Evidence map›Paper›PMID 40029466›Full record

ArticleDiscover oncology2025

Global trends and emerging research in nanotechnology for esophageal cancer: a comprehensive bibliometric analysis.

Chun-Jian Zuo, Jie Tian

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

2 authors.

Chun-Jian ZuoDepartment of Thoracic Surgery, Army Medical Center of People'S Liberation Army of China (PLA), 10# Changjiang Branch Road, Yuzhong District, Chongqing, 400042, China. 1126026632@qq.com.
Jie TianDepartment of Thoracic Surgery, West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, 610041, China. tianjiehxxwk@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the growing body of research on nanotechnology for esophageal cancer (EC), a comprehensive bibliometric analysis in this field has yet to be conducted. This study aims to fill this gap by analyzing global research trends, key contributors, and emerging themes in nanotechnology for EC.

methodsA bibliometric analysis was performed on publications from 1980 to 2024, using data from the Web of Science Core Collection. The analysis was conducted using VOSviewer, CiteSpace, and the R package 'bibliometrix' to visualize research trends, collaboration networks, and thematic areas.

resultsThe analysis included 419 documents authored by 2952 researchers from 44 countries. A significant increase in publications was observed, particularly after 2011, with China, the United States, and Japan leading the contributions. Prominent institutions, including Zhengzhou University and the Chinese Academy of Sciences, were identified as key players. The research predominantly focused on drug delivery systems, nanomedicine, and cancer treatment mechanisms, with emerging trends in the development of advanced nanomaterials for personalized therapies.

conclusionThis comprehensive bibliometric analysis of nanotechnology applications in EC highlights global research trends, key contributors, and emerging research areas. The findings underscore the crucial role of nanotechnology in advancing treatment strategies for EC and identify areas for future research and interdisciplinary collaboration.

Indexed as

Bibliometric analysisDrug delivery systemsEmerging trendsEsophageal cancerNanotechnology

Identifiers

PMID40029466
PMCPMC11876481

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.