Evidence map›Paper›PMID 17476547›Full record

ArticleLipids2007

Metabolic syndrome: effects of n-3 PUFAs on a model of dyslipidemia, insulin resistance and adiposity.

Yolanda B Lombardo, Gustavo Hein, Adriana Chicco

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Lipids, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
11.5field-weighted citation impact, top 1% 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

26 citing papers in PubMed, 126 citations in OpenAlex.

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  2. Very-long-chainThe American journal of clinical nutrition · 2017
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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

3 authors at 1 institution in 1 country.

Yolanda B LombardoDepartment of Biochemistry, School of Biochemistry, University of Litoral, Ciudad Universitaria Paraje EL Pozo, Santa Fe, Argentina. ylombard@fbcb.unl.edu.ar
Gustavo Hein
Adriana Chicco
National University of the Littoral · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Both genetic and environmental factors (e.g. nutrition, life style) contribute to the development of the plurimetabolic syndrome, which has a high prevalence in the world population. Dietary n-3 PUFAs specially those from marine oil (EPA and DHA) appear to play an important role against the adverse effects of this syndrome. The present work examined the effectiveness of fish oil (FO) in reversing or improving the dyslipidemia, insulin resistance and adiposity induced in rats by long-term feeding a sucrose-rich diet (SRD). We studied several metabolic and molecular mechanisms involved in both lipid and glucose metabolisms in different tissues (liver, skeletal muscle, fat pad) as well as insulin secretion patterns from perifused islets under the stimulation of different secretagogues. Dietary FO reverses dyslipidemia and improves insulin action and adiposity in the SRD fed rats. FO reduces adipocytes cell size and thus, the smaller adipocytes are more insulin sensitive and the release of fatty acids decreases. In muscle, FO normalizes both the oxidative and non-oxidative glucose pathways. Moreover, FO modifies the fatty acid composition of membrane phospholipids. In isolated beta cells, lipid contents and glucose oxidation return to normal. All these effects could contribute to the normalization of glucose-stimulated insulin secretion and muscle insulin insensitivity.

Indexed as

Adipose TissueAnimalsBody WeightDyslipidemiasFatty Acids, Omega-3GlucoseInsulin ResistanceIntra-Abdominal FatIslets of LangerhansLipid MetabolismLiverMaleMetabolic SyndromeMuscle, SkeletalRatsRats, WistarFatty Acids, Omega-3GlucoseSucroseTriglycerides

Identifiers

PMID17476547
OpenAlexW2050609146

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.