Evidence map›Paper›PMID 37779878›Full record

ArticleJournal of Cancer2023

Knowledge mapping and current trends of global research on snoRNA in the field of cancer.

Runsen Xu, Lina Wang, Junhui Hou, Xia Wang, Yibing Wang, Kefeng Wang

Abstract read
In one paragraph

Article in Journal of Cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Review
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.

Runsen XuDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Lina WangDepartment of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Junhui HouDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Xia WangDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Yibing WangDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Kefeng WangDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang 110004, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a major health hazard for humans. Recent studies have indicated the involvement of small nucleolar RNAs (snoRNAs) in the occurrence and development of cancer and indicated its potential role as a diagnostic/prognostic marker and therapeutic target. The purpose of this study was to use the bibliometrics method to analyze the published literature on this subject. We collected articles pertaining to the field of snoRNA and cancer from the Web of Science Core Collection database. The data were analyzed to identify the research hotspots and frontiers. The number of articles in this field was low in the early period. Chu Liang and Montanaro Lorenzo were the most prolific authors on this subject, while Jiang and Feng were the most frequently cited authors. In China, three institutions published the most articles, namely Wuhan Univ, China Med Univ, and Guangxi Med Univ. The journal with the highest number of articles on this subject was Oncotarget. The country with the most published articles was China. Analysis of keywords and burst words indicated that early studies mainly focused on molecular mechanisms. Available evidence suggests the involvement of snoRNAs in the molecular mechanism of cancer development and their potential role as a diagnostic and prognostic biomarker.

Indexed as

Bibliometric studyCancerDiagnosisMolecular mechanismPrognosisSmall nucleolar RNA

Identifiers

PMID37779878
PMCPMC10539387

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.