---
OA_place: repository
OA_type: green
_id: '17868'
abstract:
- lang: eng
text: Reversed conductance decay describes increasing conductance of a molecular
chain series with increasing chain length. Realizing reversed conductance decay
is an important step toward making long and highly conducting molecular wires.
Recent work has shown that one-dimensional topological insulators (1D TIs) can
exhibit reversed conductance decay due to their nontrivial edge states. The Su–Schrieffer–Heeger
(SSH) model for 1D TIs relates to the electronic structure of these isolated molecules
but not their electron transport properties as single-molecule junctions. Herein,
we use a tight-binding approach to demonstrate that polyacetylene and other diradicaloid
1D TIs show a reversed conductance decay at the short chain limit. We explain
these conductance trends by analyzing the impact of the edge states in these 1D
systems on the single-molecule junction transmission. Additionally, we discuss
how the self-energy from the electrode-molecule coupling and the on-site energy
of the edge sites can be tuned to create longer wires with reversed conductance
decays.
article_processing_charge: No
article_type: original
author:
- first_name: Liang
full_name: Li, Liang
last_name: Li
- first_name: Suman
full_name: Gunasekaran, Suman
last_name: Gunasekaran
- first_name: Yujing
full_name: Wei, Yujing
last_name: Wei
- first_name: Colin
full_name: Nuckolls, Colin
last_name: Nuckolls
- first_name: Latha
full_name: Venkataraman, Latha
id: 9ebb78a5-cc0d-11ee-8322-fae086a32caf
last_name: Venkataraman
orcid: 0000-0002-6957-6089
citation:
ama: Li L, Gunasekaran S, Wei Y, Nuckolls C, Venkataraman L. Reversed conductance
decay of 1D topological insulators by tight-binding analysis. The Journal of
Physical Chemistry Letters. 2022;13(41):9703-9710. doi:10.1021/acs.jpclett.2c02812
apa: Li, L., Gunasekaran, S., Wei, Y., Nuckolls, C., & Venkataraman, L. (2022).
Reversed conductance decay of 1D topological insulators by tight-binding analysis.
The Journal of Physical Chemistry Letters. American Chemical Society. https://doi.org/10.1021/acs.jpclett.2c02812
chicago: Li, Liang, Suman Gunasekaran, Yujing Wei, Colin Nuckolls, and Latha Venkataraman.
“Reversed Conductance Decay of 1D Topological Insulators by Tight-Binding Analysis.”
The Journal of Physical Chemistry Letters. American Chemical Society, 2022.
https://doi.org/10.1021/acs.jpclett.2c02812.
ieee: L. Li, S. Gunasekaran, Y. Wei, C. Nuckolls, and L. Venkataraman, “Reversed
conductance decay of 1D topological insulators by tight-binding analysis,” The
Journal of Physical Chemistry Letters, vol. 13, no. 41. American Chemical
Society, pp. 9703–9710, 2022.
ista: Li L, Gunasekaran S, Wei Y, Nuckolls C, Venkataraman L. 2022. Reversed conductance
decay of 1D topological insulators by tight-binding analysis. The Journal of Physical
Chemistry Letters. 13(41), 9703–9710.
mla: Li, Liang, et al. “Reversed Conductance Decay of 1D Topological Insulators
by Tight-Binding Analysis.” The Journal of Physical Chemistry Letters,
vol. 13, no. 41, American Chemical Society, 2022, pp. 9703–10, doi:10.1021/acs.jpclett.2c02812.
short: L. Li, S. Gunasekaran, Y. Wei, C. Nuckolls, L. Venkataraman, The Journal
of Physical Chemistry Letters 13 (2022) 9703–9710.
date_created: 2024-09-06T13:02:46Z
date_published: 2022-10-11T00:00:00Z
date_updated: 2024-12-10T09:21:49Z
day: '11'
doi: 10.1021/acs.jpclett.2c02812
extern: '1'
external_id:
pmid:
- '36219846'
intvolume: ' 13'
issue: '41'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.26434/chemrxiv-2022-b1fh9-v3
month: '10'
oa: 1
oa_version: Preprint
page: 9703-9710
pmid: 1
publication: The Journal of Physical Chemistry Letters
publication_identifier:
issn:
- 1948-7185
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Reversed conductance decay of 1D topological insulators by tight-binding analysis
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2022'
...
---
OA_place: repository
OA_type: green
_id: '17869'
abstract:
- lang: eng
text: The formation of carbon–carbon bonds with transition metal reagents serves
as a cornerstone of organic synthesis. Here, we show that the reactivity of an
otherwise kinetically inert transition metal complex can be induced by an external
electric field to affect a coupling reaction. These results highlight the importance
of electric field effects in reaction chemistry and offers a new strategy to modulate
organometallic reactivity.
article_processing_charge: No
article_type: letter_note
author:
- first_name: Nicholas M.
full_name: Orchanian, Nicholas M.
last_name: Orchanian
- first_name: Sophia
full_name: Guizzo, Sophia
last_name: Guizzo
- first_name: Michael L.
full_name: Steigerwald, Michael L.
last_name: Steigerwald
- first_name: Colin
full_name: Nuckolls, Colin
last_name: Nuckolls
- first_name: Latha
full_name: Venkataraman, Latha
id: 9ebb78a5-cc0d-11ee-8322-fae086a32caf
last_name: Venkataraman
orcid: 0000-0002-6957-6089
citation:
ama: Orchanian NM, Guizzo S, Steigerwald ML, Nuckolls C, Venkataraman L. Electric-field-induced
coupling of aryl iodides with a nickel(0) complex. Chemical Communications.
2022;58(90):12556-12559. doi:10.1039/d2cc03671a
apa: Orchanian, N. M., Guizzo, S., Steigerwald, M. L., Nuckolls, C., & Venkataraman,
L. (2022). Electric-field-induced coupling of aryl iodides with a nickel(0) complex.
Chemical Communications. Royal Society of Chemistry. https://doi.org/10.1039/d2cc03671a
chicago: Orchanian, Nicholas M., Sophia Guizzo, Michael L. Steigerwald, Colin Nuckolls,
and Latha Venkataraman. “Electric-Field-Induced Coupling of Aryl Iodides with
a Nickel(0) Complex.” Chemical Communications. Royal Society of Chemistry,
2022. https://doi.org/10.1039/d2cc03671a.
ieee: N. M. Orchanian, S. Guizzo, M. L. Steigerwald, C. Nuckolls, and L. Venkataraman,
“Electric-field-induced coupling of aryl iodides with a nickel(0) complex,” Chemical
Communications, vol. 58, no. 90. Royal Society of Chemistry, pp. 12556–12559,
2022.
ista: Orchanian NM, Guizzo S, Steigerwald ML, Nuckolls C, Venkataraman L. 2022.
Electric-field-induced coupling of aryl iodides with a nickel(0) complex. Chemical
Communications. 58(90), 12556–12559.
mla: Orchanian, Nicholas M., et al. “Electric-Field-Induced Coupling of Aryl Iodides
with a Nickel(0) Complex.” Chemical Communications, vol. 58, no. 90, Royal
Society of Chemistry, 2022, pp. 12556–59, doi:10.1039/d2cc03671a.
short: N.M. Orchanian, S. Guizzo, M.L. Steigerwald, C. Nuckolls, L. Venkataraman,
Chemical Communications 58 (2022) 12556–12559.
date_created: 2024-09-06T13:03:38Z
date_published: 2022-10-10T00:00:00Z
date_updated: 2024-12-10T09:27:04Z
day: '10'
doi: 10.1039/d2cc03671a
extern: '1'
external_id:
pmid:
- '36245392'
intvolume: ' 58'
issue: '90'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.26434/chemrxiv-2022-lfnw1
month: '10'
oa: 1
oa_version: Preprint
page: 12556-12559
pmid: 1
publication: Chemical Communications
publication_identifier:
eissn:
- 1364-548X
issn:
- 1359-7345
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
related_material:
link:
- relation: erratum
url: https://doi.org/10.1039/d2cc03671a
scopus_import: '1'
status: public
title: Electric-field-induced coupling of aryl iodides with a nickel(0) complex
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 58
year: '2022'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '17870'
abstract:
- lang: eng
text: The electric fields created at solid–liquid interfaces are important in heterogeneous
catalysis. Here we describe the Ullmann coupling of aryl iodides on rough gold
surfaces, which we monitor in situ using the scanning tunneling microscope-based
break junction (STM-BJ) and ex situ using mass spectrometry and fluorescence spectroscopy.
We find that this Ullmann coupling reaction occurs only on rough gold surfaces
in polar solvents, the latter of which implicates interfacial electric fields.
