• Journal of Ginseng Research
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• v.47 no.2
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• pp.274-282
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• 2023

Background: Ginsenoside compound K (CK) stimulated activation of the PI3K-Akt signaling is one of the major mechanisms in promoting cell survival after stroke. However, the underlying mediators remain poorly understood. This study aimed to explore the docking protein of ginsenoside CK mediating the neuroprotective effects. Materials and methods: Molecular docking, surface plasmon resonance, and cellular thermal shift assay were performed to explore ginsenoside CK interacting proteins. Neuroscreen-1 cells and middle cerebral artery occlusion (MCAO) model in rats were utilized as in-vitro and in-vivo models. Results: Ginsenoside CK interacted with recombinant human PTP1B protein and impaired its tyrosine phosphatase activity. Pathway and process enrichment analysis confirmed the involvement of PTP1B and its interacting proteins in PI3K-Akt signaling pathway. PTP1B overexpression reduced the tyrosine phosphorylation of insulin receptor substrate 1 (IRS1) after oxygen-glucose deprivation/reoxygenation (OGD/R) in neuroscreen-1 cells. These regulations were confirmed in the ipsilateral ischemic hemisphere of the rat brains after MCAO/R. Ginsenoside CK treatment reversed these alterations and attenuated neuronal apoptosis. Conclusion: Ginsenoside CK binds to PTP1B with a high affinity and inhibits PTP1B-mediated IRS1 tyrosine dephosphorylation. This novel mechanism helps explain the role of ginsenoside CK in activating the neuronal protective PI3K-Akt signaling pathway after ischemia-reperfusion injury.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.520-520
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• 2023

제주도 동부 중산간 지역은 화산암으로 구성된 지하지질로 인해 지하수위의 변동폭이 크고 변동양상이 복잡하여 인공신경망(Artificial Neural Network, ANN) 모델 등을 활용한 지하수위의 예측이 어렵다. ANN에 적용되는 활성화함수에 따라 지하수의 예측성능은 달라질 수 있으므로 활성화함수의 비교분석 후 적절한 활성화함수의 사용이 반드시 필요하다. 본 연구에서는 5개 활성화함수(sigmoid, hyperbolic tangent(tanh), Rectified Linear Unit(ReLU), Leaky Rectified Linear Unit(Leaky ReLU), Exponential Linear Unit(ELU))를 제주도 동부 중산간지역에 위치한 2개 지하수 관정에 대해 비교분석하여 최적 활성화함수 도출을 목표로 한다. 또한 최적 활성화함수를 활용한 ANN의 적용성을 평가하기 위해 최근 널리 사용되고 있는 순환신경망 모델인 Long Short-Term Memory(LSTM) 모델과 비교분석 하였다. 그 결과, 2개 관정 중 지하수위 변동폭이 상대적으로 큰 관정은 ELU 함수, 상대적으로 작은 관정은 Leaky ReLU 함수가 지하수위 예측에 적절하였다. 예측성능이 가장 낮은 활성화함수는 sigmoid 함수로 나타나 첨두 및 최저 지하수위 예측 시 사용을 지양해야 할 것으로 판단된다. 도출된 최적 활성화함수를 사용한 ANN-ELU 모델 및 ANN-Leaky ReLU 모델을 LSTM 모델과 비교분석한 결과 대등한 지하수위 예측성능을 나타내었다. 이것은 feed-forward 방식인 ANN 모델을 사용하더라도 적절한 활성화함수를 사용하면 최신 순환신경망과 대등한 결과를 도출하여 활용 가능성이 충분히 있다는 것을 의미한다. 마지막으로 LSTM 모델은 가장 적절한 예측성능을 나타내어 다양한 인공지능 모델의 예측성능 비교를 위한 기준이 되는 참고모델로 활용 가능하다. 본 연구에서 제시한 방법은 지하수위 예측과 더불어 하천수위 예측 등 다양한 시계열예측 및 분석연구에 유용하게 사용될 수 있다.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.277-285
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• 2023

