• Animal cells and systems
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• v.15 no.2
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• pp.115-121
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• 2011

Previous studies have demonstrated that N-methyl-D-aspartate (NMDA) receptors and acetylcholine receptors are related to learning and memory in rat and mice. In this study, we examined the effects of MK-801, a non-competitive NMDA receptor antagonist, on learning and memory in zebrafish using a passive avoidance test. We further tested whether or not nicotine, a nicotinic acetylcholine receptor agonist, and physostigmine, an acetylcholinesterase inhibitor, reverse the effects of MK-801. Crossing time was increased significantly in the training and test sessions for the controls. When 20 ${\mu}M$ MK-801 was administered prior to the training session, the crossing time did not increase in either session. The MK-801-induced learning deficit was rescued by pretreatment with 20 ${\mu}M$ physostigmine, and crossing time was increased in the training and test sessions compared to the MK-801-treated zebrafish. Further, the MK-801-induced learning deficit was prevented by pretreatment with 20 ${\mu}M$ nicotine, and crossing time was increased in the training session but not in the test session. These results show that MK-801 induced a learning deficit in zebrafish that was prevented by pretreatment with nicotine and physostigmine.

• Microbiology and Biotechnology Letters
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• v.50 no.1
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• pp.1-14
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• 2022

Bacteria communicate with each other through an intricate communication mechanism known as quorum sensing (QS). QS regulates different behavioral aspects in bacteria, such as biofilm formation, sporulation, virulence gene expression, antibiotic production, and bioluminescence. Several different chemical signals and signal detection systems play vital roles in promoting highly efficient intra- and interspecies communication. Gram-negative bacteria coordinate gene regulation through the production of acyl homoserine lactones (AHLs). Gram-positive bacteria do not code for AHL production, while some gram-negative bacteria have an incomplete AHL-QS system. Despite this fact, these microbes can detect AHLs owing to the presence of LuxR solo receptors. Various studies have reported the role of AHLs in interspecies signaling. Moreover, as bacteria live in a polymicrobial community, the production of extracellular compounds to compete for resources is imperative. Thus, AHL-mediated signaling and inhibition are considered to affect virulence in bacteria. In the current review, we focus on the synthesis and regulation mechanisms of AHLs and highlight their role in interspecies bacterial signaling. Exploring interspecies bacterial signaling will further help us understand host-pathogen interactions, thereby contributing to the development of therapeutic strategies intended to target chronic polymicrobial infections.

• Journal of Microbiology and Biotechnology
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• v.33 no.10
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• pp.1370-1375
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• 2023

In this study, we aimed to enhance the accumulation of chorismate (CHR) and anthranilate (ANT), key intermediates in the shikimate pathway, by modifying a shikimate over-producing recombinant strain of Corynebacterium glutamicum [19]. To achieve this, we utilized a CRISPR-driven genome engineering approach to compensate for the deletion of shikimate kinase (AroK) as well as ANT synthases (TrpEG) and ANT phosphoribosyltransferase (TrpD). In addition, we inhibited the CHR metabolic pathway to induce CHR accumulation. Further, to optimize the shikimate pathway, we overexpressed feedback inhibition-resistant Escherichia coli AroG and AroH genes, as well as C. glutamicum AroF and AroB genes. We also overexpressed QsuC and substituted shikimate dehydrogenase (AroE). In parallel, we optimized the carbon metabolism pathway by deleting the gntR family transcriptional regulator (IolR) and overexpressing polyphosphate/ATP-dependent glucokinase (PpgK) and glucose kinase (Glk). Moreover, acetate kinase (Ack) and phosphotransacetylase (Pta) were eliminated. Through our CRISPR-driven genome re-design approach, we successfully generated C. glutamicum cell factories capable of producing up to 0.48 g/l and 0.9 g/l of CHR and ANT in 1.3 ml miniature culture systems, respectively. These findings highlight the efficacy of our rational cell factory design strategy in C. glutamicum, which provides a robust platform technology for developing high-producing strains that synthesize valuable aromatic compounds, particularly those derived from the shikimate pathway metabolites.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.2
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• pp.100-106
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• 2004