These experimental observations are supported by density functional theory calculations
that elucidate the roles of surface roughness and local electric fields on the
reaction. More broadly, this touchstone study offers a facile method to access
and probe in real time an increasingly prominent yet incompletely understood mode
of catalysis.
article_processing_charge: Yes
article_type: original
author:
- first_name: Ilana B.
full_name: Stone, Ilana B.
last_name: Stone
- first_name: Rachel L.
full_name: Starr, Rachel L.
last_name: Starr
- first_name: Norah
full_name: Hoffmann, Norah
last_name: Hoffmann
- first_name: Xiao
full_name: Wang, Xiao
last_name: Wang
- first_name: Austin M.
full_name: Evans, Austin M.
last_name: Evans
- first_name: Colin
full_name: Nuckolls, Colin
last_name: Nuckolls
- first_name: Tristan H.
full_name: Lambert, Tristan H.
last_name: Lambert
- first_name: Michael L.
full_name: Steigerwald, Michael L.
last_name: Steigerwald
- first_name: Timothy C.
full_name: Berkelbach, Timothy C.
last_name: Berkelbach
- first_name: Xavier
full_name: Roy, Xavier
last_name: Roy
- first_name: Latha
full_name: Venkataraman, Latha
id: 9ebb78a5-cc0d-11ee-8322-fae086a32caf
last_name: Venkataraman
orcid: 0000-0002-6957-6089
citation:
ama: Stone IB, Starr RL, Hoffmann N, et al. Interfacial electric fields catalyze
Ullmann coupling reactions on gold surfaces. Chemical Science. 2022;13(36):10798-10805.
doi:10.1039/d2sc03780g
apa: Stone, I. B., Starr, R. L., Hoffmann, N., Wang, X., Evans, A. M., Nuckolls,
C., … Venkataraman, L. (2022). Interfacial electric fields catalyze Ullmann coupling
reactions on gold surfaces. Chemical Science. Royal Society of Chemistry.
https://doi.org/10.1039/d2sc03780g
chicago: Stone, Ilana B., Rachel L. Starr, Norah Hoffmann, Xiao Wang, Austin M.
Evans, Colin Nuckolls, Tristan H. Lambert, et al. “Interfacial Electric Fields
Catalyze Ullmann Coupling Reactions on Gold Surfaces.” Chemical Science.
Royal Society of Chemistry, 2022. https://doi.org/10.1039/d2sc03780g.
ieee: I. B. Stone et al., “Interfacial electric fields catalyze Ullmann coupling
reactions on gold surfaces,” Chemical Science, vol. 13, no. 36. Royal Society
of Chemistry, pp. 10798–10805, 2022.
ista: Stone IB, Starr RL, Hoffmann N, Wang X, Evans AM, Nuckolls C, Lambert TH,
Steigerwald ML, Berkelbach TC, Roy X, Venkataraman L. 2022. Interfacial electric
fields catalyze Ullmann coupling reactions on gold surfaces. Chemical Science.
13(36), 10798–10805.
mla: Stone, Ilana B., et al. “Interfacial Electric Fields Catalyze Ullmann Coupling
Reactions on Gold Surfaces.” Chemical Science, vol. 13, no. 36, Royal Society
of Chemistry, 2022, pp. 10798–805, doi:10.1039/d2sc03780g.
short: I.B. Stone, R.L. Starr, N. Hoffmann, X. Wang, A.M. Evans, C. Nuckolls, T.H.
Lambert, M.L. Steigerwald, T.C. Berkelbach, X. Roy, L. Venkataraman, Chemical
Science 13 (2022) 10798–10805.
date_created: 2024-09-06T13:04:27Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2024-12-10T09:29:53Z
day: '01'
doi: 10.1039/d2sc03780g
extern: '1'
intvolume: ' 13'
issue: '36'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/3.0/
main_file_link:
- open_access: '1'
url: https://doi.org/10.1039/D2SC03780G
month: '09'
oa: 1
oa_version: Published Version
page: 10798-10805
publication: Chemical Science
publication_identifier:
eissn:
- 2041-6539
issn:
- 2041-6520
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
scopus_import: '1'
status: public
title: Interfacial electric fields catalyze Ullmann coupling reactions on gold surfaces
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/3.0/legalcode
name: Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
short: CC BY-NC (3.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2022'
...
---
OA_place: repository
OA_type: green
_id: '17873'
abstract:
- lang: eng
text: AbstractA critical overview of the theory
of the chirality‐induced spin selectivity (CISS) effect, that is, phenomena in
which the chirality of molecular species imparts significant spin selectivity
to various electron processes, is provided. Based on discussions in a recently
held workshop, and further work published since, the status of CISS effects—in
electron transmission, electron transport, and chemical reactions—is reviewed.
For each, a detailed discussion of the state‐of‐the‐art in theoretical understanding
is provided and remaining challenges and research opportunities are identified.
article_number: '2106629'
article_processing_charge: No
article_type: review
arxiv: 1
author:
- first_name: Ferdinand
full_name: Evers, Ferdinand
last_name: Evers
- first_name: Amnon
full_name: Aharony, Amnon
last_name: Aharony
- first_name: Nir
full_name: Bar‐Gill, Nir
last_name: Bar‐Gill
- first_name: Ora
full_name: Entin‐Wohlman, Ora
last_name: Entin‐Wohlman
- first_name: Per
full_name: Hedegård, Per
last_name: Hedegård
- first_name: Oded
full_name: Hod, Oded
last_name: Hod
- first_name: Pavel
full_name: Jelinek, Pavel
last_name: Jelinek
- first_name: Grzegorz
full_name: Kamieniarz, Grzegorz
last_name: Kamieniarz
- first_name: Mikhail
full_name: Lemeshko, Mikhail
last_name: Lemeshko
- first_name: Karen
full_name: Michaeli, Karen
last_name: Michaeli
- first_name: Vladimiro
full_name: Mujica, Vladimiro
last_name: Mujica
- first_name: Ron
full_name: Naaman, Ron
last_name: Naaman
- first_name: Yossi
full_name: Paltiel, Yossi
last_name: Paltiel
- first_name: Sivan
full_name: Refaely‐Abramson, Sivan
last_name: Refaely‐Abramson
- first_name: Oren
full_name: Tal, Oren
last_name: Tal
- first_name: Jos
full_name: Thijssen, Jos
last_name: Thijssen
- first_name: Michael
full_name: Thoss, Michael
last_name: Thoss
- first_name: Jan M.
full_name: van Ruitenbeek, Jan M.
last_name: van Ruitenbeek
- first_name: Latha
full_name: Venkataraman, Latha
id: 9ebb78a5-cc0d-11ee-8322-fae086a32caf
last_name: Venkataraman
orcid: 0000-0002-6957-6089
- first_name: David H.
full_name: Waldeck, David H.
last_name: Waldeck
- first_name: Binghai
full_name: Yan, Binghai
last_name: Yan
- first_name: Leeor
full_name: Kronik, Leeor
last_name: Kronik
citation:
ama: 'Evers F, Aharony A, Bar‐Gill N, et al. Theory of chirality induced spin selectivity:
Progress and challenges. Advanced Materials. 2022;34(13). doi:10.1002/adma.202106629'
apa: 'Evers, F., Aharony, A., Bar‐Gill, N., Entin‐Wohlman, O., Hedegård, P., Hod,
O., … Kronik, L. (2022). Theory of chirality induced spin selectivity: Progress
and challenges. Advanced Materials. Wiley. https://doi.org/10.1002/adma.202106629'
chicago: 'Evers, Ferdinand, Amnon Aharony, Nir Bar‐Gill, Ora Entin‐Wohlman, Per
Hedegård, Oded Hod, Pavel Jelinek, et al. “Theory of Chirality Induced Spin Selectivity:
Progress and Challenges.” Advanced Materials. Wiley, 2022. https://doi.org/10.1002/adma.202106629.'
ieee: 'F. Evers et al., “Theory of chirality induced spin selectivity: Progress
and challenges,” Advanced Materials, vol. 34, no. 13. Wiley, 2022.'
ista: 'Evers F, Aharony A, Bar‐Gill N, Entin‐Wohlman O, Hedegård P, Hod O, Jelinek
P, Kamieniarz G, Lemeshko M, Michaeli K, Mujica V, Naaman R, Paltiel Y, Refaely‐Abramson
S, Tal O, Thijssen J, Thoss M, van Ruitenbeek JM, Venkataraman L, Waldeck DH,
Yan B, Kronik L. 2022. Theory of chirality induced spin selectivity: Progress
and challenges. Advanced Materials. 34(13), 2106629.'
mla: 'Evers, Ferdinand, et al. “Theory of Chirality Induced Spin Selectivity: Progress
and Challenges.” Advanced Materials, vol. 34, no. 13, 2106629, Wiley, 2022,
doi:10.1002/adma.202106629.'
short: F. Evers, A. Aharony, N. Bar‐Gill, O. Entin‐Wohlman, P. Hedegård, O. Hod,
P. Jelinek, G. Kamieniarz, M. Lemeshko, K. Michaeli, V. Mujica, R. Naaman, Y.
Paltiel, S. Refaely‐Abramson, O. Tal, J. Thijssen, M. Thoss, J.M. van Ruitenbeek,
L. Venkataraman, D.H. Waldeck, B. Yan, L. Kronik, Advanced Materials 34 (2022).
date_created: 2024-09-06T13:07:43Z
date_published: 2022-04-01T00:00:00Z
date_updated: 2024-12-10T09:43:10Z
day: '01'
doi: 10.1002/adma.202106629
extern: '1'
external_id:
arxiv:
- '2108.09998'
pmid:
- '35064943'
intvolume: ' 34'
issue: '13'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2108.09998
month: '04'
oa: 1
oa_version: Preprint
pmid: 1
publication: Advanced Materials
publication_identifier:
issn:
- 0935-9648
- 1521-4095
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Theory of chirality induced spin selectivity: Progress and challenges'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2022'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '17874'
abstract:
- lang: eng
text: Redox-active two-dimensional polymers (RA-2DPs) are promising lithium battery
organic cathode materials due to their regular porosities and high chemical stabilities.
