Evidence map›Paper›PMID 24464334›Full record

ArticleJournal of applied genetics2014

Castration-induced changes in microRNA expression profiles in subcutaneous adipose tissue of male pigs.

Zhaowei Cai, Lifan Zhang, Minli Chen, Xiaoling Jiang, Ningying Xu

Abstract read
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In one paragraph

Article in Journal of applied genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

9 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. The Novel-miR-659/Animals : an open access journal from MDPI · 2022
    Article
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  4. 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

5 authors at 3 institutions in 1 country.

Zhaowei CaiLaboratory Animal Research Center, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Lifan Zhang
Minli Chen
Xiaoling Jiang
Ningying Xu
Zhejiang University · CNNanjing Agricultural University · CNZhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are class of molecular regulators found to participate in numerous biological processes, such as adipogenesis and obesity in mammals. To determine the roles of miRNAs involved in castration-induced body fatness, we investigated the different miRNA expression patterns in subcutaneous adipose tissue between intact and castrated male pigs. Our results showed that castration led to decrease serum testosterone but increase serum Leptin levels (P < 0.01). Moreover, castration also increased adipocyte size, body fat content and backfat thickness in male pigs (P < 0.01). Meanwhile, miRNA expression profiles in adipose tissue were changed by castration, and 18 miRNAs were considered as the differentially expressed candidates between intact and castrated male pigs. Furthermore, functional analysis indicated that the differential expressed miRNAs and their target genes are involved in the regulation of fatty acid metabolism. In brief, our present study provides a comprehensive view on how miRNAs works in subcutaneous adipose tissue with castration. These results suggested that miRNAs might play an important role in the castration-induced fat deposition in male pigs.

Indexed as

CastrationGene Expression ProfilingAdiposityAnimalsCluster AnalysisDown-RegulationGene OntologyHormonesMaleMicroRNAsOligonucleotide Array Sequence AnalysisQuantitative Trait, HeritableReal-Time Polymerase Chain ReactionReproducibility of ResultsSubcutaneous FatSus scrofaHormonesMicroRNAs

Identifiers

PMID24464334
OpenAlexW1989577598

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.