In this study, pneumonia identification networks with the small number of layers were constructed by using chest X-ray images. The networks had similar trainable-parameters, and the performance of the trained models was quantitatively evaluated with the modification of the network architectures. A total of 6 networks were constructed: convolutional neural network (CNN), VGGNet, GoogleNet, residual network with identity blocks, ResNet with bottleneck blocks and ResNet with identity and bottleneck blocks. Trainable parameters for the 6 networks were set in a range of 273,921-294,817 by adjusting the output channels of convolution layers. The network training was implemented with binary cross entropy (BCE) loss function, sigmoid activation function, adaptive moment estimation (Adam) optimizer and 100 epochs. The performance of the trained models was evaluated in terms of training time, accuracy, precision, recall, specificity and F1-score. The results showed that the trained models with the small number of layers precisely detect pneumonia from chest X-ray images. In particular, the overall quantitative performance of the trained models based on the ResNets was above 0.9, and the performance levels were similar or superior to those based on the CNN, VGGNet and GoogleNet. Also, the residual blocks affected the performance of the trained models based on the ResNets. Therefore, in this study, we demonstrated that the object detection networks with the small number of layers are suitable for detecting pneumonia using chest X-ray images. And, the trained models based on the ResNets can be optimized by applying appropriate residual-blocks.

• The Journal of Internal Korean Medicine
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• v.43 no.6
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• pp.1089-1104
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• 2022

Objective: The aim of this study was to identify the efficacy and underlying mechanism of cloves as an osteoarthritis (OA) treatment in a monosodium iodoacetate (MIA)-induced rat OA model. Osteoarthritis (OA) is nowadays one of the most prevalent degenerative joint diseases. Methods: Sprague-Dawley rats treated with MIA (50 μL; 80 mg/mL) were used as in vivo OA models. Cloves (100 and 200 mg/kg b.w.) were administered orally once daily for 2 weeks from 7 days after MIA injection. Changes in hindpaw weight distribution (HWD) were measured as a joint discomfort index. Activation markers related to inflammatory responses and cartilage degeneration in the right knee joints were evaluated by serum analysis and western blotting. Results: HWD decreased in the MIA control group but showed a dose-dependent elevation after clove treatment. Clove treatment inhibited inflammatory factors by PI3K/Akt/NF-κB signaling pathways, while also activating antioxidant factors through Sirt1/AMPK signaling pathways. Clove treatment also suppressed matrix metalloproteinase (MMP) overexpression and significantly increased the levels of tissue inhibitors of metalloproteinases (TIMPs). Conclusions: Treatment with cloves effectively reversed MIA-induced effects. Therefore, clove treatment could have the potential to protect against or treat OA.

• Journal of the Korean Institute of Gas
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• v.27 no.1
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• pp.78-85
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• 2023

Fixed-bed reactor Computational Fluid Dynamics (CFD) simulation of methanol steam reforming reaction was performed using the intrinsic kinetic data of the copper-impregnated hydrotalcite catalyst. The activation energy of the copper hydrotalcite catalyst obtained from the previous study results was 97.4 kJ/mol, and the pre-exponential was 5.904 × 10¹⁰. Process simulation was performed using the calculated values and showed a similar tendency to the experimental results. And the conversion rate according to the change of the reaction temperature (200 - 450 ℃) and the molar ratio of methanol and water was observed using the intrinsic kinetic data. In addition, mass and heat transfer phenomena analysis of a commercial reactor (I.D. 0.05 - 0.1m, Length 1m) was predicted through axial 2D Symmetry simulation using the power law model of the above kinetic constants.