However, weak electrical conductivities inherent to the non-conjugated molecular
motifs used thus far limit device performance and the practical relevance of these
materials. We herein address this problem by developing a modular approach to
construct π-conjugated RA-2DPs with a new polycyclic aromatic redox-active building
block PDI-DA. Efficient imine-condensation between PDI-DA and two polyfunctional
amine nodes followed by quantitative alkyl chain removal produced RA-2DPs TAPPy-PDI
and TAPB-PDI as conjugated, porous, polycrystalline networks. In-plane conjugation
and permanent porosity endow these materials with high electrical conductivity
and high ion diffusion rates. As such, both RA-2DPs function as organic cathode
materials with good rate performance and excellent cycling stability. Importantly,
the improved design enables higher areal mass-loadings than were previously available,
which drives a practical demonstration of TAPPy-PDI as the power source for a
series of LED lights. Collectively, this investigation discloses viable synthetic
methodologies and design principles for the realization of high-performance organic
cathode materials.
article_processing_charge: Yes
article_type: original
author:
- first_name: Zexin
full_name: Jin, Zexin
last_name: Jin
- first_name: Qian
full_name: Cheng, Qian
last_name: Cheng
- first_name: Austin M.
full_name: Evans, Austin M.
last_name: Evans
- first_name: Jesse
full_name: Gray, Jesse
last_name: Gray
- first_name: Ruiwen
full_name: Zhang, Ruiwen
last_name: Zhang
- first_name: Si Tong
full_name: Bao, Si Tong
last_name: Bao
- first_name: Fengkai
full_name: Wei, Fengkai
last_name: Wei
- first_name: Latha
full_name: Venkataraman, Latha
id: 9ebb78a5-cc0d-11ee-8322-fae086a32caf
last_name: Venkataraman
orcid: 0000-0002-6957-6089
- first_name: Yuan
full_name: Yang, Yuan
last_name: Yang
- first_name: Colin
full_name: Nuckolls, Colin
last_name: Nuckolls
citation:
ama: Jin Z, Cheng Q, Evans AM, et al. π-Conjugated redox-active two-dimensional
polymers as organic cathode materials. Chemical Science. 2022;13(12):3533-3538.
doi:10.1039/d1sc07157b
apa: Jin, Z., Cheng, Q., Evans, A. M., Gray, J., Zhang, R., Bao, S. T., … Nuckolls,
C. (2022). π-Conjugated redox-active two-dimensional polymers as organic cathode
materials. Chemical Science. Royal Society of Chemistry. https://doi.org/10.1039/d1sc07157b
chicago: Jin, Zexin, Qian Cheng, Austin M. Evans, Jesse Gray, Ruiwen Zhang, Si Tong
Bao, Fengkai Wei, Latha Venkataraman, Yuan Yang, and Colin Nuckolls. “π-Conjugated
Redox-Active Two-Dimensional Polymers as Organic Cathode Materials.” Chemical
Science. Royal Society of Chemistry, 2022. https://doi.org/10.1039/d1sc07157b.
ieee: Z. Jin et al., “π-Conjugated redox-active two-dimensional polymers
as organic cathode materials,” Chemical Science, vol. 13, no. 12. Royal
Society of Chemistry, pp. 3533–3538, 2022.
ista: Jin Z, Cheng Q, Evans AM, Gray J, Zhang R, Bao ST, Wei F, Venkataraman L,
Yang Y, Nuckolls C. 2022. π-Conjugated redox-active two-dimensional polymers as
organic cathode materials. Chemical Science. 13(12), 3533–3538.
mla: Jin, Zexin, et al. “π-Conjugated Redox-Active Two-Dimensional Polymers as Organic
Cathode Materials.” Chemical Science, vol. 13, no. 12, Royal Society of
Chemistry, 2022, pp. 3533–38, doi:10.1039/d1sc07157b.
short: Z. Jin, Q. Cheng, A.M. Evans, J. Gray, R. Zhang, S.T. Bao, F. Wei, L. Venkataraman,
Y. Yang, C. Nuckolls, Chemical Science 13 (2022) 3533–3538.
date_created: 2024-09-06T13:08:38Z
date_published: 2022-03-08T00:00:00Z
date_updated: 2024-12-10T09:54:17Z
day: '08'
doi: 10.1039/d1sc07157b
extern: '1'
intvolume: ' 13'
issue: '12'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1039/D1SC07157B
month: '03'
oa: 1
oa_version: Published Version
page: 3533-3538
publication: Chemical Science
publication_identifier:
eissn:
- 2041-6539
issn:
- 2041-6520
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
scopus_import: '1'
status: public
title: π-Conjugated redox-active two-dimensional polymers as organic cathode materials
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/3.0/legalcode
name: Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
short: CC BY-NC (3.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2022'
...
---
_id: '18191'
abstract:
- lang: eng
text: 'Large-scale quantum devices provide insights beyond the reach of classical
simulations. However, for a reliable and verifiable quantum simulation, the building
blocks of the quantum device require exquisite benchmarking. This benchmarking
of large-scale dynamical quantum systems represents a major challenge due to lack
of efficient tools for their simulation. Here, we present a scalable algorithm
based on neural networks for Hamiltonian tomography in out-of-equilibrium quantum
systems. We illustrate our approach using a model for a forefront quantum simulation
platform: ultracold atoms in optical lattices. Specifically, we show that our
algorithm is able to reconstruct the Hamiltonian of an arbitrary sized bosonic
ladder system using an accessible amount of experimental measurements. We are
able to significantly increase the previously known parameter precision.'
article_number: '023302'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Agnes
full_name: Valenti, Agnes
last_name: Valenti
- first_name: Guliuxin
full_name: Jin, Guliuxin
last_name: Jin
- first_name: Julian
full_name: Leonard, Julian
id: b75b3f45-7995-11ef-9bfd-9a9cd02c3577
last_name: Leonard
- first_name: Sebastian D.
full_name: Huber, Sebastian D.
last_name: Huber
- first_name: Eliska
full_name: Greplova, Eliska
last_name: Greplova
citation:
ama: Valenti A, Jin G, Leonard J, Huber SD, Greplova E. Scalable Hamiltonian learning
for large-scale out-of-equilibrium quantum dynamics. Physical Review A.
2022;105(2). doi:10.1103/physreva.105.023302
apa: Valenti, A., Jin, G., Leonard, J., Huber, S. D., & Greplova, E. (2022).
Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics.
Physical Review A. American Physical Society. https://doi.org/10.1103/physreva.105.023302
chicago: Valenti, Agnes, Guliuxin Jin, Julian Leonard, Sebastian D. Huber, and Eliska
Greplova. “Scalable Hamiltonian Learning for Large-Scale out-of-Equilibrium Quantum
Dynamics.” Physical Review A. American Physical Society, 2022. https://doi.org/10.1103/physreva.105.023302.
ieee: A. Valenti, G. Jin, J. Leonard, S. D. Huber, and E. Greplova, “Scalable Hamiltonian
learning for large-scale out-of-equilibrium quantum dynamics,” Physical Review
A, vol. 105, no. 2. American Physical Society, 2022.
ista: Valenti A, Jin G, Leonard J, Huber SD, Greplova E. 2022. Scalable Hamiltonian
learning for large-scale out-of-equilibrium quantum dynamics. Physical Review
A. 105(2), 023302.
mla: Valenti, Agnes, et al. “Scalable Hamiltonian Learning for Large-Scale out-of-Equilibrium
Quantum Dynamics.” Physical Review A, vol. 105, no. 2, 023302, American
Physical Society, 2022, doi:10.1103/physreva.105.023302.
short: A. Valenti, G. Jin, J. Leonard, S.D. Huber, E. Greplova, Physical Review
A 105 (2022).
date_created: 2024-10-07T11:46:53Z
date_published: 2022-02-01T00:00:00Z
date_updated: 2024-10-08T10:00:23Z
day: '01'
doi: 10.1103/physreva.105.023302
extern: '1'
external_id:
arxiv:
- '2103.01240'
intvolume: ' 105'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2103.01240
month: '02'
oa: 1
oa_version: Preprint
publication: Physical Review A
publication_identifier:
eissn:
- 2469-9934
issn:
- 2469-9926
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 105
year: '2022'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18220'
abstract:
- lang: eng
text: Synonymous codons translate into the same amino acid. Although the identity
of synonymous codons is often considered inconsequential to the final protein
structure, there is mounting evidence for an association between the two. Our
study examined this association using regression and classification models, finding
that codon sequences predict protein backbone dihedral angles with a lower error
than amino acid sequences, and that models trained with true dihedral angles have
better classification of synonymous codons given structural information than models
trained with random dihedral angles. Using this classification approach, we investigated
local codon–codon dependencies and tested whether synonymous codon identity can
be predicted more accurately from codon context than amino acid context alone,
and most specifically which codon context position carries the most predictive
power.
article_number: '21968'
article_processing_charge: Yes
article_type: original
author:
- first_name: Linor
full_name: Ackerman-Schraier, Linor
last_name: Ackerman-Schraier
- first_name: Aviv A.
full_name: Rosenberg, Aviv A.
last_name: Rosenberg
- first_name: Ailie
full_name: Marx, Ailie
last_name: Marx
- first_name: Alexander
full_name: Bronstein, Alexander
id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
last_name: Bronstein
orcid: 0000-0001-9699-8730
citation:
ama: Ackerman-Schraier L, Rosenberg AA, Marx A, Bronstein AM. Machine learning approaches
demonstrate that protein structures carry information about their genetic coding.
