• Journal of Korean Neurosurgical Society
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• v.63 no.5
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• pp.579-589
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• 2020

Objective : No optimum genetic rat Huntington model both neuropathological using an adeno-associated virus (AAV-2) vector vector has been reported to date. We investigated whether direct infection of an AAV2 encoding a fragment of mutant huntingtin (AV2-82Q) into the rat striatum was useful for optimizing the Huntington rat model. Methods : We prepared ten unilateral models by injecting AAV2-82Q into the right striatum, as well as ten bilateral models. In each group, five rats were assigned to either the 2×10¹² genome copies (GC)/mL of AAV2-82Q (×1, low dose) or 2×10¹³ GC/mL of AAV2-82Q (×10, high dose) injection model. Ten unilateral and ten bilateral models injected with AAV-empty were also prepared as control groups. We performed cylinder and stepping tests 2, 4, 6, and 8 weeks after injection, tested EM48 positive mutant huntingtin aggregates. Results : The high dose of unilateral and bilateral AAV2-82Q model showed a greater decrease in performance on the stepping and cylinder tests. We also observed more prominent EM48-positive mutant huntingtin aggregates in the medium spiny neurons of the high dose of AAV2-82Q injected group. Conclusion : Based on the results from the present study, high dose of AAV2-82Q is the optimum titer for establishing a Huntington rat model. Delivery of high dose of human AAV2-82Q resulted in the manifestation of Huntington behaviors and optimum expression of the huntingtin protein in vivo.

• Progress in Medical Physics
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• v.14 no.4
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• pp.225-233
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• 2003

The goal of a radiation treatment plan is to deliver a homogeneous dose to a target with minimal irradiation of the adjacent normal tissues. Dose uniformity is especially important for stereotactic radiosurgery using a linear accelerator. The dose uniformity and high dose delivery of a single spherical dose distribution exceed 70％. This also results with a similar stereotactic radiosurgical plan using a Gamma Knife. The dose distribution produced in a stereotactic radiosurgical plan using a Gamma Knife and Linear accelerator is spherical, and the application of the sphere packing arrangement in a real radiosurgical plan requires much time and skill. In this study, we found a characteristic of dose distribution with transformation of beam parameters that must be considered in a radiosurgical plan for effective radiosurgery. First, we assumed a cylinder type tumor model and a cube type tumor model. Secondly, the results of the tumor models were compared and analyzed with dose profiles and DVH_(Dose Volume Histogram) representative dose distribution. We found the optimal composition of beam parameters_(i.e. collimator size, number of isocenter, gap of isocenters etc.), which allowed the tumor models to be involved in the isodose curve at a high level. In conclusion, the characteristics found in this study are helpful for improving the effectiveness and speed of a radiosurgical plan for stereotactic radiosurgery.

• Journal of Astronomy and Space Sciences
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• v.18 no.1
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• pp.71-80
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• 2001

The threshold voltage shift observed in TDE (Total Dose Experiment) on board the KITAT-1 is converted into dose (rad($SiO_2$)) using the result of laboratory calibration with Co-60 gamma ray source in KAERI (Korea Atomic Energy Research Institute). Simulation using the NASA radiation model of geomagnetosphere verifies that the dose difference between RADFET1 and RADFET3 observed on KITSAT-1 comes from the difference in shielding thickness at the position of these RADFETs.

• Advances in environmental research
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• v.3 no.3
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• pp.231-251
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• 2014

The present study examines the phosphate adsorption potential and behavior of mixture of Ground Burnt Patties (GBP), a solid waste generated from cooking fuel used in earthen stoves and Red Soil (RS), a natural substance in fixed bed column mode operation. The characterization of adsorbent was done by Proton Induced X-ray Emission (PIXE), and Proton Induced ${\gamma}$-ray Emission (PIGE) methods. The FTIR spectroscopy of spent adsorbent reveals the presence of absorbance peak at $1127cm^{-1}$ which appears due to P = O stretching, thus confirming phosphate adsorption. The effects of bed height (10, 15 and 20 cm), flow rate (2.5, 5 and 7.5 mL/min) and initial phosphate concentration (5 and 15 mg/L) on breakthrough curves were explored. Both the breakthrough and exhaustion time increased with increase in bed depth, decrease in flow rate and influent concentration. Thomas model, Yoon-Nelson model and Modified Dose Response model were used to fit the column adsorption data using nonlinear regression analysis while Bed Depth Service Time model followed linear regression analysis under different experimental condition to evaluate model parameters that are useful in scale up of the process. The values of correlation coefficient ($R^2$) and the Sum of Square Error (SSE) revealed the Modified Dose Response model as the best fitted model to the experimental data. The adsorbent mixture responded effectively to the desorption and reusability experiment. The results of this finding advocated that mixture of GBP and RS can be used as a low cost, highly efficient adsorbent for phosphate removal from aqueous solution.

