Park, Sa-Yoon;Park, Ji-Hun;Kim, Hyo-Su;Lee, Choong-Yeol;Lee, Hae-Jeung;Kang, Ki Sung;Kim, Chang-Eop
Journal of Ginseng Research
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v.42
no.1
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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.
Although microscopic analysis of tissue slides has been the basis for disease diagnosis for decades, intra- and inter-observer variabilities remain issues to be resolved. The recent introduction of digital scanners has allowed for using deep learning in the analysis of tissue images because many whole slide images (WSIs) are accessible to researchers. In the present study, we investigated the possibility of a deep learning-based, fully automated, computer-aided diagnosis system with WSIs from a stomach adenocarcinoma dataset. Three different convolutional neural network architectures were tested to determine the better architecture for tissue classifier. Each network was trained to classify small tissue patches into normal or tumor. Based on the patch-level classification, tumor probability heatmaps can be overlaid on tissue images. We observed three different tissue patterns, including clear normal, clear tumor and ambiguous cases. We suggest that longer inspection time can be assigned to ambiguous cases compared to clear normal cases, increasing the accuracy and efficiency of histopathologic diagnosis by pre-evaluating the status of the WSIs. When the classifier was tested with completely different WSI dataset, the performance was not optimal because of the different tissue preparation quality. By including a small amount of data from the new dataset for training, the performance for the new dataset was much enhanced. These results indicated that WSI dataset should include tissues prepared from many different preparation conditions to construct a generalized tissue classifier. Thus, multi-national/multi-center dataset should be built for the application of deep learning in the real world medical practice.
Young Woo Kim;Seon Been Bak;Won-Yung Lee;Su Jin Bae;Eun Hye Lee;Ju-Hye Yang;Kwang Youn Kim;Chang Hyun Song;Sang Chan Kim;Un-Jung Yun;Kwang Il Park
Journal of Ginseng Research
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v.47
no.3
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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.
Objectives : Sagunja-Tang is a famous prescription used in Korean medicine for the purpose of promoting vital energy, and there are few studies using Sagunja-Tang on cerebrovascular diseases yet. As previous studies confirmed that Sagunja-tang is highly likely to be used effectively for stroke, this study was intended to predict the mechanism through which Sagunja-tang would act effectively on stroke. Methods : In this study, a network pharmacology analysis method was used, and oral bioavailability (OB), drug likeness (DL), Caco-2 and BBB permeability were utilized to select compounds with potential activity. For the values of each variable used in this study, OB ≥ 30%, DL ≥ 0.18, Caco-2 ≥ 0, and BBB ≥ 0.3 were applied. Using the above variables, the relations between target genes and diseases that are presumed to be involved in the selected bioavailable compounds were constructed in a network format, and proteins thought to play a major role were identified. Results : Among the compounds included in Sagunja-Tang, 26 bioavailable compounds were selected and it was confirmed that these compounds can be effectively used in cerebrovascular diseases such as Alzheimer's disease and stroke. These compounds are considered to act on proteins related in cell death and growth. The most important mechanism of action was predicted to be apoptosis, and the protein that is thought to play the most key action in this mechanism was caspase-3. Conclusions : In our future study, Sagunja-Tang will be used in an ischemic stroke mouse model, and the mechanism of action will be explored focusing on apoptosis and cell proliferation.
