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Ophiopogonin C


Catalogue Number : AV-P12579
Specification : 98%
CAS number : 911819-08-4
Formula : C46H72O17
Molecular Weight : 897.05
PUBCHEM ID : 90477999
Volume : 5mg

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Catalogue Number


Analysis Method






Molecular Weight




Botanical Source

Ophiopogonis Radix

Structure Type







[(1S,2S,4S,5'R,6R,7S,8R,9S,12S,13R,14R,16R)-14-[(2S,3R,4S,5S,6R)-5-hydroxy-6-methyl-3-[(2S,3R,4R,5R,6S)-3,4,5-trihydroxy-6-methyloxan-2-yl]oxy-4-[(2S,3R,4S,5R)-3,4,5-trihydroxyoxan-2-yl]oxyoxan-2-yl]oxy-5',7,9,13-tetramethylspiro[5-oxapentacyclo[,9.04,8.013,18]icos-18-ene-6,2'-oxane]-16-yl] acetate


1.5±0.1 g/cm3


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

Flash Point

Boiling Point

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#:911819-08-4) 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.




Type 1 diabetes is a condition in which the pancreas produces little or no insulin. People with type 1 diabetes must manage their blood glucose levels by monitoring the amount of glucose in their blood and administering appropriate amounts of insulin via injection or an insulin pump. Continuous glucose monitoring may be beneficial compared to self-monitoring of blood glucose using a blood glucose meter. It provides insight into a person’s blood glucose levels on a continuous basis, and can identify whether blood glucose levels are trending up or down.

We conducted a health technology assessment, which included an evaluation of clinical benefit, value for money, and patient preferences related to continuous glucose monitoring. We compared continuous glucose monitoring with self-monitoring of blood glucose using a finger-prick and a blood glucose meter. We performed a systematic literature search for studies published since January 1, 2010. We created a Markov model projecting the lifetime horizon of adults with type 1 diabetes, and performed a budget impact analysis from the perspective of the health care payer. We also conducted interviews and focus group discussions with people who self-manage their type 1 diabetes or support the management of a child with type 1 diabetes.

Twenty studies were included in the clinical evidence review. Compared with self-monitoring of blood glucose, continuous glucose monitoring improved the percentage of time patients spent in the target glycemic range by 9.6% (95% confidence interval 8.0-11.2) to 10.0% (95% confidence interval 6.75-13.25) and decreased the number of severe hypoglycemic events.

Continuous glucose monitoring was associated with higher costs and small increases in health benefits (quality-adjusted life-years). Incremental cost-effectiveness ratios (ICERs) ranged from $592,206 to $1,108,812 per quality-adjusted life-year gained in analyses comparing four continuous glucose monitoring interventions to usual care. However, the uncertainty around the ICERs was large. The net budget impact of publicly funding continuous glucose monitoring assuming a 20% annual increase in adoption of continuous glucose monitoring would range from $8.5 million in year 1 to $16.2 million in year 5.

Patient engagement surrounding the topic of continuous glucose monitoring was robust. Patients perceived that these devices provided important social, emotional, and medical and safety benefits in managing type 1 diabetes, especially in children.

Continuous glucose monitoring was more effective than self-monitoring of blood glucose in managing type 1 diabetes for some outcomes, such as time spent in the target glucose range and time spent outside the target glucose range (moderate certainty in this evidence). We were less certain that continuous glucose monitoring would reduce the number of severe hypoglycemic events. Compared with self-monitoring of blood glucose, the costs of continuous glucose monitoring were higher, with only small increases in health benefits. Publicly funding continuous glucose monitoring for the type 1 diabetes population in Ontario would result in additional costs to the health system over the next 5 years. Adult patients and parents of children with type 1 diabetes reported very positive experiences with continuous glucose monitoring. The high ongoing cost of continuous glucose monitoring devices was seen as the greatest barrier to their widespread use.


Continuous Monitoring of Glucose for Type 1 Diabetes: A Health Technology Assessment


Health Quality Ontario

Publish date





Digital PCR offers very high sensitivity compared to many other technologies for processing molecular detection assays. Herein, a process is outlined for determining the lower limit of detection (LoD) of two droplet-based digital PCR assays for point mutations of the epidermal growth factor receptor (EGFR) gene. Hydrolysis probe mutation-detection assays for EGFR p.L858R and p.T790M mutations were characterized in detail. Furthermore, sixteen additional cancer-related mutation assays were explored by the same approach. For the EGFR L8585R assay, the assay sensitivity is extremely good, and thus, the LoD is limited by the amount of amplifiable DNA that is analyzed. With 95% confidence limits, the LoD is one mutant in 180,000 wild-type molecules for the evaluation of 3.3 μg of genomic DNA, and detection of one mutant molecule in over 4 million wild-type molecules was achieved when 70 million copies of DNA were processed. The measured false-positive rate for the EGFR L8585R assay is one in 14 million, which indicates the theoretical LoD if an unlimited amount of DNA is evaluated. For the EFGR T790M assay, the LoD is one mutant in 13,000 for analysis of a 3.3 μg sample of genomic DNA, and the dPCR assay limit sensitivity approaches one mutant in 22,000 wild-type molecules.

Abbreviations: PCR, Polymerase Chain Reaction; EGFR, epidermal growth factor receptor; LoB, limit of blank; LoD, limit of detection; N, total number of droplet events counted; NWT, number of droplets with only wild-type DNA; NMut, number of droplets with only mutated DNA; λ, average number of targets “loaded” per droplet; p, fraction of PCR-positive droplets; R, ratio of mutant to wild-type molecules; ΛFP, average number of false-positive events; RFP, average false positive rate (ΛFP/#WT)


Digital PCR, Mutation detection, Limit of detection, Assay sensitivity, EGFR L858R, EGFR T790M


Determining lower limits of detection of digital PCR assays for cancer-related gene mutations


Coren A. Milbury,1,? Qun Zhong,1 Jesse Lin, Miguel Williams, Jeff Olson, Darren R. Link, and Brian Hutchison

Publish date

2014 Sep;