ArticleScience immunology2026
The rise of spatial TCR profiling: Emerging technologies and open challenges.
Article in Science immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- An interpretable AI model decodes the rules of cell recruitment to specific destinations.Nature biomedical engineering · 2026Article
- Interpretable AI model reveals spatial codes of cell recruitment in tissues.Nature biomedical engineering · 2026Article
Corrections and comments
- Comment on
Authors and funding
2 authors.
Funding
Abstract
High-definition spatial TCR profiling illuminates how clonal identity and T cell state are coordinated in the tumor microenvironment (see related Research Article by McCord
Indexed as
Identifiers
41961947What 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.