--- _id: '11196' abstract: - lang: eng text: "One of the fundamental questions in Neuroscience is how the structure of synapses and their physiological properties are related. While synaptic transmission remains a dynamic process, electron microscopy provides images with comparably low temporal resolution (Studer et al., 2014). The current work overcomes this challenge and describes an improved “Flash and Freeze” technique (Watanabe et al., 2013a; Watanabe et al., 2013b) to study synaptic transmission at the hippocampal mossy fiber-CA3 pyramidal neuron synapses, using mouse acute brain slices and organotypic slices culture. The improved method allowed for selective stimulation of presynaptic mossy fiber boutons and the observation of synaptic vesicle pool dynamics at the active zones. Our results uncovered several intriguing morphological features of mossy fiber boutons. First, the docked vesicle pool was largely depleted (more than 70%) after stimulation, implying that the docked synaptic vesicles pool and readily releasable pool are vastly overlapping in mossy fiber boutons. Second, the synaptic vesicles are skewed towards larger diameters, displaying a wide range of sizes. An increase in the mean diameter of synaptic vesicles, after single and repetitive stimulation, suggests that smaller vesicles have a higher release probability. Third, we observed putative endocytotic structures after moderate light stimulation, matching the timing of previously described ultrafast endocytosis (Watanabe et al., 2013a; Delvendahl et al., 2016). \r\n\tIn addition, synaptic transmission depends on a sophisticated system of protein machinery and calcium channels (Südhof, 2013b), which amplifies the challenge in studying synaptic communication as these interactions can be potentially modified during synaptic plasticity. And although recent study elucidated the potential correlation between physiological and morphological properties of synapses during synaptic plasticity (Vandael et al., 2020), the molecular underpinning of it remains unknown. Thus, the presented work tries to overcome this challenge and aims to pinpoint changes in the molecular architecture at hippocampal mossy fiber bouton synapses during short- and long-term potentiation (STP and LTP), we combined chemical potentiation, with the application of a cyclic adenosine monophosphate agonist (i.e. forskolin) and freeze-fracture replica immunolabelling. This method allowed the localization of membrane-bound proteins with nanometer precision within the active zone, in particular, P/Q-type calcium channels and synaptic vesicle priming proteins Munc13-1/2. First, we found that the number of clusters of Munc13-1 in the mossy fiber bouton active zone increased significantly during STP, but decreased to lower than the control value during LTP. Secondly, although the distance between the calcium channels and Munc13-1s did not change after induction of STP, it shortened during the LTP phase. Additionally, forskolin did not affect Munc13-2 distribution during STP and LTP. These results indicate the existence of two distinct mechanisms that govern STP and LTP at mossy fiber bouton synapses: an increase in the readily realizable pool in the case of STP and a potential increase in release probability during LTP. “Flash and freeze” and functional electron microscopy, are versatile methods that can be successfully applied to intact brain circuits to study synaptic transmission even at the molecular level.\r\n" acknowledged_ssus: - _id: EM-Fac - _id: PreCl alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Olena full_name: Kim, Olena id: 3F8ABDDA-F248-11E8-B48F-1D18A9856A87 last_name: Kim citation: ama: Kim O. Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses. 2022. doi:10.15479/at:ista:11196 apa: Kim, O. (2022). Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:11196 chicago: Kim, Olena. “Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal Neuron Synapses.” Institute of Science and Technology Austria, 2022. https://doi.org/10.15479/at:ista:11196. ieee: O. Kim, “Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses,” Institute of Science and Technology Austria, 2022. ista: Kim O. 2022. Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses. Institute of Science and Technology Austria. mla: Kim, Olena. Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal Neuron Synapses. Institute of Science and Technology Austria, 2022, doi:10.15479/at:ista:11196. short: O. Kim, Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal Neuron Synapses, Institute of Science and Technology Austria, 2022. date_created: 2022-04-20T09:47:12Z date_published: 2022-04-20T00:00:00Z date_updated: 2023-08-18T06:31:52Z day: '20' ddc: - '570' degree_awarded: PhD department: - _id: PeJo - _id: GradSch doi: 10.15479/at:ista:11196 ec_funded: 1 file: - access_level: open_access checksum: 1616a8bf6f13a57c892dac873dcd0936 content_type: application/pdf creator: okim date_created: 2022-04-20T14:21:56Z date_updated: 2023-04-20T22:30:03Z embargo: 2023-04-19 file_id: '11220' file_name: Olena_KIM_thesis_final.pdf file_size: 21273537 relation: main_file - access_level: closed checksum: 1acb433f98dc42abb0b4b0cbb0c4b918 content_type: application/x-zip-compressed creator: okim date_created: 2022-04-20T14:22:56Z date_updated: 2023-04-20T22:30:03Z embargo_to: open_access file_id: '11221' file_name: KIM_thesis_final.zip file_size: 59248569 relation: source_file file_date_updated: 2023-04-20T22:30:03Z has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '04' oa: 1 oa_version: Published Version page: '132' project: - _id: 25BAF7B2-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '708497' name: Presynaptic calcium channels distribution and impact on coupling at the hippocampal mossy fiber synapse - _id: 25B7EB9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '692692' name: Biophysics and circuit function of a giant cortical glumatergic synapse - _id: 25C3DBB6-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: W01205 name: Zellkommunikation in Gesundheit und Krankheit - _id: 25C5A090-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00312 name: The Wittgenstein Prize publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '11222' relation: part_of_dissertation status: public - id: '7473' relation: part_of_dissertation status: public status: public supervisor: - first_name: Peter M full_name: Jonas, Peter M id: 353C1B58-F248-11E8-B48F-1D18A9856A87 last_name: Jonas orcid: 0000-0001-5001-4804 title: Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2022' ... --- _id: '11943' abstract: - lang: eng text: Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive visualization of the architecture of living brain tissue with its cellular and molecular components would open up major opportunities. However, electron microscopy (EM) provides nanometre-scale resolution required for full in-silico reconstruction1–5, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches6–12 facilitating nanoscale visualization, but comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue. We developed an integrated imaging and analysis technology, adapting stimulated emission depletion (STED) microscopy6,13 in extracellularly labelled tissue14 for high SNR and near-isotropic resolution. Centrally, a two-stage deep-learning approach leveraged previously obtained information on sample structure to drastically reduce photo-burden and enable automated volumetric reconstruction down to single synapse level. Live reconstruction provides unbiased analysis of tissue architecture across time in relation to functional activity and targeted activation, and contextual understanding of molecular labelling. This adoptable technology will facilitate novel insights into the dynamic functional architecture of living brain tissue. article_processing_charge: No author: - first_name: Philipp full_name: Velicky, Philipp id: 39BDC62C-F248-11E8-B48F-1D18A9856A87 last_name: Velicky orcid: 0000-0002-2340-7431 - first_name: Eder full_name: Miguel Villalba, Eder id: 3FB91342-F248-11E8-B48F-1D18A9856A87 last_name: