• Parasites, Hosts and Diseases
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• v.56 no.2
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• pp.135-145
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• 2018

Due to the critical location and physiological activities of the retinal pigment epithelial (RPE) cell, it is constantly subjected to contact with various infectious agents and inflammatory mediators. However, little is known about the signaling events in RPE involved in Toxoplasma gondii infection and development. The aim of the study is to screen the host mRNA transcriptional change of 3 inflammation-related gene categories, PI3K/Akt pathway regulatory components, blood vessel development factors and ROS regulators, to prove that PI3K/Akt or mTOR signaling pathway play an essential role in regulating the selected inflammation-related genes. The selected genes include PH domain and leucine- rich-repeat protein phosphatases (PHLPP), casein kinase2 (CK2), vascular endothelial growth factor (VEGF), pigment epithelium-derived factor (PEDF), glutamate-cysteine ligase (GCL), glutathione S-transferase (GST), and NAD(P)H: quinone oxidoreductase (NQO1). Using reverse transcription polymerase chain reaction (RT-PCR) and quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR), we found that T. gondii up-regulates PHLPP2, $CK2{\beta}$, VEGF, GCL, GST and NQO1 gene expression levels, but down-regulates PHLPP1 and PEDF mRNA transcription levels. PI3K inhibition and mTOR inhibition by specific inhibitors showed that most of these host gene expression patterns were due to activation of PI3K/Akt or mTOR pathways with some exceptional cases. Taken together, our results reveal a new molecular mechanism of these gene expression change dependent on PI3K/Akt or mTOR pathways and highlight more systematical insight of how an intracellular T. gondii can manipulate host genes to avoid host defense.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of Ginseng Research
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• v.42 no.4
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• pp.496-503
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• 2018

Background: Korean ginseng (Panax ginseng) plays an anti-inflammatory role in a variety of inflammatory diseases such as gastritis, hepatitis, and colitis. However, inflammation-regulatory activity of the calyx of the P. ginseng berry has not been thoroughly evaluated. To understand whether the calyx portion of the P. ginseng berry is able to ameliorate inflammatory processes, an ethanolic extract of P. ginseng berry calyx (Pg-C-EE) was prepared, and lipopolysaccharide-activated macrophages and HEK293 cells transfected with inflammation-regulatory proteins were used to test the anti-inflammatory action of Pg-C-EE. Methods: The ginsenoside contents of Pg-C-EE were analyzed by HPLC. Suppressive activity of Pg-C-EE on NO production, inflammatory gene expression, transcriptional activation, and inflammation signaling events were examined using the Griess assay, reverse transcription-polymerization chain reaction, luciferase activity reporter gene assay, and immunoblotting analysis. Results: Pg-C-EE reduced NO production and diminished mRNA expression of inflammatory genes such as cyclooxygenase-2, inducible NO synthase, and tumor necrosis factor-${\alpha}$ in a dose-dependent manner. This extract suppressed luciferase activity induced only by nuclear factor-${\kappa}B$. Interestingly, immunoblotting analysis results demonstrated that Pg-C-EE reduced the activities of protein kinase B (AKT)1 and AKT2. Conclusion: These results suggest that Pg-C-EE may have nuclear-factor-${\kappa}B$-targeted anti-inflammatory properties through suppression of AKT. The calyx of the P. ginseng berry is an underused part of the ginseng plant, and development of calyx-derived extracts may be useful for treatment of inflammatory diseases.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.147-156
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• 2013

Each field of modern society, industrialization and the development of science and technology are rapidly changing. However, as a side effect of rapid social change has caused various problems. Crime of the side effects of rapid social change is a big problem. In this paper, a model for predicting crime and Markov chains applied to the crime, predictive modeling is proposed. Markov chain modeling of the existing one with the overall status of the case determined the probability of predicting the future, but this paper predict the events to increase the probability of occurrence probability of the prediction and the recent state of the entire state was divided by the probability of the prediction. And the whole state and the probability of the prediction and the recent state by applying the average of the prediction probability and the probability of the prediction model were implemented. Data was applied to the incidence of crime. As a result, the entire state applies only when the probability of the prediction than the entire state and the last state is calculated by dividing the probability value. And that means when applied to predict the probability, close to the crime was concluded that prediction.

