• Annals of Clinical Neurophysiology
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• 제25권2호
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• pp.93-102
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• 2023

Background: We aimed to identify any differences in the structural covariance network based on structural volume and those in the functional network based on cerebral blood flow between the ipsilateral and contralateral hemispheres of pain in patients with episodic migraine without aura. Methods: We prospectively enrolled 27 patients with migraine without aura, all of whom had unilateral migraine pain. We defined the ipsilateral hemisphere as the side of migraine pain. We measured structural volumes on three-dimensional T1-weighted images and cerebral blood flow using arterial spin labeling magnetic resonance imaging. We then analyzed the structural covariance network based on structural volume and the functional network based on cerebral blood flow using graph theory. Results: There were no significant differences in structural volume or cerebral blood flow between the ipsilateral and contralateral hemispheres. However, there were significant differences between the hemispheres in the structural covariance network and the functional network. In the structural covariance network, the betweenness centrality of the thalamus was lower in the ipsilateral hemisphere than in the contralateral hemisphere. In the functional network, the betweenness centrality of the anterior cingulate and paracingulate gyrus was lower in the ipsilateral hemisphere than in the contralateral hemisphere, while that of the opercular part of the inferior frontal gyrus was higher in the former hemisphere. Conclusions: The present findings indicate that there are significant differences in the structural covariance network and the functional network between the ipsilateral and contralateral hemispheres of pain in patients with episodic migraine without aura.

• 한방안이비인후피부과학회지
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• 제36권1호
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• pp.50-63
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• 2023

Objectives : This study used a network pharmacology approach to explore the active compounds and therapeutic mechanisms of Yijin-tang on Meniere's disease. Methods : The active compounds of Yijin-tang were screened via the TCMSP database and their target proteins were screened via the STITCH database. The GeneCard was used to establish the Meniere's disease-related genes. The intersection targets were obtained through Venny 2.1.0. The related protein interaction network was constructed with the STRING database, and topology analysis was performed through CytoNCA. GO biological function analysis and KEGG enrichment analysis for core targets were performed through the ClueGO. Results : Network analysis identified 126 compounds in five herbal medicines of Yijin-tang. Among them, 15 compounds(naringenin, beta-sitosterol, stigmasterol, baicalein, baicalin, calycosin, dihydrocapsaicin, formononetin, glabridin, isorhamnetin, kaempferol, mairin, quercetin, sitosterol, nobiletin) were the key chemicals. The target proteins were 119, and 7 proteins(TNF, CASP9, PARP1, CCL2, CFTR, NOS2, NOS1) were linked to Meniere's disease-related genes. Core genes in this network were TNF, CASP9, and NOS2. GO/KEGG pathway analysis results indicate that these targets are primarily involved in regulating biological processes, such as excitotoxicity, oxidative stress, and apoptosis. Conclusion : Pharmacological network analysis can help to explain the applicability of Yijin-tang on Meniere's disease.

• BMB Reports
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• 제55권9호
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• pp.417-428
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• 2022

Herbal medicine, a multi-component treatment, has been extensively practiced for treating various symptoms and diseases. However, its molecular mechanism of action on the human body is unknown, which impedes the development and application of herbal medicine. To address this, recent studies are increasingly adopting systems pharmacology, which interprets pharmacological effects of drugs from consequences of the interaction networks that drugs might have. Most conventional network-based approaches collect associations of herb-compound, compound-target, and target-disease from individual databases, respectively, and construct an integrated network of herb-compound-target-disease to study the complex mechanisms underlying herbal treatment. More recently, rapid advances in high-throughput omics technology have led numerous studies to exploring gene expression profiles induced by herbal treatments to elicit information on direct associations between herbs and genes at the genome-wide scale. In this review, we summarize key databases and computational methods utilized in systems pharmacology for studying herbal medicine. We also highlight recent studies that identify modes of action or novel indications of herbal medicine by harnessing drug-induced transcriptome data.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.187-193
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• 2021

Our final goal is to implement nursing robots that can recognize patient's faces and their medicine on prescription. They can help patients to take medicine on time and prevent its abuse for recovering their health soon. As the first step, we proposed a medicine classifier with a low computational network that is able to run on embedded PCs without GPU in order to be applied to universal nursing robots. We confirm that our proposed model called MedicineNet achieves an 99.99% accuracy performance for classifying 15 kinds of medicines and background images. Moreover, we realize that the calculation time of our MedicineNet is about 8 times faster than EfficientNet-B0 which is well known as ImageNet classification with the high performance and the best computational efficiency.

• 셀메드
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• 제5권2호
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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.