• Radiation Oncology Journal
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• v.20 no.1
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• pp.1-16
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• 2002

Purpose : Three dimensional conformal radiotherapy planning is being used widely for the treatment of patients with brain tumor. However, it takes much time to develop an optimal treatment plan, therefore, it is difficult to apply this technique to all patients. To increase the efficiency of this technique, we need to develop standard radiotherapy plant for each site of the brain. Therefore we developed several 3 dimensional conformal radiotherapy plans (3D plans) for tumors at each site of brain, compared them with each other, and with 2 dimensional radiotherapy plans. Finally model plans for each site of the brain were decide. Materials and Methods : Imaginary tumors, with sizes commonly observed in the clinic, were designed for each site of the brain and drawn on CT images. The planning target volumes (PTVs) were as follows; temporal $tumor-5.7\times8.2\times7.6\;cm$, suprasellar $tumor-3\times4\times4.1\;cm$, thalamic $tumor-3.1\times5.9\times3.7\;cm$, frontoparietal $tumor-5.5\times7\times5.5\;cm$, and occipitoparietal $tumor-5\times5.5\times5\;cm$. Plans using paralled opposed 2 portals and/or 3 portals including fronto-vertex and 2 lateral fields were developed manually as the conventional 2D plans, and 3D noncoplanar conformal plans were developed using beam's eye view and the automatic block drawing tool. Total tumor dose was 54 Gy for a suprasellar tumor, 59.4 Gy and 72 Gy for the other tumors. All dose plans (including 2D plans) were calculated using 3D plan software. Developed plans were compared with each other using dose-volume histograms (DVH), normal tissue complication probabilities (NTCP) and variable dose statistic values (minimum, maximum and mean dose, D5, V83, V85 and V95). Finally a best radiotherapy plan for each site of brain was selected. Results : 1) Temporal tumor; NTCPs and DVHs of the normal tissue of all 3D plans were superior to 2D plans and this trend was more definite when total dose was escalated to 72 Gy (NTCPs of normal brain 2D $plans:27\%,\;8\%\rightarrow\;3D\;plans:1\%,\;1\%$). Various dose statistic values did not show any consistent trend. A 3D plan using 3 noncoplanar portals was selected as a model radiotherapy plan. 2) Suprasellar tumor; NTCPs of all 3D plans and 2D plans did not show significant difference because the total dose of this tumor was only 54 Gy. DVHs of normal brain and brainstem were significantly different for different plans. D5, V85, V95 and mean values showed some consistent trend that was compatible with DVH. All 3D plans were superior to 2D plans even when 3 portals (fronto-vertex and 2 lateral fields) were used for 2D plans. A 3D plan using 7 portals was worse than plans using fewer portals. A 3D plan using 5 noncoplanar portals was selected as a model plan. 3) Thalamic tumor; NTCPs of all 3D plans were lower than the 2D plans when the total dose was elevated to 72 Gy. DVHs of normal tissues showed similar results. V83, V85, V95 showed some consistent differences between plans but not between 3D plans. 3D plans using 5 noncoplanar portals were selected as a model plan. 4) Parietal (fronto- and occipito-) tumors; all NTCPs of the normal brain in 3D plans were lower than in 2D plans. DVH also showed the same results. V83, V85, V95 showed consistent trends with NTCP and DVH. 3D plans using 5 portals for frontoparietal tumor and 6 portals for occipitoparietal tumor were selected as model plans. Conclusion : NTCP and DVH showed reasonable differences between plans and were through to be useful for comparing plans. All 3D plans were superior to 2D plans. Best 3D plans were selected for tumors in each site of brain using NTCP, DVH and finally by the planner's decision.

• Journal of Food Hygiene and Safety
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• v.14 no.4
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• pp.319-326
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• 1999

Recently, it is continuously rising to concern about the health risk being induced by microorganisms in food such as Escherichia coli O157:H7 and Listeria monocytogenes. Various organizations and regulatory agencies including U.S.FPA, U.S.DA and FAO/WHO are preparing the methodology building to apply microbial quantitative risk assessment to risk-based food safety program. Microbial risks are primarily the result of single exposure and its health impacts are immediate and serious. Therefore, the methodology of risk assessment differs from that of chemical risk assessment. Microbial quantitative risk assessment consists of tow steps; hazard identification, exposure assessment, dose-response assessment and risk characterization. Hazard identification is accomplished by observing and defining the types of adverse health effects in humans associated with exposure to foodborne agents. Epidemiological evidence which links the various disease with the particular exposure route is an important component of this identification. Exposure assessment includes the quantification of microbial exposure regarding the dynamics of microbial growth in food processing, transport, packaging and specific time-temperature conditions at various points from animal production to consumption. Dose-response assessment is the process characterizing dose-response correlation between microbial exposure and disease incidence. Unlike chemical carcinogens, the dose-response assessment for microbial pathogens has not focused on animal models for extrapolation to humans. Risk characterization links the exposure assessment and dose-response assessment and involve uncertainty analysis. The methodology of microbial dose-response assessment is classified as nonthreshold and thresh-old approach. The nonthreshold model have assumption that one organism is capable of producing an infection if it arrives at an appropriate site and organism have independence. Recently, the Exponential, Beta-poission, Gompertz, and Gamma-weibull models are using as nonthreshold model. The Log-normal and Log-logistic models are using as threshold model. The threshold has the assumption that a toxicant is produce by interaction of organisms. In this study, it was reviewed detailed process including risk value using model parameter and microbial exposure dose. Also this study suggested model application methodology in field of exposure assessment using assumed food microbial data(NaCl, water activity, temperature, pH, etc.) and the commercially used Food MicroModel. We recognized that human volunteer data to the healthy man are preferred rather than epidemiological data fur obtaining exact dose-response data. But, the foreign agencies are studying the characterization of correlation between human and animal. For the comparison of differences to the population sensitivity: it must be executed domestic study such as the establishment of dose-response data to the Korean volunteer by each microbial and microbial exposure assessment in food.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.503-509
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• 2020

