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Periplocin

$178

  • Brand : BIOFRON

  • Catalogue Number : BF-P4001

  • Specification : 98%(HPLC)

  • CAS number : 13137-64-9

  • Formula : C36H56O13

  • Molecular Weight : 696.825

  • PUBCHEM ID : 14463159

  • Volume : 25mg

In stock

Quantity
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Catalogue Number

BF-P4001

Analysis Method

HPLC,NMR,MS

Specification

98%(HPLC)

Storage

2-8°C

Molecular Weight

696.825

Appearance

White crystalline powder

Botanical Source

Periploca sepium

Structure Type

Others

Category

Standards;Natural Pytochemical;API

SMILES

CC1C(C(CC(O1)OC2CCC3(C4CCC5(C(CCC5(C4CCC3(C2)O)O)C6=CC(=O)OC6)C)C)OC)OC7C(C(C(C(O7)CO)O)O)O

Synonyms

Card-20(22)-enolide, 3-[(2,6-dideoxy-4-O-β-D-glucopyranosyl-β-D-ribo-hexopyranosyl)oxy]-5,14-dihydroxy-, (3β,5β)-/Glucoperiplocymarin/corchorusoside C/(3β,5β)-3-{[2,6-Dideoxy-4-O-(β-D-glucopyranosyl)-β-D-ribo-hexopyranosyl]oxy}-5,14-dihydroxycard-20(22)-enolide/(3β,5β)-3-{[2,6-Dideoxy-4-O-(β-D-glucopyranosyl)-β-D-ribo-hexopyranosyl]oxy}-5,14-dihydroxycard-20(22)-enolido(2-)/Periplogenin + D-cymarose + D-glucose [German]/periplocin/Periplogenin + D-cymarose + D-glucose/Periplocoside

IUPAC Name

3-[(3S,5S,8R,9S,10R,13R,14S,17R)-5,14-dihydroxy-3-[(2R,4S,5R,6R)-4-methoxy-6-methyl-5-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxyoxan-2-yl]oxy-10,13-dimethyl-2,3,4,6,7,8,9,11,12,15,16,17-dodecahydro-1H-cyclopenta[a]phenanthren-17-yl]-2H-furan-5-one

Applications

Density

1.4±0.1 g/cm3

Solubility

Methanol; Ethanol; Acetontrile

Flash Point

272.8±27.8 °C

Boiling Point

877.4±65.0 °C at 760 mmHg

Melting Point

205°C

InChl

InChI=1S/C36H56O13/c1-18-30(24(37)14-27(39)47-18)46-17-25-28(40)31(44-4)29(41)32(49-25)48-20-5-9-33(2)22-6-10-34(3)21(19-13-26(38)45-16-19)8-12-36(34,43)23(22)7-11-35(33,42)15-20/h13,18,20-25,27-32,37,39-43H,5-12,14-17H2,1-4H3/t18?,20-,21+,22?,23?,24?,25?,27-,28+,29?,30-,31?,32+,33+,34+,35-,36-/m0/s1

InChl Key

JVFYCULORCKYMD-WSSBEIOBSA-N

WGK Germany

RID/ADR

HS Code Reference

2938900000

Personal Projective Equipment

Correct Usage

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

Meta Tag

provides coniferyl ferulate(CAS#:13137-64-9) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate

PMID

27547279

Abstract

BACKGROUND:
In Iran, few studies have evaluated emergency medicine as a career option. In the present study, we aimed to find out how Iranian emergency-medicine specialists view their specialty as a career.

METHODS:
Following a qualitative study, a Likert-scale questionnaire was developed. Iranian emergency physician specialists who had at least two years’ job experience were contacted via email. A uniform link to a Web-based survey and a cover letter that explained the survey were sent to the recipients. We used the Kruskal-Wallis test and post hoc analysis to determine the differences between demographic subgroups.

