Evidence map›Paper›PMID 22370853›Full record

ReviewInternational journal of obesity (2005)2012

Liver X receptors and fat cell metabolism.

J Laurencikiene, M Rydén

Open access · bronzeAbstract readReview
In one paragraph

Review in International journal of obesity (2005), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
6.2field-weighted citation impact, top 3% 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

43 citing papers in PubMed, 87 citations in OpenAlex.

  1. Observational
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  6. Review
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  11. Short communication: Photoperiod impacts ovarian extracellular matrix and metabolic gene expression in Siberian hamsters.Comparative biochemistry and physiology. Part A, Molecular & integrative physiology · 2022
    Article
  12. Article
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  18. Observational
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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 at 1 institution in 1 country.

J LaurencikieneKarolinska Institutet, Department of Medicine (H7), Karolinska University Hospital, Huddinge, Sweden. Jurga.Laurencikiene@ki.se
M Rydén
Karolinska University Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver X receptors (LXRs) are members of the nuclear receptor family and are present in two isoforms, α and β, encoded by two separate genes. Originally described in the liver, LXRs have in the last 15 years been implicated in central metabolic pathways, including bile acid synthesis, lipid and glucose homeostasis. Although the vast majority of studies have been performed in non-adipose cells/tissues, results in recent years suggest that LXRs may have important modulatory roles in adipose tissue and adipocytes. Although several authors have published reviews on LXR, there have been no attempts to summarize the effects reported specifically in adipose systems. This overview gives a brief introduction to LXR and describes the sometimes-contradictory results obtained in murine cell systems and in rodent adipose tissue. The so far very limited number of studies performed in human adipocytes and adipose tissue are also presented. It should be apparent that although LXR may impact on several different pathways in metabolism, the clinical role of LXR modulation in adipose tissue is still not clear.

Indexed as

AdipocytesAdipogenesisAdipose TissueAnimalsGlucoseGlucose Transporter Type 1HomeostasisHumansLipid MetabolismLiverLiver X ReceptorsMiceMice, KnockoutOrphan Nuclear ReceptorsRatsTranscription FactorsGlucoseGlucose Transporter Type 1Liver X ReceptorsOrphan Nuclear ReceptorsTranscription Factors

Identifiers

PMID22370853
PMCPMC3520012
OpenAlexW2081952260

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.