• Journal of the Optical Society of Korea
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• v.17 no.1
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• pp.91-96
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• 2013

We report a method for optical monitoring of tumors in an animal model using optical coherence tomography (OCT). In a spectral domain OCT system, a superluminescent diode light source with a full width of 66 nm at half maximum and peak wavelength of 950 nm was used to take images having an axial resolution of 6.8 ${\mu}m$. Cancer cells of PC-3 were cultured and inoculated into the hypodermis of auricle tissues in BALB/c nude mice. We observed tumor formation and growth at the injection region of cancer cells in vivo and obtained the images of tumor mass center and sparse circumferences. On the $5^{th}$ day from an inoculation of cancer cells, histological images of the tumor region using cross-sectional slicing and dye staining of specimens were taken in order to confirm the correlation with the high resolution OCT images. The OCT image of tumor mass compared with normal tissues was analyzed using its A-scan data so as to obtain a tissue attenuation rate which increases according to tumor growth.

• Journal of Veterinary Science
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• v.22 no.2
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• pp.23.1-23.10
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• 2021

Background: Pseudorabies (PR), caused by the pseudorabies virus (PRV), is an endemic disease in some regions of China. Although there are many reports on epidemiological investigations into pseudorabies, information on PRV gI antibody dynamics in one pig farm is sparse. Objectives: To diagnose PR and analyze the course of PR eradication in one pig farm. Methods: Ten brains and 1,513 serum samples from different groups of pigs in a pig farm were collected to detect PRV gE gene and PRV gI antibody presence using real-time polymerase chain reaction and enzyme-linked immunosorbent assay, respectively. Results: The July 2015 results indicated that almost all brain samples were PRV gE gene positive, but PRV gI antibody results in the serum samples of the same piglets were all negative. In the boar herd, from October 2015 to July 2018 three positive individuals were culled in October 2015, and the negative status of the remaining boars was maintained in the following tests. In the sow herd, the PRV gI antibody positive rate was always more than 70% from October 2015 to October 2017; however, it decreased to 27% in January 2018 but increased to 40% and 52% in April and July 2018, respectively. The PRV gI antibody positive rate in 100-day pigs markedly decreased in October 2016 and was maintained at less than 30% in the following tests. For 150-day pigs, the PRV gI antibody positive rate decreased notably to 10% in April 2017 and maintained a negative status from July 2017. The positive trend of PRV gI antibody with an increase in pig age remarkably decreased in three tests in 2018. Conclusions: The results indicate that serological testing is not sensitive in the early stage of a PRV infection and that gilt introduction is a risk factor for a PRV-negative pig farm. The data on PRV gI antibody dynamics can provide reference information for pig farms wanting to eradicate PR.

• Journal of Ginseng Research
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• v.45 no.6
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• pp.754-762
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• 2021

Background: Ginsenoside Rh2, a major saponin derivative in ginseng extract, is recognized for its anti-cancer activities. Compared to coding genes, studies on long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) that are regulated by Rh2 in cancer cells, especially on competitive endogenous RNA (ceRNA) are sparse. Methods: LncRNAs whose promoter DNA methylation level was significantly altered by Rh2 were screened from methylation array data. The effect of STXBP5-AS1, miR-4425, and RNF217 on the proliferation and apoptosis of MCF-7 breast cancer cells was monitored in the presence of Rh2 after deregulating the corresponding gene. The ceRNA relationship between STXBP5-AS1 and miR-4425 was examined by measuring the luciferase activity of a recombinant luciferase/STXBP5-AS1 plasmid construct in the presence of mimic miR-4425. Results: Inhibition of STXBP5-AS1 decreased apoptosis but stimulated growth of the MCF-7 cells, suggesting tumor-suppressive activity of the lncRNA. MiR-4425 was identified to have a binding site on STXBP5-AS1 and proven to be downregulated by STXBP5-AS1 as well as by Rh2. In contrast to STXBP5-AS1, miR-4425 showed pro-proliferation activity by inducing a decrease in apoptosis but increased growth of the MCF-7 cells. MiR-4425 decreased luciferase activity from the luciferase/STXBP5-AS1 construct by 26%. Screening the target genes of miR-4425 and Rh2 revealed that Rh2, STXBP5-AS1, and miR-4425 consistently regulated tumor suppressor RNF217 at both the RNA and protein level. Conclusion: LncRNA STXBP5-AS1 is upregulated by Rh2 via promoter hypomethylation and acts as a ceRNA, sponging the oncogenic miR-4425. Therefore, Rh2 controls the STXBP5-AS1/miR-4425/RNF217 axis to suppress breast cancer cell growth.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.1-8
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• 2021

