• Molecules and Cells
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• v.38 no.5
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• pp.441-451
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• 2015

Recognition of cytosolic DNA initiates a series of innate immune responses by inducing IFN-I production and subsequent triggering JAK1-STAT1 signaling which plays critical roles in the pathogenesis of infection, inflammation and autoimmune diseases through promoting B cell activation and antibody responses. The stimulator of interferon genes protein (STING) has been demonstrated to be a critical hub of type I IFN induction in cytosolic DNA-sensing pathways. However, it still remains unknown whether cytosolic DNA can directly activate the JAK1-STAT1 signaling or not. And the role of STING is also unclear in this response. In the present study, we found that dsDNA directly triggered the JAK1-STAT1 signaling by inducing phosphorylation of the Lyn kinase. Moreover, this response is not dependent on type I IFN receptors. Interestingly, STING could inhibit dsDNA-triggered activation of JAK1-STAT1 signaling by inducing SHP-1 and SHP-2 phosphorylation. In addition, compared with normal B cells, the expression of STING was significantly lower and the phosphorylation level of JAK1 was significantly higher in B cells from MRL/lpr lupus-prone mice, highlighting the close association between STING low-expression and JAK1-STAT1 signaling activation in B cells in autoimmune diseases. Our data provide a molecular insight into the novel role of STING in dsDNA-mediated inflammatory disorders.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.8
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• pp.3273-3277
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• 2015

Network scale up (NSU) is a novel approach to estimate parameters in hard to reach populations through asking people the number of individuals they know in their active social network. Although the method have been used in hidden populations, advantages of NSU indicate that exploration of applicability to disease like cancer might be feasible. The aim of this study was to assess the application of NSU to estimate the size of the population of breast, ovarian/cervical, prostate, and bladder cancers in the South-east of Iran. A total of 3,052 (99% response rate) Kermanian people were interviewed in 2012-2013. Based on NSU, participants were asked about if they know any people on their social network who suffered from breast, ovarian/cervical, prostate, and bladder cancers, if yes, they should enumerate them. A total of 1,650 persons living with four types of cancers (breast, ovary/cervix, prostate, and bladder) were identified by the respondents. Totally, the prevalence of people living with the four types of cancers was 228.4 per 100,000 Kermanian inhabitants. The most prevalent cancer was breast cancer, at 168.9 per 100,000, followed by prostate cancer with 116.9, ovarian/cervical cancer with 99.8, and bladder cancer with 36.3 per 100000 Kerman city population. NSU values provide a usable but not very precise way of estimating the size of subpopulations in the context of the four major cancers (breast, ovary/cervix, prostate, and bladder).

• Journal of Microbiology and Biotechnology
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• v.34 no.5
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• pp.1164-1177
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• 2024

Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2561-2567
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• 2015

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.280-286
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• 2024

In this paper, layered UNet with warmup and dropout tricks was used to segment teeth instantly by using data labeled for each individual tooth and increase performance of the result. The layered UNet proposed before showed very good performance in tooth segmentation without distinguishing tooth number. To do instance segmentation of teeth, we labeled teeth CBCT data according to tooth numbering system which is devised by FDI World Dental Federation notation. Colors for labeled teeth are like AI-Hub teeth dataset. Simulation results show that layered UNet does also segment very well for each tooth distinguishing tooth number by color. Layered UNet model using warmup trick was the best with IoU values of 0.80 and 0.77 for training, validation data. To increase the performance of instance segmentation of teeth, we need more labeled data later. The results of this paper can be used to develop medical software that requires tooth recognition, such as orthodontic treatment, wisdom tooth extraction, and implant surgery.

