Evidence map›Paper›PMID 29459688›Full record

ArticleScientific reports2018

iTRAQ-based quantitative proteomic analysis reveals important metabolic pathways for arsenic-induced liver fibrosis in rats.

Shunhua Wu, Jing Li, Xiang Jin

Open access · goldAbstract read
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Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.6field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 17 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

3 authors at 1 institution in 1 country.

Shunhua WuDepartment of Occupational and Environmental health, School of public health, Xinjiang Medical University, Urumqi, 830011, China. wsh@xjmu.edu.cn.ORCID 0000-0002-1243-4119
Jing LiDepartment of Occupational and Environmental health, School of public health, Xinjiang Medical University, Urumqi, 830011, China.
Xiang JinDepartment of Occupational and Environmental health, School of public health, Xinjiang Medical University, Urumqi, 830011, China.
Xinjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long-term consumption of sodium arsenite contaminated water can cause endemic arsenic disease. The proteome profile changes of liver fibrosis after exposure to arsenite containing water remain unclear. In this study, Sprague-Dawley (SD) male rats were treated with sodium arsenite (iAs3+), using a daily dose of 1.36 mg/kg body weight (medium dose group, M), 2.73 mg/kg body weight (high dose group, H) or deionized water (control group, C). Isobaric tags for relative and absolute quantitation (iTRAQ) were used to identify the different abundant proteins (DAPs) after arsenic-induced liver fibrosis. A total of 2987 high-quality proteins were detected (95% confident peptides ≥ 2), 608 of which were differentially expressed (fold change > 2 and p < 0.05) in M group and 475 in H group. Moreover, 431 DAPs were found in both M and H groups and used in subsequent bioinformatic analyses. Gene ontology (GO) analysis revealed 4,709 GO terms could be mapped, among which purine binding, actin filament binding and protein kinase binding were the most enriched terms for molecular function category. In addition, protein-protein interaction analysis showed six clusters of interaction networks. Our data provided new insights into the proteome changes after arsenic-induced liver fibrosis in model rats.

Indexed as

Metabolic Networks and PathwaysAnimalsArsenicArsenitesDisease Models, AnimalGene OntologyLiver CirrhosisProteomeProteomicsRats, Sprague-DawleySodium CompoundsWater Pollutants, ChemicalArsenicArsenitesProteomesodium arseniteSodium CompoundsWater Pollutants, Chemical

Identifiers

PMID29459688
PMCPMC5818499
OpenAlexW2792438404

What OpenQuestion holds

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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.