ArticleBioinformatics (Oxford, England)2026
Plant Spatio-Temporal Integration Network (PSTN): a framework for dynamic single-cell and spatial transcriptomics in fungal-plant interactions.
Article in Bioinformatics (Oxford, England), 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
9 authors.
Funding
Abstract
motivationRice blast caused by Magnaporthe oryzae (M. oryzae) is a dynamic cross-kingdom infection process involving rapid transcriptional reprogramming and spatial tissue remodeling across successive stages. Although single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) provide complementary information, most integration methods analyze stages independently and ignore temporal continuity.
resultsWe developed the Plant Spatio-Temporal Integration Network (PSTN), which jointly learns stage-specific cell-to-space mappings through expression reconstruction and bidirectional maximum-similarity temporal regularization. Applied to matched rice scRNA-seq and ST data at 0, 12, and 24 h, PSTN outperformed Tangram, SpaGE, cell2location, and DestVI across three gene-set sizes. At 4000 highly variable genes (HVGs), mean squared error (MSE) remained below 0.09 at all stages, with high gene-wise and spot-wise correlations. Mapping-structure and marker-based analyses recovered tissue-associated spatial and temporal patterns. Gene-permutation controls markedly reduced performance, demonstrating reliance on correct cross-modal gene correspondence. An independent mouse-cortex benchmark supported the static reconstruction component across systems. PSTN enables temporally coupled single-cell and spatial integration in dynamic host-pathogen systems. AVAILABILITY: PSTN is available at https://github.com/zhuyuheng111/PSTN. The Zenodo DOI for the repository is 10.5281/zenodo.21365720.
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.