Objectives : The purpose of this study was to explore the compounds, targets and related diseases of garlic by the approaches of network pharmacology and bioinformatics in traditional chinese medicine. Methods : We investigated components and their target molecules of garlic using SymMap and TCMSP and they were compared with analysis platform. Results : 56 potential compounds were identified in garlic, 26 of which contained target information, and it was found that these 26 compounds and 154 targets interact with each other through a combination of 243 compounds. In addition, Apigenin was linked to the most targeted gene (78) in 26 compounds, followed by Kaempferol (61 genes), Nicotic Acid (14 genes), Geraniol (11 genes), Eee (10 genes), and Sobrol A (9 genes). Among 56 potential compounds, three compounds (Kaempferol, Dipterocarpol, and N-Methyl cytisine) corresponded to the active compound by screening criterion Absorption, Distribution, Metabolism, Excretion (ADME). In addition, 12 compounds in 56 potential compounds were associated with gastrointestinal (GI) motility disorder. Among them, Kaempferol was a compound that met the ADME parameters and the rest were potential compounds that did not meet. Also, Kaempferol was closely related to GI motility disorder, indicating that this Kaempferol could be a candidate for potential medical efficacy. Conclusions : It shows the relationship between the compound of garlic, an herbal supplement, and the biological process associated with GI motility disorder. These results are thought to help develop strategies for treating GI motility disorders.
Jung Joo Yoon;Hye Yoom Kim;Ai Lin Tai;Ho Sub Lee;Dae Gill Kang
Herbal Formula Science
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v.32
no.1
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pp.11-28
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2024
Objectives : GunRyeong-Tang(GRT) is a traditional herbal prescription that combines Oryeongsan and Sagunja-tang. This study employed network analysis methods on the components of GRT and target genes related to diabetes complications to predict the improvement effects of GRT on diabetes complications. Methods : The collection of active compounds of GRT and related target genes involved the utilization of public databases and the PubChem database. We selected diabetes complication-related genes using GeneCards and confirmed their correlation through comparative analysis with the target genes of GRT. We constructed a network using Cytoscape 3.9.1 and conducted topological analysis. To predict the mechanism, we performed functional enrichment analysis based on Gene Ontology (GO) biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Results : Through network analysis, 234 active compounds and 1361 related genes were collected from GRT. A total of 9,136 genes related to diabetes complications were collected, and 1,039 target genes overlapping with the components of GRT were identified. The core genes of this network were TP53, INS, AKT1, ALB, and EGFR. In addition, GRT significantly reduced the H9c2 cell size and the expression of myocardial hypertrophy biomarkers (ANP, BNP), which were increased by high glucose (HG). Conclusions : Through this study, we were able to predict the activity and mechanism of action of GRT on diabetes and diabetic complications, and confirmed the potential of GRT as a treatment for diabetes complications through the effect of GRT on improving myocardial hypertrophy for diabetic cardiomyopathy.
Ulmus davidiana var. japonica Rehder (Urticales: Ulmaceae) (UD) is a tree widespread in northeast Asia. It is traditionally used for anticancer and anti-inflammatory therapy. The present study investigated the effect of an ethanol extract of UD on vascular tension and its underlying mechanism in rats. The dried root bark of UD was ground and extracted with 80% ethanol. The prepared UD extract was used in further analysis. The effect of UD on the cell viability, vasoreactivity and hemodynamics were investigated using propidium iodide staining in cultured cells, isometric tension recording and blood pressure analysis, respectively. Low dose of UD ($10{\sim}100{\mu}g/ml)$ did not affect endothelial cell viability, but high dose of UD reduced cell viability. UD induced vasorelaxation in the range of $0.1{\sim}10{\mu}g/ml$ with an $ED_{50}$ value of $2{\mu}g/ml$. UD-induced vasorelaxation was completely abolished by removal of the endothelium or by pre-treatment with L-NAME, an inhibitor of nitric oxide synthase. UD inhibited calcium influx induced by phenylephrine and high $K^+$ and also completely abolished the effect of L-NAME. Intravenous injection of UD extracts (10~100 mg/kg) decreased arterial and ventricular pressure in a dose-dependent manner. Moreover, UD extracts reduced the ventricular contractility (+dP/dt) in anesthetized rats. However, UD-induced hypotensive actions were minimized in L-NAME-treated rats. Taken together, out results showed that UD induced vasorelaxation and has antihypertensive properties, which may be due the activation of nitric oxide synthase in endothelium.
