• Title/Summary/Keyword: Liu yi san

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Anti-inflammatory Effect of Yukil-san Water Extract on LPS-induced RAW 264.7 Cells (LPS로 활성화된 RAW 264.7 cell에서 NF-𝜅B억제를 통한 육일산(六一散) 물추출물의 염증억제효과)

  • Lee, Chang Wook;Park, Sang Mi;Kim, Eun Ok;Byun, Sung Hui;Kim, Sang Chan
    • Herbal Formula Science
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    • v.30 no.2
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    • pp.45-57
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    • 2022
  • Objectives : Yukil-san (YIS, 六一散; Liu yi san) is composed of Talcum and Glycyrrhizae Radix, the name is said to be derived from the proportion of the two herbal components of the formula. The YIS originated from 'Formulas from the discussion illuminating the Yellow Emperor's Basic Question'(黃帝素問宣明論方; Huang di su wen xuan ming lun fang) written by Liu Wan-Su (劉完素). YIS could clear summerheat, resolve dampness, and augment the qi. This formula may be used to treat the common cold, influenza, acute gastroenteritis, cystitis, urethritis and bacillary dysentery. But, there is insufficient of study about the effects of YIS on the anti-inflammatory activities. The present study evaluated the anti-inflammatory effects of YIS on lipopolysaccharide (LPS)-activated RAW 264.7 cells. Methods : Cell viability was assessed by MTT assay and nitric oxide (NO) was evaluated by measuring the nitrite content in culture medium. Pro-inflammatory cytokines such as tumor necrosis factor-α, interleukin-1β and IL-6 were quantified by ELISA kit. The expression of proteins related with nuclear factor-κB (NF-κB) pathway and inducible NO synthase (iNOS) were assessed by western blot analysis. Results : YIS significantly inhibited the expression of iNOS increased by LPS, and thus significantly inhibited the production of NO. In addition, YIS significantly inhibited pro-inflammatory cytokines. In the regulation of inflammation, NF-κB pathway plays a crucial role. YIS inhibited the expression of p-IκBα and thus inhibited the translocation of NF-κB to the nucleus. Conclusions : These results suggest that YIS ameliorates inflammatory response in LPS-activated RAW 264.7 cells through the inhibition of inflammatory mediators, via suppression of the NF-κB pathway. Therefore, this study provides objective evidence for the anti-inflammatory effect of YIS including the underlying mechanisms.

A Heuristic Algorithm for the Reliability Optimization of a Distributed Communication Network

  • Hung, Chih-Young;Yang, Jia-Ren;Park, Dong-Ho;Liu, Yi-Hsin
    • International Journal of Reliability and Applications
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    • v.9 no.1
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    • pp.1-5
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    • 2008
  • A heuristic algorithm for reliability optimization of a distributed network system is developed so that the reliability of a large system can be determined efficiently. This heuristic bases on the determination of maximal reliability set of maximum node capacity, maximal link reliability and maximal node degree.

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A Study on Qian Yi(錢乙)'s Medical Though (전을(錢乙)의 의학사상(醫學思想)에 관(關)한 연구(硏究))

