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A Study on the Effects of Sirtuin 1 on Dendritic Outgrowth and Spine Formation and Mechanism in Neuronal Cells (신경세포에서 sirtuin 1이 수상돌기 성장과 가시형성에 미치는 영향 및 기전에 관한 연구)

  • Seo, Mi Kyoung;Kim, Hye Kyeong;Baek, Song Young;Lee, Jung Goo;Urm, Sang-Hwa;Park, Sung Woo;Seog, Dae-Hyun
    • Journal of Life Science
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    • v.31 no.9
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    • pp.806-817
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    • 2021
  • Increasing evidence suggests that depression is associated with impairments in neural plasticity. Sirtuin 1 plays an important role in neural plasticity, and the activation of mechanistic target of rapamycin complex 1 (mTORC1) signaling is known to improve neural plasticity. In this study, we aimed to determine whether sirtuin 1 affects dendrite outgrowth and spine formation through mTORC1 signaling. Resveratrol (sirtuin 1 activator; 1 and 10 μM) and sirtinol (sirtuin 1 inhibitor; 1 and 10 μM) were treated in primary cortical culture with and without dexamethasone (500 μM). Levels of sirtuin 1, phospho-extracellular signal regulated protein kinase 1/2 (ERK1/2), phospho-mTORC1, and phospho-p70 ribosomal protein S6 kinase (p70S6K) were evaluated using Western blot analysis. Dendritic outgrowth and spine density were assessed using immunostaining. Resveratrol significantly increased levels of sirtuin 1 expression and phosphorylation of ERK1/2 (a downstream target of sirtuin 1), mTORC1, and p70S6K (a downstream target of mTORC1) in a concentration-dependent manner under dexamethasone conditions. Resveratrol also significantly increased dendritic outgrowth and spine density. Conversely, sirtinol significantly decreased levels of sirtuin 1 expression and phosphorylation of ERK1/2, mTORC1, and p70S6K in a concentration-dependent manner under normal conditions. Moreover, sirtinol significantly decreased dendritic outgrowth and spine density. Consistent with the results of sirtinol, sirtuin 1 knockdown using sirtuin 1 siRNA transfection significantly decreased dendritic outgrowth and spine density as well as phosphorylation levels of ERK1/2 and mTORC1. These data suggest that sirtuin 1 enhances dendritic outgrowth and spine density by activating mTORC1 signaling.

Evaluation of Image Quality using SE-EPI and SSH-TSE Techniques in MRDWI (자기공명확산강조영상에서 SE-EPI 와 SSH-TSE 기법을 이용한 영상의 질 평가)

  • Goo, Eun-Hoe
    • Journal of the Korean Society of Radiology
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    • v.15 no.7
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    • pp.991-998
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    • 2021
  • The purpose of this study is to investigate the image quality of the SE-EPI and SSH-TSE technique for MR DWI. Datum were analyzed for 35 PACS transmission datum(Normal part: 12 males, 13 females, Cerebral Infarction: 10(5males and 5females), and average age 68±7.32), randomly selected patients who underwent MRDWI tests. The equipment used was Ingenia CX 3.0T, SSH_TSE and SE-EPI pulse sequence and 32 Ch. head coil were used for data acquisition. Image evaluation was performed on the paired t-test and Wilcoxon tests, and was considered significant when the p value was 0.05 or less. As a result of quantitative analysis of SNR for DWI images, the mean and standard deviation values of 4 parts (WM, GM, BG, Cerebellum) in ADC (s/mm2), Diffusion b=0, 1000 images were higher in SE-EPI techniques(ADC: 120.50 ± 40, b=0: 54.50 ± 35.91, b=1000: 91.61 ± 36.63) than in SSH-TSE techniques(ADC: 99.69 ± 31.10, b=0: 43.52 ± 25.00 , b=1000: 60.74 ± 24.85)(p<0.05). The CNR values for GM-WM, BG-WM sites were also higher in SE-EPI technique (ADC: 116.08 ± 43.30, b=0:27.23 ± 09.10, b=1000: 78.50 ± 16.56) than in SSH-TSE(ADC: 101.08 ± 36.81, b=0: 23.96 ± 07.79 , b=1000: 74.30 ± 14.22). As a visual evaluation of observers, ghost artifact, magnetic susceptibility artifacts and overall image quality for SE-TSE and SSH-TSE all yielded high results from SSH-TSE techniques(ADC:3.6 ± 0.1, 2.8 ± 0.2, b=0: 4.3 ± 0.3, 3.4 ± 0.1 b=1000: 4.3 ± 0.2, 3.5 ± 0.2, p=0.000). In conclusion, the SE-EPI technique obtained an superiority in SNR and CNR measurements using SSH-TSE, SE-EPI. In the qualitative analysis, the SSH-TSE pulse sequence was obtained a high result according to the pulse sequence characteristics.

