• Fisheries and Aquatic Sciences
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• 제5권4호
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• pp.263-270
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• 2002

The Pacific oysters, Crassostrea gigas, were stressed with different concentrations of benzo(a) pyrene and depurated to determine the hemocyte lysosomal membrane stability and hydrolytic enzymatic activity as a biomarker candidate to the chemical, using NRR (neutral red retention) and API ZYM System, respectively. The membrane damage measured as NRR decrease was significant with the increase of chemical concentration and exposure time (P<0.05), providing a possible tool for biomarker. Interestingly, the control showed intrinsic stress probably due to captive life in the laboratory, and a recovering trend was also found during the depuration. The benzo(a)pyrene-exposed oysters showed increased enzyme activities in alkaline phosphatase, esterase (C4), acid phosphatase, naphthol-AS-BI-phospho­hydrolase, $\beta$-galactosidase, $\beta$-glucuronidase, and N-acetyl- $\beta$-glucosaminidase. Of them, only two enzymes, acid phosphatase and alkaline phosphatase, showed some potential available for the generation of enzymatic biomarker in the oyster. The results are suggestive of the potential availability of the cellular and enzymatic properties as a biomarker. However, considering that a robust biomarker should be insensitive to natural stress coming from normal physiological variation, but sensitive to pollutants, a concept of intrinsic stress the animal possesses should be taken into consideration. This reflects the necessity of further research on the intrinsic stress affecting the cellular and enzymatic properties of the chemical­stressed oysters prior to using the data as a biomarker.

• BMB Reports
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• 제44권12호
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• pp.765-771
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• 2011

Cancer treatment has been stratified by companion biomarker tests that serve to provide information on the genetic status of cancer patients and to identify patients who can be expected to respond to a given treatment. This stratification guarantees better efficiency and safety during treatment. Cancer patients, however, marginally benefit from the current companion biomarker-aided treatment regimens, presumably because companion biomarker tests are dependent solely on the mutation status of several genes status quo. In the true sense of the term, "personalized medicine", cancer patients are deemed to be identified individually by their molecular signatures, which are not necessarily confined to genetic mutations. Glycosylation is tremendously dynamic and shows alterations in cancer. Evidence is accumulating that aberrant glycosylation contributes to the development and progression of cancer, holding the promise for use of glycosylation status as a companion biomarker in cancer treatment. There are, however, several challenges derived from the lack of a reliable detection system for aberrant glycosylation, and a limited library of aberrant glycosylation. The challenges should be addressed if glycosylation status is to be used as a companion biomarker in cancer treatment and contribute to the fulfillment of personalized medicine.

• 한국환경독성학회:학술대회논문집
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• 한국환경독성학회 1998년도 환경의 날 기념 심포지움 : 환경위해성평가 및 관리를 위한 연구방향
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• pp.85-93
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• 1998

• Ocean and Polar Research
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• 제30권1호
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• pp.109-117
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• 2008

해양환경 건강성 평가에서 바이오마커의 적용은 상대적으로 새로운 분야이다. 국립학술원 및 세계보건기구에 따르면 바이오마커는 노출바이오마커, 영향바이오마커 및 민감바이오마커 등 3가지로 나누어진다. 해양생태계에 대한 환경오염물질의 노출 및 영향을 평가하기 위하여 다음과 같은 바이오마커들이 시험되고 있다: 해독, 산화스트레스, 분해산물, 스트레스 반응, 세포사멸, 물질대사, 신경반응, 생식, 스테로이드 호르몬, 항산화물질, 유전적 변형. 1990년대 초부터 여러 바이오마커 연구그룹들은 해양생물의 건강지수를 개발하여 해양환경의 상태를 평가하기 위한 수단으로 활용해 왔다. 바이오마커 지수는 생물학적 효과에 대한 모니터링활동으로부터 얻어진 자료의 해석에 사용될 수 있다. 본 총설에서는 이제까지 보고된 바이오마커 지수 관련 연구 중 대표적인 건강평가지수(Health assessment Index), 바이오마커 지수(Biomarker Index), 생물영향평가지수(Bioeffect Assessment Index) 및 일반화된 선형모델(Generalized Linear Model) 등의 연구를 요약하였다. 오염된 지역에 서식하는 해양생물의 바이오마커 반응 측정 및 바이오마커 지수 개발은 다양한 측면의 해양생태계 위해성 평가를 위해 고안된 환경모니터링 프로그램에 공헌할 수 있는 정보를 제공해 줄 수 있을 것이다.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.169-182
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• 2007

Receive operating characteristic (ROC) approach can be employed to rank candidate genes from a microarray experiment, in particular, for the biomarker development with the purpose of population screening of a cancer. In the cancer microarray experiment based on n patients the researcher often wants to compare the tumor tissue with the normal tissue within the same individual using a common reference RNA. Ideally, this experiment produces n pairs of microarray data. However, it is often the case that there are missing values either in the normal or tumor tissue data. Practically, we have $n_1$ pairs of complete observations, $n_2$ "normal only" and $n_3$ "tumor only" data for the microarray. We refer to this data set as a mixed data set. We develop a ROC approach on the mixed data set to rank candidate genes for the biomarker development for the colorectal cancer screening. It turns out that the correlation between two ranks in terms of ROC and t statistics based on the top 50 genes of ROC rank is less than 0.6. This result indicates that employing a right approach of ranking candidate genes for the biomarker development is important for the allocation of resources.