Miguel Villalba orcid: 0000-0001-5665-0430 - first_name: Julia M full_name: Michalska, Julia M id: 443DB6DE-F248-11E8-B48F-1D18A9856A87 last_name: Michalska orcid: 0000-0003-3862-1235 - first_name: Donglai full_name: Wei, Donglai last_name: Wei - first_name: Zudi full_name: Lin, Zudi last_name: Lin - first_name: Jake full_name: Watson, Jake id: 63836096-4690-11EA-BD4E-32803DDC885E last_name: Watson orcid: 0000-0002-8698-3823 - first_name: Jakob full_name: Troidl, Jakob last_name: Troidl - first_name: Johanna full_name: Beyer, Johanna last_name: Beyer - first_name: Yoav full_name: Ben Simon, Yoav id: 43DF3136-F248-11E8-B48F-1D18A9856A87 last_name: Ben Simon - first_name: Christoph M full_name: Sommer, Christoph M id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87 last_name: Sommer orcid: 0000-0003-1216-9105 - first_name: Wiebke full_name: Jahr, Wiebke id: 425C1CE8-F248-11E8-B48F-1D18A9856A87 last_name: Jahr - first_name: Alban full_name: Cenameri, Alban id: 9ac8f577-2357-11eb-997a-e566c5550886 last_name: Cenameri - first_name: Johannes full_name: Broichhagen, Johannes last_name: Broichhagen - first_name: Seth G. N. full_name: Grant, Seth G. N. last_name: Grant - first_name: Peter M full_name: Jonas, Peter M id: 353C1B58-F248-11E8-B48F-1D18A9856A87 last_name: Jonas orcid: 0000-0001-5001-4804 - first_name: Gaia full_name: Novarino, Gaia id: 3E57A680-F248-11E8-B48F-1D18A9856A87 last_name: Novarino orcid: 0000-0002-7673-7178 - first_name: Hanspeter full_name: Pfister, Hanspeter last_name: Pfister - first_name: Bernd full_name: Bickel, Bernd id: 49876194-F248-11E8-B48F-1D18A9856A87 last_name: Bickel orcid: 0000-0001-6511-9385 - first_name: Johann G full_name: Danzl, Johann G id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87 last_name: Danzl orcid: 0000-0001-8559-3973 citation: ama: Velicky P, Miguel Villalba E, Michalska JM, et al. Saturated reconstruction of living brain tissue. bioRxiv. doi:10.1101/2022.03.16.484431 apa: Velicky, P., Miguel Villalba, E., Michalska, J. M., Wei, D., Lin, Z., Watson, J., … Danzl, J. G. (n.d.). Saturated reconstruction of living brain tissue. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2022.03.16.484431 chicago: Velicky, Philipp, Eder Miguel Villalba, Julia M Michalska, Donglai Wei, Zudi Lin, Jake Watson, Jakob Troidl, et al. “Saturated Reconstruction of Living Brain Tissue.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/2022.03.16.484431. ieee: P. Velicky et al., “Saturated reconstruction of living brain tissue,” bioRxiv. Cold Spring Harbor Laboratory. ista: Velicky P, Miguel Villalba E, Michalska JM, Wei D, Lin Z, Watson J, Troidl J, Beyer J, Ben Simon Y, Sommer CM, Jahr W, Cenameri A, Broichhagen J, Grant SGN, Jonas PM, Novarino G, Pfister H, Bickel B, Danzl JG. Saturated reconstruction of living brain tissue. bioRxiv, 10.1101/2022.03.16.484431. mla: Velicky, Philipp, et al. “Saturated Reconstruction of Living Brain Tissue.” BioRxiv, Cold Spring Harbor Laboratory, doi:10.1101/2022.03.16.484431. short: P. Velicky, E. Miguel Villalba, J.M. Michalska, D. Wei, Z. Lin, J. Watson, J. Troidl, J. Beyer, Y. Ben Simon, C.M. Sommer, W. Jahr, A. Cenameri, J. Broichhagen, S.G.N. Grant, P.M. Jonas, G. Novarino, H. Pfister, B. Bickel, J.G. Danzl, BioRxiv (n.d.). date_created: 2022-08-23T11:07:59Z date_published: 2022-05-09T00:00:00Z date_updated: 2024-03-28T23:30:20Z day: '09' department: - _id: PeJo - _id: GaNo - _id: BeBi - _id: JoDa doi: 10.1101/2022.03.16.484431 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1101/2022.03.16.484431 month: '05' oa: 1 oa_version: Preprint publication: bioRxiv publication_status: submitted publisher: Cold Spring Harbor Laboratory related_material: record: - id: '12470' relation: dissertation_contains status: public status: public title: Saturated reconstruction of living brain tissue type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '11950' abstract: - lang: eng text: Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanoscopic synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS leverages