• CELLMED
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• v.5 no.2
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• pp.11.1-11.5
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• 2015

Traditional East Asian Medicine (TEAM) prescriptions typically consist of several herbs based on the assumption that the herbs operate synergistically and/or cooperate on several related pathways simultaneously. This is a general concept that is widely accepted in TEAM, but it has not been tested systematically. To check this assumption statistically, we have text mined traditional Korean medicine text the Inje-ji(仁濟志, Collections of benevolent savings), a text that contains more than 5000 herb-cocktail prescriptions. We created herb-pairing network based on herb-herb pairing specificity and performed a systematic network analysis. Herbs were shown to be used selectively with other herbs and not randomly. Moreover, herb pairs were more specifically associated with symptoms than were single herbs. Single herbs and combinations of herbs specifically used for diabetes mellitus were successfully identified. As conclusion, herb-pairings in TEAM are not randomly constructed; instead, each herb was selectively used with other herbs. In terms of statistical significance, herb pairs were more specifically associated with symptoms than were single herbs alone. Collectively, these results suggest that it may be important to understand the interactions among multiple ingredients contained in herb pairs rather than trying to identify a single compound to resolve symptoms.

• The Journal of Internal Korean Medicine
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• v.38 no.6
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• pp.1000-1006
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• 2017

Objectives: Head symptoms, such as headache and dizziness, are commonly presented in clinical practice. Although Donguibogam, the representative book of Korean medicine, contains many prescriptions for head symptoms, they are difficult to learn and apply because of the vast numbers. The aim of this study was to simplify and visualize the vast contents of Donguibogam by network analysis. Methods: 127 prescriptions for head symptoms, found in Donguibogam, were entered into a Microsoft office Excel 2013 file. This was used as a database for network analysis using the NetMiner 4 program. Results: Through network analysis, six networks for prescriptions for head symptoms in Donguibogam were established. The first network is similar to the herb composition of Cheongsangsahwa-tang (prescriptions for hwa-yeol syndrome). The second network is similar to the herb composition of Yanghyulgupung-tang (prescriptions for hyul-heo syndrome). The third network is similar to the herb composition of Sangcheongbaekbuja-hwan (prescriptions for dam-eum syndrome). The fourth network is similar to the herb composition of Heukseok-dan (prescriptions for yang-heo syndrome). The fifth network is similar to the herb composition of Boheo-eum (prescriptions for chil-jeong syndrome). The sixth network is similar to the herb composition of Bangpungtongseong-san (prescriptions for hwa-yeol syndrome). Conclusions: The results of the network analysis of 127 prescriptions for head symptoms in Donguibogam suggest that there are five major causes of head symptoms (hwa-yeol, hyul-heo, dam-eum, yang-heo, and chil-jeong), and that it is possible to prescribe Cheongsangsahwa-tang, Bangpungtongseong-san, Yanghyulgupung-tang, Sangcheongbaekbuja-hwan, Heukseok-dan, or Boheo-eum depending on the major causes.

• The Journal of Internal Korean Medicine
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• v.44 no.3
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• pp.313-353
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• 2023

Objectives: Heart failure is a chronic disease with increasing prevalence rates despite advancements in medical technology. Korean medicine utilizes herbal prescriptions to treat heart failure, but little is known about the specific herbal medicines comprising the network of herbal prescriptions for heart failure. This study proposes a novel methodology that can efficiently develop prescriptions and facilitate experimental research on heart failure by utilizing existing databases. Methods: Herbal medicine prescriptions for heart failure were identified through a PubMed search and compiled into a Google Sheet database. NetMiner 4 was used for network analysis, and the individual networks were classified according to the herbal medicine classification system to identify trends. K-HERB NETWORK was utilized to derive related prescriptions. Results: Network analysis of heart failure prescriptions and herbal medicines using NetMiner 4 produced 16 individual networks. Uhwangcheongsim-won (牛黃淸心元), Gamiondam-tang (加味溫膽湯), Bangpungtongseong-san (防風通聖散), and Bunsimgi-eum (分心氣飮) were identified as prescriptions with high similarity in the entire network. A total of 16 individual networks utilized K-HERB NETWORK to present prescriptions that were most similar to existing prescriptions. The results provide 1) an indication of existing prescriptions with potential for use to treat heart failure and 2) a basis for developing new prescriptions for heart failure treatment. Conclusion: The proposed methodology presents an efficient approach to developing new heart failure prescriptions and facilitating experimental research. This study highlights the potential of network pharmacology methodology and its possible applications in other diseases. Further studies on network pharmacology methodology are recommended.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.6
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• pp.419-425
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• 2016

