• YAKHAK HOEJI
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• v.39 no.6
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• pp.636-644
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• 1995

Comparison of bioavailabflity (BA) of three brands of ranitidine (RT) tablets has been studied m rats. The purpose of this study was to characterize the pharniacolunetics of RT tablets in the rat and to coinpare phannacolunetic parameters of three brands of RT tablets. In addition, it was investigated whether plasma RT concentrations m humans can be predicted from pharmacokinetic parameters obtained in rats. RT was administered intravenously in dose of RT.HCI 10mg/kg and orally in dose of RT.HCI 50mg/kg as solution or crushed sample of thablets. Plasma RT concentrations were determned by HPLC. Plasma RT concentrations as a function of time were fitted to two compartment model. Plasma RT concentrations declined with a terminal half life ($t_{{1}/2{\betha}}$) of 40.9 min. The plasma RT concentration-time curve showed two peak plasma concentrations following an oral administration of solution or crushed sample in rats like humans. No significant difference among pharmacokinetic parameters was observed except $T_{max2}$ (p<0.05). The BA for crushed sample A, B and C were found to be 54.6 40.7 and 40.0%, respectively. Equivalence of $C_{max1}$ and $T_{max2}$ were guaranteed in this study. However, it was concluded that three brands of RT tablets are bioequivalent, taking the following characteristics of RT into consideration;(1) rapid onset of the effect is not required, (2) $C_{max1}$ and $T_{max2}$ do not seem to influence the effectiveness of the drug during a long-term treatment by the usual administration of twice a day. Results from this study were combined with plarmacokinetic data for RT in dogs and humans to develop a basis for interspecies scale-up of the disposition characteristics of the drug. there were similarities in the general disposition of the drug. Allometric relationships were sought between pharmacokinetic parameters nd species body weight. Significant interspecies correlations were found for total body clearance($Cl_{t}$) and steady state volume of distribution ($Bd_{ss}$). Thus, plasma RT concentrations in humans can be predicted from pharmacokinetic parameters obtained in rats.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.121-137
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• 2020

Data from the Ozone Monitoring Instrument (OMI) satellite and national emission inventories were used in this study to analyze air quality in East Asia and estimate the impact of domestic and foreign emissions on South Korea's air quality, based on which future emissions were predicted. The concentration trends of nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) in East Asia from 2005 to 2015 showed that both substances were highest in North East China (NEC), followed by South East China (SEC) and Seoul Metropolitan Area (SMA). The average SO₂ concentration was 1.63 times higher in NEC than in SMA. Analysis on the ratios of NO₂/SO₂ and NO_x/SO_x provides an indirect picture of the effect of transboundary air pollutants on atmospheric composition in Korea. The concentration ratio of NO₂/SO₂ in all study areas peaked in 2013 and SMA's emission ratio of NO_x/SO_x increased in 2015 by over 22% from 2013. Despite the reduction in domestic emissions, the concentration-to-emission ratios (NO₂/NO_x, SO₂/SO_x) rose gradually, which implies that other factors besides domestic emissions (e.g., foreign sources, lifetime, etc.) influence air quality in SMA. We estimated future emissions of NO_x and SO_x in SMA to be 296.2 and 39.0 ktons in 2025 and 284.4 and 33.8 ktons in 2035, respectively. Application of the inter-comparison techniques of this study to the data from the Geostationary Environment Monitoring Instrument (GEMS) is expected to provide concrete information which can be used to improve national emission inventories and figure out factors and sources that affect domestic air quality.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.113-113
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• 2018

Endophthalmitis is a disease that causes ocular inflammation and has a catastrophic effect on eyesight. Recent studies show that Enterococcus faecalis is rapidly increasing causative bacterium of endophthalmitis. It is predicted that the increased endophthalmitis by E. faecalis is presumable due to the high resistance of E. faecalis to moxifloxacin (MFX), which is a common antibiotic used for eye drop. Because of the need for therapeutic agents to overcome this problem, this study sought to explore the feasibility of developing a combination therapy using Orostachys japonicus. The ethylacetate fraction of O. japonicus (OJA) used in this study. Antimicrobial activity was tested 13 E. faecalis strains including one E. faecalis standard strain, eight clinically isolated E. faecalis strains and four quinolone resistant E. faecalis strains using CLSI antibiotic susceptibility test method. Minimal Inhibitory Concentration (MIC) of OJA was confirmed to be $500{\mu}g/ml$ for all 13 strains. Then we tested for the synergistic effect of OJA to MFX using checkboard test method. The MIC of MFX was $0.25{\mu}g/ml$ for the standard strain and 8 for the clinical isolates, and $16{\sim}64{\mu}g/ml$ for the quinolone - resistant strains. When OJA was mixed with MFX, no synergistic effect was observed in all strains, but the antibacterial activity of OJA remained unchanged. Most ocular other strains can be removed by MFX except the MFX resistant E. faecalis, which can be removed by OJA in combination therapy. Therefore, OJA can be a potential candidate for the combined treatment endophthalmitis.

