ArticleFrontiers in neuroscience2026
Spatial transcriptomics on an expanded dataset at the brain-electrode interface: exploration of variability and identification of novel biomarkers.
Article in Frontiers in neuroscience, 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
6 authors.
Funding
Abstract
The foreign body reaction to implanted electrodes in the brain has long been recognized as a major challenge impacting the performance and reliability of indwelling neurotechnologies. Spatially resolved transcriptomic approaches have enabled high-resolution mapping of cellular and molecular dynamics at the device-tissue interface, yielding novel insight into both acute and chronic tissue responses. Recent whole-transcriptome profiling methods generate exceptionally dense gene expression datasets from individual samples, offering unprecedented resolution and analytical power. Yet, limited studies have explored aggregated results from larger datasets and sample-to-sample variation within an implanted cohort using such techniques due to high costs and complicated downstream analyses. In this work, we provide a comprehensive report of spatial transcriptomics data collected from an expanded cohort of rats (
Indexed as
Identifiers
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.