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Rebaudioside D

$560

  • Brand : BIOFRON

  • Catalogue Number : BD-P0606

  • Specification : 98.0%(HPLC)

  • CAS number : 63279-13-0

  • Formula : C50H80O28

  • Molecular Weight : 1129.162

  • PUBCHEM ID : 71773169

  • Volume : 20mg

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Catalogue Number

BD-P0606

Analysis Method

HPLC,NMR,MS

Specification

98.0%(HPLC)

Storage

-20℃

Molecular Weight

1129.162

Appearance

Powder

Botanical Source

Stevia rebaudiana (Bertoni) Hemsl.

Structure Type

Diterpenoids

Category

Standards;Natural Pytochemical;API

SMILES

CC12CCCC(C1CCC34C2CCC(C3)(C(=C)C4)OC5C(C(C(C(O5)CO)O)OC6C(C(C(C(O6)CO)O)O)O)OC7C(C(C(C(O7)CO)O)O)O)(C)C(=O)OC8C(C(C(C(O8)CO)O)O)OC9C(C(C(C(O9)CO)O)O)O

Synonyms

2-O-β-D-Glucopyranosyl-1-O-[(5β,8α,9β,10α,13α)-13-{[β-D-glucopyranosyl-(1->2)-[β-D-glucopyranosyl-(1->3)]-β-D-glucopyranosyl]oxy}-18-oxokaur-16-en-18-yl]-β-D-glucopyra nose/rebaudioside D

IUPAC Name

[(2S,3R,4S,5S,6R)-4,5-dihydroxy-6-(hydroxymethyl)-3-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxyoxan-2-yl] (1R,4S,5R,9S,10R,13S)-13-[(2S,3R,4S,5R,6R)-5-hydroxy-6-(hydroxymethyl)-3,4-bis[[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxy]oxan-2-yl]oxy-5,9-dimethyl-14-methylidenetetracyclo[11.2.1.01,10.04,9]hexadecane-5-carboxylate

Applications

Density

1.6±0.1 g/cm3

Solubility

Methanol; Water

Flash Point

Boiling Point

Melting Point

InChl

InChI=1S/C50H80O28/c1-18-11-49-9-5-24-47(2,7-4-8-48(24,3)46(68)77-44-39(34(64)29(59)22(15-54)72-44)75-42-36(66)32(62)27(57)20(13-52)70-42)25(49)6-10-50(18,17-49)78-45-40(76-43-37(67)33(63)28(58)21(14-53)71-43)38(30(60)23(16-55)73-45)74-41-35(65)31(61)26(56)19(12-51)69-41/h19-45,51-67H,1,4-17H2,2-3H3/t19-,20-,21-,22-,23-,24+,25+,26-,27-,28-,29-,30-,31+,32+,33+,34+,35-,36-,37-,38+,39-,40-,41+,42+,43+,44+,45+,47-,48-,49-,50+/m1/s1

InChl Key

RPYRMTHVSUWHSV-CUZJHZIBSA-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#:63279-13-0) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate

No Technical Documents Available For This Product.

PMID

24065065

Abstract

Objective
The purpose of this study was to investigate changes in dietary intake and appetite across the menopausal transition.

Methods
This was a 5-year observational, longitudinal study on the menopausal transition. The study included 94 premenopausal women at baseline (age: 49.9 ± 1.9 yrs; BMI: 23.3 ± 2.3 kg/m2). Body composition (DXA), appetite (visual analogue scale), eating frequency, energy intake (EI) and macronutrient composition (7-day food diary and buffet-type meal) were measured annually.

Results
Repeated-measures analyses revealed that total EI and carbohydrate intake from food diary decreased significantly over time in women who became postmenopausal by year 5 (P > 0.05) compared to women in the menopausal transition. In women who became postmenopausal by year 5, fat and protein intakes decreased across the menopausal transition (0.05 > P < 0.01). Although a decrease in % fat intake was observed during the menopausal transition (P < 0.05), this variable was significantly increased in the postmenopausal years (P < 0.05). Spontaneous EI and protein intake also declined over time and were higher in the years preceding menopause onset (P < 0.05). Desire to eat, hunger and prospective food consumption increased during the menopausal transition and remained at this higher level in the postmenopausal years (0.05 > P< 0.001). Fasting fullness decreased across the menopausal transition (P < 0.05). Conclusion These results suggest that menopausal transition is accompanied with a decrease in food intake and an increase in appetite.

