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Guaiacin

$1,165

  • Brand : BIOFRON

  • Catalogue Number : BD-P0811

  • Specification : 98.0%(HPLC&TLC)

  • CAS number : 36531-08-5

  • Formula : C20H24O4

  • Molecular Weight : 328.4

  • PUBCHEM ID : 11724027

  • Volume : 25mg

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Catalogue Number

BD-P0811

Analysis Method

HPLC,NMR,MS

Specification

98.0%(HPLC&TLC)

Storage

2-8°C

Molecular Weight

328.4

Appearance

Powder

Botanical Source

Powder

Structure Type

Lignans

Category

SMILES

CC1CC2=CC(=C(C=C2C(C1C)C3=CC(=C(C=C3)O)OC)O)OC

Synonyms

(6R,7S,8S)-8-(4-hydroxy-3-methoxyphenyl)-3-methoxy-6,7-dimethyl-5,6,7,8-tetrahydronaphthalen-2-ol

IUPAC Name

(6R,7S,8S)-8-(4-hydroxy-3-methoxyphenyl)-3-methoxy-6,7-dimethyl-5,6,7,8-tetrahydronaphthalen-2-ol

Applications

Density

1.2±0.1 g/cm3

Solubility

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

Flash Point

246.8±28.7 °C

Boiling Point

484.5±45.0 °C at 760 mmHg

Melting Point

InChl

InChI=1S/C20H24O4/c1-11-7-14-9-19(24-4)17(22)10-15(14)20(12(11)2)13-5-6-16(21)18(8-13)23-3/h5-6,8-12,20-22H,7H2,1-4H3/t11-,12+,20+/m1/s1

InChl Key

TZAAYUCUPIYQBR-JGRMJRGVSA-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#:36531-08-5) 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

27827403

Abstract

Our previous genome-wide miRNA microarray study revealed that miR-107 was upregulated in gastric cancer (GC). In this study we aimed to explore its biological role in the pathogenesis of GC. Integrating in silico prediction algorithms with western blotting assays revealed that miR-107 inhibition enhanced NF1 (neurofibromin 1) mRNA and protein levels, suggesting that NF1 is one of miR-107 targets in GC. Luciferase reporter assay revealed that miR-107 suppressed NF1 expression by binding to the first potential binding site within the 3′-UTR of NF1 mRNA. mRNA stable assay indicated this binding could result in NF1 mRNA instability, which might contribute to its abnormal protein expression. Functional analyses such as cell growth, transwell migration and invasion assays were used to investigate the role of interaction between miR-107 and its target on GC development and progression. Moreover, We investigated the association between the clinical phenotype and the status of miR-107 expression in 55 GC tissues, and found the high expression contributed to the tumor size and depth of invasion. The results exhibited that down regulation of miR-107 opposed cell growth, migration, and invasion, whereas NF1 repression promoted these phenotypes. Our findings provide a mechanism by which miR-107 regulates NF1 in GC, as well as highlight the importance of interaction between miR-107 and NF1 in GC development and progression.

Title

miR-107 regulates tumor progression by targeting NF1 in gastric cancer

Author

Shizhi Wang,1,2,3,* Gaoxiang Ma,1,2,* Haixia Zhu,4,* Chunye Lv,1,5,* Haiyan Chu,1,2 Na Tong,1,2 Dongmei Wu,1,2 Fulin Qiang,1,4 Weida Gong,6 Qinghong Zhao,7 Guoquan Tao,8 Jianwei Zhou,9 Zhengdong Zhang,a,1,2 and Meilin Wangb,1,2

Publish date

2016;