• Journal of Society of Preventive Korean Medicine
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• v.10 no.2
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• pp.81-93
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• 2006

This study was carried out to examine the actual condition of health promotion program through oriental medicine in the health center and to provide basic data to develop proper policy of oriental medical health promotion program for the community people. The data were collected from 26 health centers which have been implementing the oriental medical health promotion program, using selfadministered questionnaire for two weeks from 1 October to 15 October 2006. The results are as follows : Generally, the respondents have the positive views on the level of budget and facilities/equipments of the oriental medical health promotion program in health center. However, they have the negative views on the level of manpower and education/training of the program. And also more than 70% of the respondents have the negative opinion on capabilities of formulating and evaluating the oriental medical health promotion program. The respondents indicated that there was the lack of coordination between the oriental medical health promotion program and existing health promotion in health center, and that low rate of utilizing community resources. With regard to the method of selecting the target group for the program, there are differences according to the each program. Many programs tended to select the target group not through the criteria of life-course and illness group but through the efficiency of selecting group. And many programs such as stroke prevention program, constitutional medicine program, oriental medical prenatal program, oriental medical prenatal and postnatal program, oriental medical child care program are mainly composed of the development of educational program and lecture. Regarding the number of the present oriental medical health promotion programs, around 65% of respondents answered that the number of the programs was many and thus they needed to decrease to the proper level. And with regard to the priority of the need, effectiveness and the satisfaction for each programs, on the whole, Qui gong program, stroke prevention program, area-specialty program and oriental medical home visiting program have high score. In particular, oriental medical quit-smoking program has lowest score. From these results, it requires to develop and improve the oriental medical health promotion program in health center considering the need and characteristics of community.

• Journal of agricultural medicine and community health
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• v.44 no.4
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• pp.185-194
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• 2019

Objective: In Gunsan, Jeollabuk-do, Korea, we wanted to determine if the sluggish local economy could affect citizens' health behaviors, especially mental health. Methods: We divided Gunsan-si into 5 living areas and conducted Small-Area Estimations and confirmed the modified compound estimation value using the 2013-2017 Community Health Survey data and population data from Gunsan-si. Results: The health behaviors and mental health of the residents of the western living area(Soryong-dong, Misung-dong), which is an industrial hub of Gunsan, had deteriorated or decreased compared to those of other regions. Conclusions: Although there are limitations in analyzing the community health survey data using the small-area estimation method, it could be useful data for evaluating regional gaps and health level.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1003-1008
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• 2016

Breast cancer is now the leading cause of cancer death in women worldwide. Cancer progression is driven not only by cancer cell intrinsic alterations and interactions with tumor microenvironment, but also by systemic effects. Integration of multiple profiling data may provide insights into the underlying molecular mechanisms of complex systemic processes. We performed a bioinformatic analysis of two public available microarray datasets for breast tumor stroma and peripheral blood mononuclear cells, featuring integrated transcriptomics data, protein-protein interactions (PPIs) and protein subcellular localization, to identify genes and biological pathways that contribute to dialogue between tumor stroma and the peripheral circulation. Genes of the integrin family as well as CXCR4 proved to be hub nodes of the crosstalk network and may play an important role in response to stroma-derived chemoattractants. This study pointed to potential for development of therapeutic strategies that target systemic signals travelling through the circulation and interdict tumor cell recruitment.

• International journal of advanced smart convergence
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• v.5 no.3
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• pp.32-39
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• 2016

With the help of a small wearable device, patients reside in an isolated village need constant monitoring which may increase access to care and decrease healthcare delivery cost. As the number of patients' requests increases in simultaneously manner, the web service gateway located in the village hall encounters limitations for performing them successfully and concurrently. The gateway based RESTful technology responsible for handling patients' requests attests an internet latency in case a large number of them submit toward the gateway increases. In this paper, we propose the design tasks of the web service gateway for handling concurrency events. In the procedure of designing tasks, concurrency is best understood by employing multiple levels of abstraction. The way that is eminently to accomplish concurrency is to build an object-oriented environment with support for messages passing between concurrent objects. We also investigate the performance of event-driven architecture for building web service gateway using node.js. The experiments results show that server-side JavaScript with Node.js and MongoDB as database is 40% faster than Apache Sling. With Node.js developers can build a high-performance, asynchronous, event-driven healthcare hub server to handle an increasing number of concurrent connections for Remote Healthcare Monitoring System in an isolated village with no access to local medical care.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.88-95
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• 2017

As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.