---
_id: '404'
abstract:
- lang: eng
text: "We construct martingale solutions to stochastic thin-film equations by introducing
a (spatial) semidiscretization and establishing convergence. The discrete scheme
allows for variants of the energy and entropy estimates in the continuous setting
as long as the discrete energy does not exceed certain threshold values depending
on the spatial grid size $h$. Using a stopping time argument to prolongate high-energy
paths constant in time, arbitrary moments of coupled energy/entropy functionals
can be controlled. Having established Hölder regularity of approximate solutions,
the convergence proof is then based on compactness arguments---in particular on
Jakubowski's generalization of Skorokhod's theorem---weak convergence methods,
and recent tools on martingale convergence.\r\n\r\n"
article_processing_charge: No
article_type: original
author:
- first_name: Julian L
full_name: Fischer, Julian L
id: 2C12A0B0-F248-11E8-B48F-1D18A9856A87
last_name: Fischer
orcid: 0000-0002-0479-558X
- first_name: Günther
full_name: Grün, Günther
last_name: Grün
citation:
ama: Fischer JL, Grün G. Existence of positive solutions to stochastic thin-film
equations. SIAM Journal on Mathematical Analysis. 2018;50(1):411-455. doi:10.1137/16M1098796
apa: Fischer, J. L., & Grün, G. (2018). Existence of positive solutions to stochastic
thin-film equations. SIAM Journal on Mathematical Analysis. Society for
Industrial and Applied Mathematics . https://doi.org/10.1137/16M1098796
chicago: Fischer, Julian L, and Günther Grün. “Existence of Positive Solutions to
Stochastic Thin-Film Equations.” SIAM Journal on Mathematical Analysis.
Society for Industrial and Applied Mathematics , 2018. https://doi.org/10.1137/16M1098796.
ieee: J. L. Fischer and G. Grün, “Existence of positive solutions to stochastic
thin-film equations,” SIAM Journal on Mathematical Analysis, vol. 50, no.
1. Society for Industrial and Applied Mathematics , pp. 411–455, 2018.
ista: Fischer JL, Grün G. 2018. Existence of positive solutions to stochastic thin-film
equations. SIAM Journal on Mathematical Analysis. 50(1), 411–455.
mla: Fischer, Julian L., and Günther Grün. “Existence of Positive Solutions to Stochastic
Thin-Film Equations.” SIAM Journal on Mathematical Analysis, vol. 50, no.
1, Society for Industrial and Applied Mathematics , 2018, pp. 411–55, doi:10.1137/16M1098796.
short: J.L. Fischer, G. Grün, SIAM Journal on Mathematical Analysis 50 (2018) 411–455.
date_created: 2018-12-11T11:46:17Z
date_published: 2018-01-30T00:00:00Z
date_updated: 2023-09-11T13:59:22Z
day: '30'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1137/16M1098796
external_id:
isi:
- '000426630900015'
file:
- access_level: open_access
checksum: 89a8eae7c52bb356c04f52b44bff4b5a
content_type: application/pdf
creator: dernst
date_created: 2019-11-07T12:20:25Z
date_updated: 2020-07-14T12:46:22Z
file_id: '6992'
file_name: 2018_SIAM_Fischer.pdf
file_size: 557338
relation: main_file
file_date_updated: 2020-07-14T12:46:22Z
has_accepted_license: '1'
intvolume: ' 50'
isi: 1
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 411 - 455
publication: SIAM Journal on Mathematical Analysis
publication_status: published
publisher: 'Society for Industrial and Applied Mathematics '
publist_id: '7425'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Existence of positive solutions to stochastic thin-film equations
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 50
year: '2018'
...
