• Biomolecules & Therapeutics
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• v.27 no.3
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• pp.302-310
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• 2019

Melanoma cells have been shown to respond to BRAF inhibitors; however, intrinsic and acquired resistance limits their clinical application. In this study, we performed RNA-Seq analysis with BRAF inhibitor-sensitive (A375P) and -resistant (A375P/Mdr with acquired resistance and SK-MEL-2 with intrinsic resistance) melanoma cell lines, to reveal the genes and pathways potentially involved in intrinsic and acquired resistance to BRAF inhibitors. A total of 546 differentially expressed genes (DEGs), including 239 up-regulated and 307 down-regulated genes, were identified in both intrinsic and acquired resistant cells. Gene ontology (GO) analysis revealed that the top 10 biological processes associated with these genes included angiogenesis, immune response, cell adhesion, antigen processing and presentation, extracellular matrix organization, osteoblast differentiation, collagen catabolic process, viral entry into host cell, cell migration, and positive regulation of protein kinase B signaling. In addition, using the PAN-THER GO classification system, we showed that the highest enriched GOs targeted by the 546 DEGs were responses to cellular processes (ontology: biological process), binding (ontology: molecular function), and cell subcellular localization (ontology: cellular component). Ingenuity pathway analysis (IPA) network analysis showed a network that was common to two BRAF inhibitorresistant cells. Taken together, the present study may provide a useful platform to further reveal biological processes associated with BRAF inhibitor resistance, and present areas for therapeutic tool development to overcome BRAF inhibitor resistance.

• Journal of Korean Neurosurgical Society
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• v.65 no.1
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• pp.4-12
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• 2022

Objective : We reported the differentially methylated genes in patients with subarachnoid hemorrhage (SAH) using bioinformatics analyses to explore the biological characteristics of the development of delayed cerebral ischemia (DCI). Methods : DNA methylation profiles obtained from 40 SAH patients from an epigenome-wide association study were analyzed. Functional enrichment analysis, protein-protein interaction (PPI) network, and module analyses were carried out. Results : A total of 13 patients (32.5%) experienced DCI during the follow-up. In total, we categorized the genes into the two groups of hypermethylation (n=910) and hypomethylation (n=870). The hypermethylated genes referred to biological processes of organic cyclic compound biosynthesis, nucleobase-containing compound biosynthesis, heterocycle biosynthesis, aromatic compound biosynthesis and cellular nitrogen compound biosynthesis. The hypomethylated genes referred to biological processes of carbohydrate metabolism, the regulation of cell size, and the detection of a stimulus, and molecular functions of amylase activity, and hydrolase activity. Based on PPI network and module analysis, three hypermethylation modules were mainly associated with antigen-processing, Golgi-to-ER retrograde transport, and G alpha (i) signaling events, and two hypomethylation modules were associated with post-translational protein phosphorylation and the regulation of natural killer cell chemotaxis. VHL, KIF3A, KIFAP3, RACGAP1, and OPRM1 were identified as hub genes for hypermethylation, and ALB and IL5 as hub genes for hypomethylation. Conclusion : This study provided novel insights into DCI pathogenesis following SAH. Differently methylated hub genes can be useful biomarkers for the accurate DCI diagnosis.

• Journal of Ginseng Research
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• v.47 no.3
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• pp.469-478
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• 2023

