• Journal of Veterinary Science
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• v.25 no.2
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• pp.28.1-28.11
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• 2024

Background: Porcine circovirus type 2 (PCV2) infection is ubiquitous around the world. Diagnosis of the porcine circovirus-associated disease requires clinic-pathological elements together with the quantification of viral loads. Furthermore, given pig farms in regions lacking access to sufficient laboratory equipment, developing diagnostic devices with high accuracy, accessibility, and affordability is a necessity. Objectives: This study aims to investigate two newly developed diagnostic tools that may satisfy these criteria. Methods: We collected 250 specimens, including 170 PCV2-positive and 80 PCV2-negative samples. The standard diagnosis and cycle threshold (Ct) values were determined by quantitative polymerase chain reaction (qPCR). Then, two point-of-care (POC) diagnostic platforms, convective polymerase chain reaction (cPCR, qualitative assay: positive or negative results are shown) and EZtargex (quantitative assay: Ct values are shown), were examined and analyzed. Results: The sensitivity and specificity of cPCR were 88.23% and 100%, respectively; the sensitivity and specificity of EZtargex were 87.65% and 100%, respectively. These assays also showed excellent concordance compared with the qPCR assay (κ = 0.828 for cPCR and κ = 0.820 for EZtargex). The statistical analysis showed a great diagnostic power of the EZtargex assay to discriminate between samples with different levels of positivity. Conclusions: The two point-of-care diagnostic platforms are accurate, rapid, convenient and require little training for PCV2 diagnosis. These POC platforms can discriminate viral loads to predict the clinical status of the animals. The current study provided evidence that these diagnostics were applicable with high sensitivity and specificity in the diagnosis of PCV2 infection in the field.

• Journal of Veterinary Science
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• v.23 no.2
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• pp.21.1-21.7
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• 2022

Newcastle disease (ND), infectious laryngotracheitis (ILT) and avian metapneumovirus (aMPV) can be similar making it critical to quickly differentiate them. Herein, we adapted pre-existing molecular-based diagnostic assays for NDV and ILTV, and developed new assays for aMPV A and B, for use under synchronized thermocycling conditions. All assays performed equivalently with linearity over a 5 log₁₀ dynamic range, a reproducible (R² > 0.99) limit of detection of ≥ 10 target copies, and amplification efficiencies between 86.8%-98.2%. Using biological specimens for NDV and ILTV showed 100% specificity. Identical amplification conditions will simplify procedures for detection in diagnostic laboratories.

• Parasites, Hosts and Diseases
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• v.54 no.1
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• pp.39-46
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• 2016

Theileria annulata is a tick-borne intracellular protozoan parasite that causes tropical theileriosis, a fatal bovine lymphoproliferative disease. The parasite predominantly invades bovine B lymphocytes and macrophages and induces host cell transformation by a mechanism that is not fully comprehended. Analysis of signaling pathways by quantitative real-time PCR (qPCR) could be a highly efficient means to understand this transformation mechanism. However, accurate analysis of qPCR data relies on selection of appropriate reference genes for normalization, yet few papers on T. annulata contain evidence of reference gene validation. We therefore used the geNorm and NormFinder programs to evaluate the stability of 5 candidate reference genes; 18S rRNA, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ACTB (${\beta}-actin$), PRKG1 (protein kinase cGMP-dependent, type I) and TATA box binding protein (TBP). The results showed that 18S rRNA was the reference gene most stably expressed in bovine PBMCs transformed and non-transformed with T. annulata, followed by GAPDH and TBP. While 18S rRNA and GAPDH were the best combination, these 2 genes were chosen as references to study signaling pathways involved in the transformation mechanism of T. annulata.

