• Asian Pacific Journal of Cancer Prevention
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• v.15 no.7
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• pp.3001-3004
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• 2014

Annexin A3 has been identified as a novel biomarker in different types of cancers. However, little is known about its clinical significances and and biological roles in gastric cancer. In this study, we assessed annexin A3 expression in 80 patients with gastric cancer and explore its correlation with prognosis Moreover, correlations with Ki-67, Bcl-2 and Bax were also investigated. Expression of annexin A3 was increased in gastric cancer compared with that in normal gastric tissues. Annexin A3 expression was significantly associated with tumor volume and TNM stage (p<0.05). and inversely correlation with prognosis of patients. More interestingly, expression of annexin A3 was positive correlated with Ki-67 and Bcl-2 expression. Our study showed annexin A3 might be a potential prognostic marker for gastric cancer and involved in tumorigenesis by regulating apoptosis and proliferation.

• BMB Reports
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• v.44 no.12
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• pp.772-781
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• 2011

Branched N-glycans are produced by a series of glycosyltransferases including N-acetylglucosaminyltransferases and fucosyltransferases and their corresponding genes. Glycans on specific glycoproteins, which are attached via the action of glycosyltransferases, play key roles in cell adhesion and signaling. Examples of this are adhesion molecules or signaling molecules such as integrin and E-cadherin, as well as membrane receptors such as the EGF and TGF-${\beta}$ receptors. These molecules also play pivotal roles in the underlying mechanism of a variety of disease such as cancer metastasis, diabetes, and chronic obstructive pulmonary disease (COPD). Alterations in the structures of branched N-glycans are also hall marks and are useful for cancer biomarkers and therapeutics against cancer. This mini-review describes some of our recent studies on a functional glycomics approach to the study of branched N-glycans produced by N-acetylglucosaminyltransferases III, IV, V and IX (Vb) (GnT-III, GnT-IV, V and IX (Vb)) and fucosyltransferase 8 (Fut8) and their pathophysiological significance, with emphasis on the importance of a systems glycobiology approach as a future perspective for glycobiology.

• BMB Reports
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• v.41 no.10
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• pp.685-692
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• 2008

Colorectal cancer (CRC) is the third most common malignancy in the world. Because CRC develops slowly from removable precancerous lesions, detection of the disease at an early stage during regular health examinations can reduce both the incidence and mortality of the disease. Although sigmoidoscopy offers significant improvements in the detection rate of CRC, its diagnostic value is limited by its high costs and inconvenience. Therefore, there is a compelling need for the identification of noninvasive biomarkers that can enable earlier detection of CRC. Accordingly, many validation studies have been conducted to evaluate genetic, epigenetic or protein markers that can be detected in the stool or in serum. Currently, the fecal-occult blood test is the most widely used method of screening for CRC. However, advances in genomics and proteomics combined with developments in other relevant fields will lead to the discovery of novel non invasive biomarkers whose usefulness will be tested in larger validation studies. Here, non-invasive molecular biomarkers that are currently used in clinical settings and have the potential for use as CRC biomarkers are discussed.

• Journal of the Korean Society of Tobacco Science
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• v.31 no.1
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• pp.58-67
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• 2009

Biomarkers could be critical and useful tools for assessing the biological effects of smoking and detecting differences between potentially reduced exposure product (PREP) and conventional cigarettes. Smoking-related biomarkers can be classified into three categories as biomarkers of exposure, biomarkers of effects, and biomarkers of potential harm. When compared with the biomarkers of effects or harm, the biomarkers of exposure for chemical constituents of cigarette smoke are well established and characterized. In addition, they could offer the important information in understanding how cigarette smoke interacts with biological molecules and causes the disease to human. Therefore, we provide an overview of 6 biomarkers of exposure (Nicotine and nicotine metabolites, Carboxyhaemoglobin, NNAL (4-(methylnitrosoamino)-1-(3-pyridyl)-1-butanol) and NNAL - glucuronide, 3-Hydroxypropyl-mercapturic acid, and Monohydroxy-butenyl-mercapturic acids, and Urine mutagenicity) which were validated through extensive research and clinical experience. These reliable biomarkers could help identify the efficacy of PREP by predicting early toxicological effects and lead to improve it.

• Korean Journal of Biological Psychiatry
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• v.21 no.4
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• pp.115-117
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• 2014

Variety of biomarkers that are related to the Alzheimer's disease and its diagnosis and progress have been found. However, research lacks in predicting the reaction of the treatment. In addition, there is no definite treatment reaction to the disease but rather it is varied. The purpose of this review article is to study the research of the biomarkers that are able to predict the treatment reaction. There was a research that illustrated a relationship between plasma amyloid ${\beta}$ peptide, cerebrospinal fluid tau, neuroanatomical biomarkers and acetylcholinesterase inhibitors. Polymorphisms in genes of the cholinergic markers AChE, BuChE, ChAT and PON-1 were found to be associated with better clinical response to acetylcholinesterase inhibitors. Many pharmacogenetic studies have been conducted to evaluate the impact of the lipoprotein apolipoprotein E (APOE) genotype on treatment response to acetylcholinesterase inhibitor. However, there is no significant influence of the APOE genotypes on treatment response. Further research is needed to find other predictors of treatment with acetylcholinesterase inhibitors in patients with Alzheimer's disease.

