Evidence map›Paper›PMID 23042787›Full record

ArticleJournal of lipid research2013

Tracking fatty acid kinetics in distinct lipoprotein fractions in vivo: a novel high-throughput approach for studying dyslipidemia in rodent models.

David G McLaren, Sheng-Ping Wang, Steven J Stout, Dan Xie, Paul L Miller, Vivienne Mendoza, Raymond Rosa, Jose Castro-Perez, Stephen F Previs, Douglas G Johns and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of lipid research, 2013. 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
0.3field-weighted citation impact, top 41% of its field
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, 13 citations in OpenAlex.

  1. Article
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  5. Article
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

11 authors at 1 institution in 1 country.

David G McLarenMerck Research Laboratories, Rahway, NJ 07065, USA.
Sheng-Ping Wang
Steven J Stout
Dan Xie
Paul L Miller
Vivienne Mendoza
Raymond Rosa
Jose Castro-Perez
Stephen F Previs
Douglas G Johns
Thomas P Roddy
Merck & Co., Inc., Rahway, NJ, USA (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Isotopic tracers have been used to examine lipid trafficking for many years, and data from those studies have typically yielded novel insight regarding the pathophysiology of dyslipidemia. Previous experimental designs were suitable for studies in humans because relatively large volumes of plasma could be regularly sampled. We have expanded on the earlier logic by applying high-throughput analytical methods that require reduced sample volumes. Specifically, we have examined the possibility of coupling gel-based separations of lipoproteins (e.g., lipoprint) with LC-MS/MS analyses of complex lipid mixtures as a way to routinely measure the labeling profiles of distinct lipids in discrete lipoprotein subfractions. We demonstrate the ability to measure the incorporation of [U-(13)C]oleate into triglycerides (TG), PLs (PL), and cholesterol esters (CE) in VLDL, LDL, and HDL particles in mice. Although rodent models of dyslipidemia are inherently different from humans because of alterations in enzyme activities and underlying metabolism, rodent models can be used to screen novel compounds for efficacy in altering a given biochemical pathway and therein enable studies of target engagement in vivo. We expect that it is possible to translate our approach for application in other systems, including studies in humans.

Indexed as

AnimalsBiological TransportChemical FractionationDisease Models, AnimalDyslipidemiasFatty AcidsHumansIsotope LabelingLipoproteinsMaleMiceMice, Inbred C57BLFatty AcidsLipoproteins

Identifiers

PMID23042787
PMCPMC3520534
OpenAlexW2150500042

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.