Scientific Reports. 2022;12. doi:10.1038/s41598-022-25874-z
apa: Ackerman-Schraier, L., Rosenberg, A. A., Marx, A., & Bronstein, A. M. (2022).
Machine learning approaches demonstrate that protein structures carry information
about their genetic coding. Scientific Reports. Springer Nature. https://doi.org/10.1038/s41598-022-25874-z
chicago: Ackerman-Schraier, Linor, Aviv A. Rosenberg, Ailie Marx, and Alex M. Bronstein.
“Machine Learning Approaches Demonstrate That Protein Structures Carry Information
about Their Genetic Coding.” Scientific Reports. Springer Nature, 2022.
https://doi.org/10.1038/s41598-022-25874-z.
ieee: L. Ackerman-Schraier, A. A. Rosenberg, A. Marx, and A. M. Bronstein, “Machine
learning approaches demonstrate that protein structures carry information about
their genetic coding,” Scientific Reports, vol. 12. Springer Nature, 2022.
ista: Ackerman-Schraier L, Rosenberg AA, Marx A, Bronstein AM. 2022. Machine learning
approaches demonstrate that protein structures carry information about their genetic
coding. Scientific Reports. 12, 21968.
mla: Ackerman-Schraier, Linor, et al. “Machine Learning Approaches Demonstrate That
Protein Structures Carry Information about Their Genetic Coding.” Scientific
Reports, vol. 12, 21968, Springer Nature, 2022, doi:10.1038/s41598-022-25874-z.
short: L. Ackerman-Schraier, A.A. Rosenberg, A. Marx, A.M. Bronstein, Scientific
Reports 12 (2022).
date_created: 2024-10-08T12:52:29Z
date_published: 2022-12-20T00:00:00Z
date_updated: 2024-10-14T09:46:06Z
day: '20'
doi: 10.1038/s41598-022-25874-z
extern: '1'
external_id:
pmid:
- '36539476'
intvolume: ' 12'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1038/s41598-022-25874-z
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
publication: Scientific Reports
publication_identifier:
issn:
- 2045-2322
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Machine learning approaches demonstrate that protein structures carry information
about their genetic coding
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 12
year: '2022'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18221'
abstract:
- lang: eng
text: Synonymous codons translate into chemically identical amino acids. Once considered
inconsequential to the formation of the protein product, there is evidence to
suggest that codon usage affects co-translational protein folding and the final
structure of the expressed protein. Here we develop a method for computing and
comparing codon-specific Ramachandran plots and demonstrate that the backbone
dihedral angle distributions of some synonymous codons are distinguishable with
statistical significance for some secondary structures. This shows that there
exists a dependence between codon identity and backbone torsion of the translated
amino acid. Although these findings cannot pinpoint the causal direction of this
dependence, we discuss the vast biological implications should coding be shown
to directly shape protein conformation and demonstrate the usefulness of this
method as a tool for probing associations between codon usage and protein structure.
Finally, we urge for the inclusion of exact genetic information into structural
databases.
article_number: '2815'
article_processing_charge: Yes
article_type: original
author:
- first_name: Aviv A.
full_name: Rosenberg, Aviv A.
last_name: Rosenberg
- first_name: Ailie
full_name: Marx, Ailie
last_name: Marx
- first_name: Alexander
full_name: Bronstein, Alexander
id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
last_name: Bronstein
orcid: 0000-0001-9699-8730
citation:
ama: Rosenberg AA, Marx A, Bronstein AM. Codon-specific Ramachandran plots show
amino acid backbone conformation depends on identity of the translated codon.
Nature Communications. 2022;13. doi:10.1038/s41467-022-30390-9
apa: Rosenberg, A. A., Marx, A., & Bronstein, A. M. (2022). Codon-specific Ramachandran
plots show amino acid backbone conformation depends on identity of the translated
codon. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-022-30390-9
chicago: Rosenberg, Aviv A., Ailie Marx, and Alex M. Bronstein. “Codon-Specific
Ramachandran Plots Show Amino Acid Backbone Conformation Depends on Identity of
the Translated Codon.” Nature Communications. Springer Nature, 2022. https://doi.org/10.1038/s41467-022-30390-9.
ieee: A. A. Rosenberg, A. Marx, and A. M. Bronstein, “Codon-specific Ramachandran
plots show amino acid backbone conformation depends on identity of the translated
codon,” Nature Communications, vol. 13. Springer Nature, 2022.
ista: Rosenberg AA, Marx A, Bronstein AM. 2022. Codon-specific Ramachandran plots
show amino acid backbone conformation depends on identity of the translated codon.
Nature Communications. 13, 2815.
mla: Rosenberg, Aviv A., et al. “Codon-Specific Ramachandran Plots Show Amino Acid
Backbone Conformation Depends on Identity of the Translated Codon.” Nature
Communications, vol. 13, 2815, Springer Nature, 2022, doi:10.1038/s41467-022-30390-9.
short: A.A. Rosenberg, A. Marx, A.M. Bronstein, Nature Communications 13 (2022).
date_created: 2024-10-08T12:53:01Z
date_published: 2022-05-20T00:00:00Z
date_updated: 2024-10-14T09:49:02Z
day: '20'
doi: 10.1038/s41467-022-30390-9
extern: '1'
external_id:
pmid:
- '35595777'
intvolume: ' 13'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1038/s41467-022-30390-9
month: '05'
oa: 1
oa_version: Published Version
pmid: 1
publication: Nature Communications
publication_identifier:
issn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Codon-specific Ramachandran plots show amino acid backbone conformation depends
on identity of the translated codon
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2022'
...
---
OA_place: publisher
OA_type: free access
_id: '18222'
abstract:
- lang: eng
text: "STUDY QUESTION: What is the accuracy and agreement of embryologists when
assessing the implantation probability of blastocysts using time-lapse imaging
(TLI), and can it be improved with a data-driven algorithm?\r\n\r\nSUMMARY ANSWER:
The overall interobserver agreement of a large panel of embryologists was moderate
and prediction accuracy was modest, while the purpose-built artificial intelligence
model generally resulted in higher performance metrics.\r\n\r\nWHAT IS KNOWN ALREADY:
Previous studies have demonstrated significant interobserver variability amongst
embryologists when assessing embryo quality. However, data concerning embryologists’
ability to predict implantation probability using TLI is still lacking. Emerging
technologies based on data-driven tools have shown great promise for improving
embryo selection and predicting clinical outcomes.\r\n\r\nSTUDY DESIGN, SIZE,
DURATION: TLI video files of 136 embryos with known implantation data were retrospectively
collected from two clinical sites between 2018 and 2019 for the performance assessment
of 36 embryologists and comparison with a deep neural network (DNN).\r\n\r\nPARTICIPANTS/MATERIALS,
SETTING, METHODS: We recruited 39 embryologists from 13 different countries. All
participants were blinded to clinical outcomes. A total of 136 TLI videos of embryos
that reached the blastocyst stage were used for this experiment. Each embryo’s
likelihood of successfully implanting was assessed by 36 embryologists, providing
implantation probability grades (IPGs) from 1 to 5, where 1 indicates a very low
likelihood of implantation and 5 indicates a very high likelihood. Subsequently,
three embryologists with over 5 years of experience provided Gardner scores. All
136 blastocysts were categorized into three quality groups based on their Gardner
scores. Embryologist predictions were then converted into predictions of implantation
(IPG ≥ 3) and no implantation (IPG ≤ 2). Embryologists’ performance and agreement
were assessed using Fleiss kappa coefficient. A 10-fold cross-validation DNN was
developed to provide IPGs for TLI video files. The model’s performance was compared
to that of the embryologists.\r\n\r\nMAIN RESULTS AND THE ROLE OF CHANCE: Logistic
regression was employed for the following confounding variables: country of residence,
academic level, embryo scoring system, log years of experience and experience
using TLI. None were found to have a statistically significant impact on embryologist
performance at α = 0.05. The average implantation prediction accuracy for the
embryologists was 51.9% for all embryos (N = 136). The average accuracy of the
embryologists when assessing top quality and poor quality embryos (according to
the Gardner score categorizations) was 57.5% and 57.4%, respectively, and 44.6%
for fair quality embryos. Overall interobserver agreement was moderate (κ = 0.56,
N = 136). The best agreement was achieved in the poor + top quality group (κ = 0.65,
N = 77), while the agreement in the fair quality group was lower (κ = 0.25, N = 59).
