التفاصيل البيبلوغرافية
| العنوان: |
Modeling Rett Syndrome With Human Patient-Specific Forebrain Organoids |
| المؤلفون: |
Gomes, AR, Fernandes, TG, Vaz, SH, Silva, TP, Bekman, EP, Xapelli, S, Duarte, S, Ghazvini, M, Gribnau, J, Muotri, AR, Trujillo, CA, Sebastião, AM, Cabral, JM, Diogo, MM |
| المساهمون: |
Repositório do Centro Hospitalar Universitário de Lisboa Central, EPE |
| بيانات النشر: |
Frontiers Media SA, 2020. |
| سنة النشر: |
2020 |
| مصطلحات موضوعية: |
Rett syndrome, Disease modeling, Human induced pluripotent stem cells, Neurodevelopmental disorders, HDE NEU PED |
| الوصف: |
Engineering brain organoids from human induced pluripotent stem cells (hiPSCs) is a powerful tool for modeling brain development and neurological disorders. Rett syndrome (RTT), a rare neurodevelopmental disorder, can greatly benefit from this technology, since it affects multiple neuronal subtypes in forebrain sub-regions. We have established dorsal and ventral forebrain organoids from control and RTT patient-specific hiPSCs recapitulating 3D organization and functional network complexity. Our data revealed a premature development of the deep-cortical layer, associated to the formation of TBR1 and CTIP2 neurons, and a lower expression of neural progenitor/proliferative cells in female RTT dorsal organoids. Moreover, calcium imaging and electrophysiology analysis demonstrated functional defects of RTT neurons. Additionally, assembly of RTT dorsal and ventral organoids revealed impairments of interneuron's migration. Overall, our models provide a better understanding of RTT during early stages of neural development, demonstrating a great potential for personalized diagnosis and drug screening. |
| نوع الوثيقة: |
journal article |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| العلاقة: |
Front Cell Dev Biol . 2020 Dec 10;8:61042 |
| DOI: |
10.3389/fcell.2020.610427 |
| الإتاحة: |
http://hdl.handle.net/10400.17/3722Test |
| حقوق: |
open access |
| رقم الانضمام: |
rcaap.com.chlc.repositorio.chlc.min.saude.pt.10400.17.3722 |
| قاعدة البيانات: |
RCAAP |
