• 센서학회지
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• 제22권2호
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• pp.144-149
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• 2013

In this research, we developed a biosensor to detect lung cancer-specific biomarker using Anodic Aluminum Oxide (AAO) chip based on interference and nano surface plasmon resonance (nanoSPR). The nano-porous AAO chip was fabricated $2{\mu}m$ of pore-depth by two-step anodizing method for surface uniformity. NanoSPR has sensitivity to the refractive index (RI) of the surrounding medium and also provides simple and label-free detection when specific antibodies are immobilized to the Au-deposited surface of nano-porous AAO chip. To detect the lung cancer-specific biomarker, antibodies were immobilized on the surface of the chip by Self Assembled Monolayer (SAM) method. Since then lung cancer-specific biomarker was applied atop the antibodies immobilized layer. The specific reaction of the antigen-antibody contributed to the change in the refractive index that cause shift of resonance spectrum in the interference pattern. The Limit of Detection (LOD) was 1 fg/ml by using our nano-porous AAO biosensor chip.

• 생태와환경
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• 제36권2호통권103호
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• pp.97-107
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• 2003

어류 vitellogenin은 난황전구체로 난형성과정동안에 estradiol의 체내 순환에 의해 암컷의 간에서 생산되며 alkylphenol류와 같은 비이온성 계면활성제 등의 내분비계 장애물질에 의해 수컷에서도 생산된다. 물 환경의주요 생물종인 어류는 내분비계장애물질에 의해 암컷에서는 번식률 저하와 함께 수컷에서는 정소의 축소 및 이에 따른 암컷화가 관찰된다. 특히 수컷에서 내분비계 장애물질에 의해 유도된 vitellogenin의 생성을 이용하여 환경오염에 의해 유도된 생물체의 유전자 발현 변화 뿐만 아니라 이를 토대로 특정지역의 환경오염을 모니터링할 수 있다. 본 논문에서는 어류의 vitetlogenin를 이용하여 수환경의 내분비계장애물질의 검출과 환경오염모니터링을 위한 biomarker로서의 유용성을 검토하였다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2018년도 제30회 한글 및 한국어 정보처리 학술대회
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• pp.550-551
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• 2018

바이오마커는 체내의 상태 및 변화를 파악할 수 있는 지표이다. 이는 암을 비롯한 다양한 질병에 대하여 진단하는데 활용도가 높은 것으로 알려져 있으나, 새로운 바이오마커를 찾아내기 위한 임상 실험은 많은 시간과 비용을 소비되며, 모든 바이오마커가 실제 질병을 진단하는데 유용하게 사용되는 것은 아니다. 따라서 본 연구에서는 자연어처리 기술을 활용해 바이오마커를 발굴할 때 요구되는 많은 시간과 비용을 줄이고자 한다. 이 때 다양한 의미를 가진 어휘들이 해당 질병과 연관성이 높은 것으로 나타나며, 이들을 분류하는 것은 매우 어렵다. 따라서 우리는 Word2Vec과 가우시안 혼합 모델을 사용하여 바이오마커를 분류하고자 한다. 실험 결과, 대다수의 바이오마커 어휘들이 하나의 군집에 나타나는 것을 확인할 수 있었다.

• 대한의용생체공학회:의공학회지
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• 제38권5호
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• pp.271-276
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• 2017

Cancer biomarkers are using in the diagnosis, staging, prognosis and prediction of disease progression. But, there are not sufficiently profiled and validated in early detection and risk classification of prostate cancer. In this study, we have devoted to finding a panel of serum biomarkers that are able to detect the diagnosis of prostate cancer. The serum samples were consisted of 111 prostate cancer and 343 control samples and examined. Eleven biomarkers were constructed in this study, and then nine biomarkers were relevant to candidate biomarkers by using t test. Finally, four biomarkers, PSA, ApoA2, CYFRA21.1 and TTR, were selected as the prostate cancer biomarker panel, logistic regression was used to identify algorithms for diagnostic biomarker combinations(AUC = 0.9697). A panel of combination biomarkers is less invasive and could supplement clinical diagnostic accuracy.

• 식품기술
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• 제23권2호
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• pp.205-211
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• 2010

• Asian Pacific Journal of Cancer Prevention
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• 제13권12호
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• pp.6145-6149
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• 2012

Objective: To identify whether saliva supernatant miR-21 can serve as a novel potential biomarker in patients with esophageal cancer (EC). Methods: 32 patients with EC and 16 healthy controls were recruited in this study. Total RNA was extracted from saliva supernatant samples for measurement of miR-21 levels using RT-qPCR and relationships between miR-21 levels and clinical characteristics of EC patients were analyzed. Results: miR-21 was significantly higher in the EC than control groups. The sensitivity and specificity were 84.4% and 62.5% respectively. Supernatant miR-21 levels showed no significant correlation with cancer stage, differentiation and nodal metastasis. Conclusions: Saliva supernatant miR-21 may be a novel biomarker for EC.

