Evidence map›Paper›PMID 30154394›Full record

ArticleInternational journal of molecular sciences2018

Comparative Proteome Analysis Reveals Lipid Metabolism-Related Protein Networks in Response to Rump Fat Mobilization.

Juanjuan Wang, Mengsi Xu, Xinhua Wang, Jinquan Yang, Lei Gao, Yan Zhang, Xin Huang, Mengli Han, Rui Gao, Shangquan Gan

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

6 citing papers in PubMed, 9 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

10 authors at 2 institutions in 1 country.

Juanjuan WangCollege of Animal Science and Technology, Shihezi University, Shihezi 832000, China. wangjuanjuand10@163.com.
Mengsi XuState Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China. xumengsi100@163.com.
Xinhua WangState Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China. wangxinhua5751@163.com.
Jinquan YangState Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China. xssxmjq@126.com.
Lei GaoState Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China. w.n007@163.com.
Yan ZhangLaboratory of Epigenetics, Beijing Institute of Biotechnology, Beijing 100071, China. zany1983@gmail.com.
Xin HuangState Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China. ahx512@163.com.
Mengli HanState Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China. hanmenglimm@163.com.
Rui GaoThe Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of Medicine, Shihezi 832000, China. gaorui@shzu.edu.cn.
Shangquan GanState Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China. shangquangan@shzu.edu.cn.
Xinjiang Academy of Agricultural and Reclamation Science · CNShihezi University · CN

Funding

Doctoral Fund program of Xinjiang Bingtuan Doctoral Fund program of Xinjiang BingtuanNational Natural Science Foundation of China and the government of Xinjiang province U1130302Special Prophase Project of the Basic Research of The National Department of Science and Technology 2011CB111501
6 · The paper itself

Abstract

Altay is a typical fat-tailed sheep breed displaying the unique ability to rapidly mobilize fat, which is vital for maintaining a normal metabolism that facilitates its survival in lengthy winter conditions. However, the physiological, biochemical, and molecular mechanisms underlying fat mobilization remain to be elucidated. In this study, the monitoring of rump fat adipocyte sizes disclosed a positive correlation between cell size and fat deposition ability. In addition, we subjected sheep to persistent starvation to imitate the conditions that trigger rump fat mobilization and screened 112 differentially expressed proteins using the isobaric peptide labeling approach. Notably, increased secretion of leptin and adiponectin activated the key fat mobilization signaling pathways under persistent starvation conditions. Furthermore, the upregulation of resistin (RETN), heat-shock protein 72 (HSP72), and complement factor D (CFD) promoted lipolysis, whereas the downregulation of cell death-inducing DFFA-like effector C (CIDEC) inhibited lipid droplet fusion, and the increase in HSP72 and apolipoprotein AI (Apo-AI) levels activated the body's stress mechanisms. The synergistic actions of the above hormones, genes, and signaling pathways form a molecular network that functions in improving the adaptability of Altay sheep to extreme environments. Our findings provide a reference for elucidating the complex molecular mechanisms underlying rump fat mobilization.

Indexed as

AdiposityLipid MetabolismProteomeProteomicsAdipocytesAdipose TissueAnimalsBiomarkersGene Expression RegulationLipidsSheepStarvationBiomarkersLipidsProteomealtay sheepisobaric tags for relative or absolute quantitation (iTRAQ)persistent starvationproteomicrump fat

Identifiers

PMID30154394
PMCPMC6164786
OpenAlexW2888786048

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.