• Journal of Preventive Medicine and Public Health
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• v.42 no.6
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• pp.371-376
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• 2009

In this article, we reviewed the literature on risk assessment (RA) models with and without molecular genomic markers and the current utility of the markers in the pharmacogenetic field. Epidemiological risk assessment is applied using statistical models and equations established from current scientific knowledge of risk and disease. Several papers have reported that traditional RA tools have significant limitations in decision-making in management strategies for individuals as predictions of diseases and disease progression are inaccurate. Recently, the model added information on the genetic susceptibility factors that are expected to be most responsible for differences in individual risk. On the continuum of health care, from diagnosis to treatment, pharmacogenetics has been developed based on the accumulated knowledge of human genomic variation involving drug distribution and metabolism and the target of action, which has the potential to facilitate personalized medicine that can avoid therapeutic failure and serious side effects. There are many challenges for the applicability of genomic information in a clinical setting. Current uses of genetic markers for managing drug therapy and issues in the development of a valid biomarker in pharmacogenetics are discussed.

• International Neurourology Journal
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• v.22 no.4
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• pp.228-236
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• 2018

Neuromodulation was introduced for patients with poor outcomes from the existing traditional treatment approaches. It is well-established as an alternative, novel treatment option for voiding dysfunction. The current system of neuromodulation uses an open-loop system that only delivers continuous stimulation without considering the patient's state changes. Though the conventional open-loop system has shown positive clinical results, it can cause problems such as decreased efficacy over time due to neural habituation, higher risk of tissue damage, and lower battery life. Therefore, there is a need for a closed-loop system to overcome the disadvantages of existing systems. The closed-loop neuromodulation includes a system to monitor and stimulate micturition reflex pathways from the lower urinary tract, as well as the central nervous system. In this paper, we reviewed the current technological status to measure biomarker for closed-loop neuromodulation systems for voiding dysfunction.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.32 no.3
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• pp.85-92
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• 2021

Attention-deficit/hyperactivity disorder (ADHD) leads to functional decline in academic performance, interpersonal relationships, and development in school-aged children. Early diagnosis and appropriate intervention can significantly reduce the functional decline caused by ADHD. Currently, there is no established biological marker for ADHD. Some studies have suggested that various indicators from the quantitative electroencephalogram (QEEG) may be useful biological markers for the diagnosis of ADHD. Until the 2010s, theta/beta ratio (TBR) was a biomarker candidate for ADHD that consistently showed high diagnostic value. However, limitations of TBR have recently been reported. Studies have demonstrated that phase-amplitude coupling, especially theta phase-gamma amplitude coupling, are related to cognitive dysfunction and may assist in the diagnosis of ADHD. As yet, the underlying mechanism is not clearly established, and the clinical efficacy of these biomarkers needs to be proven through well-controlled studies. Based on the heterogeneous characteristics of ADHD, subgrouping through QEEG plays a key role in diagnosis and treatment planning. Sophisticated, well-designed studies and meta-analyses are necessary to confirm these findings.

• Journal of the Korean Electrochemical Society
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• v.25 no.1
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• pp.13-21
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• 2022

There is an increasing interest in monitoring of specific biomarker for determining progression of a disease or efficacy of a treatment. Conventional method for quantification of specific biomarkers as enzyme linked immunosorbent assay (ELISA) has high material costs, long incubation periods, requires large volume of samples and involves special instruments, which necessitates clinical samples to be sent to a lab. This paper reports on the development of an electrochemical biosensor to measure total immunoglobulin E (IgE), a marker of asthma disease that varies with age, gender, and disease in concentrations from 0.3-1000 ng/mL with consuming 20 µL volume of whole blood sample. The sensor provides rapid, accurate, easy, point-of-care measurement of IgE, also, sequential monitoring of total IgE with ovalbumin (OVA) induced mice is another application of sensor. Taken together, these results provide an alternative way for detection of biomarkers in whole blood with low volumes and long-term ex-vivo assessments for understanding the progression of a disease.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.576-590
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• 2023

Machine learning is widely used in various academic fields, and recently it has been actively applied in the medical research. In the medical field, machine learning is used in a variety of ways, such as speeding up diagnosis, discovering new biomarkers, or discovering latent traits of a disease. In the respiratory field, a relative regional air volume change (RRAVC) map based on quantitative inspiratory and expiratory computed tomography (CT) imaging can be used as a useful functional imaging biomarker for characterizing regional ventilation. In this study, we seek to predict RRAVC using various regular machine learning models such as extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multi-layer perceptron (MLP). We experimentally show that MLP performs best, followed by XGBoost. We also propose several relative coordinate systems to minimize intersubjective variability. We confirm a significant experimental performance improvement when we apply a subject's relative proportion coordinates over conventional absolute coordinates.