Evidence map›Paper›PMID 42601913›Full record

SynthesisFrontiers in cellular and infection microbiology2026

Non-coding RNAs in parasitic diseases: a bibliometric analysis of knowledge structure, research hotspots, and future directions.

Xin Wang, Yuan Zhang, Jingyuan Li, Feng Xue, Di Zhang, Na Li, Jie Zhang, Zengru Xie, Hailong Guo, Wen Zhao

Abstract readReviewSystematic Review
In one paragraph

Synthesis in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

10 authors.

Xin Wang *Department of Minimally Invasive Spine Surgery and Precision Orthopedics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Yuan Zhang *Xinjiang Engineering Technology Research Center for Medicine-Industry Integration, Xinjiang Medical University, Urumqi, China.
Jingyuan Li *Department of Orthopedics and Trauma, the First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Feng Xue *Department of Minimally Invasive Spine Surgery and Precision Orthopedics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Di ZhangMedical Laboratory Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Na LiXinjiang Engineering Technology Research Center for Medicine-Industry Integration, Xinjiang Medical University, Urumqi, China.
Jie ZhangDepartment of Minimally Invasive Spine Surgery and Precision Orthopedics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Zengru XieDepartment of Orthopedics and Trauma, the First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Hailong GuoDepartment of Minimally Invasive Spine Surgery and Precision Orthopedics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Wen ZhaoDepartment of Minimally Invasive Spine Surgery and Precision Orthopedics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-coding RNAs (ncRNAs) have emerged as critical regulators in host-parasite interactions, yet the rapid proliferation of publications has made it challenging to obtain a comprehensive, unbiased view of the field's intellectual structure and evolving frontiers. Methods: We performed a bibliometric analysis of research articles on ncRNAs in parasitic diseases published from 2015 to 2025. A multi-database search was conducted across the Web of Science Core Collection, PubMed, and the Cochrane Library, yielding 432 records for annual publication trend analysis, with 409 original research articles from the Web of Science Core Collection used for bibliometric network analyses, including co-citation, collaboration networks, keyword clustering, burst detection, and dual-map overlay. Results: Annual publications grew steadily from 21 to 44 over the decade, with a peak of 51 in 2022. China ranked first in output (175 articles), while the United States showed the highest centrality (0.37). Author collaboration networks were sparse (density = 0.0032), indicating fragmented research efforts. Keyword clustering identified 11 clusters, with "liver" and "immune responses" as persistent core themes; "extracellular vesicles" emerged as a key hub after 2018. Citation burst analysis revealed a three-phase evolution-from molecular identification (2015-2019) to functional regulation and communication (2019-2021), and then to host-pathogen interactions and translational applications (2022-2025). The most highly cited references collectively established the "extracellular vesicles-ncRNA" paradigm, and persistently bursting references point toward clinical diagnostics. Circular RNAs and the NF-κB pathway appeared as emerging hotspots. Journal overlay mapping showed knowledge flowing from molecular biology toward veterinary and parasitology disciplines. Conclusions: The field is transitioning from fundamental discovery toward translational applications, with extracellular vesicle-encapsulated ncRNAs holding promise as biomarkers and therapeutic targets. Enhanced international collaboration and interdisciplinary integration are urgently needed to accelerate progress.

Indexed as

BibliometricsHost-Parasite InteractionsParasitic DiseasesRNA, UntranslatedAnimalsHumansRNA, UntranslatedbibliometricsCiteSpaceextracellular vesiclesnon−coding RNAsparasitic diseasesresearch hotspots

Identifiers

PMID42601913
PMCPMC13472806

What OpenQuestion holds

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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.