• Environmental Engineering Research
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• v.12 no.1
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• pp.16-20
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• 2007

Toxicity of metal plating wastewater was evaluated by using acute toxicity tests on Daphnia magna. To identify toxicants of metal plating wastewater, several manipulations such as solid phase extraction (SPE), ion exchange and graduated pH adjustment were used. The SPE test had no significant effect on baseline toxicity, suggesting absence of toxic non-polar organics in metal plating wastewater. However, anion exchange largely decreased the baseline toxicity by 88%, indicating the causative toxicants were inorganic anions. Considering high concentration of chromium in metal plating wastewater, it is thought the anion is Cr(VI) species. Graduated pH test showing independence of the toxicity on pH change strongly supports this assumption. However, as revealed by toxicity confirmation experiment, the initial toxicity of metal plating wastewater (24-h TU=435) was not explained only by Cr(VI) (24-h TU = 725 at $280\;mg\;L^{-1}$). Addition of nickel($29.5\;mg\;L^{-1}$) and copper ($26.5\;mg\;L^{-1}$) largely decreased the chromium toxicity up to 417 TU, indicating antagonistic interaction between heavy metals. This heavy metal interaction was successfully predicted by an equation of 24-h $TU\;=\;3.67\;{\times}\;\ln([Cu]\;+\;[Ni])\;+\;79.44$ at a fixed concentration of chromium.

• Journal of Environmental Health Sciences
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• v.44 no.6
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• pp.539-547
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• 2018

Objectives: Ozone ($O_3$) advisories are issued by provincial/prefectural and city governments in Korea and Japan when oxidant concentrations exceed the criteria of the related country. Advisories issued only after exposure to high $O_3$ concentrations cannot be considered ideal measures. Forecasts of $O_3$ would be more beneficial to citizens' health and daily life than real-time advisories. The present study was undertaken to present a simplified forecasting model that can predict surface $O_3$ concentrations for the afternoon of the day of the forecast. Methods: For the construction of a simple and practical model, a multivariate regression model was applied. The monitored data on gases and climate variables from Japan's air quality networks that were recorded over nearly one year starting from April 2016 were applied as the subject for our model. Results: A well-known inverse correlation between $NO_2$ and $O_3$ was confirmed by the monitored data for Iksan, Korea and Fukuoka, Japan. Typical time fluctuations for $O_3$ and $NO_x$ were also found. Our model suggests that insolation is the most influential factor in determining the concentration of $O_3$. $CH_4$ also plays a major role in our model. It was possible to visually check for the fit of a theoretical distribution to the observed data by examining the probability-probability (P-P) scatter plot. The goodness of fit of the model in this study was also successfully validated through a comparison (r=0.8, p<0.05) of the measured and predicted $O_3$ concentrations. Conclusions: The advantage of our model is that it is capable of immediate forecasting of surface $O_3$ for the afternoon of the day from the routinely measured values of the precursor and meteorological parameters. Although a comparison to other approaches for $O_3$ forecasting was not carried out, the model suggested in this study would be very helpful for the citizens of Korea and Japan, especially during the $O_3$ season from May to June.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.119-133
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• 2023

With the rapid growth of the economy and fossil fuel consumption, the concentration of air pollutants has increased significantly and the air pollution problem is no longer limited to small areas. We conduct statistical analysis with the actual data related to air quality that covers the entire of South Korea using R and Python. Some factors such as SO₂, CO, O₃, NO₂, PM₁₀, precipitation, wind speed, wind direction, vapor pressure, local pressure, sea level pressure, temperature, humidity, and others are used as covariates. The main goal of this paper is to predict air quality index (AQI) spatio-temporal data. The observations of spatio-temporal big datasets like AQI data are correlated both spatially and temporally, and computation of the prediction or forecasting with dependence structure is often infeasible. As such, the likelihood function based on the spatio-temporal model may be complicated and some special modelings are useful for statistically reliable predictions. In this paper, we propose several methods for this big spatio-temporal AQI data. First, random effects with spatio-temporal basis functions model, a classical statistical analysis, is proposed. Next, neural networks model, a deep learning method based on artificial neural networks, is applied. Finally, random forest model, a machine learning method that is closer to computational science, will be introduced. Then we compare the forecasting performance of each other in terms of predictive diagnostics. As a result of the analysis, all three methods predicted the normal level of PM_2.5 well, but the performance seems to be poor at the extreme value.

