• Molecules and Cells
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• v.43 no.2
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• pp.107-113
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• 2020

The Runt-related transcription factors (RUNX) transcription factors have been known for their critical roles in numerous developmental processes and diseases such as autoimmune disorders and cancer. Especially, RUNX proteins are best known for their roles in hematopoiesis, particularly during the development of T cells. As scientists discover more types of new immune cells, the functional diversity of RUNX proteins also has been increased over time. Furthermore, recent research has revealed complicated transcriptional networks involving RUNX proteins by the current technical advances. Databases established by next generation sequencing data analysis has identified ever increasing numbers of potential targets for RUNX proteins and other transcription factors. Here, we summarize diverse functions of RUNX proteins mainly on lymphoid lineage cells by incorporating recent discoveries.

• Biomedical Science Letters
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• v.29 no.1
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• pp.11-25
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• 2023

In hepatocellular carcinoma (HCC), chromosome 4 open-reading frame 47 (C4orf47) has not been so far investigated for its prognostic value or association with infiltrating immune cells. We performed bioinformatics analysis on HCC data and analyzed the data using online databases such as TIMER, UALCAN, Kaplan-Meier plotter, LinkedOmics, and GEPIA2. We found that C4orf47 expression in HCC was higher compared to normal tissues. High C4orf47 expression was associated with a worse prognosis in HCC. The correlation between C4orf47 and infiltrating immune cells is positively associated with CD4+T cells, B cells, neutrophils, macrophages, and dendritic cells in HCC. Moreover, high C4orf47 expression was correlated with a poor prognosis of infiltrating immune cells. Analysis of C4orf47 gene co-expression networks revealed that 12501 genes were positively correlated with C4orf47, whereas 7200 genes were negatively correlated. The positively related genes of C4orf47 are associated with a high hazard ratio in different types of cancer, including HCC. Regarding the biological functions of C4orf47 gene, it mainly regulates RNA metabolic process, DNA replication, and cell cycle. The C4orf47 gene may play a prognostic role by regulating the global transcriptome process in HCC. Our findings demonstrate that high C4orf47 expression correlates with poor prognosis and tumor-infiltrating immune cells in HCC. We suggest that C4orf47 is a novel prognostic biomarker and potential immune therapeutic target for HCC.

• Journal of Life Science
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• v.34 no.5
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• pp.356-364
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• 2024

Lymph nodes (LNs) are crucial sites where immune responses are initiated to combat invading pathogens in the body. LNs are organized into distinctive compartments by stromal cells. Stromal cell subsets constitute special niches supporting the trafficking, activation, differentiation, and crosstalk of immune cells in LNs. Fibroblastic reticular cells (FRC) are a type of stromal cell that form the three-dimensional structure networks of the T cell-rich zones in LNs, providing guidance paths for immigrating T lymphocytes. FRCs imprint immune responses by supporting LN architecture, recruiting immune cells, coordinating immune cell crosstalk, and presenting antigens. During inflammation, FRCs exert both spatial and molecular regulation on immune cells through their topological and secretory responses, thereby steering immune responses. Here, we propose a model in which FRCs regulate immune responses through a three-part scheme: setting up, supporting, or suppressing immune responses. FRCs engage in bidirectional interactions that enhance T cell biological efficiency. In addition, FRCs have profound effects on the innate immune response through phagocytosis. Thus, FRCs in LNs act as gatekeepers of immune responses. Overall, this study aims to highlight the emerging roles of FRCs in controlling both innate and adaptive immunity. This collaborative feedback loop mediated by FRCs may help maintain tissue function during inflammatory responses.

• IMMUNE NETWORK
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• v.1 no.1
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• pp.26-31
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• 2001

Background : Follicular dendritic cells (FDCs) play key roles during T cell-dependent humoral immune responses by allowing antigen-specific B cells to survive, proliferate, and differentiate within the FDC networks of secondary follicles, i.e., germinal centers (GC). Methods: A novel monoclonal antibody, 3C8, was generated by immunizing with an FDC line HK, in order to understand the molecular signals involved in the FDC-B cell interactions in the microenvironment of the GC. Results: The 3C8 antibody did not bind to mononuclear cells, including T cells, B cells, and monocytes. Murine L929 and human skin fibroblasts exhibited no or little reactivity to 3C8. However, 3C8 specifically recognized HK cells by flowcytometry. Furthermore, the antigen recognized by 3C8 was restricted to the GC of the human tonsil. Dendritic networks of the GC were intensely stained by 3C8, but cells outside the GC were not. Conclusion: Our results suggest that the antigen 3C8 may play some unique role on FDCs during the GC reactions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4680-4697
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• 2017

In future, since the user experience plays a more and more important role in the development of today's communication systems, quality of experience (QoE) becomes a widely used metric, which reflects the subjective experience of end users for wireless service. In addition, the energy efficiency is an increasingly important problem with the explosive growth in the amount of wireless terminals and nodes. Hence, a QoE-aware energy efficiency maximization based joint user access selection and power allocation approach is proposed to solve the problem. We transform the joint allocation process to an optimization of energy efficiency by establishing an energy efficiency model, and then the optimization problem is solved by chaotic clone immune algorithm (CCIA). Numerical simulation results indicate that the proposed algorithm can efficiently and reliably improve the QoE and ensure high energy efficiency of networks.

• ETRI Journal
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• v.38 no.6
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• pp.1153-1162
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• 2016

This paper addresses the resource allocation (RA) problem in multi-cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered-such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP-hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub-gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.74-90
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• 2014

Routing in mobile wireless sensor networks (MWSNs) is an extremely challenging issue due to the features of MWSNs. In this paper, we present a novel bio-inspired trusted routing protocol (B-iTRP) based on artificial immune system (AIS), ant colony optimization (ACO) and Physarum optimization (PO). For trust mechanism, B-iTRP monitors neighbors' behavior in real time and then assesses neighbors' trusts based on AIS. For routing strategy, each node proactively finds routes to the Sink based on ACO. When a backward ant is on the way to return source, it senses the energy residual and trust value of each node on the discovered route, and calculates the link trust and link energy of the route. Moreover, B-iTRP also assesses the availability of route based on PO to maintain the route table. Simulation results show how B-iTRP can achieve the effective performance compared to existing state-of-the-art algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.402-410
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• 2004

In this paper, an optimal design method of clonal selection based Fuzzy-Neural Networks (FNN) model for complex and nonlinear systems is presented. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. Also Advanced Clonal Selection (ACS) is proposed to find the parameters such as parameters of membership functions, learning rates and momentum coefficients. The proposed method is based on an Immune Algorithm (IA) using biological Immune System and The performance is improved by control of differentiation rate. Through that procedure, the antibodies are producted variously and the parameter of FNN are optimized by selecting method of antibody with the best affinity against antigens such as object function and limitation condition. To evaluate the performance of the proposed method, we use the time series data for gas furnace and traffic route choice process.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.40-46
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• 2015

In a mobile ad hoc network (MANET), communication between mobile nodes occurs without centralized control. In this environment the mobility of a node is unpredictable; this is considered as a characteristic of wireless networks. Because of faulty or malicious nodes, the network is vulnerable to routing misbehavior. The resource constrained characteristics of MANETs leads to increased query delay at the time of data access. In this paper, AntHocNet+ Security (ANTSEC) framework is proposed that includes an enhanced cooperative caching scheme embedded with artificial immune system. This framework improves security by injecting immunity into the data packets, improves the packet delivery ratio and reduces end-to-end delay using cross layer design. The issues of node failure and node malfunction are addressed in the cache management.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.