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SBR00052

Sigma-Aldrich

Semi Polar Metabolites QC Mix

suitable for LC-MS

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About This Item

UNSPSC Code:
41116107
NACRES:
NA.28

form

liquid

Quality Level

packaging

pkg of 1 vial

suitability

suitable for LC-MS

storage temp.

2-8°C

General description

In order to assess any variations in LC-MS-based metabolomics analysis data, it is recommended to add an additional QC (quality control) sample at the beginning of every analytical experiment batch. It is recommended that QC be injected every 4-10 injections into the workflow steps . The QC sample evaluates any drifting phenomenon like intensity values, ion suppression, or any changes in the retention time of the material’s peaks in the LC-MS data. The Semi Polar Metabolites QC Mix is a ready to use solution for mass spectroscopy workflows. By utilizing the QC mix, the user will be able to assess drifting and ion suppression phenomenon. The Semi Polar Metabolites QC Mix is comprised of 9 components (Uridine, Adenosine, Guanosine, 4-Hydroxybenzoic acid, Vanillic acid, Melatonin, Taurocholic acid, Cholic acid, and Hyodeoxycholic acid) which covers ~100-500 Da mass range.

Features and Benefits

  • The mix was designed for ESI (+/-) detection.
  • The mixture comes as a ready to use solution(~9:1 water: ACN) format in crimp top (Silicone/PTFE liner) amber vial, which is suitable for use with most of the LC-MS autosamplers.
  • The recommended storage temperature of the mixture is 2-8°C, thawing of the sample is not required.

Suitability

The Semi Polar Metabolites QC Mix is suitable for mass spectroscopy.

Pictograms

Flame

Signal Word

Warning

Hazard Statements

Hazard Classifications

Flam. Liq. 3

Storage Class Code

3 - Flammable liquids

WGK

WGK 3

Flash Point(F)

80.6 °F

Flash Point(C)

27 °C


Certificates of Analysis (COA)

Search for Certificates of Analysis (COA) by entering the products Lot/Batch Number. Lot and Batch Numbers can be found on a product’s label following the words ‘Lot’ or ‘Batch’.

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LC-MS-based metabolomics
Zhou, B et al
Molecular Biosystems, 8(2), 470-481 (2012)
From samples to insights into metabolism: Uncovering biologically relevant information in LC-HRMS metabolomics data
Ivanisevic, J., & Want, E. J.
Metabolites, 9(12), 308-308 (2019)

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