Evidence map›Paper›PMID 25408843›Full record

ReviewComputational and structural biotechnology journal2014

MicroRNA Functions in Brite/Brown Fat - Novel Perspectives towards Anti-Obesity Strategies.

Michael Karbiener, Marcel Scheideler

Open access · goldAbstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

21 citing papers in PubMed, 39 citations in OpenAlex.

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  13. Long Non-Coding RNAs in Metabolic Organs and Energy Homeostasis.International journal of molecular sciences · 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

2 authors at 1 institution in 1 country.

Michael KarbienerRNA Biology Group, Institute of Molecular Biotechnology, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria.
Marcel ScheidelerRNA Biology Group, Institute of Molecular Biotechnology, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria.
Institute of Molecular Biotechnology · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current anti-obesity strategies are aiming at restricting energy uptake, but still, obesity treatment is far from being satisfactory. The discovery of active brown adipose tissue (BAT) in adult humans currently opens new avenues to combat obesity and follow-up complications as it tackles the other site of the energy balance: energy expenditure via non-shivering thermogenesis. This process of energy dissipation in the adipose tissue is tightly controlled, and the elucidation of its regulatory network is a key plank for therapeutic applications. MicroRNAs (miRNAs) belong to a novel class of regulatory determinants which are small non-coding RNAs with vital roles in regulating gene expression that also play a role in many human diseases. In this review we summarize miRNAs which have been shown to govern thermogenic, i.e. brite or brown, adipocyte recruitment and physiology. Notably, most miRNAs in this context have so far been characterized solely in mice, revealing a great demand for more human studies. As in the context of other diseases, RNA-based therapeutics have meanwhile entered clinical trials, further exploring the functions of miRNAs in brown and white adipose tissues could result in novel therapeutic approaches to treat obesity and its follow-up complications.

Indexed as

Adipose tissueBrite/beige adipocyteBrown adipocyteMicroRNANon-coding RNAObesity

Identifiers

PMID25408843
PMCPMC4232565
OpenAlexW2164777629

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.