15 research outputs found

    Retinal aging in 3× Tg-AD mice model of Alzheimer's disease

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    The retina, as part of the central nervous system (CNS), can be the perfect target for in vivo, in situ, and noninvasive neuropathology diagnosis and assessment of therapeutic efficacy. It has long been established that several age-related brain changes are more pronounced in Alzheimer’s disease (AD). Nevertheless, in the retina such link is still under-explored. This study investigates the differences in the aging of the CNS through the retina of 3×Tg-AD and wild-type mice. A dedicated optical coherence tomograph imaged mice’s retinas for 16 months. Two neural networks were developed to model independently each group’s ages and were then applied to an independent set containing images fromboth groups. Our analysis shows amean absolute error of 0.875±1.1×10−2 and 1.112 ± 1.4 × 10−2 months, depending on training group. Our deep learning approach appears to be a reliable retinal OCT aging marker. We show that retina aging is distinct in the two classes: the presence of the three mutated human genes in the mouse genome has an impact on the aging of the retina. For mice over 4 months-old, transgenic mice consistently present a negative retina age-gap when compared to wildtype mice, regardless of training set. This appears to contradict AD observations in the brain. However, the ‘black-box” nature of deep-learning implies that one cannot infer reasoning. We can only speculate that some healthy age-dependent neural adaptations may be altered in transgenic animals.This study was supported by The Portuguese Foundation for Science and Technology (FCT) through PTDC/EMD-EMD/28039/2017, UIDB/04950/2020, PestUID/NEU/04539/2019, and by FEDER-COMPETE through POCI-01-0145-FEDER-028039.info:eu-repo/semantics/publishedVersio

    Longitudinal normative OCT retinal thickness data for wild-type mice, and characterization of changes in the 3×Tg-AD mice model of Alzheimer's disease

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    Mice are widely used as models for many diseases, including eye and neurodegenerative diseases. However, there is a lack of normative data for retinal thickness over time, especially at young ages. In this work, we present a normative thickness database from one to four-months-old, for nine layers/layer-aggregates, including the total retinal thickness, obtained from the segmentation of spectral-domain optical coherence tomography (SD-OCT) data from the C57BL6/129S mouse strain. Based on fifty-seven mice, this normative database provides an opportunity to study the ageing of control mice and characterize disease models' ageing, such as the triple transgenic mouse model of Alzheimer's disease (3×Tg-AD) used in this work. We report thickness measurements, the differences in thickness per layer, demonstrate a nasal-temporal asymmetry, and the variation of thickness as a function to the distance to the optic disc center. Significant differences were found between the transgenic group's thickness and the normative database for the entire period covered in this study. Even though it is well accepted that retinal nerve fiber layer (RNFL) thinning is a hallmark of neurodegeneration, our results show a thicker RNFL-GCL (RNFL-Ganglion cell layer) aggregate for the 3×Tg-AD mice until four-months-old.This study was supported by The Portuguese Foundation for Science and Technology (FCT) through PTDC/ EMD-EMD/28039/2017, UIDB/04950/2020, Pest-UID/ NEU/04539/2019, and by FEDER-COMPETE through POCI-01-0145-FEDER-028039.info:eu-repo/semantics/publishedVersio

    Stage-independent biomarkers for Alzheimer’s disease from the living retina: an animal study

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    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.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.info:eu-repo/semantics/publishedVersio

    Normative mice retinal thickness: 16-month longitudinal characterization of wild-type mice and changes in a model of Alzheimer's disease

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    Animal models of disease are paramount to understand retinal development, the pathophysiology of eye diseases, and to study neurodegeneration using optical coherence tomography (OCT) data. In this study, we present a comprehensive normative database of retinal thickness in C57BL6/129S mice using spectral-domain OCT data. The database covers a longitudinal period of 16 months, from 1 to 16 months of age, and provides valuable insights into retinal development and changes over time. Our findings reveal that total retinal thickness decreases with age, while the thickness of individual retinal layers and layer aggregates changes in different ways. For example, the outer plexiform layer (OPL), photoreceptor inner segments (ILS), and retinal pigment epithelium (RPE) thickened over time, whereas other retinal layers and layer aggregates became thinner. Additionally, we compare the retinal thickness of wild-type (WT) mice with an animal model of Alzheimer's disease (3 × Tg-AD) and show that the transgenic mice exhibit a decrease in total retinal thickness compared to age-matched WT mice, with statistically significant differences observed at all evaluated ages. This normative database of retinal thickness in mice will serve as a reference for future studies on retinal changes in neurodegenerative and eye diseases and will further our understanding of the pathophysiology of these conditions