• Journal of Environmental Health Sciences
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• v.46 no.1
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• pp.1-10
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• 2020

Objectives: This study intends to evaluate the ecological risk of lead (Pb), arsenic (As), and their compounds according to the 2010 action plan on inventory and management for national priority chemicals and provide calculations of risks to the environment. By doing so, we aim to inform risk management measures for the target chemicals. Methods: We conducted species sensitivity distribution (SSD) analysis using the collected ecotoxicity data and obtained predicted no effect concentrations (PNECs) for the in-water environment using a hazardous concentration of 5% (HC5) protective of most species (95%) in the environment. Based on the calculated PNECs for aquatic organisms, PNEC values for soil and sediment were calculated using the partition coefficient. We also calculated predicted exposure concentration (PEC) from nation-wide environmental monitoring data and then the hazard quotient (HQ) was calculated using PNEC for environmental media. Results: Ecological toxicity data was categorized into five groups and five species for Pb and four groups and four species for As. Based on the HC5 values from SSD analysis, the PNEC value for aquatic organisms was calculated as 0.40 ㎍/L for Pb and 0.13 ㎍/L for As. PNEC values for soil and sediment calculated using a partition coefficient were 77.36 and 350.50 mg/kg for Pb and 24.20 and 112.75 mg/kg for As. The analysis of national environmental monitoring data showed that PEC values in water were 0.284 ㎍/L for Pb and 0.024 ㎍/L for As, while those in soil and sediment were respectively 45.9 and 44 mg/kg for Pb, and 11.40 and 19.80 mg/kg for As. Conclusions: HQs of Pb and As were 0.70 and 0.18 in water, while those in soil and sediment were 0.59 and 0.13 for Pb and 0.47 and 0.18 for As. With HQs <1 of lead and arsenic in the environment, their ecological risk levels are found to be low.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.5
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• pp.236-241
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• 2016

This study conducted a screening-level ecological risk assessment for heavy metals in dredged sediment for recycling in terrestrial environment. Toxicological information of six heavy metals (i.e., Cu, Zn, Cd, Pb, Cr, and Ni) was collected from ECOTOX of US Environmental Protection Agency, and screened and qualified for the use in the screening-level ecological risk assessment. According to the number of terrestrial ecological receptors for which toxicological information is available, PNEC (Predicted No Effect Concentration) of each heavy metal was derived using either stochastic approach (for Cu, Zn, and Cd), or deterministic approach (for Pb, Cr, and Ni). Hazard quotients of the six heavy metals were derived for a field-collected dredged sediment using the PNEC derived and the PEC (Predicted Environmental Concentration) determined for the dredged sediment. The HQs of Cu, Zn, Cr, Pb and Ni were higher than unity indicating a possibility of ecological risk of the five heavy metals when the dredged sediment is applied in terrestrial environment. Accordingly, remediation processes or a higher-level ecological risk assessment would be needed for the recycling of the material.

• Environmental Analysis Health and Toxicology
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• v.15 no.1_2
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• pp.19-29
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• 2000

Acetanilide may be released into the environment through air and wastewater from its production and use sites as an intermediate in the synthesis of pharmaceuticals and dyes. Acetanilide is biodegraded rapidly under aerobic conditions and decomposed by indirect photolysis in the presence of OH radicals. An estimated bioconcentration factor of 4.5 suggests that bioaccumulation in aquatic organisms is low. Ecotoxicological data on acetanilide exist on acute toxicity to fishes of 4 species only. According to the EUSES system, the lowest PNEC (Predicted no effect concentration) in fishes is 0.01 mg/1 and PEC (Predicted environmental concentration) for surface water on a regional scale is 9.1$\times$10$\^$－5/mg/l as the worst case. RCR (Risk characterization ratio) of acetanilide for surface water on a regional scale was estimated as 9.1$\times$10-3, which is safe enough for fishes, RCR on a local basis slightly exceeds the value 1 in water and sediment; that is, 1.3 and 1.6, respectively, which suggests the existence of ecotoxicological risk at the vicinity of the manufacturing site. For the refinement of environmental risk assessment on acetanilide, more data should be collected regarding prolonged fish toxicity, acute toxicity toward daphnia and algae. It is, therefore, recommended that acetanilide should be a candidate for further work to supplement the lacking data until it is proved to be safe in the ecotoxicological aspects.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.95-106
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• 2014

This research analyzed biosignals associated with the change of emotion from lighting felt by the occupants and task type under various indoor thermal environments and illuminance, and examined the biosignals' impacts on work. To this end, the indoor thermal environment was constructed on the basis of PMV (predicted mean vote) index value, and various indoor environments were created by changing the brightness of LED stands. In this manner, a variety of indoor environments were constructed, and experiments were carried out. This research evaluates the sensibility response to lighting through a questionnaire survey in the given environment and incorporates different types of error searches. In this way, changes were analyzed by measuring electroencephalogram (EEG) and electrocardiograms (ECG). As a result, all biosignals on the task type showed significant differences from the thermal environment change. When PMV index value was 0.8 (temperature: $25^{\circ}C$, humidity: 50 %), concentration and attention were the most activated. However, the biosignals did not show significant differences from the illuminance change. Concentration on an occupant's work capability was confirmed to be closely related to the thermal environment. As for the subjective emotional response to lighting, the occupants felt comfort as illuminance was lower, while they felt discomfort as illuminance was higher. However, there were no significant differences from the thermal environment change.