Unique Deep Radiomic Signature Shows NMN Treatment Reverses Morphology of Oocytes from Aged Mice

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dc.contributor.authorHabibalahi, A.
dc.contributor.authorCampbell, J.M.
dc.contributor.authorBertoldo, M.J.
dc.contributor.authorMahbub, S.B.
dc.contributor.authorGoss, D.M.
dc.contributor.authorLedger, W.L.
dc.contributor.authorGilchrist, R.B.
dc.contributor.authorWu, L.E.
dc.contributor.authorGoldys, E.M.
dc.date.issued2022
dc.description.abstractThe purpose of this study is to develop a deep radiomic signature based on an artificial intelligence (AI) model. This radiomic signature identifies oocyte morphological changes corresponding to reproductive aging in bright field images captured by optical light microscopy. Oocytes were collected from three mice groups: young (4- to 5-week-old) C57BL/6J female mice, aged (12-monthold) mice, and aged mice treated with the NAD+ precursor nicotinamide mononucleotide (NMN), a treatment recently shown to rejuvenate aspects of fertility in aged mice. We applied deep learning, swarm intelligence, and discriminative analysis to images of mouse oocytes taken by bright field microscopy to identify a highly informative deep radiomic signature (DRS) of oocyte morphology. Predictive DRS accuracy was determined by evaluating sensitivity, specificity, and cross-validation, and was visualized using scatter plots of the data associated with three groups: Young, old and Old + NMN. DRS could successfully distinguish morphological changes in oocytes associated with maternal age with 92% accuracy (AUC~1), reflecting this decline in oocyte quality. We then employed the DRS to evaluate the impact of the treatment of reproductively aged mice with NMN. The DRS signature classified 60% of oocytes from NMN-treated aged mice as having a ‘young’ morphology. In conclusion, the DRS signature developed in this study was successfully able to detect aging-related oocyte morphological changes. The significance of our approach is that DRS applied to bright field oocyte images will allow us to distinguish and select oocytes originally affected by reproductive aging and whose quality has been successfully restored by the NMN therapy.
dc.description.statementofresponsibilityAbbas Habibalahi, Jared M. Campbell, Michael J. Bertoldo, Saabah B. Mahbub, Dale M. Goss, William L. Ledger, Robert B. Gilchrist, Lindsay E. Wu, and Ewa M. Goldys
dc.identifier.citationBiomedicines, 2022; 10(7):1544-1-1544-13
dc.identifier.doi10.3390/biomedicines10071544
dc.identifier.issn2227-9059
dc.identifier.issn2227-9059
dc.identifier.orcidCampbell, J.M. [0000-0003-0163-4251]
dc.identifier.urihttps://hdl.handle.net/2440/136260
dc.language.isoen
dc.publisherMDPI AG
dc.relation.granthttp://purl.org/au-research/grants/arc/CE140100003
dc.relation.granthttp://purl.org/au-research/grants/arc/DP170101863
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1139763
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1117538
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1127821
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1122484
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1103689
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1093643
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
dc.source.urihttps://doi.org/10.3390/biomedicines10071544
dc.subjectNMN
dc.subjectaging
dc.subjectmachine learning
dc.subjectmorphology
dc.subjectoocyte
dc.titleUnique Deep Radiomic Signature Shows NMN Treatment Reverses Morphology of Oocytes from Aged Mice
dc.typeJournal article
pubs.publication-statusPublished

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