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Catalogue Number
AV-B03229
Analysis Method
HPLC,NMR,MS
Specification
95%
Storage
2-8°C
Molecular Weight
320.47
Appearance
Powder
Botanical Source
Structure Type
Diterpenoids
Category
Standards;Natural Pytochemical;API
SMILES
CC1(C2CCC34CCC(CC3C2(CCC1=O)C)C(C4)(CO)O)C
Synonyms
(5β,8α,9β,10α)-16,17-Dihydroxyatisan-3-one/Atisan-3-one, 16,17-dihydroxy-, (5β,8α,9β,10α)-
IUPAC Name
(1S,4S,9S,10R,12R,13S)-13-hydroxy-13-(hydroxymethyl)-5,5,9-trimethyltetracyclo[10.2.2.01,10.04,9]hexadecan-6-one
Applications
Density
1.2±0.1 g/cm3
Solubility
Soluble in Chloroform,Dichloromethane,Ethyl Acetate,DMSO,Acetone,etc.
Flash Point
246.1±25.2 °C
Boiling Point
460.0±45.0 °C at 760 mmHg
Melting Point
174-175℃
InChl
InChI=1S/C20H32O3/c1-17(2)14-5-9-19-8-4-13(20(23,11-19)12-21)10-15(19)18(14,3)7-6-16(17)22/h13-15,21,23H,4-12H2,1-3H3/t13-,14-,15+,18-,19-,20-/m1/s1
InChl Key
GFMRAAZMCOCUCY-ALCQSMKISA-N
WGK Germany
RID/ADR
HS Code Reference
Personal Projective Equipment
Correct Usage
For Reference Standard and R&D, Not for Human Use Directly.
Meta Tag
provides coniferyl ferulate(CAS#:112523-91-8) 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.
20852632
Ovarian cancer (OC) accounts for more deaths than all other gynecological cancers combined. To identify common low-penetrance OC susceptibility genes, we conducted a genome-wide association study (GWAS) of 507,094 SNPs in 1,768 cases and 2,354 controls, with follow-up of 21,955 SNPs in 4,162 cases and 4,810 controls, leading to the identification of a confirmed susceptibility locus at 9p22 (BNC2)1. Here, we report on nine additional candidate loci (p≤10-4), identified after stratifying cases by histology, genotyped in an additional 4,353 cases and 6,021 controls. Two novel susceptibility loci with p≤5×10-8 were confirmed (8q24, p=8.0×10-15 and 2q31, p=3.8×10-14); two additional loci were also identified that approached genome-wide significance (3q25, p=7.1×10-8 and 17q21, p=1.4×10-7). The associations with serous OC were generally stronger than other subtypes. Analysis of HOXD1, MYC, TiPARP, and SKAP1 at these loci, and BNC2 at 9p22, supports a functional role for these genes in OC development.
A Genome-Wide Association Study Identifies Susceptibility Loci for Ovarian Cancer at 2q31 and 8q24
Ellen L. Goode, Georgia Chenevix-Trench, Honglin Song, Susan J. Ramus, Maria Notaridou, Kate Lawrenson, Martin Widschwendter, Robert A. Vierkant, Melissa C. Larson, Susanne K. Kjaer, Michael J. Birrer, Andrew Berchuck, Joellen Schildkraut, Ian Tomlinson, Lambertus A. Kiemeney, Linda S. Cook, Jacek Gronwald, Montserrat Garcia-Closas, Martin E. Gore, Ian Campbell, Alice S. Whittemore, Rebecca Sutphen, Catherine Phelan, Hoda Anton-Culver, Celeste Leigh Pearce, Diether Lambrechts, Mary Anne Rossing, Jenny Chang-Claude, Kirsten B. Moysich, Marc T. Goodman, Thilo Dork, Heli Nevanlinna, Roberta B. Ness, Thorunn Rafnar, Claus Hogdall, Estrid Hogdall, Brooke L. Fridley, Julie M. Cunningham, Weiva Sieh, Valerie McGuire, Andrew K. Godwin, Daniel W. Cramer, Dena Hernandez, Douglas Levine, Karen Lu, Edwin S. Iversen, Rachel T. Palmieri, Richard Houlston, Anne M. van Altena, Katja K.H. Aben, Leon F.A.G. Massuger, Angela Brooks-Wilson, Linda E. Kelemen, Nhu D. Le, Anna Jakubowska, Jan Lubinski, Krzysztof Medrek, Anne Stafford, Douglas F. Easton, Jonathan Tyrer, Kelly L. Bolton, Patricia Harrington, Diana Eccles, Ann Chen, Ashley N. Molina, Barbara N. Davila, Hector Arango, Ya-Yu Tsai, Zhihua Chen, Harvey A. Risch, John McLaughlin, Steven A. Narod, Argyrios Ziogas, Wendy Brewster, Aleksandra Gentry-Maharaj, Usha Menon, Anna H. Wu, Daniel O. Stram, Malcolm C. Pike, The Wellcome Trust Case-Control Consortium, Jonathan Beesley, Penelope M. Webb, The Australian Cancer Study (Ovarian Cancer), The Australian Ovarian Cancer Study Group, Xiaoqing Chen, Arif B. Ekici, Falk C. Thiel, Matthias W. Beckmann, Hannah Yang, Nicolas Wentzensen, Jolanta Lissowska, Peter A. Fasching, Evelyn Despierre, Frederic Amant, Ignace Vergote, Jennifer Doherty, Rebecca Hein, Shan Wang-Gohrke, Galina Lurie, Michael E. Carney, Pamela J. Thompson, Ingo Runnebaum, Peter Hillemanns, Matthias Durst, Natalia Antonenkova, Natalia Bogdanova, Arto Leminen, Ralf Butzow, Tuomas Heikkinen, Kari Stefansson, Patrick Sulem, Soren Besenbacher, Thomas A. Sellers, Simon A. Gayther, Paul D.P. Pharoah