fixation-compatible extracellular labeling and advanced optical readout, in particular stimulated-emission depletion and expansion microscopy, to comprehensively delineate cellular structures. It enables 3D-reconstructing single synapses and mapping synaptic connectivity by identification and tailored analysis of putative synaptic cleft regions. Applying CATS to the hippocampal mossy fiber circuitry, we demonstrate its power to reveal the system’s molecularly informed ultrastructure across spatial scales and assess local connectivity by reconstructing and quantifying the synaptic input and output structure of identified neurons. article_processing_charge: No author: - first_name: Julia M full_name: Michalska, Julia M id: 443DB6DE-F248-11E8-B48F-1D18A9856A87 last_name: Michalska orcid: 0000-0003-3862-1235 - first_name: Julia full_name: Lyudchik, Julia id: 46E28B80-F248-11E8-B48F-1D18A9856A87 last_name: Lyudchik - first_name: Philipp full_name: Velicky, Philipp id: 39BDC62C-F248-11E8-B48F-1D18A9856A87 last_name: Velicky orcid: 0000-0002-2340-7431 - first_name: Hana full_name: Korinkova, Hana id: ee3cb6ca-ec98-11ea-ae11-ff703e2254ed last_name: Korinkova - first_name: Jake full_name: Watson, Jake id: 63836096-4690-11EA-BD4E-32803DDC885E last_name: Watson orcid: 0000-0002-8698-3823 - first_name: Alban full_name: Cenameri, Alban id: 9ac8f577-2357-11eb-997a-e566c5550886 last_name: Cenameri - first_name: Christoph M full_name: Sommer, Christoph M id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87 last_name: Sommer orcid: 0000-0003-1216-9105 - first_name: Alessandro full_name: Venturino, Alessandro id: 41CB84B2-F248-11E8-B48F-1D18A9856A87 last_name: Venturino orcid: 0000-0003-2356-9403 - first_name: Karl full_name: Roessler, Karl last_name: Roessler - first_name: Thomas full_name: Czech, Thomas last_name: Czech - first_name: Sandra full_name: Siegert, Sandra id: 36ACD32E-F248-11E8-B48F-1D18A9856A87 last_name: Siegert orcid: 0000-0001-8635-0877 - first_name: Gaia full_name: Novarino, Gaia id: 3E57A680-F248-11E8-B48F-1D18A9856A87 last_name: Novarino orcid: 0000-0002-7673-7178 - first_name: Peter M full_name: Jonas, Peter M id: 353C1B58-F248-11E8-B48F-1D18A9856A87 last_name: Jonas orcid: 0000-0001-5001-4804 - first_name: Johann G full_name: Danzl, Johann G id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87 last_name: Danzl orcid: 0000-0001-8559-3973 citation: ama: Michalska JM, Lyudchik J, Velicky P, et al. Uncovering brain tissue architecture across scales with super-resolution light microscopy. bioRxiv. doi:10.1101/2022.08.17.504272 apa: Michalska, J. M., Lyudchik, J., Velicky, P., Korinkova, H., Watson, J., Cenameri, A., … Danzl, J. G. (n.d.). Uncovering brain tissue architecture across scales with super-resolution light microscopy. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2022.08.17.504272 chicago: Michalska, Julia M, Julia Lyudchik, Philipp Velicky, Hana Korinkova, Jake Watson, Alban Cenameri, Christoph M Sommer, et al. “Uncovering Brain Tissue Architecture across Scales with Super-Resolution Light Microscopy.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/2022.08.17.504272. ieee: J. M. Michalska et al., “Uncovering brain tissue architecture across scales with super-resolution light microscopy,” bioRxiv. Cold Spring Harbor Laboratory. ista: Michalska JM, Lyudchik J, Velicky P, Korinkova H, Watson J, Cenameri A, Sommer CM, Venturino A, Roessler K, Czech T, Siegert S, Novarino G, Jonas PM, Danzl JG. Uncovering brain tissue architecture across scales with super-resolution light microscopy. bioRxiv, 10.1101/2022.08.17.504272. mla: Michalska, Julia M., et al. “Uncovering Brain Tissue Architecture across Scales with Super-Resolution Light Microscopy.” BioRxiv, Cold Spring Harbor Laboratory, doi:10.1101/2022.08.17.504272. short: J.M. Michalska, J. Lyudchik, P. Velicky, H. Korinkova, J. Watson, A. Cenameri, C.M. Sommer, A. Venturino, K. Roessler, T. Czech, S. Siegert, G. Novarino, P.M. Jonas, J.G. Danzl, BioRxiv (n.d.). date_created: 2022-08-24T08:24:52Z date_published: 