• Journal of Microbiology
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• v.38 no.2
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• pp.105-108
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• 2000

Oligonucleotide primers amplifying a 344 bp fragment on the integrin-like protein alpha-INT1p gene (${\alpha}$INT1) of Candida albicans were synthesized for screenign of C. albicans from clinicalsamples by the polymerase chain reaction (PCR). The PCR specifically amplified DNA from C. albicans and none from any other Candida, fungal, or human DNA in standard used here. The PCR assay showed that the primers (LH1 and LH2) were specific for 26 isolates of C. albicans from clinical smaples, whereas the positive fragment, 344 bp, was not amplified from 15 clinical isolates including 14 other medically important Candida species and an isolate of Saccharomyces cerevisiae. PCR was conducted on the urine samples of 20 patients and 4 samples were C. albicans positive. The detection limit of the PCR assay for C. albicans was shown to be approximately 10 cells/ml saline. The PCR system using 344 bp ${\alpha}$INT1 as a target is more specific and rapid than the conventional culture method, and the sensitive detection method is applicable to clinical diagnosis of C. albicans infections.

• Animal Bioscience
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• v.34 no.9
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• pp.1532-1543
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• 2021

Objective: This study was aimed to establish a quantitative detection method for meat contamination based on specific polypeptides. Methods: Thermally stable peptides with good responses were screened by high resolution liquid chromatography tandem mass spectrometry. Standard curves of specific polypeptide were established by triple quadrupole mass spectrometry. Finally, the adulteration of commercial samples was detected according to the standard curve. Results: Fifteen thermally stable peptides with good responses were screened. The selected specific peptides can be detected stably in raw meat and deep processed meat with the detection limit up to 1% and have a good linear relationship with the corresponding muscle composition. Conclusion: This method can be effectively used for quantitative analysis of commercial samples.

• Analytical Science and Technology
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• v.36 no.6
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• pp.281-290
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• 2023

Zidovudine is an antiretroviral agent prescribed for the prevention and treatment of human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS). It is typically recommended to be used in combination with other antiretroviral drugs. Zidovudine has the potential to generate N-nitrosodimethylamine (NDMA) in the presence of dimethylamine and nitrite salt under acidic reaction conditions during the drug manufacturing process. NDMA is a potent human carcinogen that may be detected in drug substances or drug products. An analytical method was developed to determine NDMA in pharmaceuticals including zidovudine using high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The analysis involved reversed-phase chromatography on a Kinetex F5 column with a mobile phase comprising water-acetonitrile mixtures. The detection of positively charged ions was conducted using atmospheric pressure chemical ionization (APCI). The calibration curve demonstrated excellent linearity (r = 0.9997) across the range of 1-50 ng/mL with a highly sensitive limit of detection (LOD) at 0.3 ng/mL. The developed method underwent thorough validation for specificity, linearity, accuracy, precision, robustness, and system suitability. This sensitive and specific analytical method was applied for detecting NDMA in zidovudine drug substance and its formulation currently available in the market, indicating its suitability for drug quality management purposes.

• Journal of Microbiology and Biotechnology
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• v.26 no.8
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• pp.1457-1463
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• 2016

Vibrio anguillarum, a devastating pathogen causing vibriosis among marine fish, is prevailing in worldwide fishery industries and accounts for grievous economic losses. Therefore, a rapid on-site detection and diagnostic technique for this pathogen is in urgent need. In this study, two mouse monoclonal antibodies (MAbs) against V. anguillarum, 6B3-C5 and 8G3-B5, were generated by using hybridoma technology and their isotypes were characterized. MAb 6B3-C5 was chosen as the detector antibody and conjugated with quantum dots. Based on MAb 6B3-C5 labeled with quantum dots, a modified dot blot assay was developed for the on-site determination of V. anguillarum. It was found that the method had no cross-reactivity with other than V. anguillarum bacteria. The detection limit (LOD) for V. anguillarum was 1 × 10³ CFU/ml in cultured bacterial suspension samples, which was a 100-fold higher sensitivity than the reported colloidal gold immunochromatographic test strip. When V. anguillarum was mixed with turbot tissue homogenates, the LOD was 1 × 10³ CFU/ml, suggesting that tissue homogenates did not influence the detection capabilities. Preenrichment with the tissue homogenates for 12 h could raise the LOD up to 1 × 10² CFU/ml, confirming the reliability of the method.

