ReviewNature reviews. Nephrology2024
Spatial transcriptomics in health and disease.
Review in Nature reviews. Nephrology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 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
80 citing papers in PubMed.
- Article
- T-Cell Remodeling in Renal Fibrosis: From Acute Injury to Chronic Kidney Disease.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Next-generation kidney tissue analysis - spatial omics and digital pathology.Nature reviews. Nephrology · 2026Review
- Integration of Multi-Omics Data To Understand the Multifaceted Role of RAMP1 across Different Cancer Types.Cell biochemistry and biophysics · 2026Review
- STcompare: comparative spatial transcriptomics data analysis of structurally matched tissues to characterize differentially spatially patterned genes.Bioinformatics (Oxford, England) · 2026Article
- Article
- Spatial multi-omics unveils sphingolipid metabolic reprogramming within the retinal pathological niche.iMeta · 2026Article
- Decoding Spatial Heterogeneity and Multi-Omics Regulation with Hierarchical Graph Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Deciphering lung cancer at high resolution: a narrative review of applications of single-cell and spatial transcriptomics sequencing.Translational lung cancer research · 2026Review
- Omics Approaches in Hantavirus Research: Current Advances, Challenges, and Future Perspectives.Biotech (Basel (Switzerland)) · 2026Review
- Toward simultaneous pseudo-space reconstruction and cell-type deconvolution of single-cell spatial transcriptome using SpaDicer.Cell reports methods · 2026Article
- A MEF2C transcription factor network regulates proliferation of glomerular endothelial cells in diabetic kidney disease.Kidney international · 2026Article
- Bridging Kidney Organoid Innovation and Regenerative Medicine: Current Advances and Future Directions.Cell proliferation · 2026Review
- The applications of single-cell and spatial transcriptomics in neuroscience and brain disorders.Neuroscience and biobehavioral reviews · 2026Review
- BNC2 in Development and Disease: Regulatory Mechanisms and Translational Implications.Molecules (Basel, Switzerland) · 2026Review
- Spatial Gene Set Enrichment Analysis with Applications to Spatially Resolved Transcriptomic Data.bioRxiv : the preprint server for biology · 2026Article
- Decoding spatial transcriptomics across multicellular and subcellular resolutions.Nature communications · 2026Article
- Single-cell Stereo-seq reveals regulatory mechanisms driving regeneration of injured proximal tubules during AKI.Nature communications · 2026Article
- Biased multi-view contrastive learning with attentive masking for spatial transcriptomic analysis.Briefings in bioinformatics · 2026Article
- Defining the tumor microenvironment of non-small cell lung cancer.Immunology and cell biology · 2026Review
20 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The ability to localize hundreds of macromolecules to discrete locations, structures and cell types in a tissue is a powerful approach to understand the cellular and spatial organization of an organ. Spatially resolved transcriptomic technologies enable mapping of transcripts at single-cell or near single-cell resolution in a multiplex manner. The rapid development of spatial transcriptomic technologies has accelerated the pace of discovery in several fields, including nephrology. Its application to preclinical models and human samples has provided spatial information about new cell types discovered by single-cell sequencing and new insights into the cell-cell interactions within neighbourhoods, and has improved our understanding of the changes that occur in response to injury. Integration of spatial transcriptomic technologies with other omics methods, such as proteomics and spatial epigenetics, will further facilitate the generation of comprehensive molecular atlases, and provide insights into the dynamic relationships of molecular components in homeostasis and disease. This Review provides an overview of current and emerging spatial transcriptomic methods, their applications and remaining challenges for the field.
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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.