Objectives : The root of Salvia miltiorrhiza, known as 'Dansam (DS, 丹參)', is used for and treating cardiovascular diseases based on its efficacy of promoting blood circulation and breaking through a blood stasis. In this study, we would like to see if DS could be effectively used for stroke from the perspective of network pharmacology. Methods : The analysis was conducted using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database to derive the main active compounds of DS and identify the mechanism of each compound acting on the human body. The networks between compounds, target protein and disease were expressed through Cytoscape. Protein-protein interaction (PPI) analysis was performed using STRING database. Results : Fifty two active compounds of DS were identified by screening the ingredients of DS through TCMSP. Based on the networks of these compounds with target protein and disease, it can be said that DS might be effective for preventing and treating stroke. PPI result showed that adrenergic receptor has many interactions among proteins, indicating its significance in stroke pathway. Conclusion : In this study, we derived target proteins and target diseases of DS that could be used in study of stroke. However, since it is uncertain if these targets can be controlled by DS extracts or not, we would like to confirm the results with further animal experiments.
International journal of advanced smart convergence
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v.11
no.4
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pp.247-252
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2022
The purpose of the domestic physician scientist support program is to promote the development of various biotechnology. Therefore, it can be said that examining whether the purpose of support is being faithfully implemented has an important meaning for the future domestic biotechnology development ecosystem. Therefore, this study limited the subject of analysis to 79 MD-PhD experts who participated or participated in doctor scientist programs at major universities in Korea. Among them, a total of 25 researchers, one researcher from each classroom in parasitology, microbiology, pharmacology, biochemistry, physiology, and anatomy, which had the highest paper citations in the last five years (2016-2021), were selected to examine the relationship between joint research. It was selected as the subject of review. As a result, 25 selected pseudo-scientists(MD-PhD) identified domestic and foreign researchers who participated as co-researchers when publishing in overseas academic journals for the last 5 years(2016-2021), and identified the affiliation and name of the top 5 among them, as well as the pseudo-scientist(MD-PhD), it was possible to identify the relationship of a total of 123 co-researchers(excluding 2 missing values) of the top 5 co-researchers with a high degree of cooperation with respect to the researcher(25 in total), and the collaboration of pseudo-scientists. Relationships, major researchers, and research institutes were examined. Nodexl Basic 2018 ver. (Microsof) was used for the analysis, and the relationship between researchers could be visualized by applying network analysis techniques.
Young Hoon, Kim;Woo Jin, Jeong;Gwang Hee, Jeong;Youn Sook, Kim;Won Gun, An
Journal of Physiology & Pathology in Korean Medicine
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v.36
no.6
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pp.229-234
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2022
Lung cancer is the leading cause of cancer-related deaths worldwide. Indigo Naturalis (IN) is a dark blue powder obtained by processing leaves or stems of indigo plants, its anticancer effects have been reported in several studies. However, the pharmacological mechanism of IN in small cell lung cancer (SCLC) is not elucidated. In this study, to investigate the anticancer efficacy of IN for SCLC, we presented potential active ingredients, SCLC-related targets, and pharmacological mechanisms of IN that are expected to have anticancer activity for SCLC using a network pharmacological analysis. The phytochemical compounds of IN have been collected through TCMSP, SymMap, or HPLC documents. The active ingredients of IN such as indirubin, indican, isatin, and tryptanthrin were selected through ADME parameters or literature investigations for each compound. Using the Compounds, Disease-Target associations Databases, 124 common targets of IN and SCLC were obtained. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment analysis was carried out. GO biological processes are associated with response to xenobiotic stimulus, positive regulation of protein phosphorylation, regulation of mitotic cell cycle, and regulation of apoptotic signaling pathway. KEGG disease pathways included Gastric cancer, Bladder cancer, SCLC, and Melanoma. The main anticancer targets of the IN for SCLC were analyzed in 14 targets, including BCL2, MYC, and TP53. In conclusion, the results of this study based on the network pharmacology of IN can provide important data for the effective prevention and treatment of SCLC.
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