To simulate a process model in the field of chemical engineering, it is very important to identify the physical properties of novel materials as well as existing materials. However, it is difficult to measure the physical properties throughout a set of experiments due to the potential risk and cost. To address this, this study aims to develop a property prediction model based on the group contribution method for aromatic chemical compounds including benzene rings. The benzene rings of aromatic materials have a significant impact on their physical properties. To establish the prediction model, 42 important functional groups that determine the physical properties are considered, and the total numbers of functional groups on 147 aromatic chemical compounds are counted to prepare a dataset. Support vector regression is employed to prepare a prediction model to handle sparse and high-dimensional data. To verify the efficacy of this study, the results of this study are compared with those of previous studies. Despite the different datasets in the previous studies, the comparison indicated the enhanced performance in this study. Moreover, there are few reports on predicting the physical properties of aromatic compounds. This study can provide an effective method to estimate the physical properties of unknown chemical compounds and contribute toward reducing the experimental efforts for measuring physical properties.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.1-7
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• 2021

In this paper, we propose a feature selection technique for multi-label classification. Many existing feature selection techniques have selected features by calculating the relation between features and labels such as a mutual information scale. However, since the mutual information measure requires a joint probability, it is difficult to calculate the joint probability from an actual premise feature set. Therefore, it has the disadvantage that only a few features can be calculated and only local optimization is possible. Away from this regional optimization problem, we propose a feature selection technique that constructs a low-rank space in the entire given feature space and selects features with sparsity. To this end, we designed a regression-based objective function using Nuclear norm, and proposed an algorithm of gradient descent method to solve the optimization problem of this objective function. Based on the results of multi-label classification experiments on four data and three multi-label classification performance, the proposed methodology showed better performance than the existing feature selection technique. In addition, it was showed by experimental results that the performance change is insensitive even to the parameter value change of the proposed objective function.

• Journal of Chest Surgery
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• v.55 no.6
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• pp.470-477
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• 2022

Background: Upfront surgery followed by systemic treatment is recommended to treat clinical stage I-IIA small cell lung cancer (SCLC), but data on the clinical outcomes are sparse. Thus, this study evaluated the stage migration and long-term prognosis of surgically treated clinical stage I-IIA SCLC. Methods: We retrospectively reviewed 49 patients with clinical stage I-IIA SCLC who underwent upfront surgery between 2000 and 2020. Additionally, we re-evaluated the TNM (tumor-node-metastasis) staging according to the eighth edition of the American Joint Committee on Cancer staging system for lung cancer. Results: The clinical stages of SCLC were cIA in 75.5%, cIB in 18.4%, and cIIA in 6.1% of patients. A preoperative histologic diagnosis was made in 65.3% of patients. Lobectomy and systematic lymph node dissection were performed in 77.6% and 83.7% of patients, respectively. The pathological stages were pI in 67.3%, pII in 24.5%, pIII in 4.1%, and pIV in 4.1% of patients. The concordance rate between clinical and pathological stages was 44.9%, and the upstaging rate was 49.0%. The 5-year overall survival (OS) rate was 67.8%. No significant difference in OS was found between stages pI and pII. However, the OS for stages pIII/IV was significantly worse than for stages pI/II (p<0.001). Conclusion: In clinical stage I-IIA SCLC, approximately half of the patients were pathologically upstaged, and OS was favorable after upfront surgery, particularly in pI/II patients. The poor prognosis of pIII/IV patients indicates the necessity of intensive preoperative pathologic mediastinal staging.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• Journal of Veterinary Science
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• v.25 no.4
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• pp.58.1-58.8
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• 2024

