{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["11(1)"],"submitter":["Rosales Jubal E"],"funding":["Stiftung Rheinland-Pfalz für Innovation","Boehringer Ingelheim Foundation","Focus Program Translational Neurosciences","Alfred Dollwet Foundation","Universitätsmedizin der Johannes Gutenberg-Universität Mainz"],"pubmed_abstract":["Aberrant activity of local functional networks underlies memory and cognition deficits in Alzheimer's disease (AD). Hyperactivity was observed in microcircuits of mice AD-models showing plaques, and also recently in early stage AD mutants prior to amyloid deposition. However, early functional effects of AD on cortical microcircuits remain unresolved. Using two-photon calcium imaging, we found altered temporal distributions (burstiness) in the spontaneous activity of layer II/III visual cortex neurons, in a mouse model of familial Alzheimer's disease (5xFAD), before plaque formation. Graph theory (GT) measures revealed a distinct network topology of 5xFAD microcircuits, as compared to healthy controls, suggesting degradation of parameters related to network robustness. After treatment with acitretin, we observed a re-balancing of those network measures in 5xFAD mice; particularly in the mean degree distribution, related to network development and resilience, and post-treatment values resembled those of age-matched controls. Further, behavioral deficits, and the increase of excitatory synapse numbers in layer II/III were reversed after treatment. GT is widely applied for whole-brain network analysis in human neuroimaging, we here demonstrate the translational value of GT as a multi-level tool, to probe networks at different levels in order to assess treatments, explore mechanisms, and contribute to early diagnosis."],"journal":["Scientific reports"],"pagination":["6649"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7988040"],"repository":["biostudies-literature"],"pubmed_title":["Acitretin reverses early functional network degradation in a mouse model of familial Alzheimer's disease."],"pmcid":["PMC7988040"],"pubmed_authors":["Wierczeiko A","Schmitt U","Dos Santos Guilherme M","Tose A","Endres K","Schuck F","Rosales Jubal E","Schmeisser MJ","Roesler MK","Reinhardt S","Ruffini N","Schwalm M","Barger Z","Stroh A"],"additional_accession":[]},"is_claimable":false,"name":"Acitretin reverses early functional network degradation in a mouse model of familial Alzheimer's disease.","description":"Aberrant activity of local functional networks underlies memory and cognition deficits in Alzheimer's disease (AD). Hyperactivity was observed in microcircuits of mice AD-models showing plaques, and also recently in early stage AD mutants prior to amyloid deposition. However, early functional effects of AD on cortical microcircuits remain unresolved. Using two-photon calcium imaging, we found altered temporal distributions (burstiness) in the spontaneous activity of layer II/III visual cortex neurons, in a mouse model of familial Alzheimer's disease (5xFAD), before plaque formation. Graph theory (GT) measures revealed a distinct network topology of 5xFAD microcircuits, as compared to healthy controls, suggesting degradation of parameters related to network robustness. After treatment with acitretin, we observed a re-balancing of those network measures in 5xFAD mice; particularly in the mean degree distribution, related to network development and resilience, and post-treatment values resembled those of age-matched controls. Further, behavioral deficits, and the increase of excitatory synapse numbers in layer II/III were reversed after treatment. GT is widely applied for whole-brain network analysis in human neuroimaging, we here demonstrate the translational value of GT as a multi-level tool, to probe networks at different levels in order to assess treatments, explore mechanisms, and contribute to early diagnosis.","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Mar","modification":"2025-04-18T21:43:28.234Z","creation":"2025-04-07T09:34:14.593Z"},"accession":"S-EPMC7988040","cross_references":{"pubmed":["33758244"],"doi":["10.1038/s41598-021-85912-0"]}}