---
_id: '9813'
abstract:
- lang: eng
text: 'File S1 contains figures that clarify the following features: (i) effect
of population size on the average number/frequency of SI classes, (ii) changes
in the minimal completeness deficit in time for a single class, and (iii) diversification
diagrams for all studied pathways, including the summary figure for k = 8. File
S2 contains the code required for a stochastic simulation of the SLF system with
an example. This file also includes the output in the form of figures and tables.'
article_processing_charge: No
author:
- first_name: Katarína
full_name: Bod'ová, Katarína
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bod'ová
orcid: 0000-0002-7214-0171
- first_name: Tadeas
full_name: Priklopil, Tadeas
id: 3C869AA0-F248-11E8-B48F-1D18A9856A87
last_name: Priklopil
- first_name: David
full_name: Field, David
id: 419049E2-F248-11E8-B48F-1D18A9856A87
last_name: Field
orcid: 0000-0002-4014-8478
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Melinda
full_name: Pickup, Melinda
id: 2C78037E-F248-11E8-B48F-1D18A9856A87
last_name: Pickup
orcid: 0000-0001-6118-0541
citation:
ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material
for Bodova et al., 2018. 2018. doi:10.25386/genetics.6148304.v1
apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018).
Supplemental material for Bodova et al., 2018. Genetics Society of America. https://doi.org/10.25386/genetics.6148304.v1
chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and
Melinda Pickup. “Supplemental Material for Bodova et Al., 2018.” Genetics Society
of America, 2018. https://doi.org/10.25386/genetics.6148304.v1.
ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental
material for Bodova et al., 2018.” Genetics Society of America, 2018.
ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material
for Bodova et al., 2018, Genetics Society of America, 10.25386/genetics.6148304.v1.
mla: Bodova, Katarina, et al. Supplemental Material for Bodova et Al., 2018.
Genetics Society of America, 2018, doi:10.25386/genetics.6148304.v1.
short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018).
date_created: 2021-08-06T13:04:32Z
date_published: 2018-04-30T00:00:00Z
date_updated: 2023-09-11T13:57:42Z
day: '30'
department:
- _id: NiBa
- _id: GaTk
doi: 10.25386/genetics.6148304.v1
main_file_link:
- open_access: '1'
url: https://doi.org/10.25386/genetics.6148304.v1
month: '04'
oa: 1
oa_version: Published Version
publisher: Genetics Society of America
related_material:
record:
- id: '316'
relation: used_in_publication
status: public
status: public
title: Supplemental material for Bodova et al., 2018
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2018'
...
---
_id: '5780'
abstract:
- lang: eng
text: Bioluminescence is found across the entire tree of life, conferring a spectacular
set of visually oriented functions from attracting mates to scaring off predators.
Half a dozen different luciferins, molecules that emit light when enzymatically
oxidized, are known. However, just one biochemical pathway for luciferin biosynthesis
has been described in full, which is found only in bacteria. Here, we report identification
of the fungal luciferase and three other key enzymes that together form the biosynthetic
cycle of the fungal luciferin from caffeic acid, a simple and widespread metabolite.
Introduction of the identified genes into the genome of the yeast Pichia pastoris
along with caffeic acid biosynthesis genes resulted in a strain that is autoluminescent
in standard media. We analyzed evolution of the enzymes of the luciferin biosynthesis
cycle and found that fungal bioluminescence emerged through a series of events
that included two independent gene duplications. The retention of the duplicated
enzymes of the luciferin pathway in nonluminescent fungi shows that the gene duplication
was followed by functional sequence divergence of enzymes of at least one gene
in the biosynthetic pathway and suggests that the evolution of fungal bioluminescence
proceeded through several closely related stepping stone nonluminescent biochemical
reactions with adaptive roles. The availability of a complete eukaryotic luciferin
biosynthesis pathway provides several applications in biomedicine and bioengineering.
article_processing_charge: No
author:
- first_name: Alexey A.
full_name: Kotlobay, Alexey A.
last_name: Kotlobay
- first_name: Karen
full_name: Sarkisyan, Karen
id: 39A7BF80-F248-11E8-B48F-1D18A9856A87
last_name: Sarkisyan
orcid: 0000-0002-5375-6341
- first_name: Yuliana A.
full_name: Mokrushina, Yuliana A.
last_name: Mokrushina
- first_name: Marina
full_name: Marcet-Houben, Marina
last_name: Marcet-Houben
- first_name: Ekaterina O.
full_name: Serebrovskaya, Ekaterina O.
last_name: Serebrovskaya
- first_name: Nadezhda M.
full_name: Markina, Nadezhda M.
last_name: Markina
- first_name: Louisa
full_name: Gonzalez Somermeyer, Louisa
id: 4720D23C-F248-11E8-B48F-1D18A9856A87
last_name: Gonzalez Somermeyer
orcid: 0000-0001-9139-5383
- first_name: Andrey Y.