• Journal of Gastric Cancer
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• v.7 no.2
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• pp.59-66
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• 2007

Purpose: This study was aimed at evaluating the diagnostic validity of peritoneal dissemination of gastric cancer cells by performing multiple genetic marker analysis via quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) in gastric cancer cell lines and gastric cancer tissues. Materials and Methods: Quantitative RT-PCR was performed on 12 human gastric cancer cell lines and 10 gastric cancer tissues with four mRNAs of carcinoembryonic antigen (CEA), Cytokeratin 20 (CK20), dopa decarboxylase (DDC), and L-3-phosphoserine phosphatase (L3PP). Results: Out of the 12 human gastric cancer cell lines we tested, CEA was overexpressed in four cell lines (33%), CK20 in one (8%), DDC in six (50%) and L3PP was expessed in all the lines (100%). Out of the 10 gastric cancer tissues we tested, CEA was overexpressed in nine tissues, CK20 in eight, DOC in nine and L3PP was overexpressed in all the tissues. L3PP was overexpressed in all the gastric cancer cell lines and tissues, but the levels of overexpression were lower than those of CEA and DDC. Conclusion: Multiple genetic marker analysis can compensate for the weak points of single marker analysis when testing gastric cancer, and three mRNAs of CEA, DDC and L3PP can be used as candidate genes.

• Microbiology and Biotechnology Letters
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• v.36 no.1
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• pp.34-42
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• 2008

Bovine blood, cell, tissue, and organ are used as raw materials for manufacturing biologics such as biopharmaceuticals, tissue engineered products, and cell therapy. Manufacturing processes for the biologics using bovine materials have the risk of viral contamination. Therefore viral validation is essential in ensuring the safety of the products. Bovine viral diarrhoea virus (BVDV) is the most common bovine pathogen and has widely been known as a contaminant of biologics. In order to establish the validation system for the BVDV safety of biologics, a real-time RT-PCR method was developed for quantitative detection of BVDV contamination in raw materials, manufacturing processes, and final products. Specific primers for amplification of BVDV RNA was selected, and BVDV RNA was quantified by use of SYBR Green I. The sensitivity of the assay was calculated to be 1 $TCID_{50}/mL$. The rent-time RT-PCR method was validated to be reproducible and very specific to BVDV. The established real-time RT-PCR assay was successfully applied to the validation of Chinese hamster ovary (CHO) cell artificially infected with BVDV. BVDV RNA could be quantified in CHO cell as well as culture supernatant. Also the real-time RT-PCR assay could detect $10TCID_{50}/mL$ of BVDV artificially contaminated in bovine collagen.

• Korean Journal of Food Science and Technology
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• v.52 no.1
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• pp.40-45
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• 2020

Over 500 genetically modified organisms (GMOs) have been developed since 1996, of which nearly 44% have glufosinate herbicide-tolerant traits. Identification of specific markers that can be used to identify herbicide-tolerant traits is challenging as the DNA sequences of the gene(s) of a trait are highly variable depending on the origin of the gene(s), plant species, and developers. To develop specific PCR marker(s) for the detection of the glufosinate-tolerance trait, DNA sequences of several pat or bar genes were compared and a diverse combination of PCR primer sets were examined using certified reference materials or transgenic plants. Based on both the qualitative and quantitative PCR tests, a primer set specific for pat and non-specific for bar was developed. Additionally, a set of markers that can detect both pat and bar was developed, and the quantitative PCR data indicated that the primer pairs were sensitive enough to detect 0.1% of the mixed seed content rate.

• Journal of Life Science
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• v.33 no.12
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• pp.1025-1035
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• 2023

In this study, we analyzed SNPs that appear between Korean and Chinese Scapharca subcrenata using the nucleotide sequence data of S. subcrenata analyzed by genotyping by sequencing (GBS). To distinguish the country of origin for S. subcrenata in Korean and Chinese, we developed a primer set as single nucleotide polymorphism (SNP) markers for quantitative real-time PCR (qPCR) analysis and validated by sequencing SNPs. A total of 180 samples of S. subcrenata were analyzed by genotyping by sequencing, and 15 candidate SNPs were selected. SNP marker selection for country of origin were identified through real-time qPCR. Insertion 1 and SNP 21 markers showed the most distinct separation between the sequence types as well as the country of origin through qPCR, with the observed amplification patterns matching the expected outcomes.. Additionally, in a blind test conducted by mixing samples of S. subcrenata at random, Insertion 1 showed 74% accuracy, 52% sensitivity, and 96% specificity, and SNP 21 showed 86% accuracy, 79% sensitivity, and 93% specificity. Therefore, the two SNP markers developed are expected to be useful in verifying the authenticity of the country of origin of S. subcrenata when used independently or in combination.