This study analyzed research methodologies based on network pharmacology to build a new system architecture optimized for Korean Medicine research. Results form studies using network pharmacology were collected and analyzed to evaluate the strength and weakness. Finally, an improved system architecture was proposed. Whether the predicted effects of drugs or herbs from network pharmacological analyses were in agreement with those from conventioanl knowledge of Korean Medicine was evaluated. These results were used to verify the applicability of research methodologies to the modern pharmacology and Korean Medicine respectively. Eighteen papers using TCMSP were collected and analyzed. The results suggest that the research methodology based on network pharmacology is appropriate only for the modern pharmacology but not for Korean Medicine. Information about compound-compound, herb-herb and drug-compound interactions need to be considered. We propose the modified system architecture with those information.

• Journal of Society of Preventive Korean Medicine
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• v.17 no.1
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• pp.1-11
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• 2013

Objectives : The aim of this research is to produce information by gathering up the data on the interaction between medicinal herbs which lie scattered in oriental medical books, and to provide people with easy access to the information by visualizing it. Methods : For this purpose, this study established the fundamental data by organizing the patterns of interaction into some kinds after selecting a part of Bonchogangmok(本草綱目) and extracting its text. In addition, in an effort to visualize the data, the study converted the data into 'net' file and visualized the interaction between medicinal herbs on Pajek. The visualization was done targeting a total of three patterns, such as 1 medicinal herb, 2 medicinal herbs, and 1 prescription. With the data on 'Chinese Lacquer(乾漆)' for 1 medicinal herb, data on 'Licorice(甘草)' and 'Chinese Lacquer(乾漆)' for 2 medicinal herbs, and data on 'Iijin-tang(二陳湯)' for prescription, the research conducted the analysis of the network using 'Kamada-Kawaii Algorithm' on Pajek. Results : As a result of the analysis, it was possible to see the meanings at a single glance as the scattered and fractional meanings were integrated with focus on medicinal herbs, but the increasing number of analyzed medicinal herbs tended to more and more complicate their relationships, thus, requiring additional work like filtering. Conclusions : Such results are fairly applicable in on-line database, and it is judged that if further research expands its scope to include systematic classification of medicinal herbs or cover other medical books than Bonchogangmok, it will create more objective, abundant information.

• Journal of Physiology & Pathology in Korean Medicine
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• v.32 no.3
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• pp.149-156
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• 2018

Traditional medicines (TM) in Korea, China, and Japan share most of the theories and therapeutic tools, but there are also differences due to their unique histories and cultures. Here, we aim to identify the differences in the utilization of TM theory between three countries by analyzing herb usage data in terms of the related traditional theories. Herb usage data of each country was collected from "Investigation of Korean medicine use and herbal medicine consumption survey" (Korea), "Analytical report on circulation of key Chinese medicinal materials" (China), and "Survey report on raw material crude drug usage" (Japan). Fifty five herbs with sixty features belonging to five theoretical categories (four properties, five tastes, targeting meridians, treatment strategies, and herbal parts) were selected and analyzed. Weight Sum Model (WSM) and Network-Based Group Features (NBGF) were used to compare the theoretical characteristics of TM between three countries. For the statistical evaluation, we developed and applied Herb Set Enrichment Analysis (HSEA) for WSM and NBGF results. HSEA for WSM results revealed the kidney meridian were targeted more in Korea than Japan, while the spleen meridian were targeted more in Japan than Korea. Herbs with sour taste were used more in Japan than China. HSEA for NBGF results found that NBGF including warm, neutral, sweet, and tonifying features were more dominant in Korea and than Japan, while NBGF including cold, bitter, heat-clearing features were more dominant in Japan than the others. These results suggest that TM in Korea, China, and Japan have unique aspects of practice patterns and theoretical utilization.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.12
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• pp.4795-4800
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• 2014

