ReviewDevelopmental cell2026
Dissecting human organ development using spatial technologies.
Review in Developmental cell, 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
4 authors.
Funding
Abstract
Spatial technologies have revolutionized the study of human development by enabling molecular profiling within intact tissue architecture. Advances in spatial transcriptomics, epigenomics, proteomics, metabolomics, and multiomics have generated high-resolution atlases of embryonic and fetal organs, which have revealed how gene regulatory programs, cell-cell interactions, and tissue patterning are organized in space and time during organogenesis. However, limited access to human developmental tissues and ethical constraints restrict experimental validation and mechanistic studies. Stem cell-derived organoids offer tractable, human-relevant models that recapitulate key structural and cellular features of developing organs while allowing controlled perturbation and longitudinal analysis. Integrating spatial profiling with organoids constitutes a sophisticated methodology for systematic analysis of lineage specification, niche signaling, and metabolic maturation. This review synthesizes current spatial technologies, highlights emerging organoid-based technologies, and discusses future directions integrating spatial multiomics, machine learning, and accessible data resources to advance mechanistic and predictive developmental biology.
Indexed as
Identifiers
What Socratic 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 Socratic graph.