Changes in Greenhouse Temperature and Solar Radiation by Fogging and Shading During Hydroponics in Summer Season (여름철 수경재배 시 포그 분무와 차광에 의한 하우스 내부 온도 및 광 환경 변화)

  • Lim, Mi Young;Jeong, Ho Jeong;Roh, Mi Young;Choi, Gyeong Lee;Kim, So Hui;Choi, Su Hyun
    • Journal of Bio-Environment Control
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    • v.30 no.3
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    • pp.230-236
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    • 2021
  • Changes in greenhouse temperature and solar radiation due to fogging and shading were monitored during hydroponics in high temperature in summer season. Experiment 1 consists of four treatments, namely, Control, Shading, Fogging, and Fogging + Shading based on sunny days August. For Experiment 2, two melon cultivars of 'Dalgona' and 'Sopoong gaza' were cultivated in summer of 2020 using Fogging + Shading with the best result for temperature reduction effect from Experiment 1. As a result of Experiment 1, the effect of Fogging + Shading on temperature reduction was apparent where the inside was about 4℃ (as the lowest temperature) lower than the outside. Fogging + Shading showed the inside was 2-4℃ lower than the outside, and Fogging or Shading treatments had little difference, compared to the Control where the internal temperature of greenhouse was 3-4℃ higher than the external. For solar radiation changes between greenhouse inside and outside, the internal change was in a similar pattern between Fogging and Control, and between Shading and Fogging + Shading, respectively. In case of the Fogging treatment (similar with the Control) only the effect of solar radiation reduction as influenced by plastic greenhouse covering materials was examined. The Fogging + Shading had a very similar change in solar radiation to the Shading. Based on these results, Experiment 2 was conducted in summer of 2020 and resulted in a temperature reduction effect of about 3.9℃ according as the inside of air-conditioned greenhouse was kept 32.4℃ when the maximum temperature of the outside reached 36.3℃ in August during the cultivation period. In addition, the quality of melon fruit was good (1.3-1.5 kg of fruit weight, 12.6-13.3 of soluble solids content. In the case of using Fogging + Shading cooling treatment, it can bring about the effect of reducing the temperature during the high temperature in summer, and normal growth of melon and fruit harvesting were possible.

Host-Based Intrusion Detection Model Using Few-Shot Learning (Few-Shot Learning을 사용한 호스트 기반 침입 탐지 모델)

  • Park, DaeKyeong;Shin, DongIl;Shin, DongKyoo;Kim, Sangsoo
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.7
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    • pp.271-278
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    • 2021
  • As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

Effects of Myopia Alleviation Lenses in accordance with Parents' Refractive Errors (부모의 굴절이상에 따른 근시완화렌즈 효과)

  • Cho, Yoon Chul;Kang, JoongGu;Leem, Hyun Sung
    • The Korean Journal of Vision Science
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    • v.20 no.4
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    • pp.569-577
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    • 2018
  • Purpose : The study looked at how effective each group wearing MyoVison lens, MC lens, and Single Vision lensdepending on their parents' myopia condition. Methods : The study observed the changeof spherical equivalent among customers, who visited between January 2010 and December 2016,of an optical shop in Incheon Metropolitan City. And we observed MyoVision 152 eyes, MC Lens 86 eyes and Single Vision lens 270 eyes. This study was conducted using SPSS ver18, which analyzes the changes in average values of MyoVision, MC Lens, and Single Vision for a year.In each group, the differences in the group were compared using the Paired T-test and then one-way ANOVA (post-hoc; Bonferroni) Results : Group-to-group comparisons showed that MyoVision and MC Lens have a shorterinhibition than Single Vision. In particular, MyoVisionand MC Lens showed different relief effects depending on the degree of refraction of parents.When both parents had normal refractive, the change between MyoVision and Single Vision lens was $-0.35{\pm}0.05D$. When the father had a refraction MC lens were $-0.36{\pm}0.14D$ more effective than Single Vision. When only the mother had refraction, the mean value between MyoVision and Single Vision lens was $-0.37{\pm}0.06D$, and the mean between MC lens and Single Vision lens was $-0.38{\pm}0.08D$. And when both parents had refraction problems, the mean value change between MyoVision and Single Vision lens was $-0.28{\pm}0.07D$, and $-0.31{\pm}0.07D$, respectively. Conclusion : MyoVision and MC Lens appeared to have no effect on the functions of mitigating myopia in within group comparisons, but MyoVision and MC Lens showed reducing myopia than Single Vision in between group.