2022-08-18T00:00:00Z date_updated: 2024-03-28T23:30:20Z day: '18' department: - _id: SaSi - _id: GaNo - _id: PeJo - _id: JoDa doi: 10.1101/2022.08.17.504272 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1101/2022.08.17.504272 month: '08' oa: 1 oa_version: Preprint publication: bioRxiv publication_status: submitted publisher: Cold Spring Harbor Laboratory related_material: record: - id: '12470' relation: dissertation_contains status: public status: public title: Uncovering brain tissue architecture across scales with super-resolution light microscopy type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '9097' abstract: - lang: eng text: Psoriasis is a chronic inflammatory skin disease clinically characterized by the appearance of red colored, well-demarcated plaques with thickened skin and with silvery scales. Recent studies have established the involvement of a complex signalling network of interactions between cytokines, immune cells and skin cells called keratinocytes. Keratinocytes form the cells of the outermost layer of the skin (epidermis). Visible plaques in psoriasis are developed due to the fast proliferation and unusual differentiation of keratinocyte cells. Despite that, the exact mechanism of the appearance of these plaques in the cytokine-immune cell network is not clear. A mathematical model embodying interactions between key immune cells believed to be involved in psoriasis, keratinocytes and relevant cytokines has been developed. The complex network formed of these interactions poses several challenges. Here, we choose to study subnetworks of this complex network and initially focus on interactions involving TNFα, IL-23/IL-17, and IL-15. These are chosen based on known evidence of their therapeutic efficacy. In addition, we explore the role of IL-15 in the pathogenesis of psoriasis and its potential as a future drug target for a novel treatment option. We perform steady state analyses for these subnetworks and demonstrate that the interactions between cells, driven by cytokines could cause the emergence of a psoriasis state (hyper-proliferation of keratinocytes) when levels of TNFα, IL-23/IL-17 or IL-15 are increased. The model results explain and support the clinical potentiality of anti-cytokine treatments. Interestingly, our results suggest different dynamic scenarios underpin the pathogenesis of psoriasis, depending upon the dominant cytokines of subnetworks. We observed that the increase in the level of IL-23/IL-17 and IL-15 could lead to psoriasis via a bistable route, whereas an increase in the level of TNFα would lead to a monotonic and gradual disease progression. Further, we demonstrate how this insight, bistability, could be exploited to improve the current therapies and develop novel treatment strategies for psoriasis. acknowledgement: RP acknowledges the Department of Science and Technology, India for the support through the DST-INSPIRE Faculty Award (DST/INSPIRE/04/2015/001939). This work was supported by the Engineering and Physical Sciences Research Council (EPSRC), United Kingdom (Grant numbers EP/J018295/1, EP/J018392/1, EP/N014391/1). The contribution of RP was also supported by the later Grant. This work was generously supported by the Welcome Trust Institutional Strategic Support Award (204909/Z/16/Z) too. The contribution of MG was supported by the EPSRC via EP/N014391/1 and a Wellcome Trust Institutional Strategic Support Award (WT105618MA). The contribution of YA was generously supported by the Wellcome Trust Institutional Strategic Support Award (WT105618MA). article_number: '2204' article_processing_charge: No article_type: original author: - first_name: Rakesh full_name: Pandey, Rakesh last_name: Pandey - first_name: Yusur full_name: Al-Nuaimi, Yusur last_name: Al-Nuaimi - first_name: Rajiv Kumar full_name: Mishra, Rajiv Kumar id: 46CB58F2-F248-11E8-B48F-1D18A9856A87 last_name: Mishra - first_name: Sarah K. full_name: Spurgeon, Sarah K. last_name: Spurgeon - first_name: Marc full_name: Goodfellow, Marc last_name: Goodfellow citation: ama: Pandey R, Al-Nuaimi Y, Mishra RK, Spurgeon SK, Goodfellow M. Role of subnetworks mediated by TNF α, IL-23/IL-17 and IL-15 in a network involved in the pathogenesis of psoriasis. Scientific Reports. 