91521
癸酰基- L -肉碱
analytical standard
别名:
L -肉碱癸酸酯, C10-肉碱, （2 R ）-3-羧基- N ， N ， N -三甲基-2-[（1-氧代十二烷基）氧基]-1-丙胺 内盐
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关于此项目
经验公式（希尔记法）:
C17H33NO4
化学文摘社编号:
分子量:
315.45
NACRES:
NB.21
UNSPSC Code:
41116107
MDL number:
Beilstein/REAXYS Number:
4145305
grade
analytical standard
Quality Level
assay
≥94.0% (HPLC)
optical activity
[α]/D -15±3°, c = 0.1 in H2O
shelf life
limited shelf life, expiry date on the label
impurities
≤10% water
application(s)
clinical testing
format
neat
storage temp.
2-8°C
SMILES string
C[N+](C)(C)C[C@H](OC(CCCCCCCCC)=O)CC([O-])=O
InChI
1S/C17H33NO4/c1-5-6-7-8-9-10-11-12-17(21)22-15(13-16(19)20)14-18(2,3)4/h15H,5-14H2,1-4H3/t15-/m1/s1
InChI key
LZOSYCMHQXPBFU-OAHLLOKOSA-N
General description
Decanoyl-L-carnitine, belonging to the class of acylcarnitines, serves as a specific diagnostic metabolite biomarker, found in medium-chain acyl CoA dehydrogenase (MCAD) deficiency especially in newborns.
Application
Decanoyl-L-carnitine may be used as an analytical reference standard for the quantification of the analyte in the following:
- In dried blood spots using chip-based nanoelectrospray source coupled with high resolution mass spectrometry (chip-based nanoESI- HRMS) and targeted liquid chromatography-tandem mass spectrometry (LC/MS/MS).
- In biological samples using high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC/MS/MS).
Other Notes
Find a digital Reference Material for this product available on our online platform ChemisTwin® for NMR. You can use this digital equivalent on ChemisTwin® for your sample identity confirmation and compound quantification (with digital external standard). An NMR spectrum of this substance can be viewed and an online comparison against your sample can be performed with a few mouseclicks. Learn more here and start your free trial.
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存储类别
11 - Combustible Solids
wgk
WGK 3
flash_point_f
Not applicable
flash_point_c
Not applicable
Non-invasive test using palmitate in patients with suspected fatty acid oxidation defects: disease-specific acylcarnitine patterns can help to establish the diagnosis
Janzen N, et al.
Orphanet Journal of Rare Diseases, 12(1), 187-187 (2017)
Supervised machine learning techniques for the classification of metabolic disorders in newborns
Baumgartner C, et al.
Bioinformatics, 20(17), 2985-2996 (2004)
Quantification of metabolites in dried blood spots by direct infusion high resolution mass spectrometry
Van der Ham M, et al., et al.
Analytica Chimica Acta, 979, 45-50 (2017)
全球贸易项目编号
| 货号 | GTIN |
|---|---|
| D131504-25G | 04061833559413 |
| 91521-10MG | 04061834157175 |
| 91521-50MG | 04061834157182 |