What Is a Monster Narrative? Seven Fragments on the Relationship between a Monster Narrative and a Catastrophic Narrative (괴물서사란 무엇인가? - 괴물서사에서 파국서사로 나아가기 위한 일곱 개의 단편 -)

  • Moon, Hyong-jun
    • Cross-Cultural Studies
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    • v.50
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    • pp.31-51
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    • 2018
  • The concept of 'monsters' have become popular, again, in recent times. A number of 'monster narratives' that discuss monsters such as zombies, humanoids, viruses, extraterrestrials, and serial killers have been made and re-made in popular media. Noting such an interesting cultural context, this article attempts, first, to find out some essential prototypical elements of a monster narrative and, second, to relate it with a catastrophic narrative. Correspondingly, the word 'monster' has been used as a conceptual prototype category that denies universal and clear definition, which makes it as one of the most widely used and familiar subjects of the use of metaphor. The prototypical meanings of various monster figures can be converged on a certain creature of being in this way held out as bizarre, curious, and abnormal. The monster figure that surpasses existing normality is also connected to 'abjection,' such as something that is cast aside from the body such as the bodily functions seen in its associated blood, tears, vomit, excrement, or semen, and so on. Nevertheless, both the monster figure and abjection produce disgust and horror in the minds of ordinary spectators or readers of media using this metaphor to heighten excitement for the viewers. The abject characteristic of the monster figure also has something in common with the posthuman figure, meaning to apply to a category of inhuman others who are held outside of the normal category of human beings. In the similar vein, it is natural that the most typical monster figures in our times are posthuman creatures embodied in such forms as seen with zombies, humanoids, cyborgs, robots, and so on. In short, the monster figure includes all of the creatures and beings that disarray normalized humanist categories and values. The monster narrative, in the same sense, is a type of story that tells about others outside modern, anthropocentric, male-centered, and Westernized categories of thought. It can be argued that a catastrophic narrative, a literary genre which depicts the world where a series of catastrophic events demolish the existing human civilization, ought to be seen as a typical modern-day monster narrative, because it also discounts and criticizes normalized humanist categories and values as is the result of the monster narrative. Going beyond the prevailing humanist realist narrative that are so familiar with existing values, the catastrophic narrative is not only a monster narrative per se, but also a monstrous narrative which disrupts and reinvents currently mainstream narratives and ways of thinking.

Genetic Variation of Parental Inbred Lines for Korean Waxy Corn Hybrid Varieties revealed by SSR markers (우리나라 찰옥수수 품종들의 교배친 자식계통들에 대한 유전적 변이성)

  • Park, Jun-Sung;Sa, Kyu-Jin;Park, Ki Jin;Jang, Jin-Sun;Lee, Ju Kyong
    • Korean Journal of Breeding Science
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    • v.41 no.2
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    • pp.106-114
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    • 2009
  • In maize, knowledge of genetic diversity and genetic relationships among elite inbred lines is an significant impact on the selection of parental lines for hybrid varieties. Genetic diversity and genetic relationships among 11 parental inbred lines of Korean waxy and normal corn varieties were analyzed using 50 SSR markers distributed over the whole genome. A total of 171 allele bands were detected with an average of 3.4 alleles per locus. Number of allele bands per locus ranged from two to six and gene diversity varied from 0.165 to 0.900 with an average of 0.596 depending on the SSR loci. The cluster tree recognized three major groups with 61.6% genetic similarity. Group I includes 7 inbred lines (KL103, HW1, HW4, HW6, HW7, HW8, HW9), with similarity coefficients of between 0.616 and 0.730. Group II includes 2 inbred lines (HF1, HF2), with similarity coefficients of 0.959. Group III includes 2 inbred lines (HW3, HW5), with similarity coefficients of 0.713. The present study indicates that the SSR markers chosen for this analysis are effective for the assessment of genetic diversity and genetic relationships among 11 parental inbred lines.

