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[(1(10)E,2R,4R)]-2-Methoxy-8,12-epoxygemacra-1(10),7,11-trien-6-one

$896

  • Brand : BIOFRON

  • Catalogue Number : BD-P0383

  • Specification : 98.0%(HPLC)

  • CAS number : 75412-95-2

  • Formula : C16H22O3

  • Molecular Weight : 262.35

  • PUBCHEM ID : 44576244

  • Volume : 25mg

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Quantity
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Catalogue Number

BD-P0383

Analysis Method

HPLC,NMR,MS

Specification

98.0%(HPLC)

Storage

-20℃

Molecular Weight

262.35

Appearance

Powder

Botanical Source

Structure Type

Sesquiterpenoids

Category

SMILES

CC1CC(C=C(CC2=C(C(=CO2)C)C(=O)C1)C)OC

Synonyms

(6R,8R)-8-methoxy-3,6,10-trimethyl-6,7,8,11-tetrahydro-5H-cyclodeca[b]furan-4-one

IUPAC Name

(6R,8R)-8-methoxy-3,6,10-trimethyl-6,7,8,11-tetrahydro-5H-cyclodeca[b]furan-4-one

Applications

Density

Solubility

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

Flash Point

Boiling Point

Melting Point

InChl

InChI=1S/C16H22O3/c1-10-5-13(18-4)6-11(2)8-15-16(14(17)7-10)12(3)9-19-15/h6,9-10,13H,5,7-8H2,1-4H3/t10-,13-/m1/s1

InChl Key

JUFDIKOOORFASQ-ZWNOBZJWSA-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#:75412-95-2) 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

10792205

Abstract

Aims
To assess the risk of acute pancreatitis associated with use of acid-suppressing drugs.

Methods
We conducted a retrospective cohort study with a nested case-control design within the General Practice Research Database (GPRD) in the United Kingdom. The cohort included 180 178 persons aged 20-74 years, who had received at least one prescription of cimetidine, famotidine, nizatidine, ranitidine, lansoprazole, or omeprazole from January 1992 to September 1997 and who did not have major risk factors for pancreatic diseases. Patients with a computerized medical history compatible with idiopathic acute pancreatitis were validated through review of medical records. For the nested case-control analysis 1000 controls were randomly selected from the study population.

Results
We identified 88 potential cases of idiopathic acute pancreatitis. Medical records were available for 86. After review of these records 36 cases of acute pancreatitis were confirmed. Seven cases occurred during nonuse, corresponding to a background incidence rate (IR) of 4.4/100 000 person-years (PY). Six cases occurred during current use of ranitidine (IR 10.5/100 000 PY), five patients were current users of cimetidine (IR 13.9/100 000 PY), and three were current users of omeprazole (IR 7.8/100 000 PY). There were no cases among current users of famotidine, lansoprazole, or nizatidine. Relative risk (RR) compared with nonuse and corrected for age, gender, calendar year and use of medication known to be associated with acute pancreatitis was 1.3 (95% CI: 0.4,4.1) for ranitidine, 2.1 (95% CI: 0.6,7.2) for cimetidine, and 1.1 (95% CI: 0.3,4.6) for omeprazole.

Conclusions
The results of this study do not support an association between acute pancreatitis and the use of acid-suppressing drugs, although a substantial increase in risk cannot be excluded with confidence.