• Korean Journal of Microbiology
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• v.49 no.3
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• pp.292-296
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• 2013

This study utilized an analysis method for detecting six microorganisms, such as Actinobacillus actinomycetemcomitans, Campylobacter rectus, Porphyromonas gingivalis, Tannerella forsythus, Treponema denticola, and Prevotella intermedia, triggering periodontal disease, using multiplex real-time polymerase chain reaction (PCR). The analysis including internal control was made by dividing the six species into two groups using four fluorescence dyes, and it was verified that there was no interference or cross-reaction between the target species and different kinds of oral microbial species. Qualitative and quantitative analyses were conducted on each microorganism in various samples, such as saliva and the plaque, using the multiplex real-time PCR and comparative analysis between periodontitis patients and healthy people, revealing obvious differences between them.

• Journal of Genetic Medicine
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• v.12 no.2
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• pp.72-78
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• 2015

Recently, noninvasive prenatal test (NIPT) has been adopted as a primary screening tool for fetal chromosomal aneuploidy. The principle of NIPT lies in isolating the fetal fraction of cell-free DNA in maternal plasma and analyzing it with bioinformatic tools to measure the amount of gene from the target chromosome, such as chromosomes 21, 18, and 13. NIPT will contribute to decreasing the need for unnecessary invasive procedures, including amniocentesis and chorionic villi sampling, for confirming fetal aneuploidy because of its higher positive predictive value than that of the conventional prenatal screening method. However, its greater cost than that of the current antenatal screening protocol may be an obstacle to the adoption of this innovative technique in clinical practice. Digital polymerase chain reaction (dPCR) is a novel approach for detecting and quantifying nucleic acid. dPCR provides real-time diagnostic advantages with higher sensitivity, accuracy, and absolute quantification than conventional quantitative PCR. Since the groundbreaking discovery that fetal cell-free nucleic acid exists in maternal plasma was reported, dPCR has been used for the quantification of fetal DNA and for screening for fetal aneuploidy. It has been suggested that dPCR will decrease the cost by targeting specific sequences in the target chromosome, and dPCR-based noninvasive testing will facilitate progress toward the implementation of a noninvasive approach for screening for trisomy 21, 18, and 13. In this review, we highlight the principle of dPCR and discuss its future implications in clinical practice.

• Journal of Pharmaceutical Investigation
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• v.37 no.6
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• pp.377-395
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• 2007

Near infrared(NIR) spectral data have been used for the noninvasive analysis of various biological samples. Nonetheless, absorption bands of NIR region are overlapped extensively. It is very difficult to select the proper wavelengths of spectral data, which give the best PCR(principal component regression) models for the analysis of constituents of biological samples. The NIR data were used after polynomial smoothing and differentiation of 1st order, using Savitzky-Golay filters. To find the best PCR models, all-possible combinations of available principal components from the given NIR spectral data were derived by in-house programs written in MATLAB codes. All of the extensively generated PCR models were compared in terms of SEC(standard error of calibration), $R^2$, SEP(standard error of prediction) and SECP(standard error of calibration and prediction) to find the best combination of principal components of the initial PCR models. The initial PCR models were found by SEC or Malinowski's indicator function and a priori selection of spectral points were examined in terms of correlation coefficients between NIR data at each wavelength and corresponding concentrations. For the test of the developed program, aqueous solutions of BSA(bovine serum albumin) and glucose were prepared and analyzed. As a result, the best PCR models were found using a priori selection of spectral points and the final model selection by SEP or SECP.