• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8035-8040
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• 2014

Gastric cancer is the second after lung cause of cancer-related mortality in the world. Early detection and treatment can lead to a long survival time. Recently microarrays and next generation sequencing (NGS) have become very useful tools of comprehensive research into gastric cancer, facilitating the identification of treatment targets and personalized treatments. However, there are numerous challenges from cancer target discovery to practical clinical benefits. Although there are many biomarkers and target agents, only a minority of patients are tested and treated accordingly. Microarray technology with maturity was established more than 10 years ago, and has been widely used in the study of functional genomics, systems biology, and genomes in medicine. Second generation sequencing technology is more recent, but development is very fast, and it has been applied to the genome, including sequencing and epigenetics and many aspects of functional genomics. Here we review insights gained from these studies regarding the technology of microarray and NGS, how to elucidate the molecular basis of gastric cancer and identify potential therapeutic targets, and how to analyse candidate genes. We also discuss the challenges and future directions of such efforts.

• Journal of Korean Neurosurgical Society
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• v.61 no.3
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• pp.292-301
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• 2018

Medulloblastoma is the most common malignant brain tumor of childhood and remains a major cause of cancer related mortality in children. Significant scientific advancements have transformed the understanding of medulloblastoma, leading to the recognition of four distinct clinical and molecular subgroups, namely wingless (WNT), sonic hedgehog, group 3, and group 4. Subgroup classification combined with the recognition of subgroup specific molecular alterations has also led to major changes in risk stratification of medulloblastoma patients and these changes have begun to alter clinical trial design, in which the newly recognized subgroups are being incorporated as individualized treatment arms. Despite these recent advancements, identification of effective targeted therapies remains a challenge for several reasons. First, significant molecular heterogeneity exists within the four subgroups, meaning this classification system alone may not be sufficient to predict response to a particular therapy. Second, the majority of novel agents are currently tested at the time of recurrence, after which significant selective pressures have been exerted by radiation and chemotherapy. Recent studies demonstrate selection of tumor sub-clones that exhibit genetic divergence from the primary tumor, exist within metastatic and recurrent tumor populations. Therefore, tumor resampling at the time of recurrence may become necessary to accurately select patients for personalized therapy.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2575-2580
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• 2015

Cancer is a multifaceted and genomically complex disease and rapidly accumulating high impact research is deepening our understanding related to the mechanisms underlying cancer development, progression and resistance to therapeutics. Increasingly it is being realized that genetic/epigenetic mutations, inactivation of tumor suppressor genes, overexpression of oncogenes, deregulation of intracellular signaling cascades and loss of apoptosis are some of the extensively studied aspects. Confluence of information suggested that rapidly developing resistance to therapeutics is adding another layer of complexity and overwhelmingly increasing preclinical studies are identifying different natural agents with efficacy and minimal off-target effects. We partition this multi-component review into citrus fruits and their bioactive ingredients mediating rebalancing of pro- and anti-apoptotic proteins to induce apoptosis in resistant cancer cells. We also discuss how oncogenic protein networks are targeted in cancer cells and how these findings may be verified in preclinical studies.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.8 no.2
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• pp.139-150
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• 2022

Theranostics, a composite word of therapy and diagnosis, is known as personalized medicine and the concept of diagnosis and treatment at the same time. In nuclear medicine, it means performing both therapeutic and diagnostic radioisotope therapy using the same target molecule. The increased production and utilization of ⁶⁴Cu opens a new era of theranostics. The studies introduced here have shown that ⁶⁴CuCl₂ and various compounds or biomolecules labeled with ⁶⁴Cu are unique radiopharmaceuticals with physiological properties suitable for use as diagnostic and therapeutic agents. So far, these two abilities have been described only for radioactive iodine. Although ⁶⁴Cu has complex chemical properties compared to other PET radioisotopes such as ⁶⁸Ga, it has an appropriate half-life and enables high-quality PET images similar to ¹⁸F, which is an advantage in terms of diagnosis. In addition, since it also has therapeutic properties through the release of β^- particles and Auger electrons by electron capture, radiopharmaceuticals using ⁶⁴Cu stand for innovative radiopharmaceuticals for theranostic purposes. Therefore, based on the initial results obtained using ⁶⁴Cu as a therapeutic agent, it is expected that additional research on the application of ⁶⁴Cu will lead to a new era in the theranostics field.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.522-527
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• 2008

