We Offer Worldwide Shipping
Login Wishlist

(-)-Sesamin

$118

Brand : BIOFRON
Catalogue Number : BD-P0338
Specification : 98.0%(HPLC)
CAS number : 13079-95-3
Formula : C20H18O6
Molecular Weight : 354.36
PUBCHEM ID : 382073
Volume : 25mg

Available on backorder

Quantity
Checkout Bulk Order?

Catalogue Number

BD-P0338

Analysis Method

HPLC,NMR,MS

Specification

98.0%(HPLC)

Storage

2-8°C

Molecular Weight

354.36

Appearance

Powder

Botanical Source

Structure Type

Lignanoids

Category

SMILES

C1C2C(COC2C3=CC4=C(C=C3)OCO4)C(O1)C5=CC6=C(C=C5)OCO6

Synonyms

5-[(3R,3aS,6R,6aS)-3-(1,3-benzodioxol-5-yl)-1,3,3a,4,6,6a-hexahydrofuro[3,4-c]furan-6-yl]-1,3-benzodioxole

IUPAC Name

5-[(3R,3aS,6R,6aS)-3-(1,3-benzodioxol-5-yl)-1,3,3a,4,6,6a-hexahydrofuro[3,4-c]furan-6-yl]-1,3-benzodioxole

Density

1.4±0.1 g/cm3

Solubility

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

Flash Point

212.3±30.0 °C

Boiling Point

504.4±50.0 °C at 760 mmHg

Melting Point

InChl

InChI=1S/C20H18O6/c1-3-15-17(25-9-23-15)5-11(1)19-13-7-22-20(14(13)8-21-19)12-2-4-16-18(6-12)26-10-24-16/h1-6,13-14,19-20H,7-10H2/t13-,14-,19+,20+/m1/s1

InChl Key

PEYUIKBAABKQKQ-NSMLZSOPSA-N

WGK Germany

RID/ADR

HS Code Reference

2933990000

Personal Projective Equipment

Correct Usage

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

Meta Tag

provides coniferyl ferulate(CAS#:13079-95-3) 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

32065954

Abstract

Background: Eleutherococcus senticosus or Siberian ginseng is a medicinal plant containing adaptogenic substances believed to regulate immune responses. Both, the root and stem bark are commonly used in traditional medicines.

Purpose: The purpose of the present study is to chemically characterize E. senticosus root and bark extracts and to compare their effects on functions of human primary macrophages.

Study design and methods: HPLC-DAD-MS analysis was used to characterize chemical constituents of alcoholic extracts from E. senticosus root and bark. The data obtained and available databases were combined for network pharmacology analysis. Involvement of predicted pathways was further functionally confirmed by using monocyte-derived human macrophages and endotoxin-free E. senticosus root and bark extracts.

Results: Chemical analysis showed that the root extract contained more syringin, caffeic acid, and isofraxidin than the bark extract. At variance, bark extract contained more sesamin and oleanolic acid. Coniferyl aldehyde and afzelin were below the limit of quantification in both extracts. Network pharmacology analysis indicated that constituents of E. senticosus might affect the immune cell phenotype and signaling pathways involved in cell metabolism and cytoskeleton regulation. Indeed, both extracts promoted actin polymerization, migration, and phagocytosis of E. coli by macrophages pointing to macrophage polarization towards the M2 phenotype. In addition, treatment with E. senticosus root and bark extracts decreased phosphorylation of Akt on Ser473 and significantly reduced expression of the hemoglobin scavenger receptor CD163 by macrophages. Neither extract affected expression of CD11b, CD80, or CD64 by macrophages. In addition, macrophages treated with the bark extract, but not with the root extract, exhibited activated p38 MAPK and NF-κB and released increased, but still moderate, amounts of proinflammatory TNF-α and IL-6, anti-inflammatory IL-10, and chemotactic CCL1, which all together point to a M2b-like macrophage polarization. Differently, the root extract increased the IL-4-induced expression of anti-inflammatory CD200R. These changes in monocytes are in agreement with an increased M2a macrophage polarization.

Conclusion: The ability of E. senticosus root and bark extracts to promote polarization of human macrophages towards anti-inflammatory M2a and M2b phenotypes, respectively, might underlay the immunoregulatory activities and point to potential wound healing promoting effects of this medicinal plant.