• Asian Pacific Journal of Cancer Prevention
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• 제14권4호
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• pp.2167-2172
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• 2013

Lung cancer remains a major cause of morbidity and mortality worldwide, accounting for more deaths than any other cause. All the clinical practice guidelines recommended against routine screening for lung cancer have cited lack of robust evidence, at least until a few years back. However, the potential to screen lung cancers has received renewed interest due to superior performance of low dose CT (LD-CT) in detecting early stage cancers. The incremental costs and risks involved due to the invasive procedures in the screened population due to a high false positivity rate questions the use of LD-CT scan as a reliable community based screening tool. There is therefore an urgent need to find a less invasive and a more reliable biomarker that is crucial to increase the probability of early lung cancer detection. This can truly make a difference in lung cancer survival and at the same time be more cost and resource utilization effective. Sampling blood serum being minimally invasive, low risk and providing an easy to obtain biofluid, needs to be explored for potential biomarkers. This review discusses the use of circulatory miRNAs that have been able to discriminate lung cancer patients from disease free controls. Several studies conducted recently suggest that circulating miRNAs may have promising future applications for screening and early detection of lung cancer.

• Journal of Digestive Cancer Research
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• 제11권1호
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• pp.21-29
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• 2023

Despite recent advancements in the diagnosis and treatment of pancreatic cancer, clinical results remain dismal. Furthermore, there are no reliable biomarkers or alternatives beyond carbohydrate antigen 19-9. Circulating tumor cells (CTCs) may be a potential biomarker, but their therapeutic application is constrained by their rarity in peripheral venous blood. Theoretically, the portal vein can be a more appropriate location for the detection of CTCs, because the first venous drainage of pancreatic cancer is portal circulation. According to several studies, the number and detection rate of CTCs may be higher in the portal blood than in the peripheral blood. CTC counts in the portal blood are strongly correlated with several prognostic parameters such as hepatic metastasis, recurrence after surgery, and survival. The phenotypic and genotypic properties analyzed in the captured portal CTCs can assist us to comprehend tumor heterogeneity and predicting the prognosis of pancreatic cancer. The investigations to date are limited by small sample sizes and varied CTC detection techniques. Therefore, a large number of prospective studies are required to confirm portal CTCs as a valid biomarker in pancreatic cancer.

• Genomics & Informatics
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• 제6권3호
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• pp.136-141
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• 2008

A large number of studies have been performed to identify biomarkers that will allow efficient detection and determination of the precise status of a patient’s disease. The use of microarrays to assess biomarker status is expected to improve prediction accuracies, because a whole-genome approach is used. Despite their potential, however, patient samples can differ with respect to biomarker status when analyzed on different platforms, making it more difficult to make accurate predictions, because bias may exist between any two different experimental conditions. Because of this difficulty in experimental standardization of microarray data, it is currently difficult to utilize microarray-based gene sets in the clinic. To address this problem, we propose a method that predicts disease status using gene expression data that are transformed by their ranks, a concept that is easily applied to two datasets that are obtained using different experimental platforms. NCI and colon cancer datasets, which were assessed using both Affymetrix and cDNA microarray platforms, were used for method validation. Our results demonstrate that the proposed method is able to achieve good predictive performance for datasets that are obtained under different experimental conditions.

• Journal of Gastric Cancer
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• 제23권3호
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• pp.410-427
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• 2023

Recent advances in artificial intelligence (AI) have provided novel tools for rapid and precise pathologic diagnosis. The introduction of digital pathology has enabled the acquisition of scanned slide images that are essential for the application of AI. The application of AI for improved pathologic diagnosis includes the error-free detection of potentially negligible lesions, such as a minute focus of metastatic tumor cells in lymph nodes, the accurate diagnosis of potentially controversial histologic findings, such as very well-differentiated carcinomas mimicking normal epithelial tissues, and the pathological subtyping of the cancers. Additionally, the utilization of AI algorithms enables the precise decision of the score of immunohistochemical markers for targeted therapies, such as human epidermal growth factor receptor 2 and programmed death-ligand 1. Studies have revealed that AI assistance can reduce the discordance of interpretation between pathologists and more accurately predict clinical outcomes. Several approaches have been employed to develop novel biomarkers from histologic images using AI. Moreover, AI-assisted analysis of the cancer microenvironment showed that the distribution of tumor-infiltrating lymphocytes was related to the response to the immune checkpoint inhibitor therapy, emphasizing its value as a biomarker. As numerous studies have demonstrated the significance of AI-assisted interpretation and biomarker development, the AI-based approach will advance diagnostic pathology.