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Sibiricose A5

$336

  • Brand : BIOFRON

  • Catalogue Number : BD-D1233

  • Specification : 98%(HPLC)

  • CAS number : 107912-97-0

  • Formula : C22H30O14

  • Molecular Weight : 518.47

  • PUBCHEM ID : 6326020

  • Volume : 20MG

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Catalogue Number

BD-D1233

Analysis Method

HPLC,NMR,MS

Specification

98%(HPLC)

Storage

-20℃

Molecular Weight

518.47

Appearance

Powder

Botanical Source

Constit. of Polygala arillata and Polygala sibirica

Structure Type

Simple Phenylpropanoids

Category

Standards;Natural Pytochemical;API

SMILES

COC1=C(C=CC(=C1)C=CC(=O)OC2C(C(OC2(CO)OC3C(C(C(C(O3)CO)O)O)O)CO)O)O

Synonyms

3-O-[(2E)-3-(4-Hydroxy-3-methoxyphenyl)-2-propenoyl]-β-D-fructofuranosyl α-D-glucopyranoside/Sibiricose-A5/sibiricose A5/α-D-Glucopyranoside, 3-O-[(2E)-3-(4-hydroxy-3-methoxyphenyl)-1-oxo-2-propen-1-yl]-β-D-fructofuranosyl

IUPAC Name

[(2S,3S,4R,5R)-4-hydroxy-2,5-bis(hydroxymethyl)-2-[(2R,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxyoxolan-3-yl] (E)-3-(4-hydroxy-3-methoxyphenyl)prop-2-enoate

Applications

Sibiricose A5 is an oligosaccharide ester isolated from Polygalae Radix with potent antioxidant activity[1][2].

Density

1.6±0.1 g/cm3

Solubility

Methanol

Flash Point

279.7±27.8 °C

Boiling Point

821.7±65.0 °C at 760 mmHg

Melting Point

InChl

InChI=1S/C22H30O14/c1-32-12-6-10(2-4-11(12)26)3-5-15(27)34-20-17(29)14(8-24)35-22(20,9-25)36-21-19(31)18(30)16(28)13(7-23)33-21/h2-6,13-14,16-21,23-26,28-31H,7-9H2,1H3/b5-3+/t13-,14-,16-,17-,18+,19-,20+,21-,22+/m1/s1

InChl Key

ZPEADZHVGOCGKH-YQTDNFGYSA-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#:107912-97-0) 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

27066036

Abstract

In Brassica napus breeding, traits related to commercial success are of highest importance for plant breeders. However, such traits can only be assessed in an advanced developmental stage. Molecular markers genetically linked to such traits have the potential to accelerate the breeding process of B. napus by marker-assisted selection. Therefore, the objectives of this study were to identify (i) genome regions associated with the examined agronomic and seed quality traits, (ii) the interrelationship of population structure and the detected associations, and (iii) candidate genes for the revealed associations. The diversity set used in this study consisted of 405 B. napus inbred lines which were genotyped using a 6K single nucleotide polymorphism (SNP) array and phenotyped for agronomic and seed quality traits in field trials. In a genome-wide association study, we detected a total of 112 associations between SNPs and the seed quality traits as well as 46 SNP-trait associations for the agronomic traits with a P < 1.28e-05 (Bonferroni correction of α = 0.05) for the inbreds of the spring and winter trial. For the seed quality traits, a single SNP-sulfur concentration in seeds (SUL) association explained up to 67.3% of the phenotypic variance, whereas for the agronomic traits, a single SNP-blossom color (BLC) association explained up to 30.2% of the phenotypic variance. In a basic local alignment search tool (BLAST) search within a distance of 2.5 Mbp around these SNP-trait associations, 62 hits of potential candidate genes with a BLAST-score of ≥100 and a sequence identity of ≥70% to A. thaliana or B. rapa could be found for the agronomic SNP-trait associations and 187 hits of potential candidate genes for the seed quality SNP-trait associations.

