• YAKHAK HOEJI
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• v.44 no.5
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• pp.478-487
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• 2000

This study was carried out to find new anti-tumor agent producing microbe and to characterize the anti-tumor agent produced from the microbe. Purified compound that has a high cytotoxicity against tumor cell-lines could be obtained from the broth culture filtrates of Streptomyces sp.409 strain isolated from soil in Korea. The in vitro cytotoxicity the in vivo evaluation of acute toxicity the safety assessment of the anti-tumor compounds and the taxonomic characteristics of the anti-tumor agent were measured. The antitumor compound 1 and 2 were obtained from the broth culture filtrates of Streptomyces sp.409 strain. The cytotoxicity of the compound 1 against tumor cell-line P388D$_1$ showed almost 4.5 times higher than that of adriamycin. However in the cytotoxicity against normal cell line Vero E6, adriamycin showed adversely 4 times higher than the compound 1 ($IC_{50}$/ value: 228.7 $\mu\textrm{g}$/$m\ell$). In comparison study with compound 1 and compound 2 in the in vitro cytotoxin productivity against tumor cell lines, $IC_{50}$/ value of the compound 1 was 0.25 $\mu\textrm{g}$/$m\ell$ in tumor cell line P388D$_1$and 0.53 $\mu\textrm{g}$/$m\ell$ in tumor cell-line L1210, and that of the compound 2 was 7.18 $\mu\textrm{g}$/$m\ell$ and 35.71 $\mu\textrm{g}$/$m\ell$, respectively; LD$_{50}$ value of the compound 1 in the in vivo acute toxicity in mice was 22.62 $\mu\textrm{g}$/kg body weight. These results suggest that compound 1 purified from Streptomyces sp. 409 has anti-tumor activity and will be developed as an anti-tumor drug.g.

• Journal of Soil and Groundwater Environment
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• v.19 no.4
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• pp.31-44
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• 2014

In the present study, a few of recently developed geostatistical models are comparatively studied. The models are two-point statistics based sequential indicator simulation (SISIM) and generalized coupled Markov chain (GCMC), multi-point statistics single normal equation simulation (SNESIM), and object based model of FLUVSIM (fluvial simulation) that predicts structures of target object from the provided geometric information. Out of the models, SNESIM and FLUVSIM require additional information other than conditioning data such as training map and geometry, respectively, which generally claim demanding additional resources. For the comparative studies, three-dimensional fluvial reservoir model is developed considering the genetic information and the samples, as input data for the models, are acquired by mimicking realistic sampling (i.e. random sampling). For SNESIM and FLUVSIM, additional training map and the geometry data are synthesized based on the same information used for the objective model. For the comparisons of the predictabilities of the models, two different measures are employed. In the first measure, the ensemble probability maps of the models are developed from multiple realizations, which are compared in depth to the objective model. In the second measure, the developed realizations are converted to hydrogeologic properties and the groundwater flow simulation results are compared to that of the objective model. From the comparisons, it is found that the predictability of GCMC outperforms the other models in terms of the first measure. On the other hand, in terms of the second measure, the both predictabilities of GCMC and SNESIM are outstanding out of the considered models. The excellences of GCMC model in the comparisons may attribute to the incorporations of directional non-stationarity and the non-linear prediction structure. From the results, it is concluded that the various geostatistical models need to be comprehensively considered and comparatively analyzed for appropriate characterizations.

• Journal of Veterinary Science
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• v.22 no.6
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• pp.80.1-80.13
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• 2021

Background: Hyperbaric gaseous cryotherapy (HGC) is a type of cryotherapy used in human medicine for rehabilitation after orthopedic surgeries. Because HGC is known to reduce acute or chronic pain, research is needed to prove its effectiveness in veterinary medicine. Objectives: To compare the effects of HGC between the HGC treatment group and the nontreatment (NT) group on postoperative swelling, range of motion, lameness score, postoperative pain, and kinetic measurements after stifle joint surgery in dogs. Methods: Dogs were randomized in an HGC group or NT groups. In the HGC group, HGC was applied once a day for a total of 2 days after surgery. All parameters were measured postoperatively and at 1, 2, 10, and 28 days after surgery. Results: Twenty dogs were enrolled: 10 in the HGC group and 10 in the NT group. Soft tissue swelling was not significantly different between groups at any time point. In the HGC group, pain scores decreased significantly 24 h after surgery and 48 h after surgery. Dogs in the HGC group showed a significantly decreased lameness and improvement for all kinetic measurements beginning 48 h after surgery. In addition, the HGC group indicated a significant increase in range of motion as compared with the NT group at 28 days after surgery. Conclusions: HGC plays a powerful role in decreasing initial postoperative pain. Furthermore, the improvement in pain affects the use of the operated limb, and the continued use of the limb eventually assists in the quick recovery of normal function.