The DNN showed an overall accuracy rate of 62.5%, with accuracies of 62.2%, 61%
and 65.6% for the poor, fair and top quality groups, respectively. The AUC for
the DNN was higher than that of the embryologists overall (0.70 DNN vs 0.61 embryologists)
as well as in all of the Gardner groups (DNN vs embryologists—Poor: 0.69 vs 0.62;
Fair: 0.67 vs 0.53; Top: 0.77 vs 0.54).\r\n\r\nLIMITATIONS, REASONS FOR CAUTION:
Blastocyst assessment was performed using video files acquired from time-lapse
incubators, where each video contained data from a single focal plane. Clinical
data regarding the underlying cause of infertility and endometrial thickness before
the transfer was not available, yet may explain implantation failure and lower
accuracy of IPGs. Implantation was defined as the presence of a gestational sac,
whereas the detection of fetal heartbeat is a more robust marker of embryo viability.
The raw data were anonymized to the extent that it was not possible to quantify
the number of unique patients and cycles included in the study, potentially masking
the effect of bias from a limited patient pool. Furthermore, the lack of demographic
data makes it difficult to draw conclusions on how representative the dataset
was of the wider population. Finally, embryologists were required to assess the
implantation potential, not embryo quality. Although this is not the traditional
approach to embryo evaluation, morphology/morphokinetics as a means of assessing
embryo quality is believed to be strongly correlated with viability and, for some
methods, implantation potential.\r\n\r\nWIDER IMPLICATIONS OF THE FINDINGS: Embryo
selection is a key element in IVF success and continues to be a challenge. Improving
the predictive ability could assist in optimizing implantation success rates and
other clinical outcomes and could minimize the financial and emotional burden
on the patient. This study demonstrates moderate agreement rates between embryologists,
likely due to the subjective nature of embryo assessment. In particular, we found
that average embryologist accuracy and agreement were significantly lower for
fair quality embryos when compared with that for top and poor quality embryos.
Using data-driven algorithms as an assistive tool may help IVF professionals increase
success rates and promote much needed standardization in the IVF clinic. Our results
indicate a need for further research regarding technological advancement in this
field."
article_processing_charge: No
article_type: original
author:
- first_name: Daniel E
full_name: Fordham, Daniel E
last_name: Fordham
- first_name: Dror
full_name: Rosentraub, Dror
last_name: Rosentraub
- first_name: Avital L
full_name: Polsky, Avital L
last_name: Polsky
- first_name: Talia
full_name: Aviram, Talia
last_name: Aviram
- first_name: Yotam
full_name: Wolf, Yotam
last_name: Wolf
- first_name: Oriel
full_name: Perl, Oriel
last_name: Perl
- first_name: Asnat
full_name: Devir, Asnat
last_name: Devir
- first_name: Shahar
full_name: Rosentraub, Shahar
last_name: Rosentraub
- first_name: David H
full_name: Silver, David H
last_name: Silver
- first_name: Yael
full_name: Gold Zamir, Yael
last_name: Gold Zamir
- first_name: Alexander
full_name: Bronstein, Alexander
id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
last_name: Bronstein
orcid: 0000-0001-9699-8730
- first_name: Miguel
full_name: Lara Lara, Miguel
last_name: Lara Lara
- first_name: Jara
full_name: Ben Nagi, Jara
last_name: Ben Nagi
- first_name: Adrian
full_name: Alvarez, Adrian
last_name: Alvarez
- first_name: Santiago
full_name: Munné, Santiago
last_name: Munné
citation:
ama: 'Fordham DE, Rosentraub D, Polsky AL, et al. Embryologist agreement when assessing
blastocyst implantation probability: Is data-driven prediction the solution to
embryo assessment subjectivity? Human Reproduction. 2022;37(10):2275-2290.
doi:10.1093/humrep/deac171'
apa: 'Fordham, D. E., Rosentraub, D., Polsky, A. L., Aviram, T., Wolf, Y., Perl,
O., … Munné, S. (2022). Embryologist agreement when assessing blastocyst implantation
probability: Is data-driven prediction the solution to embryo assessment subjectivity?
Human Reproduction. Oxford University Press. https://doi.org/10.1093/humrep/deac171'
chicago: 'Fordham, Daniel E, Dror Rosentraub, Avital L Polsky, Talia Aviram, Yotam
Wolf, Oriel Perl, Asnat Devir, et al. “Embryologist Agreement When Assessing Blastocyst
Implantation Probability: Is Data-Driven Prediction the Solution to Embryo Assessment
Subjectivity?” Human Reproduction. Oxford University Press, 2022. https://doi.org/10.1093/humrep/deac171.'
ieee: 'D. E. Fordham et al., “Embryologist agreement when assessing blastocyst
implantation probability: Is data-driven prediction the solution to embryo assessment
subjectivity?,” Human Reproduction, vol. 37, no. 10. Oxford University
Press, pp. 2275–2290, 2022.'
ista: 'Fordham DE, Rosentraub D, Polsky AL, Aviram T, Wolf Y, Perl O, Devir A, Rosentraub
S, Silver DH, Gold Zamir Y, Bronstein AM, Lara Lara M, Ben Nagi J, Alvarez A,
Munné S. 2022. Embryologist agreement when assessing blastocyst implantation probability:
Is data-driven prediction the solution to embryo assessment subjectivity? Human
Reproduction. 37(10), 2275–2290.'
mla: 'Fordham, Daniel E., et al. “Embryologist Agreement When Assessing Blastocyst
Implantation Probability: Is Data-Driven Prediction the Solution to Embryo Assessment
Subjectivity?” Human Reproduction, vol. 37, no. 10, Oxford University Press,
2022, pp. 2275–90, doi:10.1093/humrep/deac171.'
short: D.E. Fordham, D. Rosentraub, A.L. Polsky, T. Aviram, Y. Wolf, O. Perl, A.
Devir, S. Rosentraub, D.H. Silver, Y. Gold Zamir, A.M. Bronstein, M. Lara Lara,
J. Ben Nagi, A. Alvarez, S. Munné, Human Reproduction 37 (2022) 2275–2290.
date_created: 2024-10-08T12:53:20Z
date_published: 2022-10-01T00:00:00Z
date_updated: 2024-10-14T09:54:40Z
day: '01'
doi: 10.1093/humrep/deac171
extern: '1'
intvolume: ' 37'
issue: '10'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1093/humrep/deac171
month: '10'
oa: 1
oa_version: Published Version
page: 2275-2290
publication: Human Reproduction
publication_identifier:
eissn:
- 1460-2350
issn:
- 0268-1161
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Embryologist agreement when assessing blastocyst implantation probability:
Is data-driven prediction the solution to embryo assessment subjectivity?'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2022'
...
---
OA_place: repository
_id: '18224'
abstract:
- lang: eng
text: Learning from one or few visual examples is one of the key capabilities of
humans since early infancy, but is still a significant challenge for modern AI
systems. While considerable progress has been achieved in few-shot learning from
a few image examples, much less attention has been given to the verbal descriptions
that are usually provided to infants when they are presented with a new object.
In this paper, we focus on the role of additional semantics that can significantly
facilitate few-shot visual learning. Building upon recent advances in few-shot
learning with additional semantic information, we demonstrate that further improvements
are possible by combining multiple and richer semantics (category labels, attributes,
and natural language descriptions). Using these ideas, we offer the community
new results on the popular miniImageNet and CUB few-shot benchmarks, comparing
favorably to the previous state-of-the-art results for both visual only and visual
plus semantics-based approaches. We also performed an ablation study investigating
the components and design choices of our approach. Code available on github.com/EliSchwartz/mutiple-semantics.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Eli
full_name: Schwartz, Eli
last_name: Schwartz
- first_name: Leonid
full_name: Karlinsky, Leonid
last_name: Karlinsky
- first_name: Rogerio
full_name: Feris, Rogerio
last_name: Feris
- first_name: Raja
full_name: Giryes, Raja
last_name: Giryes
- first_name: Alexander
full_name: Bronstein, Alexander
id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
last_name: Bronstein
orcid: 0000-0001-9699-8730
citation:
ama: Schwartz E, Karlinsky L, Feris R, Giryes R, Bronstein AM. Baby steps towards
few-shot learning with multiple semantics. Pattern Recognition Letters.
2022;160:142-147. doi:10.1016/j.patrec.2022.06.012
apa: Schwartz, E., Karlinsky, L., Feris, R., Giryes, R., & Bronstein, A. M.