Background: Nitrogen (N) is an essential macronutrient for plant growth and development. To support agricultural production and enhance crop yield, two major N sources, nitrate and ammonium, are applied as fertilizers to the soil. Although many studies have been conducted on N uptake and signal transduction, the molecular genetic mechanisms of N-mediated physiological roles, such as the secondary growth of storage roots, remain largely unknown. Methods: One-year-old P. ginseng seedlings treated with KNO₃ were analyzed for the secondary growth of storage roots. The histological paraffin sections were subjected to bright and polarized light microscopic analysis. Genome-wide RNA-seq and network analysis were carried out to dissect the molecular mechanism of nitrate-mediated promotion of ginseng storage root thickening. Results: Here, we report the positive effects of nitrate on storage root secondary growth in Panax ginseng. Exogenous nitrate supply to ginseng seedlings significantly increased the root secondary growth. Histological analysis indicated that the enhancement of root secondary growth could be attributed to the increase in cambium stem cell activity and the subsequent differentiation of cambium-derived storage parenchymal cells. RNA-seq and gene set enrichment analysis (GSEA) revealed that the formation of a transcriptional network comprising auxin, brassinosteroid (BR)-, ethylene-, and jasmonic acid (JA)-related genes mainly contributed to the secondary growth of ginseng storage roots. In addition, increased proliferation of cambium stem cells by a N-rich source inhibited the accumulation of starch granules in storage parenchymal cells. Conclusion: Thus, through the integration of bioinformatic and histological tissue analyses, we demonstrate that nitrate assimilation and signaling pathways are integrated into key biological processes that promote the secondary growth of P. ginseng storage roots.

• Food Science of Animal Resources
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• v.38 no.2
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• pp.362-375
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• 2018

This study proposed a rapid microscopic examination method for pork freshness evaluation by using the self-assembled hyperspectral microscopic imaging (HMI) system with the help of feature extraction algorithm and pattern recognition methods. Pork samples were stored for different days ranging from 0 to 5 days and the freshness of samples was divided into three levels which were determined by total volatile basic nitrogen (TVB-N) content. Meanwhile, hyperspectral microscopic images of samples were acquired by HMI system and processed by the following steps for the further analysis. Firstly, characteristic hyperspectral microscopic images were extracted by using principal component analysis (PCA) and then texture features were selected based on the gray level co-occurrence matrix (GLCM). Next, features data were reduced dimensionality by fisher discriminant analysis (FDA) for further building classification model. Finally, compared with linear discriminant analysis (LDA) model and support vector machine (SVM) model, good back propagation artificial neural network (BP-ANN) model obtained the best freshness classification with a 100 % accuracy rating based on the extracted data. The results confirm that the fabricated HMI system combined with multivariate algorithms has ability to evaluate the fresh degree of pork accurately in the microscopic level, which plays an important role in animal food quality control.

• Journal of Ginseng Research
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• v.44 no.1
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• pp.50-57
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• 2020

Background: The cellular senescence of primary cultured cells is an irreversible process characterized by growth arrest. Restoration of senescence by ginsenosides has not been explored so far. Rg3(S) treatment markedly decreased senescence-associated β-galactosidase activity and intracellular reactive oxygen species levels in senescent human dermal fibroblasts (HDFs). However, the underlying mechanism of this effect of Rg3(S) on the senescent HDFs remains unknown. Methods: We performed a label-free quantitative proteomics to identify the altered proteins in Rg3(S)-treated senescent HDFs. Upregulated proteins induced by Rg3(S) were validated by real-time polymerase chain reaction and immunoblot analyses. Results: Finally, 157 human proteins were identified, and variable peroxiredoxin (PRDX) isotypes were highly implicated by network analyses. Among them, the mitochondrial PRDX3 was transcriptionally and translationally increased in response to Rg3(S) treatment in senescent HDFs in a time-dependent manner. Conclusion: Our proteomic approach provides insights into the partial reversing effect of Rg3 on senescent HDFs through induction of antioxidant enzymes, particularly PRDX3.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.114-120
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• 2009

In this study, we employed the idea that disease-related proteins tend to be work as an important factor for architecture of the disease network. We initially obtained 43 atopy-related proteins from the Online Mendelian Inheritance in Man (OMIM) and then constructed atopy-related protein interaction network. The protein network can be derived the map of the relationship between different disease proteins, denoted disease interaction network. We demonstrate that the associations between diseases are directly correlated to their underlying protein-protein interaction networks. From constructed the disease-protein bipartite network, we derived three diseasomal proteins, CCR5, CCL11, and IL/4R. Although we use the relatively small subnetwork, an atopy-related disease network, it is sufficient that the discovery of protein interaction networks assigned by diseases will provide insight into the underlying molecular mechanisms and biological processes in complex human disease system.