  • Oh, Jun Hwan;Kim, Ki Wook;Park, Hyun Kook
    • The Journal of Korean Medical History
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    • v.14 no.2
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    • pp.109-152
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    • 2001
  • Throughout this paper, I adjusted the study of 'Qian Yi'(錢乙)'s Medical Thought, and the following is the summary. 1. 'Qian Yi' wrote 'Xiao Er Yao Zheng Zhi Jue'("小兒藥證直訣", edited by 誾季忠), and there were 'Shang Han Lun Zhi Wei'("傷寒論指微"), 'Ying Ru Lun', however those are loss of the record. 2. Qian Yi's 'Zhi Jue'("直訣") was influenced by 'Lu Xin Jing', yet if we compare the quality of 'Sheng Li, Byeng Li, Bang Jae'(生理, 病理, 方劑), 'Lu Xin Jing' cannot be the foundation of 'Zhi Jue'. He took over 'Nei Jing, Shang Han Lun, Jin Gui Yao Lue, Shen Long Ben Cao Jing, Tai Ping Sheng Hui Fang'("內經", "傷寒論", "金?要略", "神膿本草經", "太平聖惠方") and put them together to the direct clinical experiences of pediatrics. 3. There is no reference regarding the difficulties of pediatric diagnosis and diseases in 'Huang Di Nei Jing'("黃帝內經") Before 'Bei Song'(北宋), regardless of the lack of data related to pediatric diseases, 'Qian Yi' established the pediatric system in 'Xiao Er Yao Zheng Zhi Jue' for the first time. 4. In his diagnosis of the pediatric diseases, he 'Si Zhen He Can'(四診合參), also considered in the eye exam seriously. In addition, he closely combined 'Wu Zang Bian Zheng'(五臟辨證), and diagnosis the pediatric diseases. 5. 'Wu Zang Bian Zheng', what Qian established method was based on 'Zheng Ti Guan'(整體觀) in 'Huang Di Nei Jing'. It was based on clinical experiences and established the perspectives of 'Tian Ren Xiang Ying'(天人相應). First of all, he pinpointed 'Zhu Zheng'(主證) clearly. Secondly, he pinpointed the relationships to symptoms and then, he distinguished a generic character of 'Xu, Shi, Han, Re'(虛, 實, 寒, 熱). Finally, he made an induction from genealogical pediatric physiology. 6. 'Qian Yi' took a serious view of 'Ban Zhen'(斑疹), the inadequate field in those days. At that time, he criticized on the habituation of the misuse of medication. He treated separately which 'Ji Jing'(急驚) as 'Liang Xie'(凉瀉) and 'Man Jing'(慢驚) as 'Wen Bu'(溫補). He proposed 'Cong Gan Zhu Feng, Xin Zhu Jing'(從肝主風, 心主驚) theory and formulated 'Jing Feng'(驚風) theory as well. 7. As an opponent of a tendency to misusage of medicine, 'Qian Yi' made out a prescription with pliant medicine. He emphasized on the treatment to 'Gong Bu Shang Zheng, Bu Bu Zhi Xie, Xiao Bu Jian Shi'(攻不傷正, 補不滯邪, 消補兼施) because he had so lucid demonstration to 'Xu Shi Han Re'(虛實寒熱) of the five viscera in the field of 'Bang Yak'(方藥). 8. There were no pediatrics schools at that time, however, the pediatrics was being made up gradually by 'Jin Yuan Si Da Jia'(金元四大家) who was influenced by 'Qian Yi'. He raised an objection to medical treatment using pliant medicine. 'Qian Yi' applied 'Qu Xia'(驅下) treatment using 'Han Liang'(寒凉) medicine. 'Han Liang Pai'(寒凉派) is greatly influenced by Qian. 'Chen Wen Zhong'(陳文中) had a great impact on 'Han Liang Pai' who used a 'Zao Shu Wen Bu'(燥熟溫補) medicine for treatment. Since 'Song Jin'(宋金), he had a tremendous influence on pediatrics treating patients in both 'Han Wen'(寒溫) ways. 9. 'Qian Yi' had an influence on his medical thoughts on future generations, especially to 'Wan Quan'(萬全) of 'Ming Dai', 'Wu Tang'(吳塘) of 'Qing Dai'(淸代) and 'Yun Shu Jie'(?樹珏) of 'Min Guo'(民國). 'Wan Quan' is an advocate of 'You Yu, Bu Zu Zhi Shuo'(有餘, 不足之說)of 'Xiao Er Wu Zang'(小兒五臟) that he revealed Qian's 'Wu Zang Bian Zheng'(五臟辨證). 'Wu Tang' disclosed Qian's 'Xiao Er Ti Zhi Shuo'(小兒體質說) and 'Xiao Er Ke'(小兒科)'s 'Yong Yao Lun'(用藥論), therefore, he uncovered pediatric physiological characteristics through the advocate of Qian's 'Zang Fu Rou Ruo, Ji Gu Nen Qie, Yi Xu Yi Shi, Yi Han Yi Re' (臟腑柔弱, 肌骨嫩怯, 易虛易實, 易寒易熱). 'Yun Shu Jie' developed intrinsic relationships among time, symptom and 'Tian Ren Xiang Ying Guan'(天人相應觀), What 'Qian Yi' stated about them. And also, he developed Qian's 'Di Huang Wan'(地黃丸), 'Xie Qing Wan'(瀉靑丸), 'Yi Huang San'(益黃散) clinical usages as well. 10. Regarding Qian's 'Wu Zang Xu Shi'(五臟虛實), it has an influence on 'Zhang Yuan Su'(張元素)'s 'Zang Fu Bing Ji Bian Zheng'(臟腑病機辨證). 'Di Huang Wan', 'Xie Qing Wan', 'Xie Xin Tang'(瀉心湯), 'Yi Huang San', 'Xie Huang San'(瀉黃散) are the standard prescription of 'Wu Zang Bu Xie'(五臟補瀉). It is under the influence of Qian's treatment. Besides, 'Qian Yi' took a serious view of 'Xiao Er'(小兒)'s 'Pi Wei'(脾胃). 'Qian Yi' had an impact on 'Li Dong Yuan'(李東垣) one of the member of 'Bu Tu Pai'(補土派). 'Di Huang Wan', which placed great importance on 'Bu Yi Shen Yin'(補益腎陰), had a great impact on 'Da Bu Yin Wan'(大補陰丸) and 'Jin Yuan Si Da Jia' as well. 11. In a theory of Qian's 'Wu Zang Bian Zheng', though it had been stated clearly in 'Wu Zang Bian Zheng', but he neglected in 'Liu Fu Bian Zheng'(六腑辨證). In prescription field, The problem with the medicine is that it is either toxic or mineral, therefore, we are not able to use those medicine in a clinical testing at the present time.