full_name: Gorokhovatsky, Andrey Y.
last_name: Gorokhovatsky
- first_name: Andrey
full_name: Vvedensky, Andrey
last_name: Vvedensky
- first_name: Konstantin V.
full_name: Purtov, Konstantin V.
last_name: Purtov
- first_name: Valentin N.
full_name: Petushkov, Valentin N.
last_name: Petushkov
- first_name: Natalja S.
full_name: Rodionova, Natalja S.
last_name: Rodionova
- first_name: Tatiana V.
full_name: Chepurnyh, Tatiana V.
last_name: Chepurnyh
- first_name: Liliia
full_name: Fakhranurova, Liliia
last_name: Fakhranurova
- first_name: Elena B.
full_name: Guglya, Elena B.
last_name: Guglya
- first_name: Rustam
full_name: Ziganshin, Rustam
last_name: Ziganshin
- first_name: Aleksandra S.
full_name: Tsarkova, Aleksandra S.
last_name: Tsarkova
- first_name: Zinaida M.
full_name: Kaskova, Zinaida M.
last_name: Kaskova
- first_name: Victoria
full_name: Shender, Victoria
last_name: Shender
- first_name: Maxim
full_name: Abakumov, Maxim
last_name: Abakumov
- first_name: Tatiana O.
full_name: Abakumova, Tatiana O.
last_name: Abakumova
- first_name: Inna S.
full_name: Povolotskaya, Inna S.
last_name: Povolotskaya
- first_name: Fedor M.
full_name: Eroshkin, Fedor M.
last_name: Eroshkin
- first_name: Andrey G.
full_name: Zaraisky, Andrey G.
last_name: Zaraisky
- first_name: Alexander S.
full_name: Mishin, Alexander S.
last_name: Mishin
- first_name: Sergey V.
full_name: Dolgov, Sergey V.
last_name: Dolgov
- first_name: Tatiana Y.
full_name: Mitiouchkina, Tatiana Y.
last_name: Mitiouchkina
- first_name: Eugene P.
full_name: Kopantzev, Eugene P.
last_name: Kopantzev
- first_name: Hans E.
full_name: Waldenmaier, Hans E.
last_name: Waldenmaier
- first_name: Anderson G.
full_name: Oliveira, Anderson G.
last_name: Oliveira
- first_name: Yuichi
full_name: Oba, Yuichi
last_name: Oba
- first_name: Ekaterina
full_name: Barsova, Ekaterina
last_name: Barsova
- first_name: Ekaterina A.
full_name: Bogdanova, Ekaterina A.
last_name: Bogdanova
- first_name: Toni
full_name: Gabaldón, Toni
last_name: Gabaldón
- first_name: Cassius V.
full_name: Stevani, Cassius V.
last_name: Stevani
- first_name: Sergey
full_name: Lukyanov, Sergey
last_name: Lukyanov
- first_name: Ivan V.
full_name: Smirnov, Ivan V.
last_name: Smirnov
- first_name: Josef I.
full_name: Gitelson, Josef I.
last_name: Gitelson
- first_name: Fyodor
full_name: Kondrashov, Fyodor
id: 44FDEF62-F248-11E8-B48F-1D18A9856A87
last_name: Kondrashov
orcid: 0000-0001-8243-4694
- first_name: Ilia V.
full_name: Yampolsky, Ilia V.
last_name: Yampolsky
citation:
ama: Kotlobay AA, Sarkisyan K, Mokrushina YA, et al. Genetically encodable bioluminescent
system from fungi. Proceedings of the National Academy of Sciences of the United
States of America. 2018;115(50):12728-12732. doi:10.1073/pnas.1803615115
apa: Kotlobay, A. A., Sarkisyan, K., Mokrushina, Y. A., Marcet-Houben, M., Serebrovskaya,
E. O., Markina, N. M., … Yampolsky, I. V. (2018). Genetically encodable bioluminescent
system from fungi. Proceedings of the National Academy of Sciences of the United
States of America. National Academy of Sciences. https://doi.org/10.1073/pnas.1803615115
chicago: Kotlobay, Alexey A., Karen Sarkisyan, Yuliana A. Mokrushina, Marina Marcet-Houben,
Ekaterina O. Serebrovskaya, Nadezhda M. Markina, Louisa Gonzalez Somermeyer, et
al. “Genetically Encodable Bioluminescent System from Fungi.” Proceedings of
the National Academy of Sciences of the United States of America. National
Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1803615115.
