• Korean Journal of Food Science and Technology
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• v.47 no.3
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• pp.373-379
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• 2015

This study aimed to investigate the anti-amnesic effect of perilla oil against trimethyltin (TMT)-induced learning and memory impairment in ICR mice. Perilla oil (2.5 mL/kg of body weight) and soybean oil (2.5 mL/kg of body weight) were administered orally to mice for 3 weeks, and at the end of the experimental period, cognitive behavior was examined by Y-maze and Morris water maze (MWM) tests. Behavioral tests showed that the mice treated with perilla oil had improved cognitive function compared to that in mice administered soybean oil. Analysis of brain tissue showed that perilla oil significantly lowered acetylcholinesterase activity and malondialdehyde (MDA) levels. Oxidized glutathione (GSH)-to-total GSH ratio also decreased from 10.4% to 5.3% in perilla oil-treated mice, but superoxide dismutase (SOD) activity increased from 11.7 to 14.2 U/mg protein. Therefore, these results suggest that the perilla oil could be a potential functional substance for improving cognitive function.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.113-116
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• 2011

Purpose: Acetylcholine receptor antibodies cause acetylcholine receptor loss, which is responsible for failure of the neuromuscular junction in the acetylcholine receptor autoantibody. The disease characterized by muscle weakness and fatigue, myasthenia gravis(MG) occurs when the body inappropriately produces antibodies against acetylcholine receptors, and thus inhibits proper acetylcholine signal transmission. And this reason, the measurement of acetylcholine receptor antibodies can be of considerable value in disease diagnosis. Methods: From 2010. August to September, we tested orderd AchRAb 19 samples to get the results. 1. Pipette $5{\mu}{\ell}$ undiluted patient sera and kit control and add 125I AChR $50{\mu}{\ell}$ and incubate at R.T for 2 hours. 2. Pipette $50{\mu}{\ell}$ of anti-human IgG into each tube, and incubate at $2{\sim}8^{\circ}C$ for 2 hours. 3. Pipette $25{\mu}{\ell}$ precipitation enhancer into each tube and add 1mL washing solution into all tubes. 4. Centrifuge each tube for 20minutes at $2{\sim}8^{\circ}C$ at 1500g. 5. Aspirate or decant the supernatant. 6. Pipette 1 mL washing solution into all tubes and resuspend the pellet and repeat centrifugation. 7. Aspirate or decant the supernatant and count all tubes on a gamma counter. Results: Cut off value is 0.2 nmol/L and the results taken below 0.2 nmol/L are negative, the results above that identified as being positive values. We assayed the 19 patients samples and got 7 positive results. Of which, 6 patients were diagnosed as MG.(85.7%). Conclusions: Acetylcholine Receptor autoantibody test is intended for use by persons only for the quantitative determination of it in human serum. Even if measurement of the antibodies is not a routine test, it can be of considerable value in disease diagnosis.

• Journal of Physiology & Pathology in Korean Medicine
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• v.17 no.1
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• pp.50-56
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• 2003

This research was done to make the effective prescription and cope with various senile dementia. So Sprague-Dawley rats were injected with ibotenate to make a damage on learning and memory functions. At first acquisition test and retention rest were done in the Morris water maze. And to evaluate the effects of the sample drug(TBM) on choline acetyltranferase and acetylcholine esterase, immunoreactive measurement and enzymatic activity measuring were carried out. The ibotenic acid were injected to hippocampus CA1 and CA3 area. The results were as following. TBM improved the learning ability in the acquisition test and memory function in the retention test significantly. And TBM increased the level of ChAT which is synthesizing acetylcholine in CA3 area, and at the same time it increased the level of AChE which is resolving acetylcholine. These results show that T8M improved the cholinergic catabolism and anabolism, and the increment of metabolic activity of cholinergic system. In other words, it contributes to the recovery of damaged learning and memory function by ibotenic acid. So it can be concluded that TBM will be helpful to cholinergic brain damage induced by primary or senile reduction of acetylcholine secretive activity.

• Animal cells and systems
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• v.16 no.4
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• pp.329-336
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• 2012

This study evaluated ecological health, using various biomarkers and bioindicators, of pale chub (Zacco platypus) as a sentinel species, in Daejeon Stream, South Korea, during AprilMay 2011. The biomarkers and bioindicators were compared among three sites of control: Reference ($C_z$), transition ($T_z$), and the urban zones ($U_z$); and the 7-Ethoxyresorufin-O-deethylase (EROD) activity, DNA damage, acetylcholinesterase (AChE) activity, and vitellogenin (VTG) concentrations were more significantly increased in the $U_z$ than in the $C_z$. Also, physiological markers such as condition factor, liver somatic index, visceral somatic index, and gonad somatic index were significantly increased in the $U_z$ than in the $C_z$. For the health assessments, three categorized parameters of blood chemistry, molecular biomarkers, and physiological bioindicators were standardized and calculated as a star-plot, representing values of Integrated Health Response (IHR). Values of IHR had more significant (P<0.05) increases in the $U_z$ than any other zones, indicating an impairment of ecological health by organic matter, nutrients (N, P), and toxic chemicals. This study is based on low levels of biological organization approach of molecular and physiological biomarkers and bioindicators, so further study of high-levels of biological organization approach such as community and population is required for overall range of health assessments. The approach of IHR values, however, may be useful in providing early warning of future impacts on ecological health.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.975-976
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• 1993