(2022). Baby steps towards few-shot learning with multiple semantics. Pattern
Recognition Letters. Elsevier. https://doi.org/10.1016/j.patrec.2022.06.012
chicago: Schwartz, Eli, Leonid Karlinsky, Rogerio Feris, Raja Giryes, and Alex M.
Bronstein. “Baby Steps towards Few-Shot Learning with Multiple Semantics.” Pattern
Recognition Letters. Elsevier, 2022. https://doi.org/10.1016/j.patrec.2022.06.012.
ieee: E. Schwartz, L. Karlinsky, R. Feris, R. Giryes, and A. M. Bronstein, “Baby
steps towards few-shot learning with multiple semantics,” Pattern Recognition
Letters, vol. 160. Elsevier, pp. 142–147, 2022.
ista: Schwartz E, Karlinsky L, Feris R, Giryes R, Bronstein AM. 2022. Baby steps
towards few-shot learning with multiple semantics. Pattern Recognition Letters.
160, 142–147.
mla: Schwartz, Eli, et al. “Baby Steps towards Few-Shot Learning with Multiple Semantics.”
Pattern Recognition Letters, vol. 160, Elsevier, 2022, pp. 142–47, doi:10.1016/j.patrec.2022.06.012.
short: E. Schwartz, L. Karlinsky, R. Feris, R. Giryes, A.M. Bronstein, Pattern Recognition
Letters 160 (2022) 142–147.
date_created: 2024-10-08T12:54:03Z
date_published: 2022-08-01T00:00:00Z
date_updated: 2024-10-14T10:58:20Z
day: '01'
doi: 10.1016/j.patrec.2022.06.012
extern: '1'
external_id:
arxiv:
- '1906.01905'
intvolume: ' 160'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1906.01905
month: '08'
oa: 1
oa_version: Preprint
page: 142-147
publication: Pattern Recognition Letters
publication_identifier:
issn:
- 0167-8655
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Baby steps towards few-shot learning with multiple semantics
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 160
year: '2022'
...
---
OA_place: publisher
_id: '18225'
abstract:
- lang: eng
text: "Isometric feature mapping is an established time-honored algorithm in manifold
learning and non-linear dimensionality reduction. Its prominence can be attributed
to the output of a coherent global low-dimensional representation of data by preserving
intrinsic distances. In order to enable an efficient and more applicable isometric
feature mapping, a diverse set of sophisticated advancements have been proposed
to the original algorithm to incorporate important factors like sparsity of computation,
conformality, topological constraints and spectral geometry. However, a significant
shortcoming of most approaches is the dependence on large-scale dense-spectral
decompositions and the inability to generalize to points far away from the sampling
of the manifold.\r\nIn this paper, we explore an unsupervised deep learning approach
for computing distance-preserving maps for non-linear dimensionality reduction.
We demonstrate that our framework is general enough to incorporate all previous
advancements and show a significantly improved local and non-local generalization
of the isometric mapping. Our approach involves training with only a few landmark
points and avoids the need for population of dense matrices as well as computing
their spectral decomposition."
article_number: '104461'
article_processing_charge: No
article_type: original
author:
- first_name: Gautam
full_name: Pai, Gautam
last_name: Pai
- first_name: Alexander
full_name: Bronstein, Alexander
id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
last_name: Bronstein
orcid: 0000-0001-9699-8730
- first_name: Ronen
full_name: Talmon, Ronen
last_name: Talmon
- first_name: Ron
full_name: Kimmel, Ron
last_name: Kimmel
citation:
ama: Pai G, Bronstein AM, Talmon R, Kimmel R. Deep isometric maps. Image and
Vision Computing. 2022;123. doi:10.1016/j.imavis.2022.104461
apa: Pai, G., Bronstein, A. M., Talmon, R., & Kimmel, R. (2022). Deep isometric
maps. Image and Vision Computing. Elsevier. https://doi.org/10.1016/j.imavis.2022.104461
chicago: Pai, Gautam, Alex M. Bronstein, Ronen Talmon, and Ron Kimmel. “Deep Isometric
Maps.” Image and Vision Computing. Elsevier, 2022. https://doi.org/10.1016/j.imavis.2022.104461.
ieee: G. Pai, A. M. Bronstein, R. Talmon, and R. Kimmel, “Deep isometric maps,”
Image and Vision Computing, vol. 123. Elsevier, 2022.
ista: Pai G, Bronstein AM, Talmon R, Kimmel R. 2022. Deep isometric maps. Image
and Vision Computing. 123, 104461.
mla: Pai, Gautam, et al. “Deep Isometric Maps.” Image and Vision Computing,
vol. 123, 104461, Elsevier, 2022, doi:10.1016/j.imavis.2022.104461.
short: G. Pai, A.M. Bronstein, R. Talmon, R. Kimmel, Image and Vision Computing
123 (2022).
date_created: 2024-10-08T12:54:22Z
date_published: 2022-07-01T00:00:00Z
date_updated: 2024-10-14T11:03:26Z
day: '01'
doi: 10.1016/j.imavis.2022.104461
extern: '1'
intvolume: ' 123'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1016/j.imavis.2022.104461
month: '07'
oa: 1
oa_version: Published Version
publication: Image and Vision Computing
publication_identifier:
issn:
- 0262-8856
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Deep isometric maps
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 123
year: '2022'
...
---
OA_place: publisher
OA_type: hybrid
_id: '18226'
abstract:
- lang: eng
text: Spontaneous parametric downconversion (SPDC) in quantum optics is an invaluable
resource for the realization of high-dimensional qudits with spatial modes of
light. One of the main open challenges is how to directly generate a desirable
qudit state in the SPDC process. This problem can be addressed through advanced
computational learning methods; however, due to difficulties in modeling the SPDC
process by a fully differentiable algorithm, progress has been limited. Here,
we overcome these limitations and introduce a physically constrained and differentiable
model, validated against experimental results for shaped pump beams and structured
crystals, capable of learning the relevant interaction parameters in the process.
We avoid any restrictions induced by the stochastic nature of our physical model
and integrate the dynamic equations governing the evolution under the SPDC Hamiltonian.
We solve the inverse problem of designing a nonlinear quantum optical system that
achieves the desired quantum state of downconverted photon pairs. The desired
states are defined using either the second-order correlations between different
spatial modes or by specifying the required density matrix. By learning nonlinear
photonic crystal structures as well as different pump shapes, we successfully
show how to generate maximally entangled states. Furthermore, we simulate all-optical
coherent control over the generated quantum state by actively changing the profile
of the pump beam. Our work can be useful for applications such as novel designs
of high-dimensional quantum key distribution and quantum information processing
protocols. In addition, our method can be readily applied for controlling other
degrees of freedom of light in the SPDC process, such as spectral and temporal
properties, and may even be used in condensed-matter systems having a similar
interaction Hamiltonian.
article_processing_charge: No
article_type: original
author:
- first_name: Eyal
full_name: Rozenberg, Eyal
last_name: Rozenberg
- first_name: Aviv
full_name: Karnieli, Aviv
last_name: Karnieli
- first_name: Ofir
full_name: Yesharim, Ofir
last_name: Yesharim
- first_name: Joshua
full_name: Foley-Comer, Joshua
last_name: Foley-Comer
- first_name: Sivan
full_name: Trajtenberg-Mills, Sivan
last_name: Trajtenberg-Mills
- first_name: Daniel
full_name: Freedman, Daniel
last_name: Freedman
- first_name: Alexander
full_name: Bronstein, Alexander
id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
last_name: Bronstein
orcid: 0000-0001-9699-8730
- first_name: Ady
full_name: Arie, Ady
last_name: Arie
citation:
ama: Rozenberg E, Karnieli A, Yesharim O, et al. Inverse design of spontaneous parametric
downconversion for generation of high-dimensional qudits. Optica. 2022;9(6):602-615.
doi:10.1364/optica.451115
apa: Rozenberg, E., Karnieli, A., Yesharim, O., Foley-Comer, J., Trajtenberg-Mills,
S., Freedman, D., … Arie, A. (2022). Inverse design of spontaneous parametric
downconversion for generation of high-dimensional qudits. Optica. Optica
Publishing Group. https://doi.org/10.1364/optica.451115
chicago: Rozenberg, Eyal, Aviv Karnieli, Ofir Yesharim, Joshua Foley-Comer, Sivan
Trajtenberg-Mills, Daniel Freedman, Alex M. Bronstein, and Ady Arie. “Inverse
Design of Spontaneous Parametric Downconversion for Generation of High-Dimensional
Qudits.” Optica. Optica Publishing Group, 2022. https://doi.org/10.1364/optica.451115.
ieee: E. Rozenberg et al., “Inverse design of spontaneous parametric downconversion
for generation of high-dimensional qudits,” Optica, vol. 9, no. 6. Optica
Publishing Group, pp. 602–615, 2022.
ista: Rozenberg E, Karnieli A, Yesharim O, Foley-Comer J, Trajtenberg-Mills S, Freedman
D, Bronstein AM, Arie A. 2022. Inverse design of spontaneous parametric downconversion
for generation of high-dimensional qudits. Optica. 9(6), 602–615.
mla: Rozenberg, Eyal, et al. “Inverse Design of Spontaneous Parametric Downconversion
for Generation of High-Dimensional Qudits.” Optica, vol. 9, no. 6, Optica
Publishing Group, 2022, pp. 602–15, doi:10.1364/optica.451115.
short: E. Rozenberg, A. Karnieli, O. Yesharim, J. Foley-Comer, S. Trajtenberg-Mills,
D. Freedman, A.M. Bronstein, A. Arie, Optica 9 (2022) 602–615.
date_created: 2024-10-08T12:54:43Z
date_published: 2022-06-06T00:00:00Z
date_updated: 2024-10-14T11:07:29Z
day: '06'
doi: 10.1364/optica.451115
extern: '1'
intvolume: ' 9'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1364/OPTICA.451115
month: '06'
oa: 1
oa_version: Published Version
page: 602-615
publication: Optica
publication_identifier:
issn:
- 2334-2536
publication_status: published
publisher: Optica Publishing Group
quality_controlled: '1'
scopus_import: '1'
status: public
title: Inverse design of spontaneous parametric downconversion for generation of high-dimensional
qudits
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 9
year: '2022'
...
