ArticleiScience2026
Application of spatial transcriptomics across organoids for a high-resolution, spatial whole-transcriptome benchmarking dataset.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Natural Killer Cell Immunotherapy in Solid Tumors: Microenvironmental Obstacles and Translational 3D Models.Biology · 2026Review
- Dissecting human organ development using spatial technologies.Developmental cell · 2026Review
- Insights into neurodevelopmental features of Huntington's disease from stem cell-derived models including organoids.Journal of Huntington's disease · 2026Review
- Spatial mapping of barcoded, brain-tropic AAVs using multiplexed RNAMolecular therapy. Advances · 2026Article
- Advances in the pathophysiological study of brain development: application of cerebral organoid combined with Spatial omics technology.Stem cell research & therapy · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
38 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stem cell-derived organoids hold promise to model tissue-specific diseases. To enable this, it is crucial to assess how transcriptional signatures, cellular organization, and composition of organoids compare to
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Identifiers
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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 OpenQuestion graph.