• Journal of Drive and Control
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• v.20 no.2
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• pp.15-23
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• 2023

In this study, two-dimensional location of crops for auto weeding was detected using deep learning. To construct a dataset for soybean detection, an image-capturing system was developed using a mono camera and single-board computer and the system was mounted on a weeding robot to collect soybean images. A dataset was constructed by extracting RoI (region of interest) from the raw image and each sample was labeled with soybean and the background for classification learning. The deep learning model consisted of four convolutional layers and was trained with a weakly supervised learning method that can provide object localization only using image-level labeling. Localization of the soybean area can be visualized via CAM and the two-dimensional position of the soybean was estimated by clustering the pixels associated with the soybean area and transforming the pixel coordinates to world coordinates. The actual position, which is determined manually as pixel coordinates in the image was evaluated and performances were 6.6(X-axis), 5.1(Y-axis) and 1.2(X-axis), 2.2(Y-axis) for MSE and RMSE about world coordinates, respectively. From the results, we confirmed that the center position of the soybean area derived through deep learning was sufficient for use in automatic weeding systems.

• The Journal of Korean Medicine
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• v.43 no.3
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• pp.1-15
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• 2022

Objectives: Myrrh have been used as a traditional remedy to treat infectious and inflammatory diseases. However, it is largely unknown whether myrrh ethanol extract could exhibit the inhibitory activities against particulate matter (PM)-induced skin injury on human keratinocytes, HaCaT cells. Therefore, this study was aimed to investigate the inhibitory activity of myrrh ethanol extract on PM-induced skin injury in HaCaT cells. Methods: To investigate the inhibitory effects of myrrh ethanol extract in HaCaT cells, the skin injury model of HaCaT cells was established under PM treatment. HaCaT keratinocyte cells were pre-treated with myrrh ethanol extract for 1 h, and then stimulated with PM. Then, the cells were harvested to measure the cell viability, reactive oxygen species (ROS), pro-inflammatory cytokines including interleukin (IL) 1-beta, IL-6, and tumor necrosis factor (TNF)-𝛼, hyaluronidase, collagen, MMPs. In addition, we examined the mitogen activated protein kinases (MAPKs) and inhibitory kappa B alpha (I𝜅-B𝛼) as inhibitory mechanisms of myrrh ethanol extract. Results: The treatment of myrrh ethanol extract inhibited the PM-induced cell death and ROS production in HaCaT cells. In addition, myrrh ethanol extract treatment inhibited the PM-induced elevation of IL-1beta, IL-6, and TNF-𝛼. Also, myrrh ethanol extract treatment inhibited the increase of hyaluronidase, MMP and decrease of collagen. Furthermore, myrrh ethanol extract treatment inhibited the activation of MAPKs and the degradation of I𝜅-B𝛼. Conclusions: Our result suggest that treatment of myrrh ethanol extract could inhibit the PM-induced skin injury via deactivation of MAPKs and nuclear factor (NF)-𝜅B in HaCaT cells. This study could suggest that myrrh ethanol extract could be a beneficial agent to prevent skin damage or inflammation.

• Journal of Electrochemical Science and Technology
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• v.13 no.2
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• pp.237-253
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• 2022

The methyl 2-(1,3-dithietan -2- ylidene)-3-oxobutanoate (MDYO) and 2-(1,3-dithietan-2-ylidene) cyclohexane -1,3-dione (DYCD) were synthesized and tested at various concentrations as corrosion inhibitors for 316L stainless steel in 1 M HCl using weight loss, electrochemical impedance spectroscopy (EIS), potentiodynamic polarization (PDP), surface analysis techniques (SEM / EDX and Raman spectroscopy) and Functional Density Theory (DFT) was also used to calculate quantum parameters. The obtained results indicated that the inhibition efficiency of MDYO and DYCD increases with their concentration, and the highest value of corrosion inhibition efficiency was determined in the range of concentrations investigated (0.01 × 10^-3 - 10^-3 M). Polarization curves (Tafel extrapolation) showed that both compounds act as mixed-type inhibitors in 1M HCl solutions. Electrochemical impedance spectra (Nyquist plots) are characterized by a capacitive loop observed at high frequencies, and another small inductive loop near low frequencies. The thermodynamic data of adsorption of the two compounds on the stainless steel surface and the activation energies were determined and then discussed. Analysis of experimental results shows that MDYO and DYCD inhibitors adsorb to the metal surface according to the Langmuir model and the mechanism of adsorption of both inhibitors involves physisorption. SEM-EDX results confirm the existence of an inhibitor protective film on the stainless steel surface. The results derived from theoretical calculations supported the experimental observation.

