{"article_type":"original","has_accepted_license":"1","article_processing_charge":"No","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","date_published":"2020-09-14T00:00:00Z","file_date_updated":"2020-09-21T14:08:58Z","date_created":"2020-09-20T22:01:35Z","oa_version":"Published Version","month":"09","publication_identifier":{"eissn":["14220067"],"issn":["16616596"]},"type":"journal_article","ddc":["570"],"title":"Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses","ec_funded":1,"status":"public","department":[{"_id":"RySh"}],"intvolume":" 21","citation":{"short":"D. Kleindienst, J.-C. Montanaro-Punzengruber, P. Bhandari, M.J. Case, Y. Fukazawa, R. Shigemoto, International Journal of Molecular Sciences 21 (2020).","ama":"Kleindienst D, Montanaro-Punzengruber J-C, Bhandari P, Case MJ, Fukazawa Y, Shigemoto R. Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses. International Journal of Molecular Sciences. 2020;21(18). doi:10.3390/ijms21186737","ista":"Kleindienst D, Montanaro-Punzengruber J-C, Bhandari P, Case MJ, Fukazawa Y, Shigemoto R. 2020. Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses. International Journal of Molecular Sciences. 21(18), 6737.","ieee":"D. Kleindienst, J.-C. Montanaro-Punzengruber, P. Bhandari, M. J. Case, Y. Fukazawa, and R. Shigemoto, “Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses,” International Journal of Molecular Sciences, vol. 21, no. 18. MDPI, 2020.","mla":"Kleindienst, David, et al. “Deep Learning-Assisted High-Throughput Analysis of Freeze-Fracture Replica Images Applied to Glutamate Receptors and Calcium Channels at Hippocampal Synapses.” International Journal of Molecular Sciences, vol. 21, no. 18, 6737, MDPI, 2020, doi:10.3390/ijms21186737.","apa":"Kleindienst, D., Montanaro-Punzengruber, J.-C., Bhandari, P., Case, M. J., Fukazawa, Y., & Shigemoto, R. (2020). Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses. International Journal of Molecular Sciences. MDPI. https://doi.org/10.3390/ijms21186737","chicago":"Kleindienst, David, Jacqueline-Claire Montanaro-Punzengruber, Pradeep Bhandari, Matthew J Case, Yugo Fukazawa, and Ryuichi Shigemoto. “Deep Learning-Assisted High-Throughput Analysis of Freeze-Fracture Replica Images Applied to Glutamate Receptors and Calcium Channels at Hippocampal Synapses.” International Journal of Molecular Sciences. MDPI, 2020. https://doi.org/10.3390/ijms21186737."},"author":[{"first_name":"David","id":"42E121A4-F248-11E8-B48F-1D18A9856A87","full_name":"Kleindienst, David","last_name":"Kleindienst"},{"id":"3786AB44-F248-11E8-B48F-1D18A9856A87","first_name":"Jacqueline-Claire","last_name":"Montanaro-Punzengruber","full_name":"Montanaro-Punzengruber, Jacqueline-Claire"},{"id":"45EDD1BC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-0863-4481","first_name":"Pradeep","last_name":"Bhandari","full_name":"Bhandari, Pradeep"},{"id":"44B7CA5A-F248-11E8-B48F-1D18A9856A87","first_name":"Matthew J","last_name":"Case","full_name":"Case, Matthew J"},{"first_name":"Yugo","last_name":"Fukazawa","full_name":"Fukazawa, Yugo"},{"full_name":"Shigemoto, Ryuichi","last_name":"Shigemoto","first_name":"Ryuichi","id":"499F3ABC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8761-9444"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"isi":1,"project":[{"call_identifier":"H2020","name":"In situ analysis of single channel subunit composition in neurons: physiological implication in synaptic plasticity and behaviour","grant_number":"694539","_id":"25CA28EA-B435-11E9-9278-68D0E5697425"},{"_id":"25D32BC0-B435-11E9-9278-68D0E5697425","name":"Mechanism of formation and maintenance of input side-dependent asymmetry in the hippocampus"},{"call_identifier":"H2020","name":"Human Brain Project Specific Grant Agreement 2 (HBP SGA 2)","_id":"26436750-B435-11E9-9278-68D0E5697425","grant_number":"785907"}],"abstract":[{"lang":"eng","text":"The molecular anatomy of synapses defines their characteristics in transmission and plasticity. Precise measurements of the number and distribution of synaptic proteins are important for our understanding of synapse heterogeneity within and between brain regions. Freeze–fracture replica immunogold electron microscopy enables us to analyze them quantitatively on a two-dimensional membrane surface. Here, we introduce Darea software, which utilizes deep learning for analysis of replica images and demonstrate its usefulness for quick measurements of the pre- and postsynaptic areas, density and distribution of gold particles at synapses in a reproducible manner. We used Darea for comparing glutamate receptor and calcium channel distributions between hippocampal CA3-CA1 spine synapses on apical and basal dendrites, which differ in signaling pathways involved in synaptic plasticity. We found that apical synapses express a higher density of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors and a stronger increase of AMPA receptors with synaptic size, while basal synapses show a larger increase in N-methyl-D-aspartate (NMDA) receptors with size. Interestingly, AMPA and NMDA receptors are segregated within postsynaptic sites and negatively correlated in density among both apical and basal synapses. In the presynaptic sites, Cav2.1 voltage-gated calcium channels show similar densities in apical and basal synapses with distributions consistent with an exclusion zone model of calcium channel-release site topography."}],"related_material":{"record":[{"relation":"dissertation_contains","id":"9562","status":"public"}]},"scopus_import":"1","quality_controlled":"1","oa":1,"language":[{"iso":"eng"}],"day":"14","year":"2020","publisher":"MDPI","volume":21,"external_id":{"isi":["000579945300001"]},"publication_status":"published","file":[{"success":1,"date_created":"2020-09-21T14:08:58Z","content_type":"application/pdf","file_size":5748456,"date_updated":"2020-09-21T14:08:58Z","checksum":"2e4f62f3cfe945b7391fc3070e5a289f","creator":"dernst","access_level":"open_access","file_name":"2020_JournMolecSciences_Kleindienst.pdf","file_id":"8551","relation":"main_file"}],"acknowledgement":"This research was funded by Austrian Academy of Sciences, DOC fellowship to D.K., European Research\r\nCouncil Advanced Grant 694539 and European Union Human Brain Project (HBP) SGA2 785907 to R.S.\r\nWe acknowledge Elena Hollergschwandtner for technical support.","doi":"10.3390/ijms21186737","issue":"18","publication":"International Journal of Molecular Sciences","_id":"8532","article_number":"6737","date_updated":"2024-04-19T22:30:29Z"}