ArticleCell metabolism2019
A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry.
Article in Cell metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 195 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
195 citing papers in PubMed.
- The β-cells in type 1 diabetes mellitus: findings from human pancreas studies.Nature reviews. Endocrinology · 2026Review
- Microenvironment-aware transcriptome reconstruction in spatial transcriptomics.Nature communications · 2026Article
- Analysis of multicellular anatomical structures from spatial omics data using sosta.PLoS computational biology · 2026Article
- Article
- Deep learning-powered quantification of endocrine cells and CD3Diabetologia · 2026Article
- A 3D spatial proteomic map of the human pancreatic islet microenvironment.Research square · 2026Article
- SHIELD: A weakly supervised graph attention neural network for decoding disease-relevant cell-cell interactions.Patterns (New York, N.Y.) · 2026Article
- Distinct macrophage and T cell programs shape pancreatic inflammation during metabolic stress and aging.bioRxiv : the preprint server for biology · 2026Article
- A spatial atlas of pancreatic remodelling in type 1 diabetes.Nature metabolism · 2026Article
- Imaging mass cytometry reveals functional and immunological changes during type 1 diabetes progression in human pancreata.Nature metabolism · 2026Article
- OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.BMC bioinformatics · 2026Article
- AI-guided analysis of human pancreatic islet sociology reveals distinct cell compositional changes in type 1 diabetes.bioRxiv : the preprint server for biology · 2026Article
- In Vivo Imaging of the Innate Immune System in the Pancreas in New-Onset and Long-Standing Type 1 Diabetes.Diabetes, obesity & metabolism · 2026Article
- SOFisher: reinforcement learning-guided experiment designs for spatial omics.Nature communications · 2026Article
- Immune context governs stage-specific responses to depleting anti-PD-1 antibody in type 1 diabetes.Cell biomaterials · 2026Article
- OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.Research square · 2026Article
- MICRON learns outcome-associated representations of spatial immune microenvironments.bioRxiv : the preprint server for biology · 2026Article
- Emerging therapies for type 1 diabetes: Immunotherapy and gene editing advances.The Journal of international medical research · 2026Review
- Characterisation of human pancreatic mesenchymal stromal cells in type 1 diabetes.Diabetologia · 2026Article
- Hyaluronan induces ERK activation with minimal transcriptomic changes in pancreatic α-cells.Biochemistry and biophysics reports · 2026Article
135 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
Authors and funding
11 authors.
Funding
Abstract
Type 1 diabetes (T1D) results from the autoimmune destruction of insulin-producing β cells. A comprehensive picture of the changes during T1D development is lacking due to limited sample availability, inability to sample longitudinally, and the paucity of technologies enabling comprehensive tissue profiling. Here, we analyzed 1,581 islets from 12 human donors, including eight with T1D, using imaging mass cytometry (IMC). IMC enabled simultaneous measurement of 35 biomarkers with single-cell and spatial resolution. We performed pseudotime analysis of islets through T1D progression from snapshot data to reconstruct the evolution of β cell loss and insulitis. Our analyses revealed that β cell destruction is preceded by a β cell marker loss and by recruitment of cytotoxic and helper T cells. The approaches described herein demonstrate the value of IMC for improving our understanding of T1D pathogenesis, and our data lay the foundation for hypothesis generation and follow-on experiments.
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.