• Nutrition Research and Practice
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• v.2 no.4
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• pp.317-321
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• 2008

Macrophages play a key role in iron metabolism by recycling iron through erythrophagocytosis. Ferroportin-l (FPN1) is a transporter protein that is known to mediate iron export from macrophages. Since divalent metals often interact with iron metabolism, we examined if divalent metals could regulate the expression of FPN1 in macrophages. J774 macrophage cells were treated with copper, manganese, zinc, or cobalt at 10, 50, or $100\;{\mu}M$ for 16 to 24 h. Then, FPN1 mRNA and protein levels were determined by quantitative real-time PCR and Western blot analyses, respectively. In addition, effects of divalent metals on FPN1 promoter activity were examined by luciferase reporter assays. Results showed that copper significantly increased FPN1 mRNA levels in a dose-dependent manner. The copper-induced expression of FPN1 mRNA was associated with a corresponding increase in FPN1 protein levels. Also, copper directly stimulated the activity of FPN1 promoter-driven reporter construct. In contrast, manganese and zinc had no effect on the FPN1 gene expression in J774 cells. Interestingly, cobalt treatment in J774 cells decreased FPN1 protein levels without affecting FPN1 mRNA levels. In conclusion, our study results demonstrate that divalent metals differentially regulate FPN1 expression in macrophages and indicate a potential interaction of divalent metals with the FPN1-mediated iron export in macrophages.

• Journal of Nutrition and Health
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• v.42 no.5
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• pp.434-441
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• 2009

Ferroportin-1 (FPN) is a transporter protein that is known to mediate iron export from macrophages. The purpose of this study was to investigate the effect of copper on the regulation of FPN gene expression in J774 mouse macrophage cells. J774 cells were treated with various concentrations of $CuSO_4$ and RT-PCR analyses were performed to measure the steady-state levels of mRNAs for FPN and divalent metal transporter 1 (DMT1, an iron importer). Copper treatment significantly increased FPN mRNAs in a dose-dependent manner, but didn't change the levels of DMT1 mRNA. Experiments with transcriptional inhibitor actinomycin D (0.5 ${\mu}g$/mL) revealed that copper treatment did not affect the half-life of FPN mRNAs in J774 cells. On the other hand, results from luciferase reporter assays showed that copper directly stimulated the promoter activity of FPN. In summary, our data showed copper induced FPN mRNA of macrophages via a transcriptional rather than post-transcriptional mechanisms.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.11
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• pp.857-861
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• 2012

FPN (fixed-pattern-noise) mainly comes from the device or pattern mismatches in pixel and color filter, pixel photodiode leakage in CMOS image sensor. In this paper, optical stack module related pixel FPN was investigated and the classification of pixel FPN contribution with the individual optical module process was presented. The methodology and procedure would be helpful in reducing the greater pixel FPN and distinguishing the complex FPN sources with respect to various noise factors.

• Nutrition Research and Practice
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• v.3 no.3
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• pp.192-199
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• 2009

Cadmium intoxication has been associated with the dysregulation of iron homeostasis. In the present study, we investigated the effect of cadmium on the expression of ferroportin 1 (FPN1), an important iron transporter protein that is involved in iron release from macrophages. When we incubated cadmium with J774 mouse macrophage cells, FPN1 mRNA levels were significantly increased in a dose- and time-dependent manner. Furthermore, the cadmium-induced FPN1 mRNA expression was associated with increased levels of FPN1 protein. On the other hand, cadmium-mediated FPN1 mRNA induction in J774 cells was completely blocked when cells were co-treated with a transcription inhibitor, acitomycin D. Also, cadmium directly stimulated the activity of the FPN1-promoter driven luciferase reporter, suggesting that the cadmium up-regulates FPN1 gene expression in a transcription-dependent manner. Finally, cadmium exposure to J774 macrophages increased intracellular reactive oxygen species (ROS) levels by ${\sim}2$-fold, compared to untreated controls. When J774 cells were co-treated with antioxidant N-acetylcystein, the cadmium-induced FPN1 mRNA induction was significantly attenuated. In summary, the results of this study clearly demonstrated that cadmium increased FPN1 expression in macrophages through a mechanism that involves ROS production, and suggests another important interaction between iron and cadmium metabolism.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.7
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• pp.677-687
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• 1992

This paper presents a Fuzzy Pertri Net(FPN)model, which can be used to verify the validity and effectiveness of nervous system bebaviors. The similarities and differences between communication network and neural network are analyzed with respect to the representation and verification of the system behaviors. For the effective representation for the ambiguities of nervous system we combein fuzzy set theory to the PetriNet, and then design a new model, FPN, Also show that FPN is superior to the multiplayer perceptron model using computer simulation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.92-101
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• 1996