RESULTS:
A total of 109 eligible responses were received, a response rate of 72.63%. Of the responders, 57.8% were 30-40 years of age, 86.2% were male, 86.2% were single, 84.4% were faculty members and 90.8% had fewer than 10 years’ job experience. The main problems occurring during the career of Iranian emergency physicians were: insufficient income, inadequate recognition of the specialty by the community, inadequate union support, insecurity in the emergency wards, overcrowding, job stresses and night shifts. Despite insufficiency of income, Iranian emergency physicians (EPs) did not care about the financial benefits of patient care. Academic activity had positive effects on the perspectives of Iranian emergency physicians regarding their careers.

CONCLUSION:
Iranian emergency physicians and leaders in emergency medicine should struggle to improve the present situation, aiming at an ideal state.

KEYWORDS

Emergency medicine, Career, Survey

Title

Emergency medicine as a growing career in Iran: an Internet-based survey

Author

Shervin Farahmand,1 Ehsan Karimialavijeh,2 Hojjat Sheikh Mottahar Vahedi,2 and Amirhossein Jahanshir2

Publish date

2016

PMID

31309745

Abstract

Background
Some genetic association studies tried to investigate potential associations of transmembrane 6 superfamily member 2 (TM6SF2) polymorphisms with chronic liver disease. However, the results of these studies were not consistent. Thus, we performed the present meta‐analysis to explore associations between TM6SF2 polymorphisms and chronic liver disease in a larger pooled population.

Methods
Systematic literature research of PubMed, Web of Science, Embase, and CNKI was performed to identify eligible studies for pooled analyses. I2 statistics were employed to assess between‐study heterogeneities. If I2 was greater than 50%, random‐effect models (REMs) would be used to pool the data. Otherwise, fixed‐effect models (FEMs) would be applied for synthetic analyses.

Results
Totally 28 studies were included for analyses (13,137 cases and 11,010 controls). The pooled analyses showed that rs58542926 polymorphism was significantly associated with chronic liver disease in overall population (dominant model: p < 0.0001, OR = 0.70, 95% CI = 0.64-0.76, I2 = 47%; recessive model: p < 0.0001, OR = 2.94, 95% CI = 2.05-4.20, I2 = 0%; over‐dominant model: p < 0.0001, OR = 1.34, 95% CI = 1.23-1.47, I2 = 0%; allele model: p < 0.0001, OR = 0.68, 95% CI = 0.63-0.73, I2 = 47%), and these significant findings were further confirmed in both Asians and Caucasians. Stratified analyses by type of disease revealed similar positive results in hepatocellular carcinoma (HCC), cirrhosis, alcoholic liver disease (ALD) and NAFLD (Nonalcoholic fatty liver disease), but not in chronic hepatitis B infection (CHB) and chronic hepatitis C infection (CHC).

Conclusions
These results suggested that TM6SF2 rs58542926 could be used to identify individuals at higher susceptibility to chronic liver disease, especially for HCC, cirrhosis, ALD, and NAFLD.

KEYWORDS

chronic liver disease, meta‐analysis, rs58542926 polymorphisms, transmembrane 6 superfamily member 2 (TM6SF2)

Title

The roles of transmembrane 6 superfamily member 2 rs58542926 polymorphism in chronic liver disease: A meta‐analysis of 24,147 subjects

Author

Xinpei Chen, 1 Pengcheng Zhou, 1 Luo De, 1 Bo Li, 1 and Song Sucorresponding author 1

Publish date

2019 Jul 15

PMID

29634829

Abstract

Introduction
Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state.

Objective
To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016.

Design and Setting
A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year.

Main Outcomes and Measures
Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed.

Results
Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states).

Conclusions and Relevance
There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.

Title

The State of US Health, 1990-2016Burden of Diseases, Injuries, and Risk Factors Among US States

