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Cucurbitacin Q1


Catalogue Number : BD-P0396
Specification : 98.0%(HPLC)
CAS number : 99530-82-2
Formula : C32H48O8
Molecular Weight : 560.71872
PUBCHEM ID : 14165733
Volume : 25mg

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[(E,6R)-6-hydroxy-2-methyl-5-oxo-6-[(2S,3S,8S,9R,10R,13R,14S,16R,17R)-2,3,16-trihydroxy-4,4,9,13,14-pentamethyl-11-oxo-1,2,3,7,8,10,12,15,16,17-decahydrocyclopenta[a]phenanthren-17-yl]hept-3-en-2-yl] acetate


[(E,6R)-6-hydroxy-2-methyl-5-oxo-6-[(2S,3S,8S,9R,10R,13R,14S,16R,17R)-2,3,16-trihydroxy-4,4,9,13,14-pentamethyl-11-oxo-1,2,3,7,8,10,12,15,16,17-decahydrocyclopenta[a]phenanthren-17-yl]hept-3-en-2-yl] acetate



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

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

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provides coniferyl ferulate(CAS#:99530-82-2) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate

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In recent decades, there has been a shift to later childbearing in high-income countries. There is limited large-scale evidence of the relationship between maternal age and child outcomes beyond the perinatal period. The objective of this study is to quantify a child’s risk of developmental vulnerability at age five, according to their mother’s age at childbirth.

Methods and findings
Linkage of population-level perinatal, hospital, and birth registration datasets to data from the Australian Early Development Census (AEDC) and school enrolments in Australia’s most populous state, New South Wales (NSW), enabled us to follow a cohort of 99,530 children from birth to their first year of school in 2009 or 2012. The study outcome was teacher-reported child development on five domains measured by the AEDC, including physical health and well-being, emotional maturity, social competence, language and cognitive skills, and communication skills and general knowledge. Developmental vulnerability was defined as domain scores below the 2009 AEDC 10th percentile cut point.

The mean maternal age at childbirth was 29.6 years (standard deviation [SD], 5.7), with 4,382 children (4.4%) born to mothers aged <20 years and 20,026 children (20.1%) born to mothers aged ≥35 years. The proportion vulnerable on ≥1 domains was 21% overall and followed a reverse J-shaped distribution according to maternal age: it was highest in children born to mothers aged ≤15 years, at 40% (95% CI, 32-49), and was lowest in children born to mothers aged between 30 years and ≤35 years, at 17%-18%. For maternal ages 36 years to ≥45 years, the proportion vulnerable on ≥1 domains increased to 17%-24%. Adjustment for sociodemographic characteristics significantly attenuated vulnerability risk in children born to younger mothers, while adjustment for potentially modifiable factors, such as antenatal visits, had little additional impact across all ages. Although the multi-agency linkage yielded a broad range of sociodemographic, perinatal, health, and developmental variables at the child’s birth and school entry, the study was necessarily limited to variables available in the source data, which were mostly recorded for administrative purposes. Conclusions Increasing maternal age was associated with a lesser risk of developmental vulnerability for children born to mothers aged 15 years to about 30 years. In contrast, increasing maternal age beyond 35 years was generally associated with increasing vulnerability, broadly equivalent to the risk for children born to mothers in their early twenties, which is highly relevant in the international context of later childbearing. That socioeconomic disadvantage explained approximately half of the increased risk of developmental vulnerability associated with younger motherhood suggests there may be scope to improve population-level child development through policies and programs that support disadvantaged mothers and children.


Maternal age and offspring developmental vulnerability at age five: A population-based cohort study of Australian children


Kathleen Falster, Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Writing - original draft,1,2,3,* Mark Hanly, Conceptualization, Data curation, Formal analysis, Methodology, Writing - review & editing,1 Emily Banks, Conceptualization, Funding acquisition, Methodology, Supervision, Writing - review & editing,2,4 John Lynch, Conceptualization, Funding acquisition, Methodology, Writing - review & editing,5,6 Georgina Chambers, Methodology, Writing - review & editing,1 Marni Brownell, Conceptualization, Funding acquisition, Methodology, Writing - review & editing,7 Sandra Eades, Conceptualization, Funding acquisition, Methodology, Writing - review & editing,8 and Louisa Jorm, Conceptualization, Funding acquisition, Methodology, Supervision, Writing - review & editing1

Publish date

2018 Apr;




Retrievals of atmospheric composition from near-infrared measurements require measurements of airmass to better than the desired precision of the composition. The oxygen bands are obvious choices to quantify airmass since the mixing ratio of oxygen is fixed over the full range of atmospheric conditions. The OCO-2 mission is currently retrieving carbon dioxide concentration using the oxygen A-band for airmass normalization. The 0.25% accuracy desired for the carbon dioxide concentration has pushed the required state-of-the-art for oxygen spectroscopy. To measure O2 A-band cross-sections with such accuracy through the full range of atmospheric pressure requires a sophisticated line-shape model (Rautian or Speed-Dependent Voigt) with line mixing (LM) and collision induced absorption (CIA). Models of each of these phenomena exist, however, this work presents an integrated self-consistent model developed to ensure the best accuracy.

It is also important to consider multiple sources of spectroscopic data for such a study in order to improve the dynamic range of the model and to minimize effects of instrumentation and associated systematic errors. The techniques of Fourier Transform Spectroscopy (FTS) and Cavity Ring-Down Spectroscopy (CRDS) allow complimentary information for such an analysis. We utilize multispectrum fitting software to generate a comprehensive new database with improved accuracy based on these datasets. The extensive information will be made available as a multi-dimensional cross-section (ABSCO) table and the parameterization will be offered for inclusion in the HITRANonline database.


oxygen, atmospheric absorption, collision-induced absorption, multispectrum fitting, spectral lineshapes


Multispectrum analysis of the oxygen A-band


Brian J. Drouin,a D. Chris Benner,b Linda R. Brown,a Matthew J. Cich,a Timothy J. Crawford,a V. Malathy Devi,b Alexander Guillaume,a Joseph T. Hodges,c Eli J. Mlawer,d David J. Robichaud,e Fabiano Oyafuso,a Vivienne H. Payne,a Keeyoon Sung,a Edward H. Wishnow,f and Shanshan Yua

Publish date

2018 Jan 1.




Heterochronic development has been proposed to have played an important role in the evolution of echinoderms. In the class Ophiuroidea, paedomorphosis (retention of juvenile characters into adulthood) has been documented in the families Ophiuridae and Ophiolepididae but not been investigated on a broader taxonomic scale. Historical errors, confusing juvenile stages with paedomorphic species, show the difficulties in correctly identifying the effects of heterochrony on development and evolution. This study presents a detailed analysis of 40 species with morphologies showing various degrees of juvenile appearance in late ontogeny. They are compared to a range of early ontogenetic stages from paedomorphic and non-paedomorphic species. Both quantitative and qualitative measurements are taken and analysed. The results suggest that strongly paedomorphic species are usually larger than other species at comparable developmental stage. The findings support recent notions of polyphyletic origin of the families Ophiuridae and Ophiolepididae. The importance of paedomorphosis and its correct recognition for the practice of taxonomy and phylogeny are emphasized.


Paedomorphosis as an Evolutionary Driving Force: Insights from Deep-Sea Brittle Stars


Sabine Stohr1,* and Alexander Martynov2,*

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