• The Plant Pathology Journal
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• v.39 no.5
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• pp.486-493
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• 2023

Cowpea mild mottle virus (CPMMV) is a global plant virus that poses a threat to the production and quality of legume crops. Early and accurate diagnosis is essential for effective managing CPMMV outbreaks. With the advancement in isothermal recombinase polymerase amplification and lateral flow strips technologies, more rapid and sensitive methods have become available for detecting this pathogen. In this study, we have developed a reverse transcription recombinase polymerase amplification combined with lateral flow strips (RT-RPA-LFS) method for the detection of CPMMV, specifically targeting the CPMMV coat protein (CP) gene. The RT-RPA-LFS assay only requires 20 min at 40℃ and demonstrates high specificity. Its detection limit was 10 copies/µl, which is approximately up to 100 times more sensitive than RT-PCR on agarose gel electrophoresis. The developed RT-RPA-LFS method offers a rapid, convenient, and sensitive approach for field detection of CPMMV, which contribute to controlling the spread of the virus.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.130-139
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• 2024

Artificial intelligence models are being used to detect facility anomalies using physics data such as vibration, current, and temperature for predictive maintenance in the manufacturing industry. Since the types of facility anomalies, such as facility defects and failures, anomaly detection methods using autoencoder-based unsupervised learning models have been mainly applied. Normal or abnormal facility conditions can be effectively classified using the reconstruction error of the autoencoder, but there is a limit to identifying facility anomalies specifically. When facility anomalies such as unbalance, misalignment, and looseness occur, the facility vibration frequency shows a pattern different from the normal state in a specific frequency range. This paper presents an N-segmentation anomaly detection method that performs anomaly detection by dividing the entire vibration frequency range into N regions. Experiments on nine kinds of anomaly data with different frequencies and amplitudes using vibration data from a compressor showed better performance when N-segmentation was applied. The proposed method helps materialize them after detecting facility anomalies.

• Journal of Food Hygiene and Safety
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• v.30 no.4
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• pp.366-371
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• 2015

This work was conducted to apply the multi class pesticide multiresidue method for determining the use of hexaconazole in the agricultural products using GC-NPD. The multi class pesticide multiresidue method results were validated for the assay of hexaconazole by using linearity, accuracy, precision, limit of detection and quantitation. The linearity in the concentration ranged from 0.025 to 5.0 mg/L ($R^2$ > 0.999). Lettuce recoveries ranged from 89.42% to 94.15% with relative standard deviations below 7.78%, for spiking levels from 0.04 to 4.0 mg/kg. The limit of detection was 0.04 mg/kg, and the limit of quantitation was 0.11 mg/kg. The intra- and inter-day precisions were 2.42~3.49% and 4.90~7.78%, respectively. We suggested that the multi class pesticide multiresidue method for determining hexaconazole was highly accurate and reproducible, and it will be used as a routine analysis in agricultural products.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.105-118
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• 2016

Game companies are frequently attacked by attackers while the companies are servicing their own games. This paper analyzes the limit of the Signature detection method, which is a way of detecting hacking modules in online games, and then this paper proposes the Scoring Signature detection scheme to make up for these problems derived from the limits. The Scoring Signature detection scheme enabled us to detect unknown hacking attacks, and this new scheme turned out to have more than twenty times of success than the existing signature detection methods. If we apply this Scoring Signature detection scheme and the existing detection methods at the same time, it seems to minimize the inconvenient situations to collect hacking modules. And also it is expected to greatly reduce the amount of using hacking modules in games which had not been detected yet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.365-380
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• 2022

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

• Korean Journal of Veterinary Service
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• v.43 no.3
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• pp.189-196
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• 2020

This study was conducted to analyze feasibility of monitoring of fluoroquinolnes residual through feather analysis in broilers. The calibration curve showed good linearity (r²≥0.99) within the concentration range of 1~100 ㎍/kg. The limit of detection (LOD) and limit of quantification (LOQ) were validated at ≤0.66 and ≤1.99 ㎍/kg in broiler feather, respectively. The recoveries in feather samples ranged from 94.6 to 114.4% (5.1-15.8% RSD) at the 5 to 20 ㎍/kg spiking levels. The proposed new analytical method proved to be suitable and effective for fluoroquinolnes determination. We also monitored fluoroquinolones residue in 36 samples (broiler that were slaughtered in Gyonggi-do) using this method. Among tested feather samples, enrofloxacin and ciprofloxacin were detected in all samples. In muscle samples, enrofloxacin was detected in 20 (55.6%) samples and ciprofloxacin was not detected.