ieee: A. A. Kotlobay et al., “Genetically encodable bioluminescent system
from fungi,” Proceedings of the National Academy of Sciences of the United
States of America, vol. 115, no. 50. National Academy of Sciences, pp. 12728–12732,
2018.
ista: Kotlobay AA, Sarkisyan K, Mokrushina YA, Marcet-Houben M, Serebrovskaya EO,
Markina NM, Gonzalez Somermeyer L, Gorokhovatsky AY, Vvedensky A, Purtov KV, Petushkov
VN, Rodionova NS, Chepurnyh TV, Fakhranurova L, Guglya EB, Ziganshin R, Tsarkova
AS, Kaskova ZM, Shender V, Abakumov M, Abakumova TO, Povolotskaya IS, Eroshkin
FM, Zaraisky AG, Mishin AS, Dolgov SV, Mitiouchkina TY, Kopantzev EP, Waldenmaier
HE, Oliveira AG, Oba Y, Barsova E, Bogdanova EA, Gabaldón T, Stevani CV, Lukyanov
S, Smirnov IV, Gitelson JI, Kondrashov F, Yampolsky IV. 2018. Genetically encodable
bioluminescent system from fungi. Proceedings of the National Academy of Sciences
of the United States of America. 115(50), 12728–12732.
mla: Kotlobay, Alexey A., et al. “Genetically Encodable Bioluminescent System from
Fungi.” Proceedings of the National Academy of Sciences of the United States
of America, vol. 115, no. 50, National Academy of Sciences, 2018, pp. 12728–32,
doi:10.1073/pnas.1803615115.
short: A.A. Kotlobay, K. Sarkisyan, Y.A. Mokrushina, M. Marcet-Houben, E.O. Serebrovskaya,
N.M. Markina, L. Gonzalez Somermeyer, A.Y. Gorokhovatsky, A. Vvedensky, K.V. Purtov,
V.N. Petushkov, N.S. Rodionova, T.V. Chepurnyh, L. Fakhranurova, E.B. Guglya,
R. Ziganshin, A.S. Tsarkova, Z.M. Kaskova, V. Shender, M. Abakumov, T.O. Abakumova,
I.S. Povolotskaya, F.M. Eroshkin, A.G. Zaraisky, A.S. Mishin, S.V. Dolgov, T.Y.
Mitiouchkina, E.P. Kopantzev, H.E. Waldenmaier, A.G. Oliveira, Y. Oba, E. Barsova,
E.A. Bogdanova, T. Gabaldón, C.V. Stevani, S. Lukyanov, I.V. Smirnov, J.I. Gitelson,
F. Kondrashov, I.V. Yampolsky, Proceedings of the National Academy of Sciences
of the United States of America 115 (2018) 12728–12732.
date_created: 2018-12-23T22:59:18Z
date_published: 2018-12-11T00:00:00Z
date_updated: 2023-09-11T14:04:05Z
day: '11'
ddc:
- '580'
department:
- _id: FyKo
doi: 10.1073/pnas.1803615115
external_id:
isi:
- '000452866000068'
file:
- access_level: open_access
checksum: 46b2c12185eb2ddb598f4c7b4bd267bf
content_type: application/pdf
creator: dernst
date_created: 2019-02-05T15:21:40Z
date_updated: 2020-07-14T12:47:11Z
file_id: '5926'
file_name: 2018_PNAS_Kotlobay.pdf
file_size: 1271988
relation: main_file
file_date_updated: 2020-07-14T12:47:11Z
has_accepted_license: '1'
intvolume: ' 115'
isi: 1
issue: '50'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '12'
oa: 1
oa_version: Published Version
page: 12728-12732
publication: Proceedings of the National Academy of Sciences of the United States
of America
publication_identifier:
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
scopus_import: '1'
status: public
title: Genetically encodable bioluminescent system from fungi
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: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 115
year: '2018'
...