---
_id: '18229'
abstract:
- lang: eng
text: We present Self-Classifier – a novel self-supervised end-to-end classification
learning approach. Self-Classifier learns labels and representations simultaneously
in a single-stage end-to-end manner by optimizing for same-class prediction of
two augmented views of the same sample. To guarantee non-degenerate solutions
(i.e., solutions where all labels are assigned to the same class) we propose a
mathematically motivated variant of the cross-entropy loss that has a uniform
prior asserted on the predicted labels. In our theoretical analysis, we prove
that degenerate solutions are not in the set of optimal solutions of our approach.
Self-Classifier is simple to implement and scalable. Unlike other popular unsupervised
classification and contrastive representation learning approaches, it does not
require any form of pre-training, expectation-maximization, pseudo-labeling, external
clustering, a second network, stop-gradient operation, or negative pairs. Despite
its simplicity, our approach sets a new state of the art for unsupervised classification
of ImageNet; and even achieves comparable to state-of-the-art results for unsupervised
representation learning. Code is available at https://github.com/elad-amrani/self-classifier.
alternative_title:
- LNCS
article_processing_charge: No
arxiv: 1
author:
- first_name: Elad
full_name: Amrani, Elad
last_name: Amrani
- first_name: Leonid
full_name: Karlinsky, Leonid
last_name: Karlinsky
- first_name: Alexander
full_name: Bronstein, Alexander
id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
last_name: Bronstein
orcid: 0000-0001-9699-8730
citation:
ama: 'Amrani E, Karlinsky L, Bronstein AM. Self-supervised classification network.
In: 17th European Conference on Computer Vision. Vol 13691. Springer Nature;
2022:116-132. doi:10.1007/978-3-031-19821-2_7'
apa: 'Amrani, E., Karlinsky, L., & Bronstein, A. M. (2022). Self-supervised
classification network. In 17th European Conference on Computer Vision
(Vol. 13691, pp. 116–132). Tel Aviv, Israel: Springer Nature. https://doi.org/10.1007/978-3-031-19821-2_7'
chicago: Amrani, Elad, Leonid Karlinsky, and Alex M. Bronstein. “Self-Supervised
Classification Network.” In 17th European Conference on Computer Vision,
13691:116–32. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-19821-2_7.
ieee: E. Amrani, L. Karlinsky, and A. M. Bronstein, “Self-supervised classification
network,” in 17th European Conference on Computer Vision, Tel Aviv, Israel,
2022, vol. 13691, pp. 116–132.
ista: 'Amrani E, Karlinsky L, Bronstein AM. 2022. Self-supervised classification
network. 17th European Conference on Computer Vision. ECCV: European Conference
on Computer Vision, LNCS, vol. 13691, 116–132.'
mla: Amrani, Elad, et al. “Self-Supervised Classification Network.” 17th European
Conference on Computer Vision, vol. 13691, Springer Nature, 2022, pp. 116–32,
doi:10.1007/978-3-031-19821-2_7.
short: E. Amrani, L. Karlinsky, A.M. Bronstein, in:, 17th European Conference on
Computer Vision, Springer Nature, 2022, pp. 116–132.
conference:
end_date: 2022-10-27
location: Tel Aviv, Israel
name: 'ECCV: European Conference on Computer Vision'
start_date: 2022-10-23
date_created: 2024-10-08T12:55:44Z
date_published: 2022-10-23T00:00:00Z
date_updated: 2024-10-15T07:04:39Z
day: '23'
doi: 10.1007/978-3-031-19821-2_7
extern: '1'
external_id:
arxiv:
- '2103.10994'
intvolume: ' 13691'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2103.10994
month: '10'
oa: 1
oa_version: None
page: 116-132
publication: 17th European Conference on Computer Vision
publication_identifier:
eisbn:
- '9783031198212'
eissn:
- 1611-3349
isbn:
- '9783031198205'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/elad-amrani/self-classifier
scopus_import: '1'
status: public
title: Self-supervised classification network
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13691
year: '2022'
...
---
_id: '18291'
article_processing_charge: No
author:
- first_name: Georgios
full_name: Katsaros, Georgios
id: 38DB5788-F248-11E8-B48F-1D18A9856A87
last_name: Katsaros
orcid: 0000-0001-8342-202X
- first_name: Daniel
full_name: Jirovec, Daniel
id: 4C473F58-F248-11E8-B48F-1D18A9856A87
last_name: Jirovec
orcid: 0000-0002-7197-4801
citation:
ama: "Katsaros G, Jirovec D. Dynamics of Hole Singlet-Triplet Qubits with Large
\U0001D454-Factor Differences. 2022. doi:10.15479/AT:ISTA:18291"
apa: "Katsaros, G., & Jirovec, D. (2022). Dynamics of Hole Singlet-Triplet Qubits
with Large \U0001D454-Factor Differences. Institute of Science and Technology
Austria. https://doi.org/10.15479/AT:ISTA:18291"
chicago: "Katsaros, Georgios, and Daniel Jirovec. “Dynamics of Hole Singlet-Triplet
Qubits with Large \U0001D454-Factor Differences.” Institute of Science and Technology
Austria, 2022. https://doi.org/10.15479/AT:ISTA:18291."
ieee: "G. Katsaros and D. Jirovec, “Dynamics of Hole Singlet-Triplet Qubits with
Large \U0001D454-Factor Differences.” Institute of Science and Technology Austria,
2022."
ista: "Katsaros G, Jirovec D. 2022. Dynamics of Hole Singlet-Triplet Qubits with
Large \U0001D454-Factor Differences, Institute of Science and Technology Austria,
10.15479/AT:ISTA:18291."
mla: "Katsaros, Georgios, and Daniel Jirovec. Dynamics of Hole Singlet-Triplet
Qubits with Large \U0001D454-Factor Differences. Institute of Science and
Technology Austria, 2022, doi:10.15479/AT:ISTA:18291."
short: G. Katsaros, D. Jirovec, (2022).
corr_author: '1'
date_created: 2024-10-09T19:35:03Z
date_published: 2022-03-01T00:00:00Z
date_updated: 2025-04-15T07:15:24Z
day: '01'
department:
- _id: GeKa
doi: 10.15479/AT:ISTA:18291
file:
- access_level: open_access
checksum: 3128dffbd09267b93c2d0b1425fd3ba2
content_type: application/x-zip-compressed
creator: gkatsaro
date_created: 2024-10-09T19:31:35Z
date_updated: 2024-10-09T19:31:35Z
file_id: '18292'
file_name: SOIPaper.zip
file_size: 25566516
relation: main_file
success: 1
- access_level: open_access
checksum: df077d2f4652afeb3bf100068e88aa48
content_type: text/plain
creator: gkatsaro
date_created: 2024-10-14T18:11:45Z
date_updated: 2024-10-14T18:11:45Z
file_id: '18442'
file_name: Readme.txt
file_size: 6776
relation: main_file
success: 1
file_date_updated: 2024-10-14T18:11:45Z
has_accepted_license: '1'
month: '03'
oa: 1
oa_version: None
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '10920'
relation: research_paper
status: public
status: public
title: "Dynamics of Hole Singlet-Triplet Qubits with Large \U0001D454-Factor Differences"
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: research_data
user_id: 68b8ca59-c5b3-11ee-8790-cd641c68093d
year: '2022'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18606'
abstract:
- lang: eng
text: "Shear thickening is an intriguing rheological behaviour which consists in
a brutal increase in the viscosity above a critical shear rate. It is famously
encountered in suspensions of corn starch in water. Despite having been discovered
in the early 1930's, its underlying mechanisms remained a mystery for a long time.