• Genomics & Informatics
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• v.17 no.4
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• pp.42.1-42.6
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• 2019

Robust identification of genetic alterations is important for the diagnosis and subsequent treatment of tumors. Screening for genetic alterations using tumor tissue samples may lead to biased interpretations because of the heterogeneous nature of the tumor mass. Liquid biopsy has been suggested as an attractive tool for the non-invasive follow-up of cancer treatment outcomes. In this study, we aimed to verify whether the mutations identified in primary tumor tissue samples could be consistently detected in plasma cell-free DNA (cfDNA) by digital polymerase chain reaction (dPCR). We first examined the genetic alteration profiles of three colorectal cancer (CRC) tissue samples by targeted next-generation sequencing (NGS) and identified 11 non-silent amino acid changes across six cancer-related genes (APC, KRAS, TP53, TERT, ARIDIA, and BRCA1). All three samples had KRAS mutations (G12V, G12C, and G13D), which were well-known driver events. Therefore, we examined the KRAS mutations by dPCR. When we examined the three KRAS mutations by dPCR using tumor tissue samples, all of them were consistently detected and the variant allele frequencies (VAFs) of the mutations were almost identical between targeted NGS and dPCR. When we examined the KRAS mutations using the plasma cfDNA of the three CRC patients by dPCR, all three mutations were consistently identified. However, the VAFs were lower (range, 0.166% to 2.638%) than those obtained using the CRC tissue samples. In conclusion, we confirmed that the KRAS mutations identified from CRC tumor tissue samples were consistently detected in the plasma cfDNA of the three CRC patients by dPCR.

• Clinical and Experimental Reproductive Medicine
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• v.48 no.2
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• pp.132-141
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• 2021

Objective: Lipopolysaccharide (LPS) from Gram-negative bacteria causes poor uterine receptivity by inducing excessive inflammation at the maternal-fetal interface. This study aimed to investigate the detrimental effects of LPS on the attachment and outgrowth of various types of trophoblastic spheroids on endometrial epithelial cells (ECC-1 cells) in an in vitro model of implantation. Methods: Three types of spheroids with JAr, JEG-3, and JAr mixed JEG-3 (JmJ) cells were used to evaluate the effect of LPS on early implantation events. ECC-1 cells were treated with LPS to mimic endometrial infection, and the expression of inflammatory cytokines and adhesion molecules was analyzed by quantitative real-time polymerase chain reaction and western blotting. The attachment rates and outgrowth areas were evaluated in the various trophoblastic spheroids and ECC-1 cells treated with LPS. Results: LPS treatment significantly increased the mRNA expression of inflammatory cytokines (CXCL1, IL-8, and IL-33) and decreased the protein expression of adhesion molecules (ITGβ3 and ITGβ5) in ECC-1 cells. The attachment rates of JAr and JmJ spheroids on ECC-1 cells significantly decreased after treating the ECC-1 cells with 1 and 10 ㎍/mL LPS. In the outgrowth assay, JAr spheroids did not show any outgrowth areas. However, the outgrowth areas of JEG-3 spheroids were similar regardless of LPS treatment. LPS treatment of JmJ spheroids significantly decreased the outgrowth area after 72 hours of coincubation. Conclusion: An in vitro implantation model using novel JmJ spheroids was established, and the inhibitory effects of LPS on ECC-1 endometrial epithelial cells were confirmed in the early implantation process.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.27 no.2
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• pp.123-130
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• 2005

Many of the molecular and genotypic events taking place at the osteoblast cell level during bone-implant integration are still largely unknown. The objective of this study was to examine expression patterns of TGF-$\beta$ and IGF-I related genes during bone-implant integration. Titanium implants with machined surface were placed into 8 rabbit tibias. At 3rd, 7th, 14th, 28th day after implantation, the expression pattern of TGF-$\beta$ and IGF-I genes in bone with or without implant was examined using reverse transcriptase-polymerase chain reaction (RT-PCR). At the same time, histomorphometric analysis was evaluated, respectively. The bone-to-implant contacts (BIC) of experimental groups were 5.2%, 6.2%, 6.6%, 24.6% at 3rd, 7th, 14th, 28th day. This indicated that newly formed bone increased at the implant surface in bone marrow space after implantation. The expressions of TGF-$\beta$ and IGF-I were higher in implantation groups than untreated control groups during all experimental days. The increased expression of TGF-$\beta$ and IGF-I genes may be associated with the increased bone-to-implant contact. This result provided the evidence for existing biologic differences in tissue response after implantation and helped us to understand molecular biologic processes in tissue-implant integration.