• 한국양식학회지
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• 제18권3호
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• pp.196-199
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• 2005

Farmed red sea breams, Pagrus major, were fed for 60 days with pellets containing different concentrations of benzo(a)pyrene (0, 0.2, 2, 20 mg/kg) to generate a biomarker of the chemical toxicity in the fish. The fish exposed to the chemical concentrations did not show any significant difference in the weight gain, conditioning, factor, and hepatosomatic index. However, some haematological parameters, such as glucose, calcium, magnesium, GOT (glutamic oxalate transaminase), and GPT (glutamic pyruvate transaminase) were influenced by the chemical exposure. Of them, two enzymes, GOT and GPT, increased significantly 60 days after the exposure in a way of concentration dependence (P<0.05). In the study of ecotoxicological biomarker, sensitivity to adverse environments is one of the key available factors. The fish changes in GOT and GPT were an earlier and reliable sign of the fish response against the chemical exposure, rendering the two enzymatic factors as a useful biomarker at least to benzo(a)pyrene exposure in the farming waters.

• Asian Pacific Journal of Cancer Prevention
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• 제17권4호
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• pp.2297-2299
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• 2016

Background: Early detection of malignant transformation with expression biomarkers has significant potential to improve the survival rate of patients as such biomarkers enable prediction of progression and assess sensitivity to chemotherapy. The expression of interferon inducible transmembrane protein 1 (IFITM1) has been associated with early invasion events in several carcinomas, including head and neck cancers, and hence has been proposed as a novel candidate biomarker. As the incidence of oral squamous cell carcinoma (OSCC) is highest in the Indian population, we sought to investigate: 1) the expression pattern of IFITM1 in OSCC tissue samples obtained from Indian patients of Dravidian origin; and 2) the possibility of using IFITM1 expression as a potential biomarker. Materials and Methods: Total RNA extracted from thirty eight OSCC biopsy samples was subjected to semi-quantitative RT-PCR with IFITM1 and GAPDH specific primers. Results: Of the thirty eight OSCC samples that were analyzed, IFITM1 overexpression was identified in fifteen (39%). Seven expressed a low level, while the remainder expressed high level of IFITM1. Conclusions: The overexpression of IFITM1 in OSCC samples indicates that IFITM1 may be explored for the possibility of use as a high confidence diagnostic biomarker in oral cancers. To the best of our knowledge, this is the first time that IFITM1 overexpression is being reported in Indian OSCC samples.

• BMB Reports
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• 제45권6호
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• pp.323-330
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• 2012

The glycome consists of all glycans (or carbohydrates) within a biological system, and modulates a wide range of important biological activities, from protein folding to cellular communications. The mining of the glycome for disease markers represents a new paradigm for biomarker discovery; however, this effort is severely complicated by the vast complexity and structural diversity of glycans. This review summarizes recent developments in analytical technology and methodology as applied to the fields of glycomics and glycoproteomics. Mass spectrometric strategies for glycan compositional profiling are described, as are potential refinements which allow structure-specific profiling. Analytical methods that can discern protein glycosylation at a specific site of modification are also discussed in detail. Biomarker discovery applications are shown at each level of analysis, highlighting the key role that glycoscience can play in helping scientists understand disease biology.

• 한국멀티미디어학회논문지
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• 제23권8호
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• pp.940-952
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• 2020

The Alzheimer's disease (AD) is a neurodegenerative disease commonly found in the elderly individuals. It is one of the most common forms of dementia; patients with AD suffer from a degradation of cognitive abilities over time. To correctly diagnose AD, compuated-aided system equipped with automatic classification algorithm is of great importance. In this paper, we propose a novel deep learning based classification algorithm that takes advantage of MRI biomarker images including brain areas of hippocampus and cerebrospinal fluid for the purpose of improving the AD classification performance. In particular, we develop a new approach that effectively applies MRI biomarker patch images as input to 3D Deep Convolution Neural Network. To integrate multiple classification results from multiple biomarker patch images, we proposed the effective confidence score fusion that combine classification scores generated from soft-max layer. Experimental results show that AD classification performance can be considerably enhanced by using our proposed approach. Compared to the conventional AD classification approach relying on entire MRI input, our proposed method can improve AD classification performance of up to 10.57% thanks to using biomarker patch images. Moreover, the proposed method can attain better or comparable AD classification performances, compared to state-of-the-art methods.

• KSBB Journal
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• 제26권4호
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• pp.352-356
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• 2011

The detection of biomarkers is an important issue for disease diagnosis. However, many systems are not suitable to detect the biomarker itself directly. For direct detection of biomarker proteins in human serum, a new affinity-capture method using aptamers combined with the mass spectrometry was suggested. Since signals from protein samples cannot be amplified, modified chromatin immunoprecipitation (ChIP) and subsequent cross-linking with formaldehyde between aptamers and target proteins were used not to lose the captured target proteins, which allowed us to perform a harsh washing step to remove the non-specifically bound proteins. As a model system, a thrombin aptamer was used as a bait and thrombin as a target protein. Using our modified ChIP and affinity-capture method, non-specific binding proteins on the beads decreased significantly, suggesting that our new method is efficient and can be applied to developing diagnosis systems for various biomarkers.