KEYWORDS

Brassica napus, agronomic traits, seed quality, genome-wide association mapping, flowering, erucic acid, marker-assisted selection, candidate genes

Title

Agronomic and Seed Quality Traits Dissected by Genome-Wide Association Mapping in Brassica napus

Author

Niklas Korber,1,2,* Anja Bus,1,2 Jinquan Li,1 Isobel A. P. Parkin,3 Benjamin Wittkop,4 Rod J. Snowdon,4 and Benjamin Stich1,*

Publish date

2016 Mar 31.

PMID

30863154

Abstract

Background
The 8th edition of the American Joint Committee on Cancer (AJCC) staging system for breast cancer has incorporated tumor grade, estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 status as staging biologic factors reflecting prognosis. The purpose of this study was to compare the 7th and 8th edition of AJCC staging system for prognostic impact.

Materials and methods
Primary breast cancer patients diagnosed from 2010 to 2014 were identified using the Surveillance, Epidemiology and End Results 18 registries research database. Breast cancer-specific survival (BCSS) and overall survival (OS) between stages were estimated using the Kaplan-Meier method and compared using the log-rank test. Multivariable analysis was performed using Cox proportional hazards regression analysis to identify factors independently associated with outcome. Akaike’s information criterion (AIC) was calculated to estimate how well the staging system fitted the data and the complexity of the model.

Results
A total of 184,221 primary breast cancer patients were identified in the 7th AJCC staging system; 16,145 (8.8%) patients could not be categorized according to 8th AJCC prognostic staging system leaving 168,076 patients included for final analyses. The 8th AJCC performed well with the BCSS and OS concordant with stage. A total of 89,494 (53.2%) of patients were restaged to a different stage group in the 8th AJCC; stage IIIA in the 7th AJCC migrated to stage IB with a worse prognosis than IIA and IIB in the 8th AJCC. Nevertheless, the 8th AJCC had a better AIC than the 7th staging system.

Conclusion
The prognostic accuracy of the 8th AJCC staging system was generally superior to the 7th AJCC, although subtle differences between the two systems should be noted in comparative studies.

KEYWORDS

breast cancer, prognosis, AJCC

Title

Comparison of the 7th and 8th edition of American Joint Committee on Cancer (AJCC) staging systems for breast cancer patients: a Surveillance, Epidemiology and End Results (SEER) Analysis

Author

Nan Shao,1,* Chuanbo Xie,2,* Yawei Shi,1 Runyi Ye,1 Jianting Long,3 Huijuan Shi,4 Zhen Shan,1 Alastair M Thompson,5 and Ying Lin1

Publish date

2019 Feb 13

PMID

23332031

Abstract

Background
MicroRNAs (miRNAs) are a family of ~22 nucleotide small RNA molecules that regulate gene expression by fully or partially binding to their complementary sequences. Recently, a large number of miRNAs and their expression patterns have been identified in various species. However, to date no miRNAs have been reported to modulate muscle development in beef cattle.

Results
Total RNAs from the Chinese Qinchuan bovine longissimus thoracis at fetal and adult stages were used to construct small RNA libraries for Solexa SBS technology sequencing. A total of 15,454,182 clean reads were obtained from the fetal bovine library and 13,558,164 clean reads from the adult bovine library. In total, 521 miRNAs including 104 novel miRNA candidates were identified. Furthermore, the nucleotide bias, base edit and family of the known miRNAs were also analyzed. Based on stem-loop qPCR, 25 high-read miRNAs were detected, and the results showed that bta-miRNA-206, miRNA-1, miRNA-133, miRNAn12, and miRNAn17 were highly expressed in muscle-related tissue or organs, suggesting that these miRNAs may play a role in the development of bovine muscle tissues.

Conclusions
This study confirmed the authenticity of 417 known miRNAs, discovered 104 novel miRNAs in bos taurus, and identified five muscle-specific miRNAs. The identification of novel miRNAs significantly expanded the repertoire of bovine miRNAs and could contribute to further studies on the muscle development of cattle.

KEYWORDS

Bovine, Deep sequencing technology, microRNA, Muscle, Proliferation, Differentiation

Title

Identification and profiling of conserved and novel microRNAs from Chinese Qinchuan bovine longissimus thoracis

Author

Jiajie Sun,1 Mijie Li,1 Zhuanjian Li,1 Jing Xue,1 Xianyong Lan,1 Chunlei Zhang,2 Chuzhao Lei,1 and Hong Chencorresponding author1

Publish date

2013 Jan 18