• 대한의용생체공학회:의공학회지
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• 제44권2호
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• pp.139-146
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• 2023

Osteoporosis is a disease in which the risk of bone fractures increases due to a decrease in bone density caused by aging. Osteoporosis is diagnosed by measuring bone density in the total hip, femoral neck, and lumbar spine. To accurately measure bone density in the lumbar spine, the vertebral region must be segmented from the lumbar X-ray image. Deep learning-based automatic spinal segmentation methods can provide fast and precise information about the vertebral region. In this study, we used 695 lumbar spine images as training and test datasets for a deep learning segmentation model. We proposed a lumbar automatic segmentation model, CM-Net, which combines the center point of the spine and the modified U-Net network. As a result, the average Dice Similarity Coefficient(DSC) was 0.974, precision was 0.916, recall was 0.906, accuracy was 0.998, and Area under the Precision-Recall Curve (AUPRC) was 0.912. This study demonstrates a high-performance automatic segmentation model for lumbar X-ray images, which overcomes noise such as spinal fractures and implants. Furthermore, we can perform accurate measurement of bone density on lumbar X-ray images using an automatic segmentation methodology for the spine, which can prevent the risk of compression fractures at an early stage and improve the accuracy and efficiency of osteoporosis diagnosis.

• 대한의용생체공학회:의공학회지
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• 제44권4호
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• pp.255-263
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• 2023

Clinical ultrasound (US) is a widely used imaging modality with various clinical applications. However, capturing a large field of view often requires specialized transducers which have limitations for specific clinical scenarios. Panoramic imaging offers an alternative approach by sequentially aligning image sections acquired from freehand sweeps using a standard transducer. To reconstruct a 3D volume from these 2D sections, an external device can be employed to track the transducer's motion accurately. However, the presence of optical or electrical interferences in a clinical setting often leads to incorrect measurements from such sensors. In this paper, we propose a deep learning (DL) framework that enables the prediction of scan trajectories using only US data, eliminating the need for an external tracking device. Our approach incorporates diverse data types, including correlation volume, optical flow, B-mode images, and rawer data (IQ data). We develop a DL network capable of effectively handling these data types and introduce an attention technique to emphasize crucial local areas for precise trajectory prediction. Through extensive experimentation, we demonstrate the superiority of our proposed method over other DL-based approaches in terms of long trajectory prediction performance. Our findings highlight the potential of employing DL techniques for trajectory estimation in clinical ultrasound, offering a promising alternative for panoramic imaging.

• 대한한방부인과학회지
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• 제22권2호
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• pp.94-118
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• 2009

Purpose: Gleditsiae spina (GS) has been used to treat patients with several diseases such as carbuncle, swelling and parasites. Recently GS is known to have anticancer activity in abdominal solid tumor, but the effects of GS on breast cancers is not clarified. For these reasons, we investigated effects of Gleditsiae spina (GS) on gene expression of human breast cancer cells. Methods: We investigated the effects of GS on proliferation of breast cancer cell line, MDA-MB-231. In addition, the genetic profile for the effect of GS on breast cancer cells was measured using microarray technique, and the functional analysis on these genes was conducted. Results: Total 1,434 genes were up-regulated and 2,483 genes down-regulated in the cells treated with GS. Genes induced or suppressed by GS were all mainly concerned with metabolic process, regulation of biological process and protein binding. The network of total protein interactions was measured using cytoscape program, and some key molecules that can be used for elucidation of therapeutical mechanism of medicine in future were identified. Conclusion: These results suggest possibility of GS as anti-cancer drug for breast cancer, and also suggest that related mechanisms are involved in regulation of intra-cellular metabolism in breast cancer cells.

• 대한한방부인과학회지
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• 제22권3호
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• pp.117-134
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• 2009

Purpose: In the theory of traditional medicine, Scutellariae Radix (SR) can clear away heat and remove dampness, purge the sthenic fire and remove toxic materials, cool blood and stop bleeding to prevent miscarriage. Recently, SR is known to have anti-cancer activity. For this reason, the present author designed to investigate the effect of SR on proliferation rates of cervical cancer cell line, then effects on genetic profile by SR. Methods: The genetic profile for the effect of SR on human derived cervical cancer cell line, SNU-703, was measured using microarray technique, and the functional analysis on these genes was conducted. Results: Total 519 genes were up-regulated and 606 genes down-regulated in cells treated with SR. Genes induced or suppressed by SR were all mainly concerned with metabolic process, regulation of biological process and protein binding. The network of total protein interactions was measured using cytoscape program, and some key molecules, such as TNFRSF1A, AKT1, MAPK3, and STAT3 that can be used for elucidation of therapeutical mechanism of medicine in future were identified. Conclusion: These results suggest possibility of SR as anti-cancer drug and also suggest that related mechanisms are involved in TNFRSF1A, AKT1, MAPK3, and STAT3 related signalling pathways.

