Evidence map›Paper›PMID 32946185›Full record

ArticleJournal of separation science2020

Comparison of microcapillary column length and inner diameter investigated with gradient analysis of lipids by ultrahigh-pressure liquid chromatography-mass spectrometry.

Kelsey E Miller, James W Jorgenson

Abstract readComparative Study
In one paragraph

Article in Journal of separation science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Kelsey E MillerCenter for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, 27709, USA.ORCID https://orcid.org/0000-0002-7704-4103
James W JorgensonDepartment of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, 27599, USA.

Funding

High Resolution MetabolomicsR01DK101473 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KENNEDY, ROBERT T · 2015 to 2018
$1000k
NIDDK NIH HHS R01 DK101473
6 · The paper itself

Abstract

Biological samples in lipidomic studies can consist of extremely complex mixtures due to the diverse range of species and isomerism. Herein, highly efficient, in-house packed microcapillary columns introduce the potential to better separate these complex mixtures. We compared the effects of changing column length (15, 30, and 60 cm) and inner diameter (75 and 100 μm) on lipid separation efficiency by reversed-phase gradient analysis using ultrahigh-pressure liquid chromatography coupled to mass spectrometry with operating pressures ranging from 450 to 2200 bar. Seven lipid standards composed of phosphatidylcholine and triacylglycerol species were analyzed at four different gradient rates to calculate conditional peak capacity. The longest column, 60 cm, at the shallowest gradient of 2% gave the highest peak capacity of 359 with a separation window of 2 h. The intermediate column length of 30 cm with 75 μm inner diameter provided a peak capacity of 287 with a separation window of 1 h. There was no significant difference in peak capacity between 75 and 100 μm inner diameter columns. This study showed that using highly efficient microcapillary columns increased peak capacity and resolution of lipids, and thus, this technique seems promising for enhancing lipid coverage and enabling better discovery of lipid biomarkers.

Indexed as

Chromatography, High Pressure LiquidLipidsMass SpectrometryParticle SizeLipidsgradient elutionlipidomicsmass spectrometrypeak capacityultrahigh-pressure liquid chromatography

Identifiers

PMID32946185
PMCPMC7727313

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.