Publication
Stage-independent biomarkers for Alzheimer’s disease from the living retina: an animal study
| dc.contributor.author | Ferreira, Hugo | |
| dc.contributor.author | Serranho, Pedro | |
| dc.contributor.author | Guimarães, Pedro | |
| dc.contributor.author | Trindade, Rita | |
| dc.contributor.author | Martins, João | |
| dc.contributor.author | Moreira, Paula I. | |
| dc.contributor.author | Ambrósio, António Francisco | |
| dc.contributor.author | Castelo-Branco, Miguel | |
| dc.contributor.author | Bernardes, Rui | |
| dc.date.accessioned | 2023-01-03T15:43:11Z | |
| dc.date.available | 2023-01-03T15:43:11Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | The early diagnosis of neurodegenerative disorders is still an open issue despite the many efforts to address this problem. In particular, Alzheimer’s disease (AD) remains undiagnosed for over a decade before the first symptoms. Optical coherence tomography (OCT) is now common and widely available and has been used to image the retina of AD patients and healthy controls to search for biomarkers of neurodegeneration. However, early diagnosis tools would need to rely on images of patients in early AD stages, which are not available due to late diagnosis. To shed light on how to overcome this obstacle, we resort to 57 wild-type mice and 57 triple-transgenic mouse model of AD to train a network with mice aged 3, 4, and 8 months and classify mice at the ages of 1, 2, and 12 months. To this end, we computed fundus images from OCT data and trained a convolution neural network (CNN) to classify those into the wild-type or transgenic group. CNN performance accuracy ranged from 80 to 88% for mice out of the training group’s age, raising the possibility of diagnosing AD before the first symptoms through the non-invasive imaging of the retina. | pt_PT |
| dc.description.sponsorship | Tis study was supported by Te Portuguese Foundation for Science and Technology (FCT) through PTDC/EMD-EMD/28039/2017, UIDB/04950/2020, UIDB/04539/2020, Pest-UID/NEU/04539/2019, and by FEDERCOMPETE through POCI-01-0145-FEDER-028039. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1038/s41598-022-18113-y | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.2/12928 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.relation | Coimbra Institute for Biomedical Imaging and Translational Research | |
| dc.relation | Center for Innovative Biomedicine and Biotechnology | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.title | Stage-independent biomarkers for Alzheimer’s disease from the living retina: an animal study | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Coimbra Institute for Biomedical Imaging and Translational Research | |
| oaire.awardTitle | Center for Innovative Biomedicine and Biotechnology | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC%2FEMD-EMD%2F28039%2F2017/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04950%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04539%2F2020/PT | |
| oaire.citation.issue | 1 | pt_PT |
| oaire.citation.title | Scientific Reports | pt_PT |
| oaire.citation.volume | 12 | pt_PT |
| oaire.fundingStream | 9471 - RIDTI | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Serranho | |
| person.familyName | Castelo-Branco | |
| person.familyName | Dias Cortesão dos Santos Bernardes | |
| person.givenName | Pedro | |
| person.givenName | Miguel | |
| person.givenName | Rui Manuel | |
| person.identifier | M-4231-2013 | |
| person.identifier.ciencia-id | 031F-5D62-E6EC | |
| person.identifier.ciencia-id | 7A12-48FE-7B56 | |
| person.identifier.ciencia-id | DB19-B18E-690C | |
| person.identifier.orcid | 0000-0003-2176-3923 | |
| person.identifier.orcid | 0000-0003-4364-6373 | |
| person.identifier.orcid | 0000-0002-6677-2754 | |
| person.identifier.scopus-author-id | 7004634386 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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