PMID

32490324

Abstract

In the United States, chronic viral hepatitis B and C (CHB and CHC), nonalcoholic fatty liver disease (NAFLD), and alcohol‐related liver disease (ALD) are the main causes of liver deaths attributable to hepatocellular carcinoma (HCC) and cirrhosis. Our aim was to assess the changes in the rates of mortality and years of potential life lost (YLL) for HCC and cirrhosis due to different liver diseases. We used multiple‐cause mortality data (2007‐2017) from the National Center for Health Statistics. Annual percentage change (APC) in age‐standardized death rate per 100,000 (ASDR) and age‐standardized years of life lost per 100,000 (ASYLLR) were calculated. In the United States in 2017, there were 2,797,265 deaths with 73,424 liver deaths, contributing to 1,467,742 of YLL. Of the liver deaths, HCC was noted in 12,169 (16.6%) and cirrhosis in 60,111 (82.0%). CHC was responsible for 50.4% of HCC deaths; NAFLD, 35.4%; HBV, 6.0%; ALD, 5.4%; and others, 2.8%. NAFLD was responsible for 48.9% of cirrhosis deaths; ALD, 34.7%; CHC, 12.3%; CHB, 0.9%; and others, 3.2%. Between 2007 and 2017, the increase in ASDR for HCC due to ALD and NAFLD accelerated after 2014 (APC, 11.38% and 6.55%, respectively) whereas CHC stabilized (APC, 0.63%; P = 0.272) after 2011. The increase in ASYLLR of HCC escalated after 2014 for ALD and NAFLD (APC, 12.12% and 6.15%, respectively) and leveled out for CHC after 2012 (APC, −1.05%; P = 0.056). Furthermore, the highest annual increase in ASDR and ASYLLR for cirrhosis was due to ALD (APC, 3.24% and 3.34%, respectively) followed by NAFLD (APC, 1.23% and 0.49%, respectively). Conclusion: Over the past decade, ASDR and ASYLLR due to ALD and NAFLD have been increasing in the United States. The rising burden of HCC and cirrhosis are primarily driven by NAFLD and ALD.

Title

Nonalcoholic Fatty Liver Disease and Alcoholic Liver Disease are Major Drivers of Liver Mortality in the United States

Author

James M. Paik, 1 Pegah Golabi, 1 Rakesh Biswas, 1 Saleh Alqahtani, 2 Chapy Venkatesan, 1 and Zobair M. Younossicorresponding author 1 , 3

Publish date

2020 Jun

PMID

31788338

Abstract

To examine the effect of frailty on diabetic kidney disease patients’ risk of progression to end-stage renal disease (ESRD), mortality, and adverse episodes, as whether frailty modifies their risk of developing ESRD and other adverse outcomes remains unclear. We identified 165,461 DKD patients from the Longitudinal Cohort of Diabetes Patients in Taiwan (n=840,000) between 2004 and 2010, classifying them into those without frailty or with 1, 2 and ≥3 frailty components based on a modified version of FRAIL scale. Using Cox proportional hazard regression analysis, we examined the long-term risk of developing ESRD along with their risk of mortality, supplemented by a competing risk analysis against mortality. Among all participants, 66.2% (n=109,586), 27.2% (n=44,986), 5.9% (n=9,799), and 0.7% (n=1090) patients did not have or had 1, 2, and ≥3 frailty components, respectively. After a 4.1-year follow-up, 4.2% patients developed ESRD and 18.5% died. Cox proportional hazard modeling revealed that patients with 1, 2, and ≥3 frailty components had increased risks of developing ESRD (for 1, 2, and ≥3 components, hazard ratio [HR] 1.13, 1.18, and 1.2, respectively) and mortality (HR 1.25, 1.41, and 1.34, respectively), with. 9% and 16% risk elevations for ESRD and mortality per component increase. Competing risk analysis showed that frailty-induced ESRD risk was attenuated partially by mortality in those with moderate frailty. The receipt of palliative care did not attenuate this risk. Frailty increased the risk of ESRD based on a dose-response relationship among DKD patients with risk competition by mortality.

KEYWORDS

chronic kidney disease, diabetes mellitus, diabetic kidney disease, dialysis, end-stage renal disease, frailty, frail phenotype

Title

Frailty Predicts an Increased Risk of End-Stage Renal Disease with Risk Competition by Mortality among 165,461 Diabetic Kidney Disease Patients

Author

Chia-Ter Chao,1,2 Jui Wang,3 Jenq-Wen Huang,4 Ding-Cheng Chan,5 and Kuo-Liong Chien3, on behalf of the COhort of GEriatric Nephrology in NTUHstudy group

Publish date

2019 Dec;