• 한국축산식품학회지
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• 제42권1호
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• pp.1-17
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• 2022

Lipids are one of the major macronutrients essential for adequate growth and maintenance of human health. Their structure is not only complex but also diverse, which makes systematic and holistic analyses challenging; consequently, little is known regarding the relationship between phenotype and mechanism of action. In recent years, rapid advancements have been made in the fields of lipidomics and bioinformatics. In comparison with traditional approaches, mass spectrometry-based lipidomics can rapidly identify as well as quantify >1,000 lipid species at the same time, facilitating comprehensive, robust analyses of lipids in tissues, cells, and body fluids. Accordingly, lipidomics is now being widely applied in various fields, particularly food and nutrition science. In this review, we discuss lipid classification, extraction techniques, and detection and analysis using lipidomics. We also cover how lipidomics is being used to assess food obtained from livestock and poultry. The information included herein should serve as a reference to determine how to characterize lipids in animal food samples, enhancing our understanding of the application of lipidomics in the field in animal husbandry.

• 한국지하수토양환경학회지:지하수토양환경
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• 제27권2호
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• pp.76-86
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• 2022

Calcium (Ca) and potassium (K) were introduced to remove Sr and Cs in soil, respectively. Four factor and three level Box-Bhenken design was employed to determine the optimal washing condition of Ca- and K-based solutions, and the ranges tested were 0.1 to 1 M of Ca or K, L/S ratio of 5 to 20, washing time of 0.5 to 2 h, and pH of 2 to 7. The optimal washing condition determined was 1 M of Ca or K, L/S ratio of 20, washing time of 1 h, and pH of 2, and Ca-based and K-based solutions showed 68 and 81% removal efficiency for Sr and Cs, respectively in soil. For comparison, widely used conventional washing agents such as 0.075 M EDTA, 0.01 M citric acid, 0.01 M oxalic acid, and 0.05 M phosphoric acid were tested, and they showed 25 to 30% of Sr and Cs removal efficiency. Tessier sequential extraction was employed to identify the changes in chemical forms of Sr and Cs during the washing. In contrast to the conventional washing agents, Ca-based and K-based solutions were able to release relatively strongly bound forms of Sr and Cs such as Fe/Mn-oxide and organic matter bound forms, suggesting the involvement of direct substitution mechanism, probably due to the physicochemical similarities between Sr-Ca and Cs-K.

• Smart Structures and Systems
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• 제30권6호
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

• 대한한의학방제학회지
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• 제30권4호
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• pp.269-280
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• 2022

Objectives : In this study, it was investigated the effects of solid-phase fermentation extraction with Phellinus linteus of discarded Schisandra chinensis extract (PS) and its action mechanism on dexamethasone-induced muscle atrophy in mice. Methods : In mice, muscle atrophy model was induced by dexamethasone (5 mg/kg, I.p) once daily for 2 weeks and with PS extract administration (100 and 300 mg/kg, p.o.) as treatment groups. The changes in body weights, grip strength, Treadmill test, muscle weights, and the expression of atrophy-related genes were measured in muscle atrophy mice. The histological changes of gastrocnemius tissues were also observed by H&E staining with measurement of myofiber size. Results : The administration of PS extract increased significantly body weights, grip strength, treadmill test and muscle weights in muscle atrophy mice. PS extract administration increased significantly the area of myofibers and inhibited structural damages of muscle and increased significantly the expression of myogenin and decreased significantly the expression of MuRF1, Atrogin1 and phosphorylation of AMPK and PGC1α in muscle tissues of muscle atrophy mice. Conclusions : These results indicate that PS extract has a improvement effects on muscle atrophy with stimulation of myogenic differentiation and inhibition of mRNA degradation that could be related with the activation of AMPK and PGC1α signaling pathways in muscle. This suggests that PS extract can apply to treat muscle atrophy in clinics.