• Genomics & Informatics
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• 제21권1호
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• pp.8.1-8.19
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• 2023

Cancer of the stomach is the second most frequent cancer-related death worldwide. The survival rate of patients with gastric cancer (GC) remains fragile. There is a requirement to discover biomarkers for prognosis approaches. Helicobacter pylori in the stomach is closely associated with the progression of GC. We identified the genes associated with poor/favorable prognosis in H. pylori-induced GC. Multivariate statistical analysis was applied on the Gene Expression Omnibus (GEO) dataset GSE54397 to identify differentially expressed miRNAs (DEMs) in gastric tissues with H. pylori-induced cancer compared with the H. pylori-positive with non-cancerous tissue. A protein interaction map (PIM) was built and subjected to DEMs targets. The enriched pathways and biological processes within the PIM were identified based on substantial clusters. Thereafter, the most critical genes in the PIM were illustrated, and their prognostic impact in GC was investigated. Considering p-value less than 0.01 and |Log2 fold change| as >1, five microRNAs demonstrated significant changes among the two groups. Gene functional analysis revealed that the ubiquitination system, neddylation pathway, and ciliary process are primarily involved in H. pylori-induced GC. Survival analysis illustrated that the overexpression of DOCK4, GNAS, CTGF, TGF-b1, ESR1, SELE, TIMP3, SMARCE1, and TXNIP was associated with poor prognosis, while increased MRPS5 expression was related to a favorable prognosis in GC patients. DOCK4, GNAS, CTGF, TGF-b1, ESR1, SELE, TIMP3, SMARCE1, TXNIP, and MRPS5 may be considered prognostic biomarkers for H. pylori-induced GC. However, experimental validation is necessary in the future.

• Genomics & Informatics
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• 제21권2호
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• pp.22.1-22.15
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• 2023

Kidney renal clear cell carcinoma (KIRC) is one of the most aggressive cancer type of the urinary system. Metastatic KIRC patients have poor prognosis and limited therapeutic options. Ankyrin 3 (ANK3) is a scaffold protein that plays important roles in maintaining physiological function of the kidney and its alteration is implicated in many cancers. In this study, we investigated differential expression of ANK3 in KIRC using GEPIA2, UALCAN, and HPA databases. Survival analysis was performed by GEPIA2, Kaplan-Meier plotter, and OS-kirc databases. Genetic alterations of ANK3 in KIRC were assessed using cBioPortal database. Interaction network and functional enrichment analyses of ANK3-correlated genes in KIRC were performed using GeneMANIA and Shiny GO, respectively. Finally, the TIMER2.0 database was used to assess correlation between ANK3 expression and immune infiltration in KIRC. We found that ANK3 expression was significantly decreased in KIRC compared to normal tissues. The KIRC patients with low ANK3 expression had poorer survival outcomes than those with high ANK3 expression. ANK3 mutations were found in 2.4% of KIRC patients and were frequently co-mutated with several genes with a prognostic significance. ANK3-correlated genes were significantly enriched in various biological processes, mainly involved in peroxisome proliferator-activated receptor (PPAR) signaling pathway, in which positive correlations of ANK3 with PPARA and PPARG expressions were confirmed. Expression of ANK3 in KIRC was significantly correlated with infiltration level of B cell, CD8+ T cell, macrophage, and neutrophil. These findings suggested that ANK3 could serve as a prognostic biomarker and promising therapeutic target for KIRC.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.46-46
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• 2022

유기물의 복잡한 혼합물인 CDOM(Colored or Chromophoric Dissolved Organic Matter)은 하천 내 BOD(Biological Oxygen Demand), COD(Chemical Oxygen Demand) 및 유기 오염물질과 상당한 관련이 있다. CDOM은 가시광선 영역에서 빛을 흡수하는 성질을 가지고 있으며, 최근 원격감지 기술로 CDOM을 모니터링하기 위한 연구가 진행되고 있다. 본 연구에서는 백제보 상류 23km 구간에서 3년(2016~2018) 중 13일의 초분광영상을 활용하여 머신러닝 기반 CDOM을 추정 알고리즘을 개발하고자 한다. 초분광영상은 400~970 nm의 범위의 4 nm 간격 127개 대역의 분광해상도와 2 m의 공간해상도를 가진 항공기 탑재 AsiaFENIX 초분광 센서를 통해 수집하였으며 CDOM은 Millipore polycarbonate filter (𝚽47, 0.2 ㎛)에서 여과된 CDOM 샘플 자료를 200~800 nm의 흡수계수 스펙트럼으로 추출하여 사용하였다. CDOM 값은 전체기간 동안 2.0~11.0 m^-1의 값 분포를 보였으며 5 m^-1이상의 고농도 구간 자료개수가 전체 153개 샘플자료 중 21개로 불균형하다. 따라서 ADASYN(Adaptive Synthesis Sampling Approach)의 oversampling 방법으로 생성된 합성 데이터를 사용하여 원본 데이터의 소수계층 데이터 불균형을 해결하고 모델 예측 성능을 개선하고자 하였다. 생성된 합성 데이터를 입력변수로 하여 ANN(Artificial Neural Netowk)을 활용한 CDOM 예측 알고리즘을 구축하였다. ADASYN 기법을 통한 합성 데이터는 관측된 데이터의 불균형을 해결하여 기계학습 모델의 CDOM 탐지 성능을 향상시킬 수 있으며, 저수지 내 유기 오염물질 관리를 위한 설계를 지원하는데 사용할 수 있을 것으로 판단된다.