Development of Prediction Model for Capsaicinoids Content in Red-Pepper Powder Using Near-Infrared Spectroscopy - Particle Size Effect (근적외선 스펙트럼을 이용한 고춧가루의 캡사이신 함량 예측 모델 개발 - 입자의 영향)

  • Mo, Changyeun;Kang, Sukwon;Lee, Kangjin;Lim, Jong-Guk;Cho, Byoung-Kwan;Lee, Hyun-Dong
    • Food Engineering Progress
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    • v.15 no.1
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    • pp.48-55
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    • 2011
  • In this research, the near-infrared absorption from 1,100-2,300 nm was used to measure the content of capsaicinoids in the red-pepper powder by using the Acousto-optic tunable filters (AOTF) spectrometer with sample plate and sample rotating unit. Non-spicy red-pepper samples from one location (Younggwang-gun. Korea) were mixed with spicy one (var. Chungyang) to make samples separated by particle size (below 0.425 mm, 0.425-0.71 mm, and 0.71- 1.4 mm). The Partial Least Squares Regression (PLSR) model to predict the capsaicinoid content on particle sizes was developed with measured spectra by AOTF spectrometer and used to analyze the amount of capsaicinoids by HPLC. The PLSR Model of red-pepper powder of below 0.425 mm, 0.425-0.71 mm, and 0.71-1.4 mm with cross validation had ${R_V}^2$ = 0.948-0.979 and Standard Error of Prediction (SEP) = 6.56-7.94 mg%. The prediction error of smaller particle size of red-pepper powder was low. The best PLSR model was found in pretreatment of Range Normalization, Standard Normal Variate, and 1st Derivatives of red-pepper powder of below 1.4 mm with cross validation, having ${R_V}^2$ = 0.959 and SEP = 8.82 mg%.

Spectral Response of Red Lettuce with Zinc Uptake: Pot Experiment in Heavy Metal Contaminated Soil (아연섭취에 따른 적상추의 분광학적 반응: 중금속 오염토양에서의 반응실험)

  • Shin, Ji Hye;Yu, Jaehyung;Kim, Jieun;Koh, Sang-Mo;Lee, Bum Han
    • Economic and Environmental Geology
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    • v.52 no.2
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    • pp.129-139
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    • 2019
  • This study investigates the spectral response of red lettuce (Lactuca sativa var crispa L.) to Zn concentration. The control group and the experimental groups treated with 1 mM(ZnT1), 5 mM(ZnT2), 10 mM(ZnT3), 50 mM(ZnT4), and 100 mM(ZnT5) were prepared for a pot experiment. Then, Zn concentration and spectral reflectance were measured for the different levels of Zn concentration in red lettuce. The Zn concentration of the control group had the range of 134-181 mg/kg, which was within the normal range of Zn concentration in uncontaminated crops. However, Zn concentration in the experimental group gradually increased with an increase in concentration of Zn injection. The spectral reflectance of red lettuce showed high peak in the red band due to anthocyanin, high reflectance in the infrared band due to the scattering effect of the cell structure, and absorption features associated with water. As Zn concentration in red lettuce leaves increased, the reflectance increased in the green and red bands and the reflectance decreased in the infrared band. The correlation analysis between Zn concentration and spectral reflectance showed that the reflectance of 700-1300 nm had a significant negative correlation with Zn concentration. The spectral band is a wavelength region closely related to the cell structure in the leaf, indicating possible cell destruction of leaf structure due to increased Zn concentration. In particular, 700-800 nm reflectance of the infrared band showed the strongest correlation with the Zn concentration. This study could be used to investigate the heavy metal contamination in soil around mining and agriculture area by spectroscopically recognizing heavy metal pollution of plant.

Development of a Classification Method for Forest Vegetation on the Stand Level, Using KOMPSAT-3A Imagery and Land Coverage Map (KOMPSAT-3A 위성영상과 토지피복도를 활용한 산림식생의 임상 분류법 개발)

  • Song, Ji-Yong;Jeong, Jong-Chul;Lee, Peter Sang-Hoon
    • Korean Journal of Environment and Ecology
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    • v.32 no.6
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    • pp.686-697
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    • 2018
  • Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.