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  • Brand : BIOFRON

  • Catalogue Number : AV-B02063

  • Specification : 95%

  • CAS number : 74336-91-7

  • Formula : C32H22O10

  • Molecular Weight : 566.51

  • PUBCHEM ID : 14015870

  • Volume : 5mg

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Catalogue Number


Analysis Method






Molecular Weight



Yellow powder

Botanical Source

Structure Type



Standards;Natural Pytochemical;API




[8,8'-Bi-4H-1-benzopyran]-4,4'-dione, 5,5',7,7'-tetrahydroxy-2,2'-bis(4-methoxyphenyl)-/4',4'''-Di-O-methylcupressuflavone/5,5',7,7'-Tetrahydroxy-2,2'-bis(4-methoxyphenyl)-4H,4'H-8,8'-bichromene-4,4'-dione




1.5±0.1 g/cm3


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

Flash Point

288.2±27.8 °C

Boiling Point

866.6±65.0 °C at 760 mmHg

Melting Point


InChl Key


WGK Germany


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#:74336-91-7) 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.




The title compound, C25H25N3O, comprises a 2-amino­pyridine ring fused with a cyclo­heptane ring, which adopts a chair conformation. The central pyridine ring (r.m.s. deviation = 0.013?a) carries three substituents, viz. a benzyl­amino group, a meth­oxy­phenyl ring and a carbo­nitrile group. The N atom of the carbo­nitrile group is significantly displaced [by 0.2247?(1)?a] from the plane of the pyridine ring, probably due to steric crowding involving the adjacent substituents. The phenyl and benzene rings are inclined to one another by 58.91?(7)° and to the pyridine ring by 76.68?(7) and 49.80?(6)°, respectively. In the crystal, inversion dimers linked by pairs of N?H?Nnitrile hydrogen bonds generate R 2 2(14) loops. The dimers are link


crystal structure, cyclo­hepta­pyridine, carbo­nitrile, hydrogen bonding, C?H?π inter­actions, slipped parallel π-π inter­actions


Crystal structure of 2-benzyl­amino-4-(4-meth­oxy­phen­yl)-6,7,8,9-tetra­hydro-5H-cyclo­hepta­[b]pyridine-3-carbo­nitrile


R. A. Nagalakshmi,a J. Suresh,a S. Maharani,b R. Ranjith Kumar,b and P. L. Nilantha Lakshmanc,*

Publish date

2014 Dec 1;




The Dothideomycete fungus Mycosphaerella graminicola is the causal agent of Septoria tritici blotch, a devastating disease of wheat leaves that causes dramatic decreases in yield. Infection involves an initial extended period of symptomless intercellular colonisation prior to the development of visible necrotic disease lesions. Previous functional genomics and gene expression profiling studies have implicated the production of secreted virulence effector proteins as key facilitators of the initial symptomless growth phase. In order to identify additional candidate virulence effectors, we re-analysed and catalogued the predicted protein secretome of M. graminicola isolate IPO323, which is currently regarded as the reference strain for this species. We combined several bioinformatic approaches in order to increase the probability of identifying truly secreted proteins with either a predicted enzymatic function or an as yet unknown function. An initial secretome of 970 proteins was predicted, whilst further stringent selection criteria predicted 492 proteins. Of these, 321 possess some functional annotation, the composition of which may reflect the strictly intercellular growth habit of this pathogen, leaving 171 with no functional annotation. This analysis identified a protein family encoding secreted peroxidases/chloroperoxidases (PF01328) which is expanded within all members of the family Mycosphaerellaceae. Further analyses were done on the non-annotated proteins for size and cysteine content (effector protein hallmarks), and then by studying the distribution of homologues in 17 other sequenced Dothideomycete fungi within an overall total of 91 predicted proteomes from fungal, oomycete and nematode species. This detailed M. graminicola secretome analysis provides the basis for further functional and comparative genomics studies.


Defining the Predicted Protein Secretome of the Fungal Wheat Leaf Pathogen Mycosphaerella graminicola


Alexandre Morais do Amaral, 1 , 2 , * John Antoniw, 2 Jason J. Rudd, 2 and Kim E. Hammond-Kosack 2

Publish date





Lifestyle risk behaviors are responsible for a large proportion of disease burden worldwide. Behavioral risk factors, such as smoking, poor diet, and physical inactivity, tend to cluster within populations and may have synergistic effects on health. As evidence continues to accumulate on emerging lifestyle risk factors, such as prolonged sitting and unhealthy sleep patterns, incorporating these new risk factors will provide clinically relevant information on combinations of lifestyle risk factors.

Methods and Findings
Using data from a large Australian cohort of middle-aged and older adults, this is the first study to our knowledge to examine a lifestyle risk index incorporating sedentary behavior and sleep in relation to all-cause mortality. Baseline data (February 2006- April 2009) were linked to mortality registration data until June 15, 2014. Smoking, high alcohol intake, poor diet, physical inactivity, prolonged sitting, and unhealthy (short/long) sleep duration were measured by questionnaires and summed into an index score. Cox proportional hazards analysis was used with the index score and each unique risk combination as exposure variables, adjusted for socio-demographic characteristics.

During 6 y of follow-up of 231,048 participants for 1,409,591 person-years, 15,635 deaths were registered. Of all participants, 31.2%, 36.9%, 21.4%, and 10.6% reported 0, 1, 2, and 3+ risk factors, respectively. There was a strong relationship between the lifestyle risk index score and all-cause mortality. The index score had good predictive validity (c index = 0.763), and the partial population attributable risk was 31.3%. Out of all 96 possible risk combinations, the 30 most commonly occurring combinations accounted for more than 90% of the participants. Among those, combinations involving physical inactivity, prolonged sitting, and/or long sleep duration and combinations involving smoking and high alcohol intake had the strongest associations with all-cause mortality. Limitations of the study include self-reported and under-specified measures, dichotomized risk scores, lack of long-term patterns of lifestyle behaviors, and lack of cause-specific mortality data.

Adherence to healthy lifestyle behaviors could reduce the risk for death from all causes. Specific combinations of lifestyle risk behaviors may be more harmful than others, suggesting synergistic relationships among risk factors.


Traditional and Emerging Lifestyle Risk Behaviors and All-Cause Mortality in Middle-Aged and Older Adults: Evidence from a Large Population-Based Australian Cohort


ing Ding, 1 , 2 ,* Kris Rogers, 1 , 3 Hidde van der Ploeg, 1 , 4 Emmanuel Stamatakis, 2 , 5 and Adrian E. Bauman 1 , 2 James K. Tumwine, Academic Editor

Publish date

2015 Dec

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