• Nutritional Sciences
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• v.6 no.3
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• pp.148-154
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• 2003

Although various raw plant materials have been demonstrated to exert anti-obesity effects to a greater or lesser extent in both humans and animals when they are used to supplement the diet, it has not been shown extensively that they influence adipocyte cell differentiation involving lipid metabolic gene expressions. Using a well-established 3T3-L1 preadipocyte differentiation system, we decided to look into molecular and cellular event occurring during adipocyte differentiation when raw plant materials aye included in the process, in an effort to demonstrate the potential use of a screening system to define the functions of traditionally well-known materials. To these ends, the effects of ethanol (EtOH) or EtOH/distilled water (DW) extracts of Wax Gourd were examined using cytochemical and molecular analyses to determine whether components of the extracts modulate adipocyte differentiation of 3T3-Ll preadipocytes in vitro. The cytochemical results demonstrated that EtOH or EtOH/DW extracts did not affect lipid accumulation and cell proliferation, although the degree of lipid accumulation was influenced slightly depending on the extract. EtOH extract was highly effective in apoptotic induction during differentiation of 3T3-Ll preadipocytes (p<0.05). Reverse transcription-polymerase chain reaction (RT-PCR) analysis of lipoprotein lipase (LPL), Uncoupling protein (Ucp) 2, 3 and 4 also showed that while LPL expression was not influenced, Ucp2, 3 and 4 were up regulated in the EtOH extract-treated group and down regulated in the EtOH/DW extract-treated group. These changes in gene expressions suggest that the components in different fractions of Wax Gourd extracts may modulate lipid metabolism by either direct or indirect action. Taking these results together, it was concluded that molecular and cellular analyses of adipocyte differentiation involving lipid metabolic genes should facilitate understanding of cellular events occurring during adipocyte differentiation. Furthermore, the experimental scheme and analytical methods used in this study should provide a screening system for the functional study of raw plant materials in obesity research.

• Archives of Plastic Surgery
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• v.39 no.2
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• pp.106-112
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• 2012

Background : Complicated diabetic patients show impaired, delayed wound healing caused by multiple factors. A study on wound healing showed that platelet-rich plasma (PRP) was effective in normal tissue regeneration. Nonetheless, there is no evidence that when platelet-rich plasma is applied to diabetic wounds, it normalizes the diabetic wound healing process. In this study, we have analyzed matrix metalloproteinase (MMP)-2, MMP-9 expression to investigate the effect of PRP on diabetic wounds. Methods : Twenty-four-week-old male Otsuka Long-Evans Tokushima Fatty rats were provided by the Tokushima Research Institute. At 50 weeks, wounds were arranged in two sites on the lateral paraspinal areas. Each wound was treated with PRP gel and physiologic saline gauze. To determine the expression of MMP-2, MMP-9, which was chosen as a marker of wound healing, reverse transcription polymerase chain reaction (RT-PCR) was performed and local distribution and expression of MMP-2, MMP-9 was also observed throughout the immunohistochemical staining. Results : RT-PCR and the immunohistochemical study showed that the levels of MMP-2, MMP-9 mRNA expression in PRP applied tissues were higher than MMP-2, MMP-9 mRNA expression in saline-applied tissues. MMP-9 mRNA expression in wounds of diabetic rats decreased after healing began to occur. But no statistical differences were detected on the basis of body weight or fasting blood glucose levels. Conclusions : This study could indicate the extracellular matrix-regulating effect observed with PRP. Our results of the acceleration of wound healing events by PRP under hyperglycemic conditions might be a useful clue for future clinical treatment for diabetic wounds.