• 고려인삼연구와산업
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• 제4권2호
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• pp.14-23
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• 2010

• Journal of Ginseng Research
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• 제42권1호
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• pp.98-106
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• 2018

Panax ginseng has been used since ancient times based on the traditional Asian medicine theory and clinical experiences, and currently, is one of the most popular herbs in the world. To date, most of the studies concerning P. ginseng have focused on specific mechanisms of action of individual constituents. However, in spite of many studies on the molecular mechanisms of P. ginseng, it still remains unclear how multiple active ingredients of P. ginseng interact with multiple targets simultaneously, giving the multidimensional effects on various conditions and diseases. In order to decipher the systems-level mechanism of multiple ingredients of P. ginseng, a novel approach is needed beyond conventional reductive analysis. We aim to review the systems-level mechanism of P. ginseng by adopting novel analytical framework-network pharmacology. Here, we constructed a compound-target network of P. ginseng using experimentally validated and machine learning-based prediction results. The targets of the network were analyzed in terms of related biological process, pathways, and diseases. The majority of targets were found to be related with primary metabolic process, signal transduction, nitrogen compound metabolic process, blood circulation, immune system process, cell-cell signaling, biosynthetic process, and neurological system process. In pathway enrichment analysis of targets, mainly the terms related with neural activity showed significant enrichment and formed a cluster. Finally, relative degrees analysis for the target-disease association of P. ginseng revealed several categories of related diseases, including respiratory, psychiatric, and cardiovascular diseases.

• 대한한의학회지
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• 제39권4호
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• pp.16-29
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• 2018

Introduction: We aimed to investigate the predictive factors and optimal age for response to herbal medicine treatment for height gain in children. Methods: This retrospective chart review included 61 children (age range, 5-16 years) treated for height gain between 2011 and 2015. A predictive model was established by multiple linear regression analysis. Dependent variables were defined by the differences in percentile before and after herbal medicine treatment. The optimal cutoff value of patient age was determined by receiver operating curve analysis. Results : The age of initiation of herbal medicine therapy (p = 0.012) and administration of Forsythiae fructus (p = 0.002) were significant variables for treatment response. The adjusted R2 value was 0.231. The mean ages of the responder and non-responder groups were significantly different (p = 0.023). The optimal cutoff value of age for predicting treatment response was 9.75 years. Treatment response was better among children below 9.75 years of age. Conclusions: Patient age and administration of Forsythiae fructus were identified as determinants of response to herbal medicine treatment. Treatment of rhinitis and initiation of height gain treatment at an early age are critical for better response. These findings will provide fundamental data for further research.

• 대한한의학회지
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• 제44권2호
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• pp.106-118
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• 2023

Objectives: Network pharmacology is a method of constructing and analyzing a drug-compound-target network to predict potential efficacy and mechanisms related to drug targets. In that large-scale analysis can be performed in a short time, it is considered a suitable tool to explore the function and role of herbal medicine. Thus, we investigated the potential functions and pathways of Chongmyunggongjin-dan (CMGJD) on Alzheimer's disease (AD) via network pharmacology analysis. Methods: Using public databases and PubChem database, compounds of CMGJD and their target genes were collected. The putative target genes of CMGJD and known target genes of AD were compared and found the correlation. Then, the network was constructed using Cytoscape 3.9.1. and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results: The result showed that total 104 compounds and 1157 related genes were gathered from CMGJD. The network consisted of 1157nodes and 10034 edges. 859 genes were interacted with AD gene set, suggesting that the effects of CMGJD are closely related to AD. Target genes of CMGJD are considerably associated with various pathways including 'Positive regulation of chemokine production', 'Cellular response to toxic substance', 'Arachidonic acid metabolic process', 'PI3K-Akt signaling pathway', 'Metabolic pathways', 'IL-17 signaling pathway' and 'Neuroactive ligand-receptor interaction'. Conclusion: Through a network pharmacological method, CMGJD was predicted to have high relevance with AD by regulating inflammation. This study could be used as a basis for effects of CMGJD on AD.

• Journal of Ginseng Research
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• 제47권3호
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• pp.479-491
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• 2023

Background: Hepatocellular carcinoma (HCC) has a high incidence and is one of the highest mortality cancers when advanced stage is proceeded. However, Anti-cancer drugs available for treatment are limited and new anti-cancer drugs and new ways to treat them are minimal. We examined that the effects and possibility of Red Ginseng (RG, Panax ginseng Meyer) as new anti-cancer drug on HCC by combining network pharmacology and molecular biology. Materials and Methods: Network pharmacological analysis was employed to investigate the systems-level mechanism of RG focusing on HCC. Cytotoxicity of RG was determined by MTT analysis, which were also stained by annexin V/PI staining for apoptosis and acridine orange for autophagy. For the analyze mechanism of RG, we extracted protein and subjected to immunoblotting for apoptosis or autophagy related proteins. Results: We constructed compound-target network of RG and identified potential pathways related to HCC. RG inhibited growth of HCC through acceleration of cytotoxicity and reduction of wound healing ability of HCC. RG also increased apoptosis and autophagy through AMPK induction. In addition, its ingredients, 20S-PPD (protopanaxadiol) and 20S-PPT (protopanaxatriol), also induced AMPK mediated apoptosis and autophagy. Conclusion: RG effectively inhibited growth of HCC cells inducing apoptosis and autophagy via ATG/AMPK in HCC cells. Overall, our study suggests possibility as new anti-cancer drug on HCC by proof for the mechanism of the anti-cancer action of RG.