Evidence map›Paper›PMID 42729026›Full record

ArticleTranslational andrology and urology2026

Identification of angiogenesis-related genes in the diagnosis of benign prostatic hyperplasia using bioinformatics analysis.

Mengfan Cui, Kristina Kostadinovic, Qi Meng, Ting Bai, Yunjia Gu, Shimin Liu

Abstract read
In one paragraph

Article in Translational andrology and urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Mengfan CuiShanghai Baoshan District Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, China.
Kristina KostadinovicShanghai University of Traditional Chinese Medicine, Shanghai, China.
Qi MengShanghai University of Traditional Chinese Medicine, Shanghai, China.
Ting BaiShanghai University of Traditional Chinese Medicine, Shanghai, China.
Yunjia GuMiaohang Community Health Service Center, Shanghai, China.
Shimin LiuShanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Benign prostatic hyperplasia (BPH), the most prevalent male chronic disease, features typical lower urinary tract symptoms (LUTS) that compromise male health. Angiogenesis, the formation of new vascular networks from pre-existing vessels, is typically related to cancer development and inflammatory microenvironments. Identifying and diagnosing angiogenesis-related genes implicated in BPH is of critical importance for the health management of the BPH population. Therefore, this study aims to identify and validate angiogenesis-related genes associated with BPH to provide potential biomarkers for its diagnosis and treatment. Methods: BPH-related datasets were from the Gene Expression Omnibus (GEO). Modules specifically linked to BPH diagnosis were identified via weighted gene co-expression network analysis (WGCNA). Hub genes were noted through machine learning (ML) approaches: random forest (RF) and support vector machine-recursive feature elimination (SVM-RFE). A protein-protein interaction (PPI) network was constructed, with diagnostic performance rated via receiver operating characteristic (ROC) curves and nomograms. Results: The emerald module identified by WGCNA exhibited a strong correlation with BPH. ML models identified three hub genes ( Conclusions: Our findings suggest that

Indexed as

Angiogenesisbenign prostatic hyperplasia (BPH)bioinformatics analysis

Identifiers

PMID42729026
PMCPMC13561713

What Socratic holds

Textmetadata
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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 Socratic graph.