2021;11. doi:10.1038/s41598-020-80507-7 apa: Pandey, R., Al-Nuaimi, Y., Mishra, R. K., Spurgeon, S. K., & Goodfellow, M. (2021). Role of subnetworks mediated by TNF α, IL-23/IL-17 and IL-15 in a network involved in the pathogenesis of psoriasis. Scientific Reports. Springer Nature. https://doi.org/10.1038/s41598-020-80507-7 chicago: Pandey, Rakesh, Yusur Al-Nuaimi, Rajiv Kumar Mishra, Sarah K. Spurgeon, and Marc Goodfellow. “Role of Subnetworks Mediated by TNF α, IL-23/IL-17 and IL-15 in a Network Involved in the Pathogenesis of Psoriasis.” Scientific Reports. Springer Nature, 2021. https://doi.org/10.1038/s41598-020-80507-7. ieee: R. Pandey, Y. Al-Nuaimi, R. K. Mishra, S. K. Spurgeon, and M. Goodfellow, “Role of subnetworks mediated by TNF α, IL-23/IL-17 and IL-15 in a network involved in the pathogenesis of psoriasis,” Scientific Reports, vol. 11. Springer Nature, 2021. ista: Pandey R, Al-Nuaimi Y, Mishra RK, Spurgeon SK, Goodfellow M. 2021. Role of subnetworks mediated by TNF α, IL-23/IL-17 and IL-15 in a network involved in the pathogenesis of psoriasis. Scientific Reports. 11, 2204. mla: Pandey, Rakesh, et al. “Role of Subnetworks Mediated by TNF α, IL-23/IL-17 and IL-15 in a Network Involved in the Pathogenesis of Psoriasis.” Scientific Reports, vol. 11, 2204, Springer Nature, 2021, doi:10.1038/s41598-020-80507-7. short: R. Pandey, Y. Al-Nuaimi, R.K. Mishra, S.K. Spurgeon, M. Goodfellow, Scientific Reports 11 (2021). date_created: 2021-02-07T23:01:12Z date_published: 2021-01-26T00:00:00Z date_updated: 2022-08-19T07:22:23Z day: '26' ddc: - '570' department: - _id: PeJo doi: 10.1038/s41598-020-80507-7 file: - access_level: open_access checksum: e8a68df48750712671f5c47b0228e531 content_type: application/pdf creator: dernst date_created: 2021-02-09T07:33:23Z date_updated: 2021-02-09T07:33:23Z file_id: '9106' file_name: 2021_ScientificReports_Pandey.pdf file_size: 2885056 relation: main_file success: 1 file_date_updated: 2021-02-09T07:33:23Z has_accepted_license: '1' intvolume: ' 11' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '01' oa: 1 oa_version: Published Version publication: Scientific Reports publication_identifier: eissn: - '20452322' publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Role of subnetworks mediated by TNF α, IL-23/IL-17 and IL-15 in a network involved in the pathogenesis of psoriasis tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2021' ... --- _id: '9329' abstract: - lang: eng text: "Background: To understand information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and their interrelation in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and variable time course of synaptic events.\r\nNew method: We developed a method for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure), which combines concepts of supervised machine learning and optimal Wiener filtering. Experts were asked to manually score short epochs of data. The algorithm was trained to obtain the optimal filter coefficients of a Wiener filter and the optimal detection threshold. Scored and unscored data were then processed with the optimal filter, and events were detected as peaks above threshold.\r\nResults: We challenged MOD with EPSP traces in vivo in mice during spatial navigation and EPSC traces in vitro in slices under conditions of enhanced transmitter release. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve was, on average, 0.894 for in vivo and 0.969 for in vitro data sets, indicating high detection accuracy and efficiency.\r\nComparison with existing methods: When benchmarked using a (1 − AUC)−1 metric, MOD outperformed previous methods (template-fit, deconvolution, and Bayesian methods) by an average factor of 3.13 for in vivo data sets, but showed comparable (template-fit, deconvolution) or higher (Bayesian) computational efficacy.