SynthesisFrontiers in immunology2026
From immunological mechanisms to targeted therapies: a bibliometric analysis in the domain of research concerning neutrophil extracellular traps and pulmonary diseases (2006-2025).
Synthesis in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Neutrophil extracellular traps (NETs) are a crucial mechanism of the neutrophil immune response and exhibit complex dual pathological and physiological effects in pulmonary diseases. In recent years, this research domain has increased significantly, yet systematic bibliometric research remains absent. Therefore, this study utilizes bibliometric methods to thoroughly examine the research landscape and development sequence of this domain, aiming to provide theoretical references for future research. Methods: In this study, VOSviewer and CiteSpace were used to conduct a visualization analysis of the article concerning NETs and pulmonary diseases indexed in the Web of Science Core Collection (WoSCC) and Scopus databases from January 1st, 2006, to December 31st, 2025. Additionally, we utilized the R package bibliometric and Origin 2025b to optimize the data and visualization charts, ensuring that the analytical results were presented with greater clarity and intuitiveness. Results: This study covered 1, 539 articles from 561 journals. The results indicate that since 2006, this domain has seen a phased growth trend. The phase from 2010 to 2018 was a stable growth phase; After 2019, propelled by the COVID-19 virus infection (COVID-19), it entered a significant development phase, and reached its peak in 2022. In terms of influence, China and the United States are leading contributors. Mark R. Looney of the University of California is the core author, and "Frontiers in Immunology" is the most frequently cited journal. Through the visualization analysis of topic categories, keywords, and references indicates that research focal points in this domain have progressively transitioned from initial fundamental mechanisms and pathological descriptions to concerns regarding pulmonary inflammation, immune thrombosis, COVID-19, and biomarkers, subsequently extending to frontiers such as the NLRP3 inflammasome, interstitial lung disease (ILD), and tumor microenvironment (TME). Conclusions: This study is the first application of bibliometric methods to visually present research domains related to NETs and pulmonary diseases, revealing the correlation between NETs and ILD, lung cancer (LC), and respiratory infections, along with the underlying mechanisms, continues to be a hot topic in research. However, the predominant function of NETs in specific diseases and their potential utility as therapeutic targets still necessitate further systematic elaboration.
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Registered trials
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.