ArticleFrontiers in immunology2024
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- The emerging role of microbiota in lung cancer: a new perspective on lung cancer development and treatment.Cellular oncology (Dordrecht, Netherlands) · 2025Review
- Clinical validation and utility of targeted nanopore sequencing for rapid pathogen diagnosis and precision therapy in lung cancer patients with pulmonary infections.Frontiers in cellular and infection microbiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Dysbiosis of the lung microbiome can contribute to the initiation and progression of lung cancer. Synchronous multiple primary lung cancer (sMPLC) is an increasingly recognized subtype of lung cancer characterized by high morbidity, difficulties in early detection, poor prognosis, and substantial clinical challenges. However, the relationship between sMPLC pathogenesis and changes in the lung microbiome remains unclear. Methods: In this study, 16S rRNA sequencing was performed on clinical samples to analyze lung microbiome composition. Real-time quantitative PCR (qPCR) was used to quantify bacterial abundance in lung tissues. In addition, flow cytometry was conducted to evaluate cell cycle progression and apoptosis in lung tumor cells. Results: Clinical cohort studies demonstrated that sMPLC occurrence is associated with disturbances in the lung microbiome. Notably, Streptococcus intermedius was enriched in the lungs of sMPLC patients compared with non-tumor controls and accumulated preferentially in tumor tissues. Conclusions: These findings characterize the lung microbiota in sMPLC and identify
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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.