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Discovery hs f5 3 column

Manufactured by Thermo Fisher Scientific
Sourced in United States

The Discovery HS F5-3 column is a high-performance liquid chromatography (HPLC) column designed for reversed-phase separation of a wide range of compounds. The column features a 5-micron particle size and a C18 stationary phase, providing efficient and reproducible separations across a variety of applications.

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2 protocols using discovery hs f5 3 column

1

Lipid Extraction and Metabolite Profiling of Kidney Samples

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The total lipids were extracted from the kidney with the Bligh and Dyer method (Bligh and Dyer, 1959 (link)). The lipids were applied to the silica gel column (InertSep SI; GL Sciences) and eluted isocratically with chloroform and methanol. The fraction IR–9:1, which has high ligand activity, was used for further analysis. For nontargeted analysis, metabolome data obtained by orbitrap-type MS (Q-Exactive focus; Thermo Fisher Scientific) connected to an HPLC (UltiMate 3000 system; Thermo Fisher Scientific) with the discovery HS F5-3 column or an ion chromatography (ICS-5000+; Thermo Fisher Scientific) with the IonPac AS11-HC, 4-µm particle size column were analyzed. A Compound Discoverer 2.0 (Thermo Fisher Scientific) was used for the nontargeted metabolomics workflow as described (Miyajima et al., 2017 (link)).
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2

Metabolomic Analysis of Maple Sap

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Ethanol extracts of DT sap and Acer saccharum (AS) sap (Alleghanys Maple Farms Inc., Saint-Pacome, QC, Canada) were analyzed as previously described [23 (link)]. Briefly, for non-targeted analysis, metabolome data obtained by orbitrap-type MS (Q-Exactive Focus, Thermo Fisher Scientific, San Jose, CA, USA) connected to a HPLC (Ultimate3000 system, Thermo Fisher Scientific) with the discovery HS F5-3 column or an IC (ICS-5000+, Thermo Fisher Scientific) with the IonPac AS11-HC, 4-μm particle size column were analyzed. A Compound Discoverer 2.0 (Thermo Fisher Scientific) was used for the non-targeted metabolomics workflow. In brief, this software first aligned the total ion chromatograms of different samples along the retention time. Then, the detected features with an intensity of no less than 100,000 and an S/N larger than five in each set of data were extracted and merged into components. The resulting compounds were identified by both (i) formula prediction based on accurate m/z value and isotope peak patterns and (ii) MS/MS structural validation. Moreover, formula predicted signals were assigned into candidate compounds by database search (Chemspider database; http://www.chemspider.com/, accessed on 19 December 2019).
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