KEYWORDS

acute pancreatitis, acid-suppressing drugs, pharmacovigilance, epidemiology

Title

The risk of acute pancreatitis associated with acid-suppressing drugs

Author

I A Eland,1 C Huerta Alvarez,2 B H CH Stricker,1,3 and L A Garcia Rodriguez2

Publish date

2000 May;

PMID

21947390

Abstract

Single-dose nevirapine (sd-NVP) and extended NVP prophylaxis are widely used in resource-constrained settings to prevent vertical HIV-1 transmission. We assessed the pharmacokinetics of sd-NVP in 62 HIV-1-positive pregnant Ugandan woman and their newborns who were receiving sd-NVP prophylaxis to prevent mother-to-child HIV-1 transmission. Based on these data, we developed a mathematical model system to quantify the impact of different sd-NVP regimens at delivery and of extended infant NVP prophylaxis (6, 14, 21, 26, 52, 78, and 102 weeks) on the 2-year risk of HIV-1 transmission and development of drug resistance in mothers and their breast-fed infants. Pharmacokinetic parameter estimates and model-predicted HIV-1 transmission rates were very consistent with other studies. Predicted 2-year HIV-1 transmission risks were 35.8% without prophylaxis, 31.6% for newborn sd-NVP, 19.1% for maternal sd-NVP, and 19.7% for maternal/newborn sd-NVP. Maternal sd-NVP reduced newborn infection predominately by transplacental exchange, providing protective NVP concentrations to the newborn at delivery, rather than by maternal viral load reduction. Drug resistance was frequently selected in HIV-1-positive mothers after maternal sd-NVP. Extended newborn NVP prophylaxis further decreased HIV-1 transmission risks, but an overall decline in cost-effectiveness for increasing durations of newborn prophylaxis was indicated. The total number of infections with resistant virus in newborns was not increased by extended newborn NVP prophylaxis. The developed mathematical modeling framework successfully predicted the risk of HIV-1 transmission and resistance development and can be adapted to other drugs/drug combinations to a priori assess their potential in reducing vertical HIV-1 transmission and resistance spread.

Title

Quantifying the Impact of Nevirapine-Based Prophylaxis Strategies To Prevent Mother-to-Child Transmission of HIV-1: a Combined Pharmacokinetic, Pharmacodynamic, and Viral Dynamic Analysis To Predict Clinical Outcomes▿†

Author

M. Frank,1,4,‡ M. von Kleist,2,‡* A. Kunz,3 G. Harms,3 C. Schutte,2 and C. Kloft1,4,*

Publish date

2011 Dec;

PMID

26573600

Abstract

Background
The EORTC-QLQ-C30 is a widely used health related quality of life (HRQoL) questionnaire in lung cancer patients. Small HRQoL treatment effects are often reported as mean differences (MDs) between treatments, which are rarely justified or understood by patients and clinicians. An alternative approach using odds ratios (OR) for reporting effects is proposed. This may offer advantages including facilitating alignment between patient and clinician understanding of HRQoL effects.

Methods
Data from six CRUK sponsored randomized controlled lung cancer trials (2 small cell and 4 in non-small cell, in 2909 patients) were used to HRQoL effects. Results from Beta-Binomial (BB) standard mixed effects were compared. Preferences for ORs vs MDs were determined and Time to Deterioration (TD) was also compared.

Results
HRQoL effects using ORs offered coherent interpretations: MDs >0 resulted in ORs >1 and vice versa; effect sizes were classified as ‘Trivial’ if the OR was between 1 ± 0.05 (i.e. 0.95 to 1.05); ‘Small’: for 1 ± 0.1; ‘Medium’: 1 ± 0.2 and ‘Large’: OR <0.8 or >1.20. Small HRQoL effects on the MD scale may translate to important treatment differences on the OR scale: for example, a worsening in symptoms (MD) by 2.6 points (p = 0.1314) would be a 17 % deterioration (p < 0.0001) with an OR. Hence important differences may be missed with MD; conversely, small ORs are unlikely to yield large MDs because methods based on OR model skewed data well. Initial evidence also suggests oncologists prefer ORs over MDs since interpretation is similar to hazard ratios. Conclusion Reporting HRQoL benefits as MDs can be misleading. Estimates of HRQoL treatment effects in terms of ORs are preferred over MDs. Future analysis of QLQ-C30 and other HRQoL measures should consider reporting HRQoL treatment effects as ORs. Electronic supplementary material The online version of this article (doi:10.1186/s12955-015-0374-6) contains supplementary material, which is available to authorized users.

KEYWORDS

EORTC-QLQ-C30, Lung cancer, Quality of life, Beta binomial, Treatment effect size, MD: Mean Differences, ORs: Odds Ratios

Title

Interpreting small treatment differences from quality of life data in cancer trials: an alternative measure of treatment benefit and effect size for the EORTC-QLQ-C30

Author

Iftekhar Khan,corresponding author Zahid Bashir, and Martin Forster

Publish date

2015