Socially Intelligent agent is the agent not only having the ability to recognize and to process human affect through learning and adaptation, but also having human-like social intelligence. By making human feel familiar with the computer, the agent is expected to enhance human-computer interaction (HCI) by providing users with the personalized services and interfaces. This paper proposes the framework for socially intelligent agents behaving socially according to the emotions recognized by ID3 algorithm and psychological OCC model. Also, the agent could process with the emotion to make socially intelligent response through three layered affect functioning model. Finally, the proposed agent can be applied for the development and application of socially intelligent agent in wide areas as the agent framework having similar affect and cognitive structure with human being.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1205-1212
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• 2004

As electronic commerce systems have been widely used, the necessity of adaptive e-commerce agent systems has been increased. These kinds of adaptive e-commerce agents can monitor customer's behaviors and cluster thou in similar categories, and include user's preference from each category. In order to implement our adaptive e-commerce agent system, in this paper, we propose an adaptive e-commerce agent systems consider customer's information of interest and goodwill ratio about preference goods. Proposed system build user's profile more accurately to get adaptability for user's behavior of buying and provide useful product information without inefficient searching based on such user's profile. The proposed system composed with three parts , Monitor Agent which grasps user's intension using monitoring, similarity reference Agent which refers to similar group of behavior pattern after teamed behavior pattern of user, Interest Analyzing Agent which personalized behavior DB as a change of user's behavior.

• Journal of The Korean Association of Information Education
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• v.14 no.4
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• pp.527-536
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• 2010

Ubiquitous computing and mobile technologies provide much scope for designing innovative learning experiences that can take place in a variety of indoor and outdoor settings, such as botanical gardens, parks, museums and classrooms. In this paper, we present our own innovative work for bridging indoor and outdoor field-trip learning activities with the support of RFID with reader device on ubiquitous environments. The function of our system is based on strategically located RFID tags placed on objects around settings which are identified using the mobile device installed to an RFID reader. The mobile device reads the RFID tag and sends the learner's request to the field-trip learning system. And learners can be learning activities according to theirs learning levels. We also focus on the use of intelligent agents to customize learning contents for individual learners. The result of our experiment indicates that learner enjoyed learning where mobile devices are used in the system, supporting the learning activities in the context of which they are taking place.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.81-91
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• 2005

Today, mobile phones have become an essential item for man-to-man communication. As more people use mobile phones, various services based on mobile phone networks and high-end devices have been developed. In addition, with the growth of the concept of ubiquitous computing, there are many ongoing studies on novel and useful services in smartphone. In this paper, for personalized service in smartphone we propose an intelligent agent that uses user modeling based on bayesian network and rule based service selection mechanism. It infers the user's status such as his current affect, how he is busy, and how someone is familiar with him from personal information and communication history using bayesian network and Provides appropriate services on the basis of the inferred information. We apply it to some realistic situation to confirm the usefulness our proposed agent.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.365-373
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• 2005

Ubiquitous learning environment needs various new model of e-learning as web based education system has been proposed. The demand for the customized courseware which is required from the learners is increased. the needs of the efficient and automated education agents in the web-based instruction are recognized. But many education systems that had been studied recently did not service fluently the courses which learners had been wanting and could not provide the way for the learners to study the learning weakness which is observed in the continuous feedback of the course. In this paper we propose a multi-agent system for course scheduling of learner-oriented using weakness analysis algorithm via personalized ubiquitous environment factors. First proposed system analyze learner's result of evaluation and calculates learning accomplishment. From this accomplishment the multi-agent schedules the suitable course for the learner. The learner achieves an active and complete learning from the repeated and suitable course.

• Journal of Life Science
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• v.28 no.4
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• pp.488-495
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• 2018

The p53 gene plays a critical role in the transcriptional regulation of cellular response to stress, DNA damage, hypoxia, and tumor development. Keeping in mind the recently discovered manifold physiological functions of p53, its involvement in the regulation of cancer is not surprising. In about 50% of all human cancers, inactivation of p53's protein function occurs either through mutations in the gene itself or defects in the mechanisms that activate it. This disorder plays a crucial role in tumor evolution by allowing the evasion of a p53-dependent response. Many recent studies have focused on directly targeting p53 mutants by identifying selective, small molecular compounds to deplete them or to restore their tumor-suppressive function. These small molecules should effectively regulate various interactions while maintaining good drug-like properties. Among them, the discovery of the key p53-negative regulator, MDM2, has led to the design of new small molecule inhibitors that block the interaction between p53 and MDM2. Some of these small molecule compounds have now moved from proof-of-concept studies into clinical trials, with prospects for further, more personalized anti-carcinogenic medicines. Here, we review the structural and functional consequences of wild type and mutant p53 as well as the development of therapeutic agents that directly target this gene, and compounds that inhibit the interaction between it and MDM2.