---
_id: '428'
abstract:
- lang: eng
text: The plant hormone gibberellic acid (GA) is a crucial regulator of growth and
development. The main paradigm of GA signaling puts forward transcriptional regulation
via the degradation of DELLA transcriptional repressors. GA has also been shown
to regulate tropic responses by modulation of the plasma membrane incidence of
PIN auxin transporters by an unclear mechanism. Here we uncovered the cellular
and molecular mechanisms by which GA redirects protein trafficking and thus regulates
cell surface functionality. Photoconvertible reporters revealed that GA balances
the protein traffic between the vacuole degradation route and recycling back to
the cell surface. Low GA levels promote vacuolar delivery and degradation of multiple
cargos, including PIN proteins, whereas high GA levels promote their recycling
to the plasma membrane. This GA effect requires components of the retromer complex,
such as Sorting Nexin 1 (SNX1) and its interacting, microtubule (MT)-associated
protein, the Cytoplasmic Linker-Associated Protein (CLASP1). Accordingly, GA regulates
the subcellular distribution of SNX1 and CLASP1, and the intact MT cytoskeleton
is essential for the GA effect on trafficking. This GA cellular action occurs
through DELLA proteins that regulate the MT and retromer presumably via their
interaction partners Prefoldins (PFDs). Our study identified a branching of the
GA signaling pathway at the level of DELLA proteins, which, in parallel to regulating
transcription, also target by a nontranscriptional mechanism the retromer complex
acting at the intersection of the degradation and recycling trafficking routes.
By this mechanism, GA can redirect receptors and transporters to the cell surface,
thus coregulating multiple processes, including PIN-dependent auxin fluxes during
tropic responses.
acknowledgement: "We gratefully acknowledge M. Blázquez (Instituto de Biología Molecular
y Celular de Plantas), M. Fendrych, C. Cuesta Moliner (Institute of Science and
Technology Austria), M. Vanstraelen, M. Nowack (Center for Plant Systems Biology,
Ghent), C. Luschnig (Universitat fur Bodenkultur Wien, Vienna), S. Simon (Central
European Institute of Technology, Brno), C. Sommerville (Carnegie Institution for
Science), and Y. Gu (Penn State University) for making available the materials used
in this study;\r\n...funding from the European Research Council (ERC) under the
European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement
282300.\r\nCC BY NC ND"
article_processing_charge: No
author:
- first_name: Yuliya
full_name: Salanenka, Yuliya
id: 46DAAE7E-F248-11E8-B48F-1D18A9856A87
last_name: Salanenka
- first_name: Inge
full_name: Verstraeten, Inge
id: 362BF7FE-F248-11E8-B48F-1D18A9856A87
last_name: Verstraeten
orcid: 0000-0001-7241-2328
- first_name: Christian
full_name: Löfke, Christian
last_name: Löfke
- first_name: Kaori
full_name: Tabata, Kaori
id: 7DAAEDA4-02D0-11E9-B11A-A5A4D7DFFFD0
last_name: Tabata
- first_name: Satoshi
full_name: Naramoto, Satoshi
last_name: Naramoto
- first_name: Matous
full_name: Glanc, Matous
id: 1AE1EA24-02D0-11E9-9BAA-DAF4881429F2
last_name: Glanc
orcid: 0000-0003-0619-7783
- first_name: Jirí
full_name: Friml, Jirí
id: 4159519E-F248-11E8-B48F-1D18A9856A87
last_name: Friml
orcid: 0000-0002-8302-7596
citation:
ama: Salanenka Y, Verstraeten I, Löfke C, et al. Gibberellin DELLA signaling targets
the retromer complex to redirect protein trafficking to the plasma membrane. PNAS.
2018;115(14):3716-3721. doi:10.1073/pnas.1721760115
apa: Salanenka, Y., Verstraeten, I., Löfke, C., Tabata, K., Naramoto, S., Glanc,
M., & Friml, J. (2018). Gibberellin DELLA signaling targets the retromer complex
to redirect protein trafficking to the plasma membrane. PNAS. National
Academy of Sciences. https://doi.org/10.1073/pnas.1721760115
chicago: Salanenka, Yuliya, Inge Verstraeten, Christian Löfke, Kaori Tabata, Satoshi
Naramoto, Matous Glanc, and Jiří Friml. “Gibberellin DELLA Signaling Targets the
Retromer Complex to Redirect Protein Trafficking to the Plasma Membrane.” PNAS.
National Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1721760115.
ieee: Y. Salanenka et al., “Gibberellin DELLA signaling targets the retromer
complex to redirect protein trafficking to the plasma membrane,” PNAS,
vol. 115, no. 14. National Academy of Sciences, pp. 3716–3721, 2018.
ista: Salanenka Y, Verstraeten I, Löfke C, Tabata K, Naramoto S, Glanc M, Friml
J. 2018. Gibberellin DELLA signaling targets the retromer complex to redirect
protein trafficking to the plasma membrane. PNAS. 115(14), 3716–3721.
mla: Salanenka, Yuliya, et al. “Gibberellin DELLA Signaling Targets the Retromer
Complex to Redirect Protein Trafficking to the Plasma Membrane.” PNAS,
vol. 115, no. 14, National Academy of Sciences, 2018, pp. 3716–21, doi:10.1073/pnas.1721760115.
short: Y. Salanenka, I. Verstraeten, C. Löfke, K. Tabata, S. Naramoto, M. Glanc,
J. Friml, PNAS 115 (2018) 3716–3721.
date_created: 2018-12-11T11:46:25Z
date_published: 2018-04-03T00:00:00Z
date_updated: 2023-09-11T14:06:34Z
day: '03'
ddc:
- '580'
department:
- _id: JiFr
doi: 10.1073/pnas.1721760115
ec_funded: 1
external_id:
isi:
- '000429012500073'
file:
- access_level: open_access
checksum: 1fcf7223fb8f99559cfa80bd6f24ce44
content_type: application/pdf
creator: dernst
date_created: 2018-12-17T12:30:14Z
date_updated: 2020-07-14T12:46:26Z
file_id: '5700'
file_name: 2018_PNAS_Salanenka.pdf
file_size: 1924101
relation: main_file
file_date_updated: 2020-07-14T12:46:26Z
has_accepted_license: '1'
intvolume: ' 115'
isi: 1
issue: '14'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: ' 3716 - 3721'
project:
- _id: 25716A02-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '282300'
name: Polarity and subcellular dynamics in plants
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '7395'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Gibberellin DELLA signaling targets the retromer complex to redirect protein
trafficking to the plasma membrane
tmp:
image: /images/cc_by_nc_nd.png
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short: CC BY-NC-ND (4.0)
type: journal_article
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volume: 115
year: '2018'
...
---
_id: '62'
abstract:
- lang: eng
text: Imaging is a dominant strategy for data collection in neuroscience, yielding
stacks of images that often scale to gigabytes of data for a single experiment.
Machine learning algorithms from computer vision can serve as a pair of virtual
eyes that tirelessly processes these images, automatically detecting and identifying
microstructures. Unlike learning methods, our Flexible Learning-free Reconstruction
of Imaged Neural volumes (FLoRIN) pipeline exploits structure-specific contextual
clues and requires no training. This approach generalizes across different modalities,
including serially-sectioned scanning electron microscopy (sSEM) of genetically
labeled and contrast enhanced processes, spectral confocal reflectance (SCoRe)
microscopy, and high-energy synchrotron X-ray microtomography (μCT) of large tissue
volumes. We deploy the FLoRIN pipeline on newly published and novel mouse datasets,
demonstrating the high biological fidelity of the pipeline’s reconstructions.
FLoRIN reconstructions are of sufficient quality for preliminary biological study,
for example examining the distribution and morphology of cells or extracting single
axons from functional data. Compared to existing supervised learning methods,
FLoRIN is one to two orders of magnitude faster and produces high-quality reconstructions
that are tolerant to noise and artifacts, as is shown qualitatively and quantitatively.
acknowledgement: 'Equipment was generously donated by the NVIDIA Corporation, and
made available by the National Science Foundation (NSF) through grant #CNS-1629914.
