Image Tracing of Inflammatory Intestinal Organoids via Computational Clearing.
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| Title: | Image Tracing of Inflammatory Intestinal Organoids via Computational Clearing. |
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| Authors: | Jeon, Dong-Gyu1,2 (AUTHOR), Han, Min-Young2,3 (AUTHOR), Lee, Hana3,4 (AUTHOR), Hwang, Hanguk3,4 (AUTHOR), Lee, Ji-Min2,5 (AUTHOR), Kim, Eun Soo5,6 (AUTHOR), Lee, Gang Ho6,7 (AUTHOR), Chang, Yongmin1,3 (AUTHOR), Son, Mi-Young2,4 (AUTHOR), Park, Mae-Ja3,7 (AUTHOR), Nam, Sung-Wook1,2,3,4 (AUTHOR) nams@knu.ac.kr |
| Source: | Nanomaterials (2079-4991). May2026, Vol. 16 Issue 10, p629. 19p. |
| Subjects: | Fluorescence microscopy, Image enhancement (Imaging systems), Fluorimetry, RNA sequencing, Intestinal barrier function, Feature extraction, Dextran sulfate |
| Abstract: | Computational clearing (CC) enhances widefield (WF) fluorescence microscopy by suppressing out-of-focus haze and autofluorescence, yielding semi-confocal quality images suitable for segmentation and image-based phenotyping. Here, we propose an "image tracing" workflow for inflammatory mouse intestinal organoids (mIOs) using paired CC and WF images to generate a differential signal (CC − WF). mIOs were derived from intestinal crypts of Lgr5-EGFP stem cell reporter mice and expanded under epidermal growth factor, Noggin, and R-spondin (ENR) conditions. Inflammation was induced by dextran sulfate sodium (DSS) treatment. CC processing enhanced phalloidin-stained apical F-actin and improved EGFP signals by reducing background noise, enabling robust segmentation and quantitative extraction of image morphometrics including area, circularity, and perimeter. CC-WF vectors derived from three-dimensional area–perimeter–circularity plots sensitively captured DSS-induced epithelial disruption analogous to a leaky-epithelium phenotype. Transcriptomic analysis by RNA-seq of DSS-treated mIOs revealed upregulation of inflammatory pathways including TNF-α signaling via NF-κB and IL-6/JAK/STAT3, aligning with microscopy findings. In a proof-of-concept demonstration using phalloidin-stained fluorescence images, ROC analysis of the CC-WF workflow achieved an AUC = 0.95 with 87.5% sensitivity and 92.9% specificity in distinguishing intact from injured mIOs. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Computational clearing (CC) enhances widefield (WF) fluorescence microscopy by suppressing out-of-focus haze and autofluorescence, yielding semi-confocal quality images suitable for segmentation and image-based phenotyping. Here, we propose an "image tracing" workflow for inflammatory mouse intestinal organoids (mIOs) using paired CC and WF images to generate a differential signal (CC − WF). mIOs were derived from intestinal crypts of Lgr5-EGFP stem cell reporter mice and expanded under epidermal growth factor, Noggin, and R-spondin (ENR) conditions. Inflammation was induced by dextran sulfate sodium (DSS) treatment. CC processing enhanced phalloidin-stained apical F-actin and improved EGFP signals by reducing background noise, enabling robust segmentation and quantitative extraction of image morphometrics including area, circularity, and perimeter. CC-WF vectors derived from three-dimensional area–perimeter–circularity plots sensitively captured DSS-induced epithelial disruption analogous to a leaky-epithelium phenotype. Transcriptomic analysis by RNA-seq of DSS-treated mIOs revealed upregulation of inflammatory pathways including TNF-α signaling via NF-κB and IL-6/JAK/STAT3, aligning with microscopy findings. In a proof-of-concept demonstration using phalloidin-stained fluorescence images, ROC analysis of the CC-WF workflow achieved an AUC = 0.95 with 87.5% sensitivity and 92.9% specificity in distinguishing intact from injured mIOs. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20794991 |
| DOI: | 10.3390/nano16100629 |