• Nutrition Research and Practice
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• 제17권2호
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• pp.206-217
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• 2023

BACKGROUND/OBJECTIVES: The immunomodulatory effect of Platycodon grandiflorum (PG) has been reported, but studies on its mechanism are still lacking. This study was undertaken to confirm whether the hydrolyzed and fermented PG extract (HFPGE) obtained by adding hydrolysis and fermentation to the extraction process has an immune-enhancing effect in the in vivo system. MATERIALS/METHODS: Five-week-old BALB/c mice were divided into 4 groups: normal control group (NOR), control group (CON), 150 mg/kg body weight (BW)/day HFPGE-treated group (T150), and 300 mg/kg BW/day HFPGE-treated group (T300). The mice were administered HFPGE for 4 weeks and intraperitoneally injected with cyclophosphamide (CPA, 80 mg/kg BW/day) on day 6, 7, and 8, respectively, to induce immunosuppression. The levels of immunoglobulins (Igs) and cytokines were measured in the serum. In splenocytes, proliferation and cytokine levels were measured. RESULTS: Serum IgA, IgG, and IgM levels were observed to decrease after CPA treatment, which was recovered by HFPGE administration. The levels of serum interleukin (IL)-12, tumor necrosis factor (TNF)-α, IL-8, and transforming growth factor (TGF)-β were also decreased after exposure to CPA but increased after HFPGE administration. Decreased splenocyte proliferation was seen in CPA-treated mice, but was observed to increase in the T150 and T300 groups as compared to the NOR group. Compared to the CON group, splenocyte proliferation stimulated with concanavalin A (ConA) or lipopolysaccharide (LPS) in the HFPGE-treated groups was significantly increased. The cytokines secreted by ConA-stimulated splenocytes (IL-2, IL-12, interferon-γ, TNF-α) were increased in the T150 and T300 groups, and cytokines secreted by LPS-stimulated splenocytes (IL-4, IL-8, TGF-β) were also increased by HFPGE administration. CONCLUSION: These results suggest that HFPGE stimulates the immunity in immunosuppressed conditions, thereby enhancing the immune response. Therefore, it is expected that HFPGE has the potential to be used as functional food and medicine for immune recovery in various immunocompromised situations.

• BMB Reports
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• 제56권2호
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• pp.96-101
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• 2023

Particulate matter is an air pollutant composed of various components, and has adverse effects on the human body. Particulate matter is known to induce cell death by generating an imbalance in the antioxidant system; however, the underlying mechanism has not been elucidated. In the present study, we demonstrated the cytotoxic effects of the size and composition of particulate matter on small intestine cells. We found that particulate matter 2.5 (PM_2.5) with extraction ion (EI) components (PM_2.5 EI), is more cytotoxic than PM containing only polycyclic aromatic hydrocarbons (PAHs). Additionally, PM-induced cell death is characteristic of ferroptosis, and includes iron accumulation, lipid peroxidation, and reactive oxygen species (ROS) generation. Furthermore, ferroptosis inhibitor as liproxstatin-1 and iron-chelator as deferiprone attenuated cell mortality, lipid peroxidation, iron accumulation, and ROS production after PM_2.5 EI treatment in human small intestinal cells. These results suggest that PM_2.5 EI may increase ferroptotic-cell death by iron accumulation and ROS generation, and offer a potential therapeutic clue for inflammatory bowel diseases in human small intestinal cells.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권5호
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• pp.1433-1449
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• 2023

In recent years, the rapid development of social networks has led to a rapid increase in the amount of information available on the Internet, which contains a large amount of sensitive information related to pornography, politics, and terrorism. In the aspect of sensitive image detection, the existing machine learning algorithms are confronted with problems such as large model size, long training time, and slow detection speed when auditing and supervising. In order to detect sensitive images more accurately and quickly, this paper proposes a multiclassification sensitive image detection method based on lightweight Convolutional Neural Network. On the basis of the EfficientNet model, this method combines the Ghost Module idea of the GhostNet model and adds the SE channel attention mechanism in the Ghost Module for feature extraction training. The experimental results on the sensitive image data set constructed in this paper show that the accuracy of the proposed method in sensitive information detection is 94.46% higher than that of the similar methods. Then, the model is pruned through an ablation experiment, and the activation function is replaced by Hard-Swish, which reduces the parameters of the original model by 54.67%. Under the condition of ensuring accuracy, the detection time of a single image is reduced from 8.88ms to 6.37ms. The results of the experiment demonstrate that the method put forward has successfully enhanced the precision of identifying multi-class sensitive images, significantly decreased the number of parameters in the model, and achieved higher accuracy than comparable algorithms while using a more lightweight model design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2768-2787
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• 2023