Micro-fluidics is one of the major technologies used in developing micro-total analytical systems (${\mu}$-TAS), also known as “lab-on-a-chip”. With this technology, the analytical capabilities of room-size laboratories can be put on one small chip. In this paper, we will briefly introduce materials that can be used in micro-fluidic systems and a few modules (mixer, chamber, and sample prep. modules) for lab-on-a-chip to analyze biological samples. This is because a variety of fields have to be combined with micro-fluidic technologies in order to realize lab-on-a-chip.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.183-190
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• 1995

The use of ultrasound pulsed Doppler systems has become increasingly popular due to the advantages of easy measurements of blood velocity, volume blood blow, and irregularities of the circulatory system. However, the 2-D Doppler systems have several problems, such as range ambiguity, low signal to noise ratio, and slow frame rate. The mean frequency aliasing problem originating from the pulse repetition frequency is one of major limitations in pulsed Doppler systems. A conventional approach to resolve this problem is tracking the mean frequency close to and beyond the Nyquist frequency along the temporal axis. In this paper, a new concept of tracking the mean frequency along the spatial axis is proposed. The proposed technique is fault tolerant by nature and more suitable for multi gate and 2-D Doppler system than conventional methods.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.279-288
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• 1995

Ultrasonic Doppler systems for the purpose of estimating blood flow velocity, blood flow volume, and flow imaging are commonly used due to advantages of non-invasive and real time observation. Specially, the technical developments of color flow mapping (2-D Doppler) systems have made a relatively rapid progress. However, the 2-D Doppler systems have several problems, such as the range ambiguity, low signal to noise ratio, and slow frame rate. The slow frame rate problem is resolved by using the spatial average which is a method to acquire more data samples for mean frequency estimation. In this paper, spatial average method using the 2nd order sampling instead of quadrature sampling is proposed. The experimental results show that the proposed methods have good performance and easy application to the color flow mapping system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.279-284
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• 2007

Nowadays, due to development of automatic control devices and various sensors, one operator can freely handle several remote plants and processes. Automatic diagnosis and warning systems have been adopted in various fields, in order to prepare an operator's absence for patrolling plants. In this paper, a Bayesian networks based on-line diagnosis system is proposed for a wastewater treatment process. Especially, the suggested system is included learning structure, which can continuosly update conditional probabilities in the networks. To evaluate performance of proposed model, we made a lab-scale five-stage step-feed enhanced biological phosphorous removal process plant and applied on-line diagnosis system to this plant in the summer.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.31-36
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• 2008

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the enviromuent. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• Korean Journal of Environmental Agriculture
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• v.9 no.1
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• pp.61-68
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• 1990

The pressure to develop new agricultural technologies will be roughly proportional to the rate of depletion of natural resources employed in agriculture. Of these resources, land, water and gentic resources are critical. The development of agriculture is associated with a scientific and technological establishment, of remarkable capability ; responding rapidly to many problems encountered by the agricultural production. These advantages are also coupled with constraints. Agricultural systems are concerned with the efficient conversion of resources into products that are wanted by the producer or someone else who is prepared to pay for them. They are based on biological processes, but they are operated by the people for a multiplicity of purposes. Study of agricultural systems is aimed at helping in the operation of systems, their repair or their improvement. The future concerns of agriculture will center on (1) increasing and safeguarding the supplies of productive inputs to agriculture, (2) improving the efficiency with which these inputs are used in food production, (3) developing new sources of basic food materials, and (4) coping with the external costs that tend to appear in intensive, mechanized agriculture.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.191-196
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• 2005

Genetic networks are a key to unraveling dynamic properties of biological processes and regulation of genes plays an essential role in dynamic behavior of the genetic networks. A popular characterization of regulation of the gene is a kinetic model. However, many kinetic parameters in the genetic regulation have not been available. To overcome this difficulty, in this report, state-space approach to modeling gene regulation is presented. Second-order systems are used to characterize gene regulation. Interpretation of coefficients in the second order systems as resistance, capacitance and inductance is studied. The mathematical methods for transient response analysis of gene regulation to external perturbation are investigated. Criterion for classifying gene into three categories: underdamped, overdamped and critical damped is discussed. The proposed models are applied to yeast cell cycle gene expression data.