Importance: Over the past decade, catfish farming has increased in Southeast Asia. However, there has been no existing for pharmacokinetic data in the hybrid catfish (Clarias macrocephalus x C. gariepinus). Objective: This study was designed to evaluate the pharmacokinetic characteristics of oxytetracycline (OTC) in the hybrid catfish, following single intravascular (IV) or oral (PO) administration at a single dosage of 50 mg/kg body weight (BW). Methods: In total, 140 catfish (each about 100-120 g BW) were divided into two groups (n = 70). Blood samples (0.6-0.8 mL) were collected from ventral caudal vein at pre-assigned times up to 144 h (sparse samples design). OTC plasma concentrations were analyzed using high-performance liquid chromatography-photodiode array detector. Results: The pharmacokinetic parameter of OTC was evaluated using a non-compartment model. OTC plasma concentrations were detectable for up to 144 and 120 h after IV and PO, respectively. The elimination half-life value of OTC was long with slow clearance after IV administration in hybrid catfish. The average maximum concentration value of OTC was 2.72 ㎍/mL with a time at the maximum concentration of 8 h. The absolute PO bioavailability was low (2.47%). Conclusions and Relevance: These results showed that PO administration of OTC at a dosage of 50 mg/kg BW was unlikely to be effective for clinical use in catfish. The pharmacodynamic properties and clinical efficacy of OTC after multiple medicated feed are warranted.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.379-394
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• 2021

Air pollution data in South Korea is provided on a real-time basis by Air Korea stations since 2005. Previous studies have shown the feasibility of gridding air pollution data, but they were confined to a few cities. This paper examines the creation of nationwide gridded maps for PM10 concentration using 333 Air Korea stations with variogram optimization and ordinary kriging. The accuracy of the spatial interpolation was evaluated by various sampling schemes to avoid a too dense or too sparse distribution of the validation points. Using the 114,745 matchups, a four-round blind test was conducted by extracting random validation points for every 365 days in 2019. The overall accuracy was stably high with the MAE of 5.697 ㎍/m³ and the CC of 0.947. Approximately 1,500 cases for high PM10 concentration also showed a result with the MAE of about 12 ㎍/m³ and the CC over 0.87, which means that the proposed method was effective and applicable to various situations. The gridded maps for daily PM10 concentration at the resolution of 0.05° also showed a reasonable spatial distribution, which can be used as an input variable for a gridded prediction of tomorrow's PM10 concentration.

• Korean Journal of Agricultural Science
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• v.39 no.3
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• pp.357-364
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• 2012

Genomic breeding value (GEBV) has recently become available in the beef cattle industry. Genomic selection methods are exceptionally valuable for selecting traits, such as marbling, that are difficult to measure until later in life. One method to utilize information from sparse marker panels is the Bayesian model selection method with RJMCMC. The accuracy of prediction varies between a multiple SNP model with RJMCMC (0.47 to 0.73) and a least squares method (0.11 to 0.41) when using SNP information, while the accuracy of prediction increases in the multiple SNP (0.56 to 0.90) and least square methods (0.21 to 0.63) when including a polygenic effect. In the multiple SNP model with RJMCMC model selection method, the accuracy ($r^2$) of GEBV for marbling predicted based only on SNP effects was 0.47, while the $r^2$ of GEBV predicted by SNP plus polygenic effect was 0.56. The accuracies of GEBV predicted using only SNP information were 0.62, 0.68 and 0.73 for CWT, EMA and BF, respectively. However, when polygenic effects were included, the accuracies of GEBV were increased to 0.89, 0.90 and 0.89 for CWT, EMA and BF, respectively. Our data demonstrate that SNP information alone is missing genetic variation information that contributes to phenotypes for carcass traits, and that polygenic effects compensate genetic variation that whole genome SNP data do not explain. Overall, the multiple SNP model with the RJMCMC model selection method provides a better prediction of GEBV than does the least squares method (single marker regression).