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Treatment of fever with traditional Chinese medicine according to Zheng on cancer patients (based on case reports)

  • Liu, Lan-Ying;Cao, Peng;Cai, Xue-Ting;Wang, Xiao-Ning;Huo, Jie-Ge;Zhou, Zhong-Ying
    • CELLMED
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    • v.2 no.2
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    • pp.16.1-16.5
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    • 2012
  • Fever in cancer patients is often due to the following causes: evil qi and toxity stagnancy, disorders of qi and blood, deficiencies of zang and fu organs, and the disorder of yin and yang. The treatments given to cancer patients with a fever are according to five: (a) Excessive inner heat and toxicants: remove heat and the toxicant, induce purgation. We use Cheng-Qi-Tang plus Qing-Wen-Bai-Du-Yin. (b) Tangle of damp and heat, and qi stagnancy: remove damp and heat, smooth the qi channel. We use Gan-Lu-Xiao-Du-Dan or San-Ren-Tang. (c) Obvious blood and heat stagnancy: remove heat and blood stasis. We use Xue-Fu- Zhu-Yu-Tang. (d) Deficiency of spleen qi, inner heat caused by a yin deficiency: nourish spleen qi and yin to remove the inner heat. We use Bu-Zhong-Yi-Qi-Tang or Xiao-Jian-Zhong-Tang. (e) Prominent yin deficiency and hectic fever: replenish yin and remove inner heat. We use Qing-Hao-Bie-Jia-Tang or Chai- Qian-Mei-Lian-San. The pathogenesis of fever in cancer patients is complicated. We can see both deficiency and excess in one differentiation. Therefore, we must make sure of it, then we can get the most effective treatment.

Evaluation of a multi-stage convolutional neural network-based fully automated landmark identification system using cone-beam computed tomography-synthesized posteroanterior cephalometric images

  • Kim, Min-Jung;Liu, Yi;Oh, Song Hee;Ahn, Hyo-Won;Kim, Seong-Hun;Nelson, Gerald
    • The korean journal of orthodontics
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    • v.51 no.2
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    • pp.77-85
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    • 2021
  • Objective: To evaluate the accuracy of a multi-stage convolutional neural network (CNN) model-based automated identification system for posteroanterior (PA) cephalometric landmarks. Methods: The multi-stage CNN model was implemented with a personal computer. A total of 430 PA-cephalograms synthesized from cone-beam computed tomography scans (CBCT-PA) were selected as samples. Twenty-three landmarks used for Tweemac analysis were manually identified on all CBCT-PA images by a single examiner. Intra-examiner reproducibility was confirmed by repeating the identification on 85 randomly selected images, which were subsequently set as test data, with a two-week interval before training. For initial learning stage of the multi-stage CNN model, the data from 345 of 430 CBCT-PA images were used, after which the multi-stage CNN model was tested with previous 85 images. The first manual identification on these 85 images was set as a truth ground. The mean radial error (MRE) and successful detection rate (SDR) were calculated to evaluate the errors in manual identification and artificial intelligence (AI) prediction. Results: The AI showed an average MRE of 2.23 ± 2.02 mm with an SDR of 60.88% for errors of 2 mm or lower. However, in a comparison of the repetitive task, the AI predicted landmarks at the same position, while the MRE for the repeated manual identification was 1.31 ± 0.94 mm. Conclusions: Automated identification for CBCT-synthesized PA cephalometric landmarks did not sufficiently achieve the clinically favorable error range of less than 2 mm. However, AI landmark identification on PA cephalograms showed better consistency than manual identification.