• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.29-56
• /
• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Journal of Life Science
• /
• v.29 no.10
• /
• pp.1062-1070
• /
• 2019

A components of garlic (Allium sativum) have anti-proliferative effects against various types of cancer. We aimed to investigate the capacity of garlic compounds to anti-tumor on a various cancer cell lines. Fractionation of garlic extract, guided by antiproliferative activity against human gastric cancer (AGS) cells, has resulted in the isolation of N-benzyl-N-methyldecan-1-amine (NBNMA). We investigated the effect of newly isolated NBNMA from garlic cloves on the inhibition of the growth of CT-26, AGS, HepG2, HCT-116, MCF7, B16F10, and Sarcoma-180 cells for in vitro and CT-26 colon carcinoma cells in vivo. NBNMA exhibited an antiproliferative effect in CT-26 cells by apoptotic cell death. NBNMA exhibited down-regulation of anti-apoptotic Bcl-2 proteins and up-regulation of apoptotic Bad protein expression in western blot analyses. In addition, NBNMA meagre activated caspase 3 and caspase 9, initiator caspases of the extrinsic and intrinsic pathways of apoptosis. NBNMA treatment at a dose of 10 mg/kg for 21 days in experimental mice implanted with tumors resulted in significant reduction of the tumor weight (43%). NBNMA exhibited both in vitro and in vivo anticancer activity. These results indicate that NBNMA has promising potential to become a novel anticancer agent from garlic cloves for the treatment of colon carcinoma cancer.

• Journal of Nutrition and Health
• /
• v.54 no.6
• /
• pp.618-630
• /
• 2021

Purpose: The ginger rhizome (Zingiber officinale) is widely cultivated as a spice for its aromatic and pungent components. One of its constituents, 6-hydroxydopamine (6-OHDA) is usually thought to cross the cell membrane through dopamine uptake transporters, and induce inhibition of mitochondrial respiration and the generation of intracellular reactive oxygen species (ROS). This study examines the neuroprotective effect and acetylcholinesterase (AChE) inhibitory activity of fermented ginger extracts (FGEs) on 6-OHDA induced toxicity in SH-SY5Y human neuroblastoma cells. Methods: Ginger was fermented using 2 species of Bacillus subtilis, with or without enzyme pretreatment. Each sample was extracted with 70% ethanol. Neurotoxicity was assessed by applying the EZ-Cytox cell viability assay and by measuring lactic dehydrogenase (LDH) release. Morphological changes of apoptotic cell nuclei were observed by Hoechst staining. Cell growth and apoptosis of SH-SY5Y cells were determined by Western blotting and enzyme activity analysis of caspase-3, and AChE enzymatic activity was determined by the colorimetric assay. Results: In terms of cell viability and LDH release, exposure to FGE showed neuroprotective activities against 6-OHDA stimulated stress in SH-SY5Y cells. Furthermore, FGE reduced the 6-OHDA-induced apoptosis, as determined by Hoechst staining. The occurrence of apoptosis in 6-OHDA treated cells was confirmed by determining the caspase-3 activity. Exposure to 6-OHDA resulted in increased caspase-3 activity of SH-SY5Y cells, as compared to the unexposed group. However, pre-treatment with FGE inhibited the activity of caspase-3. The neuroprotective effects of FGE were also found to be caspase-dependent, based on reduction of caspase-3 activity. Exposure to FGE also inhibited the activity of AChE induced by 6-OHDA, in a dose-dependent manner. Conclusion: Taken together, our results show that FGE exhibits a neuroprotective effect in 6-OHDA treated SH-SY5Y cells, thereby making it a potential novel agent for the prevention or treatment of neurodegenerative disease.

• Journal of The Korean Society of Inherited Metabolic disease
• /
• v.21 no.1
• /
• pp.7-14
• /
• 2021

Purpose: Pseudohypoparathyroidism (PHP) is caused by genetic and epigenetic alteration in the GNAS locus, and characterized by the resistance to multiple hormones and the Albright's hereditary osteodystrophy (AHO) phenotype. This study investigated the phenotypic characteristics and molecular features of PHP. Methods: Eight patients who diagnosed as PHP were enrolled at Pusan National University Children's hospital and clinical features, biochemical and genetic findings were retrospectively reviewed. Results: Of a total of 8 patients, 5 were diagnosed with PHP1a, and 3 were diagnosed with PHP1b. Patients with PHP1a had three different mutations in the GNAS gene, and patients with PHPIb had imprinting defect in differentially methylated regions (DMRs) of the GNAS locus. Two novel GNAS variants were identified in patients with PHP1a, including c.313-2A>T and c.1094G>A. All patients with PHP1a displayed AHO features; short stature (80%), brachydactyly (80%), a round face (80%), obesity (40%), heterotopic ossification (60%), and intellectual disability (60%), whereas only one patient (33.3%) with PHP1b showed AHO feature such as a round face. When phenotypic features between PHP1a and PHP1b patients were compared, patients with PHP1b showed a tendency of higher current height standard deviation scores (SDS) compared to patients with PHP1a, (-3.2±2.1 vs.-1.1±0.8; P=0.06) Conclusions: This study summarizes the phenotypic and genetic features of the PHP patients. Although we found considerable clinical overlap between PHP1a and PHP1b, further long-term follow-up is needed to evaluate the growth and development of children with PHP, as well as the effects of end-organ resistances to endocrine hormones.