• The Korean Journal of Physiology and Pharmacology
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• v.25 no.6
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• pp.507-515
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• 2021

Postoperative ileus (POI), a symptom that occurs after abdominal surgery, reduces gastrointestinal motility. Although its mechanism is unclear, POI symptoms are known to be caused by inflammation 6 to 72 h after surgery. As proton pump inhibitors exhibit protective effect against acute inflammation, the purpose of this study was to determine the effect of ilaprazole on a POI rat model. POI was induced in rats by abdominal surgery. Rats were divided into six groups: control: normal rat + 0.5% CMC-Na, vehicle: POI rat + 0.5% CMC-Na, mosapride: POI rat + mosapride 2 mg/kg, ilaprazole 1 mg/kg: POI rat + ilaprazole 1 mg/kg, ilaprazole 3 mg/kg: POI rat + ilaprazole 3 mg/kg, and ilaprazole 10 mg/kg: POI rat + ilaprazole 10 mg/kg. Gastrointestinal motility was confirmed by measuring gastric emptying (GE) and gastrointestinal transit (GIT). In the small intestine, inflammation was confirmed by measuring TNF-α and IL-1β; oxidative stress was confirmed by SOD, GSH, and MDA levels; and histological changes were observed by H&E staining. Based on the findings, GE and GIT were decreased in the vehicle group and improved in the ilaprazole 10 mg/kg group. In the ilaprazole 10 mg/kg group, TNF-α and IL-1β levels were decreased, SOD and GSH levels were increased, and MDA levels were decreased. Histological damage was also reduced in the ilaprazole-treated groups. These findings suggest that ilaprazole prevents the decrease in gastrointestinal motility, a major symptom of postoperative ileus, and reduces inflammation and oxidative stress.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Journal of Animal Science and Technology
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• v.63 no.4
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• pp.751-758
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• 2021

The recessive white (locus c) phenotype observed in chickens is associated with three alleles (recessive white c, albino c^a, and red-eyed white c^re) and causative mutations in the tyrosinase (TYR) gene. The recessive white mutation (c) inhibits the transcription of TYR exon 5 due to a retroviral sequence insertion in intron 4. In this study, we genotyped and sequenced the insertion in TYR intron 4 to identify the mutation causing the unusual white plumage of Yeonsan Ogye chickens, which normally have black plumage. The white chickens had a homozygous recessive white genotype that matched the sequence of the recessive white type, and the inserted sequence exhibited 98% identity with the avian leukosis virus ev-1 sequence. In comparison, brindle and normal chickens had the homozygous color genotype, and their sequences were the same as the wild-type sequence, indicating that this phenotype is derived from other mutation(s). In conclusion, white chickens have a recessive white mutation allele. Since the size of the sample used in this study was limited, further research through securing additional samples to perform validation studies is necessary. Therefore, after validation studies, a selection system for conserving the phenotypic characteristics and genetic diversity of the population could be established if additional studies to elucidate specific phenotype-related genes in Yeonsan Ogye are performed.

• Geomechanics and Engineering
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• v.25 no.1
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• pp.1-16
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• 2021

Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The large number of inputs or conditioning factors for these models, however, can reduce the computation efficiency and increase the difficulty in collecting data. Feature selection is a good tool to address this problem by selecting the most important features among all factors to reduce the size of the input variables. However, two important questions need to be solved: (1) how do feature selection methods affect the performance of machine learning models? and (2) which feature selection method is the most suitable for a given machine learning model? This paper aims to address these two questions by comparing the predictive performance of 13 feature selection-based machine learning (FS-ML) models and 5 ordinary machine learning models on LSA. First, five commonly used machine learning models (i.e., logistic regression, support vector machine, artificial neural network, Gaussian process and random forest) and six typical feature selection methods in the literature are adopted to constitute the proposed models. Then, fifteen conditioning factors are chosen as input variables and 1,017 landslides are used as recorded data. Next, feature selection methods are used to obtain the importance of the conditioning factors to create feature subsets, based on which 13 FS-ML models are constructed. For each of the machine learning models, a best optimized FS-ML model is selected according to the area under curve value. Finally, five optimal FS-ML models are obtained and applied to the LSA of the studied area. The predictive abilities of the FS-ML models on LSA are verified and compared through the receive operating characteristic curve and statistical indicators such as sensitivity, specificity and accuracy. The results showed that different feature selection methods have different effects on the performance of LSA machine learning models. FS-ML models generally outperform the ordinary machine learning models. The best FS-ML model is the recursive feature elimination (RFE) optimized RF, and RFE is an optimal method for feature selection.

