ArticleNature methods2025
ESPRESSO: spatiotemporal omics based on organelle phenotyping.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Algebraic Representation of Mitochondrial Dynamics.Bulletin of mathematical biology · 2026Article
- 'FILMing' the metabolic landscape of individual cell organelles.Nature methods · 2026Article
- Kinemomics: spatiotemporal morphodynamic mapping of ventricular kinematic subpopulations in organotypic fetal heart slices.bioRxiv : the preprint server for biology · 2026Article
- Proximity labeling in neuroscience: decoding molecular landscapes for precision neurology.Translational neurodegeneration · 2026Review
- Wavefront estimation through structured detection in laser scanning microscopy.Biomedical optics express · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Omics technologies such as genomics, transcriptomics, proteomics and metabolomics methods, have been instrumental in improving our understanding of complex biological systems by providing high-dimensional phenotypes of cell populations and single cells. Despite fast-paced advancements, these methods are limited in their ability to include a temporal dimension. Here, we introduce ESPRESSO (Environmental Sensor Phenotyping RElayed by Subcellular Structures and Organelles), a technique that provides single-cell, high-dimensional phenotyping resolved in space and time. ESPRESSO combines fluorescent labeling, advanced microscopy and image and data analysis methods to extract morphological and functional information from organelles at the single-cell level. We validate ESPRESSO's methodology and its application across numerous cellular systems for the analysis of cell type, stress response, differentiation and immune cell polarization. We show that ESPRESSO can correlate phenotype changes with gene expression, and demonstrate its applicability to 3D cultures, offering a path to improved spatially and temporally resolved biological exploration of cellular states.
Indexed as
Identifiers
41184551What 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.