\r\nConclusions: MOD may become an important new tool for large-scale, real-time analysis of synaptic activity." acknowledged_ssus: - _id: SSU acknowledgement: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 692692 to P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung (Z 312-B27, Wittgenstein award to P.J.). We thank Drs. Jozsef Csicsvari, Christoph Lampert, and Federico Stella for critically reading previous manuscript versions. We are also grateful to Drs. Josh Merel and Ben Shababo for their help with applying the Bayesian detection method to our data. We also thank Florian Marr for technical assistance, Eleftheria Kralli-Beller for manuscript editing, and the Scientific Service Units of IST Austria for efficient support. article_number: '109125' article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Xiaomin full_name: Zhang, Xiaomin id: 423EC9C2-F248-11E8-B48F-1D18A9856A87 last_name: Zhang - first_name: Alois full_name: Schlögl, Alois id: 45BF87EE-F248-11E8-B48F-1D18A9856A87 last_name: Schlögl orcid: 0000-0002-5621-8100 - first_name: David H full_name: Vandael, David H id: 3AE48E0A-F248-11E8-B48F-1D18A9856A87 last_name: Vandael orcid: 0000-0001-7577-1676 - first_name: Peter M full_name: Jonas, Peter M id: 353C1B58-F248-11E8-B48F-1D18A9856A87 last_name: Jonas orcid: 0000-0001-5001-4804 citation: ama: 'Zhang X, Schlögl A, Vandael DH, Jonas PM. MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo. Journal of Neuroscience Methods. 2021;357(6). doi:10.1016/j.jneumeth.2021.109125' apa: 'Zhang, X., Schlögl, A., Vandael, D. H., & Jonas, P. M. (2021). MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo. Journal of Neuroscience Methods. Elsevier. https://doi.org/10.1016/j.jneumeth.2021.109125' chicago: 'Zhang, Xiaomin, Alois Schlögl, David H Vandael, and Peter M Jonas. “MOD: A Novel Machine-Learning Optimal-Filtering Method for Accurate and Efficient Detection of Subthreshold Synaptic Events in Vivo.” Journal of Neuroscience Methods. Elsevier, 2021. https://doi.org/10.1016/j.jneumeth.2021.109125.' ieee: 'X. Zhang, A. Schlögl, D. H. Vandael, and P. M. Jonas, “MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo,” Journal of Neuroscience Methods, vol. 357, no. 6. Elsevier, 2021.' ista: 'Zhang X, Schlögl A, Vandael DH, Jonas PM. 2021. MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo. Journal of Neuroscience Methods. 357(6), 109125.' mla: 'Zhang, Xiaomin, et al. “MOD: A Novel Machine-Learning Optimal-Filtering Method for Accurate and Efficient Detection of Subthreshold Synaptic Events in Vivo.” Journal of Neuroscience Methods, vol. 357, no. 6, 109125, Elsevier, 2021, doi:10.1016/j.jneumeth.2021.109125.' short: X. Zhang, A. Schlögl, D.H. Vandael, P.M. Jonas, Journal of Neuroscience Methods 357 (2021). date_created: 2021-04-18T22:01:39Z date_published: 2021-03-09T00:00:00Z date_updated: 2023-08-07T14:36:14Z day: '09' ddc: - '570' department: - _id: PeJo - _id: ScienComp doi: 10.1016/j.jneumeth.2021.109125 ec_funded: 1 external_id: isi: - '000661088500005' file: - access_level: open_access checksum: 2a5800d91b96d08b525e17319dcd5e44 content_type: application/pdf creator: dernst date_created: 2021-04-19T08:30:22Z date_updated: 2021-04-19T08:30:22Z file_id: '9339' file_name: 2021_JourNeuroscienceMeth_Zhang.pdf file_size: 6924738 relation: main_file success: 1 file_date_updated: 2021-04-19T08:30:22Z has_accepted_license: '1' intvolume: ' 357' isi: 1 issue: '6' language: - iso: eng month: '03' oa: 1 oa_version: Published Version project: - _id: 25B7EB9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '692692' name: Biophysics and circuit function of a giant cortical glumatergic synapse - _id: 25C5A090-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00312 name: The Wittgenstein Prize publication: Journal of Neuroscience Methods publication_identifier: eissn: - 1872-678X issn: - 0165-0270 publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: '1' status: public title: 'MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo' tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 357 year: '2021' ...