Evidence map›Paper›PMID 27363418›Full record

ArticleHerz2017

Identifying disrupted pathways by tracking altered modules in type 2 DM-related heart failure.

H Liu, X Han, Y Li

Abstract read
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In one paragraph

Article in Herz, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  1. Article
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4 · The record

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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.

H LiuDepartment of Cardiology, Binzhou People's Hospital, No. 515 Huanghe Qi Road, 256610, Binzhou, Shandong Province, China. liuhaitaobinzhou@sina.com.
X HanOut-patient Department, Binzhou People's Hospital, 256610, Binzhou, Shandong Province, China.
Y LiDepartment of Orthopedic Surgery, Binzhou People's Hospital, 256610, Binzhou, Shandong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to screen disrupted pathways in type 2 diabetes mellitus (T2DM) heart failure by systematically tracking the altered modules of reweighted protein-protein interaction (PPI) networks.

methodsWe implemented systematic identification and comparison of modules across non-T2DM and T2DM heart failure subjects by integrating gene expression data and PPI networks. The PPI networks of non-T2DM heart failure and T2DM heart failure were constructed and reweighted by means of Spearman's correlation coefficient (SCC). Subsequently, a clique-merging algorithm was used to explore the modules in the PPI network, followed by the identification of disrupted modules based on a maximum-weight bipartite matching and sorting in descending order. Finally, pathway enrichment analyses were conducted for genes in disrupted modules to determine the biological pathways in T2DM heart failure.

resultsBy comparing the modules of non-T2DM heart failure and T2DM heart failure, 804 disrupted modules were explored. The genes in disrupted modules were significantly enriched in 39 categories (p < 1.00E-06). Of these, the most significant pathways were the focal adhesion, vascular endothelial growth factor (VEGF) signaling, and mitogen-activated protein kinase (MAPK) signaling pathways.

conclusionThe identified disrupted pathways - focal adhesion, VEGF signaling, and MAPK signaling - might play important roles in the progression of T2DM heart failure.

Indexed as

Protein Interaction MapsAccessory Atrioventricular BundleDiabetes Mellitus, Type 2FemaleGene Expression ProfilingHeart FailureHumansMaleMiddle AgedProtein Interaction MappingProteomeProteomeDiabetes mellitus, type 2Gene expressionHeart failureProtein interaction networksSignaling pathways

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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.