This research used resources of the Argonne Leadership Computing Facility, which
is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.'
article_number: '14247'
article_processing_charge: No
article_type: original
author:
- first_name: Ali
full_name: Shabazi, Ali
last_name: Shabazi
- first_name: Jeffery
full_name: Kinnison, Jeffery
last_name: Kinnison
- first_name: Rafael
full_name: Vescovi, Rafael
last_name: Vescovi
- first_name: Ming
full_name: Du, Ming
last_name: Du
- first_name: Robert
full_name: Hill, Robert
last_name: Hill
- first_name: Maximilian A
full_name: Jösch, Maximilian A
id: 2BD278E6-F248-11E8-B48F-1D18A9856A87
last_name: Jösch
orcid: 0000-0002-3937-1330
- first_name: Marc
full_name: Takeno, Marc
last_name: Takeno
- first_name: Hongkui
full_name: Zeng, Hongkui
last_name: Zeng
- first_name: Nuno
full_name: Da Costa, Nuno
last_name: Da Costa
- first_name: Jaime
full_name: Grutzendler, Jaime
last_name: Grutzendler
- first_name: Narayanan
full_name: Kasthuri, Narayanan
last_name: Kasthuri
- first_name: Walter
full_name: Scheirer, Walter
last_name: Scheirer
citation:
ama: Shabazi A, Kinnison J, Vescovi R, et al. Flexible learning-free segmentation
and reconstruction of neural volumes. Scientific Reports. 2018;8(1). doi:10.1038/s41598-018-32628-3
apa: Shabazi, A., Kinnison, J., Vescovi, R., Du, M., Hill, R., Jösch, M. A., … Scheirer,
W. (2018). Flexible learning-free segmentation and reconstruction of neural volumes.
Scientific Reports. Nature Publishing Group. https://doi.org/10.1038/s41598-018-32628-3
chicago: Shabazi, Ali, Jeffery Kinnison, Rafael Vescovi, Ming Du, Robert Hill, Maximilian
A Jösch, Marc Takeno, et al. “Flexible Learning-Free Segmentation and Reconstruction
of Neural Volumes.” Scientific Reports. Nature Publishing Group, 2018.
https://doi.org/10.1038/s41598-018-32628-3.
ieee: A. Shabazi et al., “Flexible learning-free segmentation and reconstruction
of neural volumes,” Scientific Reports, vol. 8, no. 1. Nature Publishing
Group, 2018.
ista: Shabazi A, Kinnison J, Vescovi R, Du M, Hill R, Jösch MA, Takeno M, Zeng H,
Da Costa N, Grutzendler J, Kasthuri N, Scheirer W. 2018. Flexible learning-free
segmentation and reconstruction of neural volumes. Scientific Reports. 8(1), 14247.
mla: Shabazi, Ali, et al. “Flexible Learning-Free Segmentation and Reconstruction
of Neural Volumes.” Scientific Reports, vol. 8, no. 1, 14247, Nature Publishing
Group, 2018, doi:10.1038/s41598-018-32628-3.
short: A. Shabazi, J. Kinnison, R. Vescovi, M. Du, R. Hill, M.A. Jösch, M. Takeno,
H. Zeng, N. Da Costa, J. Grutzendler, N. Kasthuri, W. Scheirer, Scientific Reports
8 (2018).
date_created: 2018-12-11T11:44:25Z
date_published: 2018-09-24T00:00:00Z
date_updated: 2023-09-11T14:02:55Z
day: '24'
ddc:
- '570'
department:
- _id: MaJö
doi: 10.1038/s41598-018-32628-3
external_id:
isi:
- '000445336600015'
file:
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checksum: 1a14ae0666b82fbaa04bef110e3f6bf2
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creator: dernst
date_created: 2018-12-17T12:22:24Z
date_updated: 2020-07-14T12:47:24Z
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file_name: 2018_ScientificReports_Shahbazi.pdf
file_size: 4141645
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file_date_updated: 2020-07-14T12:47:24Z
has_accepted_license: '1'
intvolume: ' 8'
isi: 1
issue: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '09'
oa: 1
oa_version: Published Version
publication: Scientific Reports
publication_status: published
publisher: Nature Publishing Group
publist_id: '7992'
quality_controlled: '1'
related_material:
link:
- relation: erratum
url: http://doi.org/10.1038/s41598-018-36220-7
scopus_import: '1'
status: public
title: Flexible learning-free segmentation and reconstruction of neural volumes
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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: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 8
year: '2018'
...