Background: Few studies have directly compared clinical efficacy and safety among Chinese herb injections (CHIs) for gastric cancer (GC). The present study aimed to compare CHIs combined with FOLFOX regimens for GC to show which provides the best CHIs results. Materials and Methods: 9 electronic databases and 6 gray literature databases were comprehensive searched in April 20, 2013. According to inclusion and exclusion criteria, two reviewers independently selected and assessed the included trials. The risk of bias tool described in the Cochrane Handbook version 5.1.0 and CONSORT statement were used to assess the quality of the trials. All calculations and graphs were performed and produced using ADDIS 1.16.5 software. Results: A total of 541 records were searched and 38 RCTs met the inclusion criteria (2,761 participants), involving 10 CHIs. The results of network meta-analysis showed that compared with FOLFOX alone, combinations with Kanglaite, Astragalus polysaccharides, Cinobufacini, or Yadanziyouru injections could furthest strengthen ORR, improve the quality of life, reduce nausea and vomiting, and reduce the incidence of leukopenia (III-IV). Conclusions: Kanglaite injection, Astragalus polysaccharides injection, Yadanziyouru injection were superior to other CHIs in clinical efficacy and safety for GC. The conclusions now need to be confirmed by large sample size direct head-to-head studies.

• The Journal of Internal Korean Medicine
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• v.38 no.6
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• pp.1007-1020
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• 2017

Objectives: This study was carried out to investigate whether a prescription's composition varies according to the disease being caused by wind, which is one of the migratory pathogenic factors. Methods: An initial database and binary matrix of Pungmun in Dongui-Bogam, including its herbs and prescription, was constructed. With this data, a network map about wind stroke, arthralgia, acute arthritis, and tetanus in Dongui-Bogam was constructed. Results: Analysis of the network map about Pungmun in Dongui-Bogam revealed that the complete prescription network has more isolated nodes than does each disease's network map. Conclusions: The composition of prescriptions in Dongui-Bogam Pungmun differ according to the disease being caused by wind.

• Herbal Formula Science
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• v.30 no.3
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• pp.175-182
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• 2022

Objective : This study aims to investigate the active ingredients and potential mechanisms of the beneficial herb on human cancers such as the liver by employing network pharmacology. Methods : Ingredients and their target information was obtained from various databases such as TM-MC, TTD, and Drugbank. Related protein for liver cancer was retrieved from the Comparative Toxicogenomics Database and literature. A hypergeometric test and gene set enrichment analysis were conducted to evaluate associations between protein targets of red ginseng (Panax ginseng C. A. Meyer) and liver cancer-related proteins and identify related signaling pathways, respectively. Network proximity was employed to identify active ingredients of red ginseng on liver cancer. Results : A compound-target network of red ginseng was constructed, which consisted of 363 edges between 53 ingredients and 121 protein targets. MAPK signaling pathway, PI3K-Akt signaling pathway, p53 signaling pathway, TGF-beta signaling pathway, and cell cycle pathway was significantly associated with protein targets of red ginseng. Network proximity results indicated that Ginsenoside Rg1, Acetic Acid, Ginsenoside Rh2, 20(R)-Ginsenoside Rg3, Notoginsenoside R1, Ginsenoside Rk1, 2-Methylfuran, Hexanal, Ginsenoside Rd, Ginsenoside Rh1 could be active ingredients of red ginseng against liver cancer. Conclusion : This study suggests that network-based approaches could be useful to explore potential mechanisms and active ingredients of red ginseng for liver cancer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3708-3728
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• 2021

Indian herbal plants are used in agriculture and in the food, cosmetics, and pharmaceutical industries. Laboratory-based tests are routinely used to identify and classify similar herb species by analyzing their internal cell structures. In this paper, we have applied computer vision techniques to do the same. The original leaf image was preprocessed using the Chan-Vese active contour segmentation algorithm to efface the background from the image by setting the contraction bias as (v) -1 and smoothing factor (µ) as 0.5, and bringing the initial contour close to the image boundary. Thereafter the segmented grayscale image was fed to a leaky capacitance fired neuron model (LCFN), which differentiates between similar herbs by combining different groups of pixels in the leaf image. The LFCN's decay constant (f), decay constant (g) and threshold (h) parameters were empirically assigned as 0.7, 0.6 and h=18 to generate the 1D feature vector. The LCFN time sequence identified the internal leaf structure at different iterations. Our proposed framework was tested against newly collected herbal species of natural images, geometrically variant images in terms of size, orientation and position. The 1D sequence and shape features of aloe, betel, Indian borage, bittergourd, grape, insulin herb, guava, mango, nilavembu, nithiyakalyani, sweet basil and pomegranate were fed into the 5-fold Bayesian regularization neural network (BRNN), K-nearest neighbors (KNN), support vector machine (SVM), and ensemble classifier to obtain the highest classification accuracy of 91.19%.