| Title: |
Domain-specific AI segmentation of IMPDH2 rod/ring structures in mouse embryonic stem cells |
| Authors: |
Ball STM; Hennessy MJ; Tan Y; Hoettges KF; Perkins ND; Wilkinson DJ; White MRH; Zheng Y; Turner DA |
| Source: |
BMC Biology, December 2025 |
| Publisher Information: |
BioMed Central Ltd |
| Publication Year: |
2025 |
| Collection: |
Newcastle University Library ePrints Service |
| Description: |
© The Author(s) 2025.Background: Inosine monophosphate dehydrogenase 2 (IMPDH2) is an enzyme that catalyses the rate-limiting step of guanine nucleotides. In mouse embryonic stem cells (ESCs), IMPDH2 forms large multi-protein complexes known as rod-ring (RR) structures that dissociate when ESCs differentiate. Manual analysis of RR structures from confocal microscopy images, although possible, is not feasible on a large scale due to the quantity of RR structures present in each field of view. To address this analysis bottleneck, we have created a fully automatic RR image classification pipeline to segment, characterise and measure feature distributions of these structures in ESCs. Results: We find that this model can automatically segment images with a Dice score of over 80% for both rods and rings for in-domain images compared to expert annotation, with a slight drop to 70% for datasets out of domain. Important feature measurements derived from these segmentations show high agreement with the measurements derived from expert annotation, achieving an R2 score of over 90% for counting the number of RRs over the dataset. Conclusions: We have established for the first time a quantitative baseline for RR distribution in pluripotent ESCs and have made a pipeline available for training to be applied to other models in which RR remain an open topic of study. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://eprints.ncl.ac.uk/305969; https://eprints.ncl.ac.uk/fulltext.aspx?url=305969/084100F4-FA4F-4542-B720-27C7DA155609.pdf&pub_id=305969 |
| Availability: |
https://eprints.ncl.ac.uk/305969 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.85AFE95F |
| Database: |
BASE |