• Biomolecules & Therapeutics
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• v.31 no.4
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• pp.411-416
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• 2023

Methamphetamine (METH) is a powerful neurotoxic psychostimulant affecting dopamine transporter (DAT) activity and leading to continuous excess extracellular dopamine levels. Despite recent advances in the knowledge on neurobiological mechanisms underlying METH abuse, there are few effective pharmacotherapies to prevent METH abuse leading to brain damage and neuropsychiatric deficits. α-Pinene (APN) is one of the major monoterpenes derived from pine essential oils and has diverse biological properties including anti-nociceptive, anti-anxiolytic, antioxidant, and anti-inflammatory actions. In the present study, we investigated the therapeutic potential of APN in a METH abuse mice model. METH (1 mg/kg/day, i.p.) was injected into C57BL/6 mice for four alternative days, and a conditioned place preference (CPP) test was performed. The METH-administered group exhibited increased sensitivity to place preference and significantly decreased levels of dopamine-related markers such as dopamine 2 receptor (D2R) and tyrosine hydroxylase in the striatum of the mice. Moreover, METH caused apoptotic cell death by induction of inflammation and oxidative stress. Conversely, APN treatment (3 and 10 mg/kg, i.p.) significantly reduced METH-mediated place preference and restored the levels of D2R and tyrosine hydroxylase in the striatum. APN increased the anti-apoptotic Bcl-2 to pro-apoptotic Bax ratio and decreased the expression of inflammatory protein Iba-1. METH-induced lipid peroxidation was effectively mitigated by APN by up-regulation of antioxidant enzymes such as manganese-superoxide dismutase and glutamylcysteine synthase via activation of nuclear factor-erythroid 2-related factor 2. These results suggest that APN may have protective potential and be considered as a promising therapeutic agent for METH-induced drug addiction and neuronal damage.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.504-507
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• 2020

ReLU(Rectified Linear Unit) 함수는 제안된 이후로 대부분의 깊은 인공신경망 모델들에서 표준 활성함수로써 지배적으로 사용되었다. 이후에 ReLU 를 대체하기 위해 Leaky ReLU, Swish, Mish 활성함수가 제시되었는데, 이들은 영상 분류 과업에서 기존 ReLU 함수 보다 향상된 성능을 보였다. 따라서 초해상화(Super Resolution) 과업에서도 ReLU 를 다른 활성함수들로 대체하여 성능 향상을 얻을 수 있는지 실험해볼 필요성을 느꼈다. 본 연구에서는 초해상화 과업에서 안정적인 성능을 보이는 EDSR(Enhanced Deep Super-Resolution Network) 모델의 활성함수들을 변경하면서 성능을 비교하였다. 결과적으로 EDSR 의 활성함수를 변경하면서 진행한 실험에서 해상도를 2 배로 변환하는 경우, 기존 활성함수인 ReLU 가 실험에 사용된 다른 활성함수들 보다 비슷하거나 높은 성능을 보였다. 하지만 해상도를 4 배로 변환하는 경우에서는 Leaky ReLU 와 Swish 함수가 기존 ReLU 함수대비 다소 향상된 성능을 보임을 확인하였다. 구체적으로 Leaky ReLU 를 사용했을 때 기존 ReLU 보다 영상의 품질을 정량적으로 평가할 수 있는 PSNR 과 SSIM 평가지표가 평균 0.06%, 0.05%, Swish 를 사용했을 때는 평균 0.06%, 0.03%의 성능 향상을 확인할 수 있었다. 4 배의 해상도를 높이는 초해상화의 경우, Leaky ReLU 와 Swish 가 ReLU 대비 향상된 성능을 보였기 때문에 향후 연구에서는 다른 초해상화 모델에서도 성능 향상을 위해 활성함수를 Leaky ReLU 나 Swish 로 대체하는 비교실험을 수행하는 것도 필요하다고 판단된다.