ArticleGlobal medical genetics2026
Identification of core differentially expressed genes for respiratory syncytial virus infection.
Article in Global medical genetics, 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Respiratory syncytial virus (RSV) is a highly contagious pathogen and the predominant cause of upper and lower respiratory tract infections. RSV-specific antiviral drugs are at an early stage, and clinical and experimental therapies targeting pathogenesis and immune pathways are limited, with challenging application. Methods: We systematically analyzed blood transcriptome data from 92 RSV patients and 47 healthy controls. Key functional genes were identified via differential expression analysis, weighted gene co-expression network analysis (WGCNA), core module identification, machine learning, protein-protein interaction (PPI) network analysis, and co-localization mapping. An independent cohort (28 patients, 8 controls) was used for validation. Immune-cell infiltration patterns influenced by key genes were assessed, and therapeutic targets were predicted. Quantitative real-time PCR (qRT-PCR) on clinical blood samples validated disease-associated core genes. Results: We identified eight functionally critical feature genes; seven ( Conclusion: This study systematically screened potential key genes via integrated bioinformatics and molecular validation, and identified
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.