Evidence map›Paper›PMID 26949945›Full record

ArticleAsian-Australasian journal of animal sciences2016

Association Analysis of Myosin Heavy-chain Genes mRNA Transcription with the Corresponding Proteins Expression of Longissimus Muscle in Growing Pigs.

X M Men, B Deng, X Tao, K K Qi, Z W Xu

Open access · goldAbstract read
In one paragraph

Article in Asian-Australasian journal of animal sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

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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 2 institutions in 1 country.

X M Men
B Deng
X Tao
K K Qi
Z W Xu
ZheJiang Academy of Agricultural Sciences · CNAnimal Science Research Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goal of this work was to investigate the correlations between MyHC mRNA transcription and their corresponding protein expressions in porcine longissimus muscle (LM) during postnatal growth of pigs. Five DLY (Duroc×Landrace×Yorkshire) crossbred pigs were selected, slaughtered and sampled at postnatal 7, 30, 60, 120, and 180 days, respectively. Each muscle was subjected to quantity MyHCs protein contents through an indirect enzyme-linked immunosorbent assay (ELISA), to quantity myosin heavy-chains (MyHCs) mRNA abundances using real-time polymerase chain reaction. We calculated the proportion (%) of each MyHC to total of four MyHC for two levels, respectively. Moreover, the activities of several key energy metabolism enzymes were determined in LM. The result showed that mRNA transcription and protein expression of MyHC I, IIa, IIx and IIb in LM all presented some obvious changes with postnatal aging of pigs, especially at the early stage after birth, and their mRNA transcriptions were easy to be influenced than their protein expressions. The relative proportion of each MyHC mRNA was significantly positively related to that of its corresponding protein (p<0.01), and MyHC I mRNA proportion was positively correlated with creatine kinase (CK), succinate dehydrogenase (SDH), malate dehydrogenase (MDH) activities (p<0.05). These data suggested that MyHC mRNA transcription can be used to reflect MyHC expression, metabolism property and adaptive plasticity of porcine skeletal muscles, and MyHC mRNA composition could be a molecular index reflecting muscle fiber type characteristics.

Indexed as

Gene ExpressionMyofiber TypesMyosin Heavy-chainPorcine Muscle

Identifiers

PMID26949945
PMCPMC4782079
OpenAlexW1770024088

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

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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.