• Journal of Korean Dental Science
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• v.16 no.1
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• pp.35-46
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• 2023

Purpose: Culture-based methods for microbiological diagnosis and antibiotic susceptibility tests have limitations in the management of orofacial infections. We aimed to profile pus microbiota and identify antibiotic resistance genes (ARGs) using a culture-independent approach. Materials and Methods: Genomic DNA samples extracted from the pus specimens of two patients with orofacial abscesses were subjected to shotgun sequencing on the NovaSeq system. Taxonomic profiling and prediction of ARGs were performed directly from the metagenomic raw reads. Result: Taxonomic profiling revealed obligate anaerobic polymicrobial communities associated with infections of odontogenic origins: the microbial community of Patient 1 consisted of one predominant species (Prevotella oris 74.6%) with 27 minor species, while the sample from Patient 2 contained 3 abundant species (Porphyromonas endodontalis 33.0%; P. oris 31.6%; and Prevotella koreensis 13.4%) with five minor species. A total of 150 and 136 putative ARGs were predicted in the metagenome of each pus sample. The coverage of most predicted ARGs was less than 10%, and only the CfxA2 gene identified in Patient 1 was covered 100%. ARG analysis of the seven assembled genome/metagenome datasets of P. oris revealed that strain C735 carried the CfxA2 gene. Conclusion: A metagenomics-based approach is useful to profile predominantly anaerobic polymicrobial communities but needs further verification for reliable ARG detection.

• Journal of Ginseng Research
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• v.38 no.4
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• pp.278-288
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• 2014

Background: Panax ginseng Meyer is a traditional medicinal plant famous for its strong therapeutic effects and serves as an important herbal medicine. To understand and manipulate genes involved in secondary metabolic pathways including ginsenosides, transcriptome profiling of P. ginseng is essential. Methods: RNA-seq analysis of adventitious roots of two P. ginseng cultivars, Chunpoong (CP) and Cheongsun (CS), was performed using the Illumina HiSeq platform. After transcripts were assembled, expression profiling was performed. Results: Assemblies were generated from ~85 million and ~77 million high-quality reads from CP and CS cultivars, respectively. A total of 35,527 and 27,716 transcripts were obtained from the CP and CS assemblies, respectively. Annotation of the transcriptomes showed that approximately 90% of the transcripts had significant matches in public databases.We identified several candidate genes involved in ginsenoside biosynthesis. In addition, a large number of transcripts (17%) with different gene ontology designations were uniquely detected in adventitious roots compared to normal ginseng roots. Conclusion: This study will provide a comprehensive insight into the transcriptome of ginseng adventitious roots, and a way for successful transcriptome analysis and profiling of resource plants with less genomic information. The transcriptome profiling data generated in this study are available in our newly created adventitious root transcriptome database (http://im-crop.snu.ac.kr/transdb/index.php) for public use.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.9 no.4
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• pp.204-211
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• 2004

Autonomous profiling CTD floats are a useful tool for observing the oceans. We, however, cannot perform post-deployment calibration of the CTD's attached to the floats, and the assessment of the accuracy and stability of the profile data from the floats is one of the important issues in the delayed mode quality control of the profiles. Variations in salinity in the intermediate level of East Sea is comparable to the accuracy of salinity data required by the international Argo Program, which is 0.01. Therefore, we can assess the credibility of salinity data from the floats deployed in the East Sea using three independent methods while considering the East Sea as a salinity calibration bath. The methods utilized here are 1) comparison of high quality CTD data and float data obtained at similar locations at similar time, 2) comparison of float data obtained at similar locations at similar time, and 3) investigation of long term stability and accuracy of salinity data from parking depths. All three methods show that without any calibration, the salinity data satisfy the accuracy criterion by the Argo Program. While assuming that the intermediate level temperature in the East Sea is as homogeneous as the salinity, we have applied the three methods to temperature data. We found that the accuracy of temperature reading is 0.01$^{\circ}C$, which is about twice larger than the requirement by the Argo Program, 0.005$^{\circ}C$. This does not mean that the temperature readings are inaccurate, because the intermediate level temperature does vary spacially and temporally more than the accuracy interval required by the Argo Program. If we take into account the variation in the intermediate level temperature, the accuracy of temperature data from the floats is not significantly different from that proposed by the Argo Program. Therefore, one could use both temperature and salinity profiles from the floats assessed in this study without calibration.