2011 Oct 1.
28085997
Objective
To investigate whether menopausal factors are associated with development of serologic rheumatoid arthritis (RA) phenotypes.
Methods
Data were analyzed from Nurses’ Health Studies (NHS, 1976-2010; NHSII 1989-2011). In NHS 120,700 female nurses aged 30-55 and in NHSII 116,430 female nurses aged 25-42 were followed via biennial questionnaires on lifestyle and disease outcomes. In total, 1,096 incident RA cases were confirmed by questionnaire and chart review. Seropositive RA was defined as +RF or ACPA+; seronegative RA as -RF and ACPA?. We used Cox proportional hazards models to obtain multivariable adjusted hazard ratios (HR) with 95% confidence intervals (CI) of seropositive/-negative RA associated with menopausal status, age at menopause, type of menopause, ovulatory years and postmenopausal hormone therapy (PMH) use.
Results
Postmenopausal women had a two-fold increased risk of seronegative RA, compared with premenopausal women (NHS: HR 1.8, 95% CI 1.1-3.0; NHSII: HR 2.4, 95% CI 1.4-3.9; pooled HR 2.1, 95% CI 1.4-3.0). Natural menopause at early age (≤ 44) was associated with an increased risk of seronegative RA (pooled HR 2.4, 95% CI 1.5-4.0). None of the menopausal factors was significantly associated with seropositive RA. We observed no association between PMH use and the risk of seronegative or seropositive RA, except that PMH use of ≥8 years was associated with increased risk of seropositive RA (pooled HR 1.4, 95% CI 1.1-1.9).
Conclusion
Postmenopause and natural menopause at early age were strongly associated with seronegative RA, but only marginally with seropositive RA, suggesting potential differences in the etiology of RA subtypes.
Menopausal factors are associated with seronegative RA in large prospective cohorts: results from the Nurses’ Health Studies
Camilla Bengtsson, Susan Malspeis, Cecilia Orellana, Jeffrey A. Sparks, Karen H. Costenbader, Elizabeth W. Karlson
2018 Nov 1.
25033452
Background
Identifying areas that support high malaria risks and where populations lack access to health care is central to reducing the burden in Afghanistan. This study investigated the incidence of Plasmodium vivax and Plasmodium falciparum using routine data to help focus malaria interventions.
Methods
To estimate incidence, the study modelled utilisation of the public health sector using fever treatment data from the 2012 national Malaria Indicator Survey. A probabilistic measure of attendance was applied to population density metrics to define the proportion of the population within catchment of a public health facility. Malaria data were used in a Bayesian spatio-temporal conditional-autoregressive model with ecological or environmental covariates, to examine the spatial and temporal variation of incidence.
Findings
From the analysis of healthcare utilisation, over 80% of the population was within 2 hours’ travel of the nearest public health facility, while 64.4% were within 30 minutes’ travel. The mean incidence of P. vivax in 2009 was 5.4 (95% Crl 3.2-9.2) cases per 1000 population compared to 1.2 (95% Crl 0.4-2.9) cases per 1000 population for P. falciparum. P. vivax peaked in August while P. falciparum peaked in November. 32% of the estimated 30.5 million people lived in regions where annual incidence was at least 1 case per 1,000 population of P. vivax; 23.7% of the population lived in areas where annual P. falciparum case incidence was at least 1 per 1000.
Conclusion
This study showed how routine data can be combined with household survey data to model malaria incidence. The incidence of both P. vivax and P. falciparum in Afghanistan remain low but the co-distribution of both parasites and the lag in their peak season provides challenges to malaria control in Afghanistan. Future improved case definition to determine levels of imported risks may be useful for the elimination ambitions in Afghanistan.
Modelling the Incidence of Plasmodium vivax and Plasmodium falciparum Malaria in Afghanistan 2006-2009
Victor A. Alegana, Jim A. Wright, Sami M. Nahzat, Waqar Butt, Amad W. Sediqi, Naeem Habib, Robert W. Snow, Peter M. Atkinson, Abdisalan M. Noor
2014