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Syringetin 3-O-β-D-glucoside


  • Brand : BIOFRON

  • Catalogue Number : AV-P11829

  • Specification : 98%

  • CAS number : 40039-49-4

  • Formula : C23H24O13

  • Molecular Weight : 508.43

  • PUBCHEM ID : 5321577

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Catalogue Number


Analysis Method






Molecular Weight



Yellow powder

Botanical Source

Structure Type












Soluble in Chloroform,Dichloromethane,Ethyl Acetate,DMSO,Acetone,etc.

Flash Point


Boiling Point

850.6ºC at 760 mmHg

Melting Point

250ºC (dec.)


InChl Key

WGK Germany


HS Code Reference


Personal Projective Equipment

Correct Usage

For Reference Standard and R&D, Not for Human Use Directly.

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provides coniferyl ferulate(CAS#:40039-49-4) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate

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We sent out survey questionnaire forms to the departments of each category in all 1535 institutions (602 cardiovascular, 793 general thoracic and 577 esophageal) nationwide in early April 2014. The response rates in each category by the end of December 2014 were 97.8, 96.0, and 96.9 %, respectively. This high response rate has been keep throughout recent survey, and more than 96 % response rate in all fields in 2013 survey has to be congratulated.


Thoracic and cardiovascular surgery in Japan during 2013 Annual report by The Japanese Association for Thoracic Surgery


Committee for Scientific Affairs, The Japanese Association for Thoracic Surgery,1 Munetaka Masuda,corresponding author2 Hiroyuki Kuwano,#3 Meinoshin Okumura,#4 Hirokuni Arai,5 Shunsuke Endo,6 Yuichiro Doki,7 Junjiro Kobayashi,8 Noboru Motomura,9 Hiroshi Nishida,10 Yoshikatsu Saiki,11 Fumihiro Tanaka,12 Kazuo Tanemoto,13 Yasushi Toh,14 and Hiroyasu Yokomise15

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Dynamic social media content, such as Twitter messages, can be used to examine individuals’ beliefs and perceptions. By analyzing Twitter messages, this study examines how Twitter users exchanged and recognized toponyms (city names) for different cities in the United States. The frequency and variety of city names found in their online conversations were used to identify the unique spatiotemporal patterns of “geographical awareness” for Twitter users. A new analytic method, Knowledge Discovery in Cyberspace for Geographical Awareness (KDCGA), is introduced to help identify the dynamic spatiotemporal patterns of geographic awareness among social media conversations. Twitter data were collected across 50 U.S. cities. Thousands of city names around the world were extracted from a large volume of Twitter messages (over 5 million tweets) by using the Twitter Application Programming Interface (APIs) and Python language computer programs. The percentages of distant city names (cities located in distant states or other countries far away from the locations of Twitter users) were used to estimate the level of global geographical awareness for Twitter users in each U.S. city. A Global awareness index (GAI) was developed to quantify the level of geographical awareness of Twitter users from within the same city. Our findings are that: (1) the level of geographical awareness varies depending on when and where Twitter messages are posted, yet Twitter users from big cities are more aware of the names of international cities or distant US cities than users from mid-size cities; (2) Twitter users have an increased awareness of other city names far away from their home city during holiday seasons; and (3) Twitter users are more aware of nearby city names than distant city names, and more aware of big city names rather than small city names.


Do Global Cities Enable Global Views? Using Twitter to Quantify the Level of Geographical Awareness of U.S. Cities


Su Yeon Han, 1 , 2 Ming-Hsiang Tsou, 1 ,* and Keith C. Clarke 2

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Pneumonia is a serious disease associated with mortality among patients with dementia. However, the reported frequency of pneumonia as a cause of death in patients with dementia varies, the reason for which has not been fully elucidated.

We conducted a systematic search in PubMed and the Cochrane Database of Systematic Reviews (inception to December 2016). Two authors independently determined the suitability of studies and potential bias and extracted the data. The primary outcome was frequency of pneumonia-associated death in patients with dementia. Stratified subgroup analysis was conducted among studies grouped according to type of mortality cause (immediate or underlying), information source of mortality cause (autopsy or death certificate), and study setting (clinic, hospital, or nursing home).

We included 7 studies reporting the cause of death among patients with dementia and 12 studies comparing the cause of death among patients with and without dementia. The frequency of pneumonia-associated death among 19 eligible studies was 29.69% (95% confidence interval [CI], 25.86-33.53). Those frequencies differed according to whether the source for information about cause of death was an autopsy confirmation (49.98%; 95% CI, 43.75-56.71) or death certificate (19.65%; 95% CI, 15.48-23.83) and according to whether the type of mortality cause was an indirect cause of death (13.96%; 95% CI, 9.42-18.51) or direct cause of death (44.45%; 95% CI, 29.81-50.10). The risk of pneumonia-associated death in patients with dementia was twice as high as among those without dementia (odds ratio, 2.15; 95% CI, 1.63-2.83; p < 0.001). Conclusion The various frequencies of pneumonia-associated death in patients with dementia were associated with the information source, type of mortality cause, and study setting. Patients with dementia in the terminal stages urgently require careful clinical management of pneumonia, to maximize patient life expectancy and quality.


Pneumonia-associated death in patients with dementia: A systematic review and meta-analysis


Toshie Manabe, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review & editing,1,* Yuji Fujikura, Data curation, Investigation, Methodology, Writing - review & editing,2,3 Katsuyoshi Mizukami, Investigation, Writing - review & editing,4,5 Hiroyasu Akatsu, Investigation, Writing - review & editing,6,7 and Koichiro Kudo, Funding acquisition, Investigation, Supervision, Writing - review & editing8,9 Maw Pin Tan, Editor

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