• Molecules and Cells
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• v.26 no.2
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• pp.121-130
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• 2008

Methamphetamine, a commonly used addictive drug, is a powerful addictive stimulant that dramatically affects the CNS. Repeated METH administration leads to a rewarding effect in a state of addiction that includes sensitization, dependence, and other phenomena. It is well known that susceptibility to the development of addiction is influenced by sources of reinforcement, variable neuroadaptive mechanisms, and neurochemical changes that together lead to altered homeostasis of the brain reward system. These behavioral abnormalities reflect neuroadaptive changes in signal transduction function and cellular gene expression produced by repeated drug exposure. To provide a better understanding of addiction and the mechanism of the rewarding effect, it is important to identify related genes. In the present study, we performed gene expression profiling using microarray analysis in a reward effect animal model. We also investigated gene expression in four important regions of the brain, the nucleus accumbens, striatum, hippocampus, and cingulated cortex, and analyzed the data by two clustering methods. Genes related to signaling pathways including G-protein-coupled receptor-related pathways predominated among the identified genes. The genes identified in our study may contribute to the development of a gene modeling network for methamphetamine addiction.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.231-231
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• 2012

Correct determination of the interface locations is critical for the calibration of the depth scale and measurement of layer thickness in SIMS depth profiling analysis of multilayer films. However, the interface locations are difficult to determine due to the unwanted distortion from the real ones by the several effects due to sputtering with energetic ions. In this study, the layer thicknesses of Si/Ge and Si/Ti multilayer films were measured by SIMS depth profiling analysis using the oxygen and cesium primary ion beam. The interface locations in the multilayer films could be determined by two methods. The interfaces can be determined by the 50 at% definition where the atomic fractions of the constituent layer elements drop or rise to 50 at% at the interfaces. In this method, the raw depth profiles were converted to compositional depth profiles through the two-step conversion process using the alloy reference relative sensitivity factors (AR-RSF) determined by the alloy reference films with well-known compositions determined by Rutherford backscattering spectroscopy (RBS). The interface locations of the Si/Ge and Si/Ti multilayer films were also determined from the intensities of the interfacial composited ions (SiGe+, SiTi+). The determination of the interface locations from the composited ions was found to be difficult to apply due to the small intensity and the unclear variation at the interfaces.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.107-122
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• 2015

Many defensive mechanisms have been evolved as new attack methods are developed. However, APT attacks using e-mail are still hard to detect and prevent. Recently, many organizations in the government sector or private sector have been hacked by malicious e-mail based APT attacks. In this paper, first, we built hacking e-mail database based on the real e-mail data which were used in attacks on the Korean government organizations in recent years. Then, we extracted features from the hacking e-mails for profiling them. We design a case vector that can describe the specific characteristics of hacking e-mails well. Finally, based on case based reasoning, we made an algorithm for retrieving the most similar case from the hacking e-mail database when a new hacking e-mail is found. As a result, hacking e-mails have common characteristics in several features such as geo-location information, and these features can be used for classifying benign e-mails and malicious e-mails. Furthermore, this proposed case based reasoning algorithm can be useful for making a decision to analyze suspicious e-mails.

• Analytical Science and Technology
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• v.33 no.2
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• pp.98-107
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• 2020

Methamphetamine (MA) is currently the most abused illicit drug in Korea. MA is produced by chemical synthesis, and the final target drug that is produced contains small amounts of the precursor chemicals, intermediates, and by-products. To identify and quantify these trace compounds in MA seizures, a practical and feasible approach for conducting chromatographic fingerprinting with a suite of traditional chemometric methods and recently introduced machine learning approaches was examined. This was achieved using gas chromatography (GC) coupled with a flame ionization detector (FID) and mass spectrometry (MS). Following appropriate examination of all the peaks in 71 samples, 166 impurities were selected as the characteristic components. Unsupervised (principal component analysis (PCA), hierarchical cluster analysis (HCA), and K-means clustering) and supervised (partial least squares-discriminant analysis (PLS-DA), orthogonal partial least squares-discriminant analysis (OPLS-DA), support vector machines (SVM), and deep neural network (DNN) with Keras) chemometric techniques were employed for classifying the 71 MA seizures. The results of the PCA, HCA, K-means clustering, PLS-DA, OPLS-DA, SVM, and DNN methods for quality evaluation were in good agreement. However, the tested MA seizures possessed distinct features, such as chirality, cutting agents, and boiling points. The study indicated that the established qualitative and semi-quantitative methods will be practical and useful analytical tools for characterizing trace compounds in illicit MA seizures. Moreover, they will provide a statistical basis for identifying the synthesis route, sources of supply, trafficking routes, and connections between seizures, which will support drug law enforcement agencies in their effort to eliminate organized MA crime.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2023.04a
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• pp.16-16
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• 2023

Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. Metabolomics has its roots in early metabolite profiling studies but is now a rapidly expanding area of scientific research in its own right. In this study, the applications of metabolomics in natural product studies are explored. Ginseng is a well-known herbal medicine and has various pharmacological effects, which include antiaging, anticancer, antifatigue, memory enhancing, immunomodulatory, and stress reducing effects. Metabolomic analysis of organic acids has not been performed for evaluation whether ginseng has been cultivated using conventional or environmental-friendly farming methods. In this study, profiling analysis was conducted for organic acids (OAs) in ginseng roots produced using conventional or environmentfriendly farming methods at five locations in each of five regions. In OA profiles, lactic acid was the most abundant OA in all regions, with the exception for environmentally friendly farmed ginseng in two of the five regions, in which glycolic acid was most abundant OA. OA profiles in all regions showed isocitric acid levels were increased by environment-friendly cultivation, which suggests metabolic differences associated from farming method, and that isocitric acid might be a useful discriminatory biomarker of environmental-friendly and conventional cultivation. The results of the present study suggest metabolomic studies of OAs in ginseng roots might be useful for monitoring whether ginseng has been cultivated using conventional or environmentally friendly farming methods.

• Genomics & Informatics
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• v.21 no.3
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• pp.40.1-40.11
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• 2023

Microbial community profiling using 16S rRNA amplicon sequencing allows for taxonomic characterization of diverse microorganisms. While amplicon sequence variant (ASV) methods are increasingly favored for their fine-grained resolution of sequence variants, they often discard substantial portions of sequencing reads during quality control, particularly in datasets with large number samples. We present a streamlined pipeline that integrates FastP for read trimming, HmmUFOtu for operational taxonomic units (OTU) clustering, Vsearch for chimera checking, and Kraken2 for taxonomic assignment. To assess the pipeline's performance, we reprocessed two published stool datasets of normal Korean populations: one with 890 and the other with 1,462 independent samples. In the first dataset, HmmUFOtu retained 93.2% of over 104 million read pairs after quality trimming, discarding chimeric or unclassifiable reads, while DADA2, a commonly used ASV method, retained only 44.6% of the reads. Nonetheless, both methods yielded qualitatively similar β-diversity plots. For the second dataset, HmmUFOtu retained 89.2% of read pairs, while DADA2 retained a mere 18.4% of the reads. HmmUFOtu, being a closed-reference clustering method, facilitates merging separately processed datasets, with shared OTUs between the two datasets exhibiting a correlation coefficient of 0.92 in total abundance (log scale). While the first two dimensions of the β-diversity plot exhibited a cohesive mixture of the two datasets, the third dimension revealed the presence of a batch effect. Our comparative evaluation of ASV and OTU methods within this streamlined pipeline provides valuable insights into their performance when processing large-scale microbial 16S rRNA amplicon sequencing data. The strengths of HmmUFOtu and its potential for dataset merging are highlighted.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2273-2276
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• 2013

Objectives: This study employed proteomic profiling to identify specific tumor markers that might improve early diagnosis of lung squamous cell carcinoma. Methods: Serum samples were isolated from 30 patients with stage I lung squamous cell carcinoma and 30 age-and gender-matched healthy controls, and proteomic profiles were obtained by matrix-assisted laser desorption ionization time of flight mass spectrometry. Results: Three highly expressed potential tumor markers were identified in the sera of stage I lung squamous cell carcinoma patients, with molecular weights of 3261.69, 3192.07, and 2556.92 Da. One protein peak with molecular weight 3261.69 Da was chosen as the candidate biomarker and identified as a fibrinogen alpha chain through a search of the IPI, NCBI or SWISS-PROT protein databases. Conclusion: As a potential tumor biomarker, fibrinogen alpha chain may be applicable for the early diagnosis and prognosis of lung squamous cell carcinoma patients.