KEYWORDS

Adaptogen; Alternatively activated macrophages; Cytoskeleton; Eleutherococcus senticosus; Network pharmacology; Wound healing.

Title

A comparative study on root and bark extracts of Eleutherococcus senticosus and their effects on human macrophages

Author

Lu Jin 1, Michael Schmiech 1, Menna El Gaafary 2, Xinlei Zhang 3, Tatiana Syrovets 1, Thomas Simmet 4

Publish date

2020 Mar;

PMID

31674783

Abstract

Sesamin, a lignan from sesame seed, has been reported to attenuate chronic mild stress-induced depressive-like behaviors. Gut microbiota play pivotal roles in mediating psychological behaviors by regulating gut barrier integrity and systemic inflammatory responses. Here, we found that oral sesamin administration (50 mg/kg·bodyweight/day) significantly attenuated depressive, aversive, repetitive, and anxiety-like behaviors in a long-term multiple nonsocial stress-treated mice model. Sesamin inhibited stress-induced gut barrier integrity damage, reduced circulating lipopolysaccharide (LPS) levels, and suppressed neuroinflammatory responses. Moreover, sesamin treatment also restructured the gut microbiome by enhancing the relative abundances of Bacteroidales and S24-7. The correlation analysis indicated that the microbiota composition changes were strongly correlated with behavioral disorders, serotonin, norepinephrine, and LPS levels. In conclusion, sesamin has preventive effects on stress-induced behavioral and psychological disorders, which might be highly related to the reshaped microbiota composition. This study provides a clue for understanding the systemic mechanism of anti-depression effects of sesamin.

KEYWORDS

LPS; gut microbiota; inflammation; sesamin; stress.

Title

Supplementation of Sesamin Alleviates Stress-Induced Behavioral and Psychological Disorders via Reshaping the Gut Microbiota Structure

Author

Qianxu Wang 1, Mengzhen Jia 1, Yihang Zhao 1, Yan Hui 2 3, Junru Pan 1, Hongfei Yu 1, Shikai Yan 1, Xiaoshuang Dai 3, Xuebo Liu 1, Zhigang Liu 1

Publish date

2019 Nov 13;

PMID

31560746

Abstract

A combination method of ultra-performance liquid chromatography (UPLC) coupled with diode array detection has been developed for quality evaluation of Qinma prescription (QMP), based on chromatographic fingerprint technology with the similarity analysis (SA) and the quantitative analysis of 12 components by hierarchical cluster analysis (HCA). The established method has been validated by linearity, precision, repeatability, stability and recovery tests. The UPLC fingerprints with 17 common peaks of 5 QMP samples prepared by different extraction methods including water decoction extraction, water extraction-ethanol precipitation method, ethanol reflux extraction, ethanol extraction-water precipitation method and methanol ultrasonic extraction were obtained, and the SA results indicated that similarity index was greatly influenced by the large peak. The similarity index ranged from 0.816 to 0.999 basing on 17 peaks, which has been decreased to 0.683-0.999 basing on 16 peaks without the large peak of baicalin (BA). The results of simultaneous quantification of 12 components in these 5 QMP samples proved that BA, gallic acid (GA), wogonoside (WOG) and gentiopicroside (GEN) were the major ingredients in QMP with high contents >1.44 (mg/g), indicating that ethanol reflux was the most effective extraction method. Integrating fingerprint analysis, simultaneous determination and HCA, the established method is rapid, sensitive, accurate and readily applicable. All the results indicated that the combination method can control the quality of QMP and its related traditional Chinese medicinal compounds more comprehensively and scientifically.

Title

Quantitative Analysis of Twelve Active Components Combined With Chromatographic Fingerprint for Comprehensive Evaluation of Qinma Prescription by Ultra-Performance Liquid Chromatography Coupled With Diode Array Detection

Author

Yi Zhang 1, Yue Ding 1 2, Tong Zhang 2, Xiaoyi Jiang 1, Yaxiong Yi 1, Lijuan Zhang 1, Yi Chen 1, Ting Li 1 2, Ping Kang 3, Juanjuan Tian 1

Publish date

2019 Oct 17