• Smart Media Journal
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• v.11 no.3
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• pp.26-30
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• 2022

Spiking neural network is a neural network that applies the working principle of real brain neurons. Due to the biological mechanism of neurons, it consumes less power for training and reasoning than conventional neural networks. Recently, as deep learning models become huge and operating costs increase exponentially, the spiking neural network is attracting attention as a third-generation neural network that connects convolution neural networks and recurrent neural networks, and related research is being actively conducted. However, in order to apply the spiking neural network model to the industry, a lot of research still needs to be done, and the problem of model retraining to apply a new model must also be solved. In this paper, we propose a method to minimize the cost of model retraining by extracting the weights of the existing trained deep learning model and converting them into the weights of the spiking neural network model. In addition, it was found that weight conversion worked correctly by comparing the results of inference using the converted weights with the results of the existing model.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.511-515
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• 2004

In the post-genomic era, researches on proteins as well as genes have been increasingly required. Particularly, work on protein-protein interaction and protein network construction have been recently establishing. Most biologists publish their research results through papers or other media. However, biologists do not use the information effectively, since the published research results are very large. As the growth of internet, it becomes easy to access very large research results. It is significantly important to extract information with a biological meaning from varisous media. Therefore, in this research, we efficiently extract protein-protein interaction information from many open papers or other media and construct the database of the extracted information. We build a protein network from the established database and then design and implement various pathway analysis algorithms which find biological meaning from the protein network.

• Korean Journal of Biological Psychiatry
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• v.24 no.2
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• pp.68-74
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• 2017

Objectives It is well known that problem drinking is associated with alterations of brain structures and functions. Brain functions related to alcohol consumption can be determined by the resting state functional connectivity in various resting state networks (RSNs). This study aims to ascertain the alcohol effect on the structures forming predetermined RSNs by assessing their cortical thickness. Methods Twenty-six abstinent male patients with alcohol dependence and the same number of age-matched healthy control were recruited from an inpatient mental hospital and community. All participants underwent a 3T MRI scan. Averaged cortical thickness of areas constituting 7 RSNs were determined by using FreeSurfer with Yeo atlas derived from cortical parcellation estimated by intrinsic functional connectivity. Results There were significant group differences of mean cortical thicknesses (Cohen's d, corrected p) in ventral attention (1.01, < 0.01), dorsal attention (0.93, 0.01), somatomotor (0.90, 0.01), and visual (0.88, 0.02) networks. We could not find significant group differences in the default mode network. There were also significant group differences of gray matter volumes corrected by head size across the all networks. However, there were no group differences of surface area in each network. Conclusions There are differences in degree and pattern of structural recovery after abstinence across areas forming RSNs. Considering the previous observation that group differences of functional connectivity were significant only in networks related to task-positive networks such as dorsal attention and cognitive control networks, we can explain recovery pattern of cognition and emotion related to the default mode network and the mechanisms for craving and relapse associated with task-positive networks.

• Applied Biological Chemistry
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• v.41 no.2
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• pp.160-165
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• 1998

Current discriminating technique of rice variety is known to be not objective till this time because of depending on naked eye of well trained inspector. DNA finger print method based on genetic character of rice has been indicated inappropriate for on-site application, because the method need much labor and skilled expert. The purpose of this study was to develops the identification technique of polished rice varieties using CCD camera images. To minimize the noise of the captured image, thresholding and median filtering were carried out, and edge was extracted from the image data. Image data after pretreatment of normalize and FFT(fast fourier transform) were used for library model and feedforward backpropagation neural network model. Image processing technique using CCD camera could discriminate the variety of rice with high accuracy in case of quite different rice of shape, but the accuracy was reached at 85% in the similar shape of rice.