This paper presents a new mehtod with which we can improve the efficiency (both of speed and precision) of FPN$^{[1]}$. Our method makes use of the basic propositions smong the conditional propositions of a goal proposition. The basic propositions are represented as ource vertices on an FPN. Therefore, we introduce an efficient algebraic algorithm which finds source vertices of FPN.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1311-1314
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• 2022

DNN을 사용하여 객체 인식 과정에서 객체를 잘 분류하기 위해서는 시각적 설명성이 요구된다. 시각적 설명성은 object class에 대한 예측을 pixel-wise attribution으로 표현해 예측 근거를 해석하기 위해 제안되었다, Scale-invariant한 특징을 제공하도록 설계된 pyramidal features 기반 backbone 구조는 object detection 및 classification 등에서 널리 쓰이고 있으며, 이러한 특징을 갖는 feature pyramid를 trainable attention mechanism에 적용하고자 할 때 계산량 및 메모리의 복잡도가 증가하는 문제가 있다. 본 논문에서는 일반적인 FPN에서 객체 인식 성능과 설명성을 높이기 위한 피라미드-주의집중 계층네트워크 (FPN-Attention Layered Network) 방식을 제안하고, 실험적으로 그 특성을 평가하고자 한다. 기존의 FPN만을 사용하였을 때 객체 인식 과정에서 설명성을 향상시키는 방식이 객체 인식에 미치는 정도를 정량적으로 평가하였다. 제안된 모델의 적용을 통해 낮은 computing 오버헤드 수준에서 multi-level feature를 고려한 시각적 설명성을 개선시켜, 결괴적으로 객체 인식 성능을 향상 시킬 수 있음을 실험적으로 확인할 수 있었다.

• Korean Journal of Food Science and Technology
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• v.31 no.2
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• pp.527-534
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• 1999

This study was carried out to investigate the effects of pine needle extracts on lipid oxidation and free radical reaction in iron sources reacted with active oxygen species. The results were summarized as follow; the catalytic effects of active oxygen on lipid oxidation in oil emulsion tended to be showed $OH,\;H_2O_2\;and\;KO_2$ in order. At the same time, pine needle extracts itself were tended to be showed a little catalytic effects. Active oxygen scavenging ability of pine needle extracts didn't show, but pine needle extracts played role as a strong chelating agents to bind iron ion if $Fe^{2+}$ ion exist in oil emulsion. The content of $Fe^{2+}$ ion and total iron in CPNP were higher than those of HPNP and FPN. The content of ascorbic acid of FPN showed the highest (87.77 ppm) among several pine needle extracts. Electron donating ability of HPNP and CPNP were 81% and 78%, respectively, which were showed higher content than those of FPN. The SOD-like activity of HPNP showed 44.30%, compared to other pine needle extracts which means the most strong antioxidant reaction. The nitrite scavenging effects were tended to be different, depending on pH value as pH value was increased. Especially, they didn't show the nitrite scavenging effect in pH6.0.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.12-14
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• 2005

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks(SOFPNN) by means of genetically optimized fuzzy polynomial neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms(GAs). The conventional SOFPNNs hinges on an extended Group Method of Data Handling(GMDH) and exploits a fixed fuzzy inference type in each FPN of the SOFPNN as well as considers a fixed number of input nodes located in each layer. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, a collection of the specific subset of input variables, and the number of membership function) and addresses specific aspects of parametric optimization. Therefore, the proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series).

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.411-427
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• 2022

Digging historical and cultural information from seals in ancient books is of great significance. However, ancient Chinese seal samples are scarce and carving methods are diverse, and traditional digital image processing methods based on greyscale have difficulty achieving superior segmentation and recognition performance. Recently, some deep learning algorithms have been proposed to address this problem; however, current neural networks are difficult to train owing to the lack of datasets. To solve the afore-mentioned problems, we proposed an SEL-RefineMask which combines selector of feature pyramid network (SEL-FPN) with RefineMask to segment and recognize seals. We designed an SEL-FPN to intelligently select a specific layer which represents different scales in the FPN and reduces the number of anchor frames. We performed experiments on some instance segmentation networks as the baseline method, and the top-1 segmentation result of 64.93% is 5.73% higher than that of humans. The top-1 result of the SEL-RefineMask network reached 67.96% which surpassed the baseline results. After segmentation, a vision transformer was used to recognize the segmentation output, and the accuracy reached 91%. Furthermore, a dataset of seals in ancient Chinese books (SACB) for segmentation and small seal font (SSF) for recognition were established which are publicly available on the website.