As an important research direction of the application of computer science in the medical field, the automatic generation technology of radiology report has attracted wide attention in the academic community. Because the proportion of normal regions in radiology images is much larger than that of abnormal regions, words describing diseases are often masked by other words, resulting in significant feature loss during the calculation process, which affects the quality of generated reports. In addition, the huge difference between visual features and semantic features causes traditional multi-modal fusion method to fail to generate long narrative structures consisting of multiple sentences, which are required for medical reports. To address these challenges, we propose a multi-feature optimization Transformer (MFOT) for generating radiology reports. In detail, a multi-dimensional mapping attention (MDMA) module is designed to encode the visual grid features from different dimensions to reduce the loss of primary features in the encoding process; a feature pre-fusion (FP) module is constructed to enhance the interaction ability between multi-modal features, so as to generate a reasonably structured radiology report; a detail enhanced attention (DEA) module is proposed to enhance the extraction and utilization of key features and reduce the loss of key features. In conclusion, we evaluate the performance of our proposed model against prevailing mainstream models by utilizing widely-recognized radiology report datasets, namely IU X-Ray and MIMIC-CXR. The experimental outcomes demonstrate that our model achieves SOTA performance on both datasets, compared with the base model, the average improvement of six key indicators is 19.9% and 18.0% respectively. These findings substantiate the efficacy of our model in the domain of automated radiology report generation.

• 한국항행학회논문지
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• 제28권2호
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• pp.238-245
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• 2024

본 논문에서는 농작물 다중 분광 이미지에 대해 특징 융합 기법을 이용하여 의미론적 분할 성능을 향상시키기 위한 프레임워크를 제안한다. 스마트팜 분야에서 연구 중인 딥러닝 기술 중 의미론적 분할 모델 대부분은 RGB(red-green-blue)로 학습을 진행하고 있고 성능을 높이기 위해 모델의 깊이와 복잡성을 증가시키는 데에 집중하고 있다. 본 연구는 기존 방식과 달리 다중 분광과 어텐션 메커니즘을 통해 모델을 최적화하여 설계한다. 제안하는 방식은 RGB 단일 이미지와 함께 UAV (unmanned aerial vehicle)에서 수집된 여러 채널의 특징을 융합하여 특징 추출 성능을 높이고 상호보완적인 특징을 인식하여 학습 효과를 증대시킨다. 특징 융합에 집중할 수 있도록 모델 구조를 개선하고, 작물 이미지에 유리한 채널 및 조합을 실험하여 다른 모델과의 성능을 비교한다. 실험 결과 RGB와 NDVI (normalized difference vegetation index)가 융합된 모델이 다른 채널과의 조합보다 성능이 우수함을 보였다.

• Anatomy and Cell Biology
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• 제57권1호
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• pp.31-44
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• 2024

The exocrine part of the pancreas has a duct system called the pancreatic ductal system (PDS). Its mechanism of development is complex, and any reorganization during early embryogenesis can give rise to anatomical variants. The aim of this study is to collect, classify, and analyze published evidence on the importance of anatomical variants of the PDS, addressing gaps in our understanding of such variations. The MEDLINE, Web of Science, Embase, and Google Scholar databases were searched to identify publications relevant to this review. R studio with meta-package was used for data extraction, risk of bias estimation, and statistical analysis. A total of 64 studies out of 1,778 proved suitable for this review and metanalysis. The meta-analysis computed the prevalence of normal variants of the PDS (92% of 10,514 subjects). Type 3 variants and "descending" subtypes of the main pancreatic duct (MPD) predominated in the pooled samples. The mean lengths of the MPD and accessory pancreatic duct (APD) were 16.53 cm and 3.36 cm, respectively. The mean diameters of the MPD at the head and the APD were 3.43 mm and 1.69 mm, respectively. The APD was present in only 41% of samples, and the long type predominated. The pancreatic ductal anatomy is highly variable, and the incorrect identification of variants may be challenging for surgeons during ductal anastomosis with gut, failure to which may often cause ductal obstruction or pseudocysts formation.