• 대한방사선기술학회지:방사선기술과학
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• 제46권5호
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• pp.435-444
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• 2023

The purpose of this study was to analyze the factors that demographic factors, radiation knowledge level, and radiation awareness could be affecting the benefits of radiation. From July 2022 to July 2023, after receiving consent to participate by using the link of Naver through Social Network Service (SNS) for the general public, 312 people were surveyed by self-registration method without collecting personal information. The questionnaire consisted of a total of 25 questions following demographic factors (5 questions including age group by life cycle, sex, monthly household income, residence), radiation knowledge level (8 questions including basic physical, biological effects, radiation protection technology), radiation awareness (12 questions including risk, management, benefit). Independent sample T-test and ANOVA tests were performed for significant differences in the average radiation awareness between variables, and hierarchical regression was performed to identify influencing factors on radiation benefits. As a result, the benefit of radiation was significantly high among the radiation awareness, but the awareness of the danger of radiation was insufficient to the level of recognizing it as safe. Men had significantly higher awareness of radiation management and benefits than women, and the awareness of radiation management was significantly higher in the middle class with a monthly household income of 4.31 million won or more. The higher the knowledge level of radiation, the higher the awareness of the benefits of radiation. The factors that had a positive effect on radiation benefits were the high level of radiation knowledge and awareness of radiation management.

• 대한의용생체공학회:의공학회지
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• 제45권2호
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• pp.95-100
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• 2024

Vitiligo is a condition characterized by the destruction or dysfunction of melanin-producing cells in the skin, resulting in a loss of skin pigmentation. Facial vitiligo, specifically affecting the face, significantly impacts patients' appearance, thereby diminishing their quality of life. Evaluating the efficacy of facial vitiligo treatment typically relies on subjective assessments, such as the Facial Vitiligo Area Scoring Index (F-VASI), which can be time-consuming and subjective due to its reliance on clinical observations like lesion shape and distribution. Various machine learning and deep learning methods have been proposed for segmenting vitiligo areas in facial images, showing promising results. However, these methods often struggle to accurately segment vitiligo lesions irregularly distributed across the face. Therefore, our study introduces a framework aimed at improving the segmentation of vitiligo lesions on the face and providing an evaluation of vitiligo lesions. Our framework for facial vitiligo segmentation and lesion evaluation consists of three main steps. Firstly, we perform face detection to minimize background areas and identify the face area of interest using high-quality ultraviolet photographs. Secondly, we extract facial area masks and vitiligo lesion masks using a semantic segmentation network-based approach with the generated dataset. Thirdly, we automatically calculate the vitiligo area relative to the facial area. We evaluated the performance of facial and vitiligo lesion segmentation using an independent test dataset that was not included in the training and validation, showing excellent results. The framework proposed in this study can serve as a useful tool for evaluating the diagnosis and treatment efficacy of vitiligo.

• Journal of Ginseng Research
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• 제48권2호
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• pp.220-228
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• 2024

Background: Panax ginseng, one of the valuable perennial medicinal plants, stores numerous pharmacological substrates in its storage roots. Given its perennial growth habit, organ regeneration occurs each year, and cambium stem cell activity is necessary for secondary growth and storage root formation. Cytokinin (CK) is a phytohormone involved in the maintenance of meristematic cells for the development of storage organs; however, its physiological role in storage-root secondary growth remains unknown. Methods: Exogenous CK was repeatedly applied to P. ginseng, and morphological and histological changes were observed. RNA-seq analysis was used to elucidate the transcriptional network of CK that regulates P. ginseng growth and development. The HISTIDINE KINASE 3 (PgHK3) and RESPONSE REGULATOR 2 (PgRR2) genes were cloned in P. ginseng and functionally analyzed in Arabidopsis as a two-component system involved in CK signaling. Results: Phenotypic and histological analyses showed that CK increased cambium activity and dormant axillary bud formation in P. ginseng, thus promoting storage-root secondary growth and bud formation. The evolutionarily conserved two-component signaling pathways in P. ginseng were sufficient to restore CK signaling in the Arabidopsis ahk2/3 double mutant and rescue its growth defects. Finally, RNA-seq analysis of CK-treated P. ginseng roots revealed that plant-type cell wall biogenesis-related genes are tightly connected with mitotic cell division, cytokinesis, and auxin signaling to regulate CK-mediated P. ginseng development. Conclusion: Overall, we identified the CK signaling-related two-component systems and their physiological role in P. ginseng. This scientific information has the potential to significantly improve the field-cultivation and biotechnology-based breeding of ginseng.