices were significantly correlated with the MMSE scores. The classification power of most CEST indices was lower than that of GMV but adding one of the CEST indices in GMV improved the classification between the subject groups. The largest improvement was seen in the MTR_asym values at 2 ppm in the anterior cingulate (area under the ROC curve = 0.981), with a sensitivity of 100 and a specificity of 90.91. Conclusion: CEST MRI potentially allows noninvasive image alterations in the Alzheimer's disease brain without injecting isotopes for monitoring different disease states and may provide a new imaging biomarker in the future.

• Tuberculosis and Respiratory Diseases
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• 제43권6호
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• pp.945-953
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• 1996

연구배경: 진폐증을 비롯한 급만성 염증성 폐질환의 공통적인 병태생리는 활성화된 대식세포에서 분비되는 싸이토카인에 의해 염증세포 특히 독성 산화물질이나 단백분해효소 등을 분비하는 호중구의 침윤이 중요한 역할을 하며 염증이 지속되는 경우 비가역적인 섬유화를 가져오게 된다. 최근 강력한 호중구 화학주성인자로 밝혀진 IL-8은 TNF ${\alpha}$나 IL-1 에 의해 단핵세포나 대식세포, 섬유모세포등에서 분비되며 단백분해효소나 열 등에 안정하여 긴 반감기를 갖고 있어 다른 화학주성인자에 비해 지속적인 염증반응을 일으킨다. 실험 진폐증에서 유리규산에 폭로된 대식세포에서 TNF ${\alpha}$ 와 IL-1 이 증가함이 밝혀졌고, 유리규산과 같이 배양한 단핵세포에서 호중구 화학주성이 증가하며 lL-8 항체에 의해 호중구 화학주성이 억제됨이 보고된 바 있어 저자들은 IL-8 이 진폐증의 병태생리에서도 중요한 역할을 할 것으로 가정하게 되었다. 이에 진폐증 환자에서 IL-8의 분비가 증가하였는지 여부와 진폐증의 진행정도에 따른 IL-8 농도의 상관관계를 알아보고 진폐증의 조기진단에 IL-8을 생화학적 지표로 이용하고자 본 연구를 시도하였다. 방법: 분진 폭로력이 없는 아파트 경비원 16명을 대조군으로 하였고, 환자군은 흉부 X 선상 ILO 분류에 따라 의사진폐증군 16명, 소음영 진폐증군 16명, 대음영 진폐중군 16명을 대상으로 혈액 3$m{\ell}$를 채취하여 혈청을 얻은 다음 sandwich enzyme immnoassay technique 을 사용하여 IL-8을 정량분석하였다. 결과: 1. 대조군에 비하여 소음영 진폐증군과 대음영 진폐증군에서 연령이 높게 나타났으나 흡연력에는 차이가 없었으며 진폐증군사이에 분진 폭로력에도 유의한 차이는 없었다. 2. IL-8의 농도는 대조군에서 $17.85{\pm}33.85pg/m{\ell}$였던 것에 비하여 의사진폐증군에서 $70.50{\pm}53.63 pg/m{\ell}$ 소음영 진폐증군에서 $107.50{\pm}45.88pg/m{\ell}$ 대음영 진폐증군에서 $132.50{\pm}73.47pg/m{\ell}$로 대조군에 비하여 유의하게 증가하였다(p<0.001). 3. 진폐증군에서 진폐증이 진행할수록 IL-8 은 증가하는 경향을 보였고, 분산분석에서 다중비교를 하였을 때 의사진폐증군과 대음영 진폐증군사이에 통계적으로 유의한 차이가 있었다(p<0.05). 4. 진폐증 병형과 IL-8 농도사이에 상관계수는 0.4199(p<0.05)로 미약하지만 통계적으로 유의한 상관관계를 보여주었다. 결론: 진폐증의 조기진단을 위한 생화학적 지표로 IL-8 의 유용성이 클 것으로 기대되며 향후 진폐증에서의 IL-8항체의 호중구억제와 폐손상에 대한 방어 효과에 관한 연구가 이루어져야 할 것으로 생각된다.