Author

Ali H. Mokdad, PhD,1 Katherine Ballestros, PhD,1 Michelle Echko, BS,1 Scott Glenn, MSc,1 Helen E. Olsen, MA,1 Erin Mullany, BA,1 Alex Lee, BS,1 Abdur Rahman Khan, MD,2 Alireza Ahmadi, MD,3,4 Alize J. Ferrari, PhD,1,5,6 Amir Kasaeian, PhD,7 Andrea Werdecker, PhD,8 Austin Carter, BS,1 Ben Zipkin, BS,1 Benn Sartorius, PhD,9,10 Berrin Serdar, PhD,11 Bryan L. Sykes, PhD,12 Chris Troeger, MPH,1 Christina Fitzmaurice, MD,1,13 Colin D. Rehm, PhD,14 Damian Santomauro, PhD,1,5,6 Daniel Kim, DrPH,15 Danny Colombara, PhD,1 David C. Schwebel, PhD,16 Derrick Tsoi, BS,1 Dhaval Kolte, MD,17 Elaine Nsoesie, PhD,1 Emma Nichols, BA,1 Eyal Oren, PhD,18 Fiona J. Charlson, PhD,1,5,6 George C. Patton, MD,19 Gregory A. Roth, MD,1 H. Dean Hosgood, PhD,20 Harvey A. Whiteford, PhD,1,5,6 Hmwe Kyu, PhD,1 Holly E. Erskine, PhD,1,5,6 Hsiang Huang, MD,21 Ira Martopullo, MPH,1 Jasvinder A. Singh, MD,16 Jean B. Nachega, PhD,22,23,24 Juan R. Sanabria, MD,25,26 Kaja Abbas, PhD,27 Kanyin Ong, PhD,1 Karen Tabb, PhD,28 Kristopher J. Krohn, MPH,1 Leslie Cornaby, BS,1 Louisa Degenhardt, PhD,1,29 Mark Moses, MHS,1 Maryam Farvid, PhD,30,31 Max Griswold, MA,1 Michael Criqui, MD,32 Michelle Bell, PhD,33 Minh Nguyen, BS,1 Mitch Wallin, MD,34,35 Mojde Mirarefin, MPH,1,36 Mostafa Qorbani, PhD,37 Mustafa Younis, DrPH,38 Nancy Fullman, MPH,1 Patrick Liu, MPH,1 Paul Briant, BS,1 Philimon Gona, PhD,39 Rasmus Havmoller, PhD,4 Ricky Leung, PhD,40 Ruth Kimokoti, MD,41 Shahrzad Bazargan-Hejazi, PhD,42,43 Simon I. Hay, DSc,1,44 Simon Yadgir, BS,1 Stan Biryukov, BS,1 Stein Emil Vollset, DrPH,1,45 Tahiya Alam, MPH,1 Tahvi Frank, BS,1 Talha Farid, MD,2 Ted Miller, PhD,46,47 Theo Vos, PhD,1 Till Barnighausen, MD,48,49,50 Tsegaye Telwelde Gebrehiwot, MPH,51 Yuichiro Yano, MD,52 Ziyad Al-Aly, MD,53 Alem Mehari, MD,54 Alexis Handal, PhD,55 Amit Kandel, MBBS,56 Ben Anderson, MD,57 Brian Biroscak, PhD,33,58 Dariush Mozaffarian, MD,59 E. Ray Dorsey, MD,60 Eric L. Ding, ScD,30 Eun-Kee Park, PhD,61 Gregory Wagner, MD,62 Guoqing Hu, PhD,63 Honglei Chen, PhD,64 Jacob E. Sunshine, MD,57 Jagdish Khubchandani, PhD,65 Janet Leasher, OD,66 Janni Leung, PhD,57,67 Joshua Salomon, PhD,48 Jurgen Unutzer, MD,57 Leah Cahill, PhD,30,68 Leslie Cooper, MD,69 Masako Horino, MPH,70 Michael Brauer, ScD,1,71 Nicholas Breitborde, PhD,72 Peter Hotez, PhD,73 Roman Topor-Madry, PhD,74,75 Samir Soneji, PhD,76 Saverio Stranges, PhD,77,78 Spencer James, MD,1 Stephen Amrock, MD,79 Sudha Jayaraman, MD,80 Tejas Patel, MD,81 Tomi Akinyemiju, PhD,16 Vegard Skirbekk, PhD,82,83 Yohannes Kinfu, PhD,84 Zulfiqar Bhutta, PhD,85,86 Jost B. Jonas, MD,87 and Christopher J. L. Murray, DPhilcorresponding author1

Publish date

2018 Apr 10