KEYWORDS

Energy balance, energy intake, eating frequency, appetite, menopausal transition, body composition

Title

Effects of the Menopausal Transition on Dietary Intake and Appetite. A MONET Group Study

Author

Duval Karine,1 Prud’homme Denis,2 Rabasa-Lhoret Remi,3,4,5 Strychar Irene,5,6 Brochu Martin,7,8 Lavoie Jean-Marc,9 and Doucet eric2

Publish date

2013 Sep 25

PMID

22310476

Abstract

Background
Cellular glucose uptake can be enhanced by upregulating Ras signaling in either insulin-dependent or – independent manner. In presence of insulin and intact insulin signaling, Ras has a negligible role in glucose uptake. Conversely, when insulin signaling is impaired in obesity or diabetes, the insulin-independent Ras pathway may be valuable for enhancing glucose disposal. We previously reported that Ad36, a human adenovirus, enhances cellular glucose uptake by upregulating the Ras/Glut4 pathway. Here, we investigated if Ad36-upregulated Ras via the insulin-independent pathway, to enhance glucose uptake. Furthermore, uncontrolled upregulation of Ras is linked with oncogenic cell transformation, if the tumor-suppressor gene p53 is also downregulated. Hence, we determined if upregulation of Ras by Ad36 would induce oncogenic cell transformation. Finally, we determined the relevance of Ad36 to insulin resistance in humans.

Methods
Insulin receptor (IR) was knocked down with small interfering RNA in 3T3-L1 adipocytes, to determine if Ad36 increases the Ras/Glut4 pathway and glucose uptake without IR-signaling. Next, the effects of Ad36 on cell transformation and p53 abundance were determined. Finally, overweight or obese women were screened for seropositivity to Ad36, as an indicator of natural Ad36 infection. Associations of Ad36 infection with adiposity and C-reactive proteins (CRPs)—two key markers of insulin resistance, and with glucose disposal, were determined.

Results
Unaffected by IR knock-down, Ad36 significantly increased the Ras pathway, Glut4 translocation and glucose uptake in 3T3-L1 adipocytes. Despite Ras upregulation, Ad36 did not transform 3T3-L1 cells. This may be because Ad36 significantly increased p53 protein in 3T3-L1 cells or mice adipose tissue. Ad36 seropositivity was associated with greater adiposity and CRP levels, yet a significantly higher systemic glucose disposal rate.

Conclusions
Overall, the study offers Ras/Glut4 pathway as an alternate to enhance glucose disposal when insulin signaling is impaired, and, importantly, provides Ad36 as a tool to understand the modulation of that pathway.

KEYWORDS

Ras, Ad36, PI3K, Glut 4, p53, IRS1

Title

Insulin receptor-independent upregulation of cellular glucose uptake

Author

R Krishnapuram,1,4 H Kirk-Ballard,1,4 EJ Dhurandhar,1 O Dubuisson,1 V Messier,2,3 R Rabasa-Lhoret,2,3 V Hegde,1 S Aggarwal,1 and NV Dhurandhar1

Publish date

2012 Feb 7.

PMID

31800599

Abstract

Exposure to air pollutants is known to have adverse effects on human health; however, little is known about the association between hydrocarbons in air and an ischemic stroke (IS) event. We investigated whether long-term exposure to airborne hydrocarbons, including volatile organic compounds, increased IS risk. This retrospective cohort study included 283,666 people aged 40 years or older in Taiwan. Cox proportional hazards regression analysis was used to fit single- and multiple-pollutant models for two targeted pollutants, total hydrocarbons (THC) and nonmethane hydrocarbons (NMHC), and estimated the risk of IS. Before controlling for multiple pollutants, hazard ratios (HRs) of IS with 95% confidence intervals for the overall population were 2.69 (2.64-2.74) at 0.16-ppm increase in THC and 1.62 (1.59-1.66) at 0.11-ppm increase in NMHC. For the multiple-pollutant models controlling for PM2.5, the adjusted HR was 3.64 (3.56-3.72) for THC and 2.21 (2.16-2.26) for NMHC. Our findings suggest that long-term exposure to THC and NMHC may be a risk factor for IS development.

Title

Long-term ambient hydrocarbons exposure and incidence of ischemic stroke

Author

Han-Wei Zhang, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing,1,2,3,* Victor C. Kok, Data curation, Investigation, Supervision, Validation,4,5 Shu-Chun Chuang, Data curation, Supervision, Validation,6 Chun-Hung Tseng, Investigation, Supervision, Validation,7 Chin-Teng Lin, Software, Supervision,8,9,10 Tsai-Chung Li, Supervision, Validation,11,12 Fung-Chang Sung, Supervision, Validation, Visualization,13 Chi Pang Wen, Supervision, Validation, Visualization,14 Chao A. Hsiung, Project administration, Resources, Validation, Visualization,14 and Chung Y. Hsu, Funding acquisition, Project administration, Resources, Validation, Visualization15

Publish date

2019 Dec 4.