    Retinal imaging in animal models: Searching for biomarkers of neurodegeneration

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    There is a pressing need for novel diagnostic and progression biomarkers of neurodegeneration. However, the inability to determine disease duration and stage in patients with Alzheimer’s disease (AD) hinders their discovery. Because animal models of disease allow us to circumvent some of these limitations, they have proven to be of paramount importance in clinical research. Due to the clear optics of the eye, the retina combined with optical coherence tomography (OCT) offers the perfect opportunity to image neurodegeneration in the retina in vivo, non-invasively, directly, quickly, and inexpensively. Based on these premises, our group has worked towards uncovering neurodegeneration-associated changes in the retina of the triple-transgenic mouse model of familial AD (3×Tg-AD). In this work, we present an overview of our work on this topic. We report on thickness variations of the retina and retinal layers/layer aggregates caused by healthy aging and AD-like conditions and discuss the implications of focusing research efforts solely on retinal thickness. We explore what other information is embedded in the OCT data, extracted based on texture analysis and deep-learning approaches, to further identify biomarkers that could be used for early detection and diagnosis. We were able to detect changes in the retina of the animal model of AD as early as 1 month of age. We also discuss our work to develop an optical coherence elastography system to measure retinal elasticity, which can be used in conjunction with conventional OCT. Finally, we discuss the potential application of these technologies in human patients and the steps needed to make OCT a helpful screening tool for the detection of neurodegeneration

    The germline mutational landscape of BRCA1 and BRCA2 in Brazil

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    The detection of germline mutations in BRCA1 and BRCA2 is essential to the formulation of clinical management strategies, and in Brazil, there is limited access to these services, mainly due to the costs/availability of genetic testing. Aiming at the identification of recurrent mutations that could be included in a low-cost mutation panel, used as a first screening approach, we compiled the testing reports of 649 probands with pathogenic/likely pathogenic variants referred to 28 public and private health care centers distributed across 11 Brazilian States. Overall, 126 and 103 distinct mutations were identified in BRCA1 and BRCA2, respectively. Twenty-six novel variants were reported from both genes, and BRCA2 showed higher mutational heterogeneity. Some recurrent mutations were reported exclusively in certain geographic regions, suggesting a founder effect. Our findings confirm that there is significant molecular heterogeneity in these genes among Brazilian carriers, while also suggesting that this heterogeneity precludes the use of screening protocols that include recurrent mutation testing only. This is the first study to show that profiles of recurrent mutations may be unique to different Brazilian regions. These data should be explored in larger regional cohorts to determine if screening with a panel of recurrent mutations would be effective.This work was supported in part by grants from Barretos Cancer Hospital (FINEP - CT-INFRA, 02/2010), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, 2013/24633-2 and 2103/23277-8), Fundação de Apoio à Pesquisa do Rio Grande do Norte (FAPERN), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS), Ministério da Saúde, the Breast Cancer Research Foundation (Avon grant #02-2013-044) and National Institute of Health/National Cancer Institute (grant #RC4 CA153828-01) for the Clinical Cancer Genomics Community Research Network. Support in part was provided by grants from Fundo de Incentivo a Pesquisa e Eventos (FIPE) from Hospital de Clínicas de Porto Alegre, by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, BioComputacional 3381/2013, Rede de Pesquisa em Genômica Populacional Humana), Secretaria da Saúde do Estado da Bahia (SESAB), Laboratório de Imunologia e Biologia Molecular (UFBA), INCT pra Controle do Câncer and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). RMR and PAP are recipients of CNPq Productivity Grants, and Bárbara Alemar received a grant from the same agencyinfo:eu-repo/semantics/publishedVersio

    V diretriz da Sociedade Brasileira de Cardiologia sobre tratamento do infarto agudo do miocárdio com supradesnível do segmento ST

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    V diretriz da Sociedade Brasileira de Cardiologia sobre tratamento do infarto agudo do miocárdio com supradesnível do segmento ST

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    Resumo não disponíve

    Characterisation of microbial attack on archaeological bone

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    As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved
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