ArticlePNAS nexus2023
Article in PNAS nexus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Data modeling the interplay between single-cell shape, single-cell protein expression, and tissue state.Cell reports methods · 2026Article
- LYNX: a deep generative model for linking spatial dynamics and cell interactions in multimodal spatial data.bioRxiv : the preprint server for biology · 2026Article
- miniMTI: minimal multiplex tissue imaging enhances biomarker expression prediction from histology.Research square · 2026Article
- ROSIE: AI generation of multiplex immunofluorescence staining from histopathology images.Nature communications · 2025Article
- Article
- Single-cell multimodal analysis reveals tumor microenvironment predictive of treatment response in non-small cell lung cancer.Science advances · 2025Article
- Imputing single-cell protein abundance in multiplex tissue imaging.Nature communications · 2025Article
- Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data.Nature communications · 2025Article
- Intratumoral microbiota for hepatocellular carcinoma: from preclinical mechanisms to clinical cancer treatment.Cancer cell international · 2025Review
- MIM-CyCIF: masked imaging modeling for enhancing cyclic immunofluorescence (CyCIF) with panel reduction and imputation.Communications biology · 2024Article
- Multiplex protein imaging in tumour biology.Nature reviews. Cancer · 2024Review
- Expanding the coverage of spatial proteomics: a machine learning approach.Bioinformatics (Oxford, England) · 2024Article
- Spatial Morphoproteomic Features Predict Uniqueness of Immune Microarchitectures and Responses in Lymphoid Follicles.bioRxiv : the preprint server for biology · 2024Article
- Deriving spatial features from in situ proteomics imaging to enhance cancer survival analysis.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiplex immunofluorescence (mIF) assays multiple protein biomarkers on a single tissue section. Recently, high-plex CODEX (co-detection by indexing) systems enable simultaneous imaging of 40+ protein biomarkers, unlocking more detailed molecular phenotyping, leading to richer insights into cellular interactions and disease. However, high-plex data can be slower and more costly to collect, limiting its applications, especially in clinical settings. We propose a machine learning framework,
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.