• Journal of Life Science
• /
• v.33 no.2
• /
• pp.158-168
• /
• 2023

Natural products have been used to mitigate the effects of cancer and infectious diseases, as they feature diverse bioactivities, such as antioxidant, antibacterial, anti-inflammatory, and immunomodulatory effects. Here, we chose 10 natural products that are well-known as pulmonary enhancers and investigated their bactericidal effects on Streptococcus pneumoniae. In the disk diffusion assay, the growth of S. pneumoniae was significantly regulated by G. fructus treatment regardless of extraction method used. We first adopted spraying as a novel delivery method for G. fructus. Interestingly, mice exposed to G. fructus three times a day for 2 weeks were resistant to S. pneumoniae intranasal infection (shown both through body weight loss and survival rates compared to the control group). Moreover, we confirmed that exposure to G. fructus regulated the colonization of the bacteria despite the sustained inflammation in the lung after exposure to S. pneumoniae, indicating that migrated inflammatory immune cells may involve a host defense mechanism against pulmonary infectious diseases. While a similar number of granulocytes (CD11b⁺Ly6C⁺Ly6G⁺), neutrophils (CD11b⁺Ly6C^intLy6G⁺), and monocytes (CD11b⁺Ly6C^intLy6G^-) were found between groups, a significantly increased number of alveolar macrophages (CD11b⁺CD11c^hiF4/80⁺) was detected in BAL fluids of mice pre-exposed to G. fructus at 5 days after S. pneumonia infection. Taken together, our data suggest that this usage of G. fructus can induce protective immunity against bacterial infection, indicating that facial spray may be helpful in enhancing the defense mechanism against pulmonary inflammation and in evaluating the efficacy of natural products as immune enhancers against respiratory diseases.

• Journal of Food Hygiene and Safety
• /
• v.38 no.1
• /
• pp.1-11
• /
• 2023

Skin sanitizers are effective in killing or removing pathogenic microbial contaminants from the skin of food handlers, and the progressive growth of consumer interest in personal hygiene tends to drive product diversification. This review covers the advances in the application of efficacy tests for hand sanitizers to suggest future perspectives to establish an assessment system that is optimized to each product type (gel, liquid, and wipes). Previous research on the in vivo simulative test of actual consumer use has adopted diverse experimental conditions regardless of the product type. This highlights the importance of establishing optimal test protocols specialized for the compositional characteristics of sanitizers through the comparative analysis of test methods. Although the operational conditions of the mechanical actions associated with wiping can affect the efficacy of the removal and/or the inactivation of target microorganisms from the skin's surface, currently there is a lack of standardized use patterns for the exposure of hand sanitizing wipes to skin. Thus, major determinants affecting the results from each step of the overall assessment procedures [pre-treatment - exposure of sanitizers - microbial recovery] should be identified to modify current protocols and develop novel test methods. The ex vivo test, designed to overcome the limited reproducibility of in vivo human trials, is also expected to replicate the environment for the contact of sanitizers targeting skin microorganisms. Recent progress in the area of skin microbiome research revealed distinct microbial characteristics and distribution patterns after the application of sanitizers on hands to establish the test methods with the perspectives on the antimicrobial effects at the community level. The future perspectives presented in this study on the improvement of efficacy test methods for hand sanitizers can also contribute to public health and food safety through the commercialization of effective sanitizer products.

• Journal of Life Science
• /
• v.33 no.12
• /
• pp.1015-1024
• /
• 2023

Antibiotics have greatly contributed to the treatment and prevention of bacterial diseases in humans, animals, and fish. However, antibiotic misuse has led to the emergence and spread of multidrug-resistant bacteria. In addition to antibiotic discovery research, efforts are being made to combat such multidrug-resistant bacteria using antimicrobial agents, antioxidants, host immune enhancement, probiotics, and bacteriophages, as well as various symptomatic therapies. To discover novel bioactive compounds, it is crucial to adopt approaches that incorporate fresh ideas, new targets, innovative techniques, and untapped resources. Halophytes are plants that grow in high-salt soils and are known to adapt to salt-induced stress through unique metabolic processes that produce secondary metabolites. This study aimed to investigate the effects of extracts of halophytes native to Korea on oxidative stress and to determine whether they exert inhibitory activity against biofilms, which are major pathogenic factors of infectious bacteria. The Acinetobacter baumannii strain ATCC 17978, a representative drug-resistant bacterium, was used to measure anti-biofilm activity. The results showed that Aster spathulifolius, Carex kobomugi, Rosa rugosa, and Asparagus cochinchiensis exerted strong antioxidant and anti-biofilm effects without affecting bacterial growth itself. The halophytes used in this study are promising candidates for the development of pharmaceutical agents with antioxidant and antimicrobial properties.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.127-147
• /
• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.227-252
• /
• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.