ArticleMaterials today. Bio2026
AI-enabled label free monitoring of TGFβ1-induced remodeling in iPSC-derived alveolar organoids.
Article in Materials today. Bio, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.Bioactive materials · 2027Review
- Real-time sensing-integrated organoid-on-a-chip platforms: Technological progress and emerging biomedical applications.Bioactive materials · 2026Review
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
No grant is acknowledged in the PubMed record.
Abstract
Pulmonary fibrosis (PF) is a progressive interstitial lung disease with poor prognosis and limited therapeutic options, largely due to the lack of physiologically relevant and dynamically traceable preclinical models. Here, we establish an induced pluripotent stem cell (iPSC)-derived alveolar organoid platform that faithfully recapitulates PF-like remodeling upon TGFβ1 stimulation. The organoids exhibit lineage commitment to the distal lung epithelium (NKX2.1, SFTPC/SFTPB) and, following TGFβ1 exposure, undergo hallmark fibrotic changes including organoid condensation and size reduction, collagen deposition (Masson's trichrome), myofibroblast activation (α-SMA), up-regulation of profibrotic genes (COL1A1, FN, VIM, ACTA2), and partial EMT-like reprogramming (↑CDH2, TWIST1, and ↓CDH1). To enable label-free, longitudinal readouts, we integrate a deep neural network (YOLOv8-nano) that detects subtle morphological cues directly from bright-field images and classifies treatment status with high fidelity. Across augmented datasets (8892 images), the model achieved strong performance on the original context-preserving images (mAP50-95 up to 0.95; high precision/recall and 98-99% true-positive rates), supporting robust discrimination of control versus TGFβ1-treated organoids. This AI-enhanced organoid system provides a quantitative, label-free platform for monitoring fibrotic remodeling and offers a scalable foundation for preclinical antifibrotic screening and mechanism-of-action studies.
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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 Socratic graph.