---
_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
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ddc:
- '570'
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- _id: PeJo
doi: 10.1038/s41598-020-80507-7
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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'
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creator: dernst
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date_updated: 2021-04-19T08:30:22Z
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file_name: 2021_JourNeuroscienceMeth_Zhang.pdf
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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'
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legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
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short: CC BY-NC-ND (4.0)
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...