• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.259-267
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• 2003

In this paper, we propose a nonlinear variable PID controller using a cell-mediated immune response. An immune feedback response is based on the functioning of biological T-cells. An immune feedback response and P-controller of conventional PID controllers resemble each other in role and mechanism. Therefore, we extend immune feedback mechanism to nonlinear PE controller. And in order to choose the optimal nonlinear PID controller games, we also propose the on-line tuning algorithm of nonlinear functions parameters in immune feedback mechanism. The trained parameters of nonlinear functions are adapted to the variations of the system parameters and any command velocity. And the adapted parameters obtained outputs of nonlinear functions with an optimal control performance. To verify performances of the proposed control systems, the speed control of nonlinear BC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system variations.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.137-150
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• 2019

Although the research of immune-based anomaly detection technology has made some progress, there are still some defects which have not been solved, such as the loophole problem which leads to low detection rate and high false alarm rate, the exponential relationship between training cost of mature detectors and size of self-antigens. This paper proposed an intrusion detection method based on changes of antibody concentration in immune response to improve and solve existing problems of immune based anomaly detection technology. The method introduces blood relative and blood family to classify antibodies and antigens and simulate correlations between antibodies and antigens. Then, the method establishes dynamic evolution models of antigens and antibodies in intrusion detection. In addition, the method determines concentration changes of antibodies in the immune system drawing the experience of cloud model, and divides the risk levels to guide immune responses. Experimental results show that the method has better detection performance and adaptability than traditional methods.

• Journal of the Korean neurological association
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• v.36 no.4
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• pp.329-332
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• 2018

Immune checkpoint inhibitor is associated with variety of immune-related adverse events. We present a case of polyneuropathy induced by immune checkpoint inhibitor, which was refractory to steroid and immunoglobulin. While high-dose steroid and immunoglobulin were not effective, we tried rituximab which is effective in other immune-mediated polyneuropathy. After rituximab treatment, patient's clinical symptom and nerve conduction study finding was markedly improved. We suggest rituximab might be effective in polyneuropathy induced by immune checkpoint inhibitor.

• Journal of Microbiology and Biotechnology
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• v.33 no.3
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• pp.288-298
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• 2023

Host defense peptides are expressed in various immune cells, including phagocytic cells and epithelial cells. These peptides selectively alter innate immune pathways in response to infections by pathogens, such as bacteria, fungi, and viruses, and modify the subsequent adaptive immune environment. Consequently, they play a wide range of roles in both innate and adaptive immune responses. These peptides are of increasing importance due to their broad-spectrum antimicrobial activity and their functions as mediators linking innate and adaptive immune responses. This review focuses on the pleiotropic biological functions and related mechanisms of action of human host defense peptides and discusses their potential clinical applications.

• Molecules and Cells
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• v.46 no.2
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• pp.120-129
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• 2023

Recent technical advances have enabled unbiased transcriptomic and epigenetic analysis of each cell, known as "single-cell analysis". Single-cell analysis has a variety of technical approaches to investigate the state of each cell, including mRNA levels (transcriptome), the immune repertoire (immune repertoire analysis), cell surface proteins (surface proteome analysis), chromatin accessibility (epigenome), and accordance with genome variants (eQTLs; expression quantitative trait loci). As an effective tool for investigating robust immune responses in coronavirus disease 2019 (COVID-19), many researchers performed single-cell analysis to capture the diverse, unbiased immune cell activation and differentiation. Despite challenges elucidating the complicated immune microenvironments of chronic inflammatory diseases using existing experimental methods, it is now possible to capture the simultaneous immune features of different cell types across inflamed tissues using various single-cell tools. In this review, we introduce patient-based and experimental mouse model research utilizing single-cell analyses in the field of chronic inflammatory diseases, as well as multi-organ atlas targeting immune cells.

• IMMUNE NETWORK
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• v.20 no.6
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• pp.44.1-44.19
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• 2020

The human body is continuously threatened by pathogens, and the immune system must maintain a balance between fighting infection and becoming over-activated. Mucosal surfaces cover several anatomically diverse organs throughout the body, such as the respiratory and gastrointestinal tracts, and are directly exposed to the external environment. Various pathogens invade the body through mucosal surfaces, making the mucosa the frontline of immune defense. The immune systems of various mucosal tissues display distinctive features that reflect the tissues' anatomical and functional characteristics. This review discusses the cellular components that constitute the respiratory and gastrointestinal tracts; in particular, it highlights the complex interactions between epithelial and immune cells to induce Ag-specific immune responses in the lung and gut. This information on mucosal immunity may facilitate understanding of the defense mechanisms against infectious agents that invade mucosal surfaces, such as severe acute respiratory syndrome coronavirus 2, and provide insight into effective vaccine development.

• IMMUNE NETWORK
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• v.24 no.4
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• pp.30.1-30.16
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• 2024

Pregnancy represents an immunological paradox where the maternal immune system must tolerate the semi-allogeneic fetus expressing paternally-derived Ags. Accumulating evidence over decades has revealed that successful pregnancy requires the active development of robust immune tolerance mechanisms. This review outlines the multi-layered processes that establish fetomaternal tolerance, including the physical barrier of the placenta, restricted chemokine-mediated leukocyte trafficking, lack of sufficient alloantigen presentation, the presence of immunosuppressive regulatory T cells and tolerogenic decidual natural killer cells, expression of immune checkpoint molecules, specific glycosylation patterns conferring immune evasion, and unique metabolic/hormonal modulations. Interestingly, many of the strategies that enable fetal tolerance parallel those employed by cancer cells to promote angiogenesis, invasion, and immune escape. As such, further elucidating the mechanistic underpinnings of fetal-maternal tolerance may reciprocally provide insights into developing novel cancer immunotherapies as well as understanding the pathogenesis of gestational complications linked to dysregulated tolerance processes.

• 한국약용작물학회:학술대회논문집
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• 2011.04a
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• pp.94-95
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• 2011

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Smart Structures and Systems
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• v.8 no.1
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• pp.69-92
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• 2011

This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immune-network-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.