• Journal of Veterinary Science
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• v.22 no.3
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• pp.30.1-30.15
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• 2021

Background: New-generation adjuvants for foot-and-mouth disease virus (FMDV) vaccines can improve the efficacy of existing vaccines. Chinese medicinal herb polysaccharide possesses better promoting effects. Objectives: In this study, the aqueous extract from Artemisia rupestris L. (AEAR), an immunoregulatory crude polysaccharide, was utilized as the adjuvant of inactivated FMDV vaccine to explore their immune regulation roles. Methods: The mice in each group were subcutaneously injected with different vaccine formulations containing inactivated FMDV antigen adjuvanted with three doses (low, medium, and high) of AEAR or AEAR with ISA-206 adjuvant for 2 times respectively in 1 and 14 days. The variations of antibody level, lymphocyte count, and cytokine secretion in 14 to 42 days after first vaccination were monitored. Then cytotoxic T lymphocyte (CTL) response and antibody duration were measured after the second vaccination. Results: AEAR significantly induced FMDV-specific antibody titers and lymphocyte activation. AEAR at a medium dose stimulated Th1/Th2-type response through interleukin-4 and interferon-γ secreted by CD4⁺ T cells. Effective T lymphocyte counts were significantly elevated by AEAR. Importantly, the efficient CTL response was remarkably provoked by AEAR. Furthermore, AEAR at a low dose and ISA-206 adjuvant also synergistically promoted immune responses more significantly in immunized mice than those injected with only ISA-206 adjuvant and the stable antibody duration without body weight loss was 6 months. Conclusions: These findings suggested that AEAR had potential utility as a polysaccharide adjuvant for FMDV vaccines.

• Annals of Coloproctology
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• v.34 no.6
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• pp.312-316
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• 2018

Purpose: Anemia is associated with poor treatment results for a variety of cancers. The effect of low hemoglobin levels on long-term outcomes after the treatment of patients with an anal squamous cell carcinoma (SCC) remains unclear. For that reason, this study aimed to investigate the effect of anemia on treatment outcomes following chemoradiation for an anal SCC. Methods: This was a retrospective study of all patients who underwent curative treatment for an anal SCC between 2009 and 2015 at 2 trusts in the United Kingdom. Data were collated from prospectively collected cancer databases and were cross-checked with operating-room records and records in the hospitals' patient management systems. Results: We identified 103 patients with a median age of 63 years (range, 36-84 years). The median overall survival was 39 months (range, 9-90 months), and the disease-free survival was 36 months (range, 2-90 months). During the follow-up period, 16.5% patients died and 13.6% patients developed recurrence. Twenty-two people were anemic prior to treatment, with a female preponderance (20 of 22). No differences in disease-free survival (P = 0.74) and overall survival (P = 0.12) were noted between patients with anemia and those with normal hemoglobin levels. On regression the analysis, the combination of anemia, the presence of a defunctioning colostomy, lymph-node involvement and higher tumor stage correlated with poor overall survival. Conclusion: In this study, anemia did not influence disease-free survival or overall survival. We suggest that the interaction between anemia and survival is more complex than previously demonstrated and potentially reliant on other coexisting factors.

• Journal of dental hygiene science
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• v.19 no.1
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• pp.39-47
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• 2019

Background: Light-emitting diodes curing unit (LCU), which emit blue light, is used for polymerization of composite resins in many dentistry. Although the use of LCU for light-cured composite resin polymerization is considered safe, it is still controversial whether it can directly or indirectly have harmful biological influences on oral tissues. The aim of this study was to elucidate the biological effects of LCU in wavelengths ranging from 440 to 490 nm, on the cell viability and secretion of inflammatory cytokines in MDPC-23 odontoblastic cells and inflammatory-induced MDPC-23 cells by lipopolysaccharide (LPS). Methods: The MTT assay and observation using microscope were performed on MDPC-23 cells to investigate the cell viability and cytotoxic effects on LCU irradiation. Results: MDPC-23 cells and LPS stimulated MDPC-23 cells were found to have no effects on cell viability and cell morphology in the LCU irradiation. Nitric oxide (NO) and prostaglandin $E_2$ which are the pro-inflammatory mediators, and interleukin-$1{\beta}$ and tumor necrosis factor-${\alpha}$ (TNF-${\alpha}$) which are the proinflammatory cytokines were significantly increased in MCPD-23 cells after LCU irradiation as time increased in comparison with the control. LCU irradiation has the potential to induce inflammation or biological damages in normal dental tissues, including MDPC-23 cells. Conclusion: Therefore, it is necessary to limit the use of LCU except for the appropriate dose and irradiation time. In addition, LCU irradiation of inflammatory-induced MDPC-23 cells by LPS was reduced the secretion of NO compared to the LPS alone treatment group and was significantly reduced the secretion of TNF-${\alpha}$ in all the time groups. Therefore, LCU application in LPS stimulated MDPC-23 odontoblastic cells has a photodynamic therapy like effect as well as inflammation relief.