This talk presents the overview of the author's research and development activities on fuzzy inference hardware. We involved it with two distinct approaches. The first approach is to use application specific integrated circuits (ASIC) technology. The fuzzy inference method is directly implemented in silicon. The second approach, which is in its preliminary stage, is to use more conventional microprocessor architecture. Here, we use a quantitative technique used by designer of reduced instruction set computer (RISC) to modify an architecture of a microprocessor. In the ASIC approach, we implemented the most widely used fuzzy inference mechanism directly on silicon. The mechanism is beaded on a max-min compositional rule of inference, and Mandami's method of fuzzy implication. The two VLSI fuzzy inference chips are designed, fabricated, and fully tested. Both used a full-custom CMOS technology. The second and more claborate chip was designed at the University of North Carolina(U C) in cooperation with MCNC. Both VLSI chips had muliple datapaths for rule digital fuzzy inference chips had multiple datapaths for rule evaluation, and they executed multiple fuzzy if-then rules in parallel. The AT & T chip is the first digital fuzzy inference chip in the world. It ran with a 20 MHz clock cycle and achieved an approximately 80.000 Fuzzy Logical inferences Per Second (FLIPS). It stored and executed 16 fuzzy if-then rules. Since it was designed as a proof of concept prototype chip, it had minimal amount of peripheral logic for system integration. UNC/MCNC chip consists of 688,131 transistors of which 476,160 are used for RAM memory. It ran with a 10 MHz clock cycle. The chip has a 3-staged pipeline and initiates a computation of new inference every 64 cycle. This chip achieved an approximately 160,000 FLIPS. The new architecture have the following important improvements from the AT & T chip: Programmable rule set memory (RAM). On-chip fuzzification operation by a table lookup method. On-chip defuzzification operation by a centroid method. Reconfigurable architecture for processing two rule formats. RAM/datapath redundancy for higher yield It can store and execute 51 if-then rule of the following format: IF A and B and C and D Then Do E, and Then Do F. With this format, the chip takes four inputs and produces two outputs. By software reconfiguration, it can store and execute 102 if-then rules of the following simpler format using the same datapath: IF A and B Then Do E. With this format the chip takes two inputs and produces one outputs. We have built two VME-bus board systems based on this chip for Oak Ridge National Laboratory (ORNL). The board is now installed in a robot at ORNL. Researchers uses this board for experiment in autonomous robot navigation. The Fuzzy Logic system board places the Fuzzy chip into a VMEbus environment. High level C language functions hide the operational details of the board from the applications programme . The programmer treats rule memories and fuzzification function memories as local structures passed as parameters to the C functions. ASIC fuzzy inference hardware is extremely fast, but they are limited in generality. Many aspects of the design are limited or fixed. We have proposed to designing a are limited or fixed. We have proposed to designing a fuzzy information processor as an application specific processor using a quantitative approach. The quantitative approach was developed by RISC designers. In effect, we are interested in evaluating the effectiveness of a specialized RISC processor for fuzzy information processing. As the first step, we measured the possible speed-up of a fuzzy inference program based on if-then rules by an introduction of specialized instructions, i.e., min and max instructions. The minimum and maximum operations are heavily used in fuzzy logic applications as fuzzy intersection and union. We performed measurements using a MIPS R3000 as a base micropro essor. The initial result is encouraging. We can achieve as high as a 2.5 increase in inference speed if the R3000 had min and max instructions. Also, they are useful for speeding up other fuzzy operations such as bounded product and bounded sum. The embedded processor's main task is to control some device or process. It usually runs a single or a embedded processer to create an embedded processor for fuzzy control is very effective. Table I shows the measured speed of the inference by a MIPS R3000 microprocessor, a fictitious MIPS R3000 microprocessor with min and max instructions, and a UNC/MCNC ASIC fuzzy inference chip. The software that used on microprocessors is a simulator of the ASIC chip. The first row is the computation time in seconds of 6000 inferences using 51 rules where each fuzzy set is represented by an array of 64 elements. The second row is the time required to perform a single inference. The last row is the fuzzy logical inferences per second (FLIPS) measured for ach device. There is a large gap in run time between the ASIC and software approaches even if we resort to a specialized fuzzy microprocessor. As for design time and cost, these two approaches represent two extremes. An ASIC approach is extremely expensive. It is, therefore, an important research topic to design a specialized computing architecture for fuzzy applications that falls between these two extremes both in run time and design time/cost. TABLEI INFERENCE TIME BY 51 RULES {{{{Time }}{{MIPS R3000 }}{{ASIC }}{{Regular }}{{With min/mix }}{{6000 inference 1 inference FLIPS }}{{125s 20.8ms 48 }}{{49s 8.2ms 122 }}{{0.0038s 6.4㎲ 156,250 }} }}