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Notoginsenoside Fc

$300

  • Brand : BIOFRON

  • Catalogue Number : BF-N4001

  • Specification : 98%(HPLC)

  • CAS number : 88122-52-5

  • Formula : C58H98O26

  • Molecular Weight : 1211.38

  • PUBCHEM ID : 75412556

  • Volume : 20mg

In stock

Quantity
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Catalogue Number

BF-N4001

Analysis Method

HPLC,NMR,MS

Specification

98%(HPLC)

Storage

-20℃

Molecular Weight

1211.38

Appearance

Powder

Botanical Source

roots of Panax notoginseng

Structure Type

Terpenoids

Category

Standards;Natural Pytochemical;API

SMILES

CC(=CCCC(C)(C1CCC2(C1C(CC3C2(CCC4C3(CCC(C4(C)C)OC5C(C(C(C(O5)CO)O)O)OC6C(C(C(C(O6)CO)O)O)OC7C(C(C(CO7)O)O)O)C)C)O)C)OC8C(C(C(C(O8)COC9C(C(C(CO9)O)O)O)O)O)O)C

Synonyms

β-D-Glucopyranoside, (3β,12β)-12-hydroxy-20-[(6-O-β-D-xylopyranosyl-β-D-glucopyranosyl)oxy]dammar-24-en-3-yl O-β-D-xylopyranosyl-(1->2)-O-β-D-glucopyranosyl-(1->2)-/Dammarane, β-D-glucopyranoside deriv./(3β,12β)-12-Hydroxy-20-{[6-O-(β-D-xylopyranosyl)-β-D-glucopyranosyl]oxy}dammar-24-en-3-yl β-D-xylopyranosyl-(1->;2)-β-D-glucopyranosyl-(1->2)-β-D-glucopyranoside/Notoginsenoside Fc

IUPAC Name

(2S,3R,4S,5S,6R)-2-[(2S)-2-[(3S,5R,8R,9R,10R,12R,13R,14R,17S)-3-[(2R,3R,4S,5S,6R)-3-[(2S,3R,4S,5S,6R)-4,5-dihydroxy-6-(hydroxymethyl)-3-[(2S,3R,4S,5R)-3,4,5-trihydroxyoxan-2-yl]oxyoxan-2-yl]oxy-4,5-dihydroxy-6-(hydroxymethyl)oxan-2-yl]oxy-12-hydroxy-4,4,8,10,14-pentamethyl-2,3,5,6,7,9,11,12,13,15,16,17-dodecahydro-1H-cyclopenta[a]phenanthren-17-yl]-6-methylhept-5-en-2-yl]oxy-6-[[(2S,3R,4S,5R)-3,4,5-trihydroxyoxan-2-yl]oxymethyl]oxane-3,4,5-triol

Applications

Density

1.47±0.1 g/cm3

Solubility

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

Flash Point

Boiling Point

Melting Point

InChl

InChI=1S/C58H98O26/c1-24(2)10-9-14-58(8,84-51-46(74)41(69)40(68)31(80-51)23-77-49-44(72)36(64)27(62)21-75-49)25-11-16-57(7)35(25)26(61)18-33-55(5)15-13-34(54(3,4)32(55)12-17-56(33,57)6)81-52-47(42(70)38(66)29(19-59)78-52)83-53-48(43(71)39(67)30(20-60)79-53)82-50-45(73)37(65)28(63)22-76-50/h10,25-53,59-74H,9,11-23H2,1-8H3/t25-,26+,27+,28+,29+,30+,31+,32-,33+,34-,35-,36-,37-,38+,39+,40+,41-,42-,43-,44+,45+,46+,47+,48+,49-,50-,51-,52-,53-,55-,56+,57+,58-/m0/s1

InChl Key

XBGLCVZQMWKHFC-NMQALWILSA-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#:88122-52-5) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate

PMID

29152146

Abstract

It has long been proposed that the gut microbiome contributes to breast carcinogenesis by modifying systemic estrogen levels. This is often cited as a possible mechanism linking breast cancer and high-fat, low-fiber diets as well as antibiotic exposure, associations previously identified in population-based studies. More recently, a distinct microbiome has been identified within breast milk and tissue, but few studies have characterized differences in the breast tissue microbiota of patients with and without cancer, and none have investigated distant body-site microbiomes outside of the gut. We hypothesize that cancerous breast tissue is associated with a microbiomic profile distinct from that of benign breast tissue, and that microbiomes of more distant sites, the oral cavity and urinary tract, will reflect dysbiosis as well. Fifty-seven women with invasive breast cancer undergoing mastectomy and 21 healthy women undergoing cosmetic breast surgery were enrolled. The bacterial 16S rRNA gene was amplified from urine, oral rinse and surgically collected breast tissue, sequenced, and processed through a QIIME-based bioinformatics pipeline. Cancer patient breast tissue microbiomes clustered significantly differently from non-cancer patients (p=0.03), largely driven by decreased relative abundance of Methylobacterium in cancer patients (median 0.10 vs. 0.24, p=0.03). There were no significant differences in oral rinse samples. Differences in urinary microbiomes were largely explained by menopausal status, with peri/postmenopausal women showing decreased levels of Lactobacillus. Independent of menopausal status, however, cancer patients had increased levels of gram-positive organisms including Corynebacterium (p<0.01), Staphylococcus (p=0.02), Actinomyces (p<0.01), and Propionibacteriaceae (p<0.01). Our observations suggest that the local breast microbiota differ in patients with and without breast cancer. Cancer patient urinary microbiomes were characterized by increased levels of gram-positive organisms in this study, but need to be further studied in larger cohorts.

KEYWORDS

microbiome, metagenomics, breast cancer, oral, urine

Title

Breast tissue, oral and urinary microbiomes in breast cancer

Author

Hannah Wang,1,2 Jessica Altemus,1 Farshad Niazi,1 Holly Green,4 Benjamin C. Calhoun,5 Charles Sturgis,5 Stephen R. Grobmyer,2,4,6,8 and Charis Eng1,2,3,7,8

Publish date

2017 Oct 20;

PMID

26437365

Abstract

The hepatic low-density lipoprotein receptor (LDLR) pathway is essential for clearing circulating LDL-cholesterol (LDL-C). While the transcriptional regulation of LDLR is well-characterized, the post-transcriptional mechanisms which govern LDLR expression are just beginning to emerge. Here, we developed a high-throughput genome-wide screening assay to systematically identify microRNAs (miRNAs) that regulate LDLR activity in human hepatic cells. From this screen, we characterize miR-148a as a negative regulator of LDLR expression and activity, and define a novel SREBP1-mediated pathway by which miR-148a regulates LDL-C uptake. Importantly, inhibition of miR-148a increases hepatic LDLR expression and decreases plasma LDL-C in vivo. We also provide evidence that miR-148a regulates hepatic ABCA1 expression and circulating HDL-C levels. Collectively, these studies uncover miR-148a as an important regulator of hepatic LDL-C clearance through direct regulation of LDLR expression, and demonstrate the therapeutic potential of inhibiting miR-148a to ameliorate the elevated LDL-C/HDL-C ratio, a prominent risk factor for cardiovascular disease.

Title

Identification of miR-148a as a novel regulator of cholesterol metabolism

Author

Leigh Goedeke,1,2,3,4 Noemi Rotllan,1,2,* Alberto Canfran-Duque,1,2,* Juan F. Aranda,1,2,3 Cristina M. Ramirez,1,2 Elisa Araldi,1,2,3,4 Chin-Sheng Lin,3,4 Norma N. Anderson,5,6 Alexandre Wagschal,7,8 Rafael de Cabo,9 Jay D. Horton,5,6 Miguel A. Lasuncion,10,11 Anders M. Naar,7,8 Yajaira Suarez,1,2,3,4 and Carlos Fernandez-Hernando1,2,3,4,#

Publish date

2016 May 1.

PMID

27513997

Abstract

Introduction
Beginning in 2013, in addition to the 2-item disability question set asked since 2001, Behavioral Risk Factor Surveillance System (BRFSS) began using 5 of the 6 items from the US Department of Health and Human Services-recommended disability question set. We assess and compare disability prevalence using the 2-question and 5-question sets and describe characteristics of respondents who identified as having a disability using each question set.

Methods
We used data from the 2013 BRFSS to estimate the prevalence of disability for each question set and the 5 specific types of disability. Among respondents identified by each disability question set, we calculated the prevalence of selected demographic characteristics, health conditions, health behaviors, and health status.

Results
With the 2-question set, 21.6% of adults had a disability and with the 5-question set, 22.7% of adults had disability. A total of 51.2% of adults who identified as having a disability with either the 2-question or 5-question set reported having disabilities with both sets. Adults with different disability types differed by demographic and health characteristics.

Conclusion
The inclusion of the 5 new disability questions in BRFSS provides a level of detail that can help develop targeted interventions and programs and can guide the adaptation of existing health promotion programs to be more inclusive of adults who experience specific types of disabilities.

Title

Comparison of 2 Disability Measures, Behavioral Risk Factor Surveillance System, 2013

Author

Alissa C. Stevens, MPH,corresponding author Elizabeth A. Courtney-Long, MA, MSPH, Catherine A. Okoro, MS, PhD, and Dianna D. Carroll, PhD

Publish date

2016;