This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

• The Korean Journal of Physiology and Pharmacology
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• v.28 no.2
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• pp.121-127
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• 2024

Vancomycin is a frequently used antibiotic in intensive care units, and the patient's renal clearance affects the pharmacokinetic characteristics of vancomycin. Several advantages have been reported for vancomycin continuous intravenous infusion, but studies on continuous dosing regimens based on patients' renal clearance are insufficient. The aim of this study was to develop a vancomycin serum concentration prediction model by factoring in a patient's renal clearance. Children admitted to our institution between July 1, 2021, and July 31, 2022 with records of continuous infusion of vancomycin were included in the study. Sex, age, height, weight, vancomycin dose by weight, interval from the start of vancomycin administration to the time of therapeutic drug monitoring sampling, and vancomycin serum concentrations were analyzed with the linear regression analysis of the mixed effect model. Univariable regression analysis was performed using the vancomycin serum concentration as a dependent variable. It showed that vancomycin dose (p < 0.001) and serum creatinine (p = 0.007) were factors that had the most impact on vancomycin serum concentration. Vancomycin serum concentration was affected by vancomycin dose (p < 0.001) and serum creatinine (p = 0.001) with statistical significance, and a multivariable regression model was obtained as follows: Vancomycin serum concentration (mg/l) = -1.296 + 0.281 × vancomycin dose (mg/kg) + 20.458 × serum creatinine (mg/dl) (adjusted coefficient of determination, R² = 0.66). This prediction model is expected to contribute to establishing an optimal continuous infusion regimen for vancomycin.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.274-281
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• 2019

Objective: The objective of this study was to estimate the risk of Campylobacter jejuni (C. jejuni) infection from various jerky products in Korea. Methods: For the exposure assessment, the prevalence and predictive models of C. jejuni in the jerky and the temperature and time of the distribution and storage were investigated. In addition, the consumption amounts and frequencies of the products were also investigated. The data for C. jejuni for the prevalence, distribution temperature, distribution time, consumption amount, and consumption frequency were fitted with the @RISK fitting program to obtain appropriate probabilistic distributions. Subsequently, the dose-response models for Campylobacter were researched in the literature. Eventually, the distributions, predictive model, and dose-response model were used to make a simulation model with @RISK to estimate the risk of C. jejuni foodborne illness from the intake of jerky. Results: Among 275 jerky samples, there were no C. jejuni positive samples, and thus, the initial contamination level was statistically predicted with the RiskUniform distribution [RiskUniform (-2, 0.48)]. To describe the changes in the C. jejuni cell counts during distribution and storage, the developed predictive models with the Weibull model (primary model) and polynomial model (secondary model) were utilized. The appropriate probabilistic distribution was the BetaGeneral distribution, and it showed that the average jerky consumption was 51.83 g/d with a frequency of 0.61%. The developed simulation model from this data series and the dose-response model (Beta Poisson model) showed that the risk of C. jejuni foodborne illness per day per person from jerky consumption was $1.56{\times}10^{-12}$. Conclusion: This result suggests that the risk of C. jejuni in jerky could be considered low in Korea.

• Journal of Radiation Protection and Research
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• v.12 no.2
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• pp.28-36
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• 1987

Gaussian plume model is used to assess environmental dose for abnormal radioactive release in nuclear facility, but there has a problem to use it for complex terrain. In this report, MATTEW and WIND04 Codes which had been verified were used to calculate wind field in the complex terrain. Under the base of these codes principle, wind fields were obtained from the calculation of the finite difference approximation for advection-diffusion equations which satisfy the mass-conservative law. Particle concentrations and external doses were calculated by using PIC model which approximate the particle to radioactive cloud, and atmospheric diffusion of the particles from the random walk method. The results show that the adjusted wind fields and the distributions of the exposure dose vary with the topography of the complex terrain.