ReviewZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences2026
[Spatial omics in pulmonary fibrosis: advancing mechanistic insights and therapeutic strategies].
Review in Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences, 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.
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0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pulmonary fibrosis, a group of chronic interstitial lung diseases charac-terized by persistent inflammation and aberrant deposition of fibrous connective tissue, poses a significant therapeutic challenge, with idiopathic pulmonary fibrosis (IPF) being its most representative and severe form. Spatially resolved omics technologies-encompassing spatial metabolomics, transcriptomics, and proteomics-have emerged as transformative tools that preserve the architectural context of tissues while enabling high-throughput, visualization-capable analysis of metabolites, genes, and proteins. Spatial metabolomics facilitates the visualization and intelligent annotation of metabolic landscapes; spatial transcriptomics deciphers regional heterogeneity and refines the molecular timeline of early disease events; and spatial proteomics elucidates protein interaction networks and uncovers novel drug-resistance mechanisms. Collectively, spatial omics provides unprece-dented insights into disease pathogenesis, offering a powerful framework for advancing precision diagnosis, identifying therapeutic targets, and guiding drug development. This article synthesizes recent progress in applying spatial omics to pulmonary fibrosis research, underscoring its potential to translate into more effective clinical strategies.
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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 Socratic graph.