In 2013–14, numerical and theoretical works [[1], [2], [3]] put forward a frictional
transition scenario to explain this phenomenon.\r\nIn this talk, I will present
experimental work investigating this frictional transition scenario. In order
to test the ideas of this model, one has to go further than standard rheological
techniques, since they do not provide access to the frictional state of the measured
suspension. I will thus focus on the techniques that we developed in order to
evidence the frictional transition and link it to the presence of a shear-thickening
behaviour."
acknowledgement: "This talk presents parts of my PhD work, conducted at IUSTI in Marseille
under the supervision of Yoël Forterre and Bloen Metzger. It aslo benefited from
contributions from Antoine Bérut, and some of the data was acquired by Pauline Dame
as part of a summer internship.\r\nThis work was supported by the European Research
Council (ERC) under the European Union Horizon 2020 Research and Innovation program
(ERC Grant 647384) and by the Labex MEC (ANR-10-LABX-0092) under the 647384) and
by the A*MIDEX project (ANR-11-IDEX-0001-02) funded by the French government program
Investissements d'Avenir, and by ANR ScienceFriction (No. ANR-18-CE30-0024)."
article_number: '100038'
article_processing_charge: No
article_type: original
author:
- first_name: Cécile
full_name: Clavaud, Cécile
id: 5f654c5d-04a1-11eb-ab36-ba9ffec58bd8
last_name: Clavaud
orcid: 0000-0002-1843-3803
citation:
ama: 'Clavaud C. Shear thickening in dense suspensions: an experimental study. Science
Talks. 2022;3. doi:10.1016/j.sctalk.2022.100038'
apa: 'Clavaud, C. (2022). Shear thickening in dense suspensions: an experimental
study. Science Talks. Elsevier. https://doi.org/10.1016/j.sctalk.2022.100038'
chicago: 'Clavaud, Cécile. “Shear Thickening in Dense Suspensions: An Experimental
Study.” Science Talks. Elsevier, 2022. https://doi.org/10.1016/j.sctalk.2022.100038.'
ieee: 'C. Clavaud, “Shear thickening in dense suspensions: an experimental study,”
Science Talks, vol. 3. Elsevier, 2022.'
ista: 'Clavaud C. 2022. Shear thickening in dense suspensions: an experimental study.
Science Talks. 3, 100038.'
mla: 'Clavaud, Cécile. “Shear Thickening in Dense Suspensions: An Experimental Study.”
Science Talks, vol. 3, 100038, Elsevier, 2022, doi:10.1016/j.sctalk.2022.100038.'
short: C. Clavaud, Science Talks 3 (2022).
corr_author: '1'
date_created: 2024-12-01T23:01:55Z
date_published: 2022-08-01T00:00:00Z
date_updated: 2024-12-11T09:24:57Z
day: '01'
ddc:
- '530'
department:
- _id: ScWa
doi: 10.1016/j.sctalk.2022.100038
file:
- access_level: open_access
checksum: 379a5f0b2684cd5393a23be374591484
content_type: application/pdf
creator: dernst
date_created: 2024-12-03T08:41:48Z
date_updated: 2024-12-03T08:41:48Z
file_id: '18607'
file_name: 2022_ScienceTalks_Clavaud.pdf
file_size: 1128564
relation: main_file
success: 1
- access_level: open_access
checksum: 666c0bd9af8432437554d0c75c540809
content_type: video/mp4
creator: dernst
date_created: 2024-12-11T09:22:13Z
date_updated: 2024-12-11T09:22:13Z
file_id: '18646'
file_name: 2024_ScienceTalk_Clavaud_Video.mp4
file_size: 93265727
relation: main_file
success: 1
- access_level: open_access
checksum: 8fd0d6224d7a0125fcf7d9ca0d80d700
content_type: video/mp4
creator: dernst
date_created: 2024-12-11T09:22:19Z
date_updated: 2024-12-11T09:22:19Z
file_id: '18647'
file_name: 2024_ScienceTalk__Clavaud_QA.mp4
file_size: 58282147
relation: supplementary_material
file_date_updated: 2024-12-11T09:22:19Z
has_accepted_license: '1'
intvolume: ' 3'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '08'
oa: 1
oa_version: Published Version
publication: Science Talks
publication_identifier:
eissn:
- 2772-5693
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Shear thickening in dense suspensions: an experimental study'
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 3
year: '2022'
...
---
_id: '12261'
abstract:
- lang: eng
text: 'Dose–response relationships are a general concept for quantitatively describing
biological systems across multiple scales, from the molecular to the whole-cell
level. A clinically relevant example is the bacterial growth response to antibiotics,
which is routinely characterized by dose–response curves. The shape of the dose–response
curve varies drastically between antibiotics and plays a key role in treatment,
drug interactions, and resistance evolution. However, the mechanisms shaping the
dose–response curve remain largely unclear. Here, we show in Escherichia coli
that the distinctively shallow dose–response curve of the antibiotic trimethoprim
is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth,
which in turn weakens the effect of this antibiotic. At the molecular level, this
feedback is caused by the upregulation of the drug target dihydrofolate reductase
(FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim
but follows a universal trend line that depends primarily on the growth rate,
irrespective of its cause. Rewiring the feedback loop alters the dose–response
curve in a predictable manner, which we corroborate using a mathematical model
of cellular resource allocation and growth. Our results indicate that growth-mediated
feedback loops may shape drug responses more generally and could be exploited
to design evolutionary traps that enable selection against drug resistance.'
acknowledged_ssus:
- _id: M-Shop
acknowledgement: This work was in part supported by Human Frontier Science Program
GrantRGP0042/2013, Marie Curie Career Integration Grant303507, AustrianScience Fund
(FWF) Grant P27201-B22, and German Research Foundation(DFG) Collaborative Research
Center (SFB)1310to TB. SAA was supportedby the European Union’s Horizon2020Research
and Innovation Programunder the Marie Skłodowska-Curie Grant agreement No707352.
We wouldlike to thank the Bollenbach group for regular fruitful discussions. We
areparticularly thankful for the technical assistance of Booshini Fernando andfor
discussions of the theoretical aspects with Gerrit Ansmann. We areindebted to Bor
Kavˇciˇc for invaluable advice, help with setting up theluciferase-based growth
monitoring system, and for sharing plasmids. Weacknowledge the IST Austria Miba
Machine Shop for their support inbuilding a housing for the stacker of the plate
reader, which enabled thehigh-throughput luciferase-based experiments. We are grateful
to RosalindAllen, Bor Kavˇciˇc and Dor Russ for feedback on the manuscript. Open
Accessfunding enabled and organized by Projekt DEAL.
article_number: e10490
article_processing_charge: No
article_type: original
author:
- first_name: Andreas
full_name: Angermayr, Andreas
id: 4677C796-F248-11E8-B48F-1D18A9856A87
last_name: Angermayr
orcid: 0000-0001-8619-2223
- first_name: Tin Yau
full_name: Pang, Tin Yau
last_name: Pang
- first_name: Guillaume
full_name: Chevereau, Guillaume
last_name: Chevereau
- first_name: Karin
full_name: Mitosch, Karin
id: 39B66846-F248-11E8-B48F-1D18A9856A87
last_name: Mitosch
- first_name: Martin J
full_name: Lercher, Martin J
last_name: Lercher
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. Growth‐mediated
negative feedback shapes quantitative antibiotic response. Molecular Systems
Biology. 2022;18(9). doi:10.15252/msb.202110490
apa: Angermayr, A., Pang, T. Y., Chevereau, G., Mitosch, K., Lercher, M. J., &
Bollenbach, M. T. (2022). Growth‐mediated negative feedback shapes quantitative
antibiotic response. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.202110490
chicago: Angermayr, Andreas, Tin Yau Pang, Guillaume Chevereau, Karin Mitosch, Martin
J Lercher, and Mark Tobias Bollenbach. “Growth‐mediated Negative Feedback Shapes
Quantitative Antibiotic Response.” Molecular Systems Biology. Embo Press,
2022. https://doi.org/10.15252/msb.202110490.
ieee: A. Angermayr, T. Y. Pang, G. Chevereau, K. Mitosch, M. J. Lercher, and M.
T. Bollenbach, “Growth‐mediated negative feedback shapes quantitative antibiotic
response,” Molecular Systems Biology, vol. 18, no. 9. Embo Press, 2022.
ista: Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. 2022.
Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular
Systems Biology. 18(9), e10490.
mla: Angermayr, Andreas, et al. “Growth‐mediated Negative Feedback Shapes Quantitative
Antibiotic Response.” Molecular Systems Biology, vol. 18, no. 9, e10490,
Embo Press, 2022, doi:10.15252/msb.202110490.
short: A. Angermayr, T.Y. Pang, G. Chevereau, K. Mitosch, M.J. Lercher, M.T. Bollenbach,
Molecular Systems Biology 18 (2022).
date_created: 2023-01-16T09:58:34Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2025-06-11T14:10:18Z
day: '01'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.15252/msb.202110490
external_id:
isi:
- '000856482800001'
pmid:
- '36124745'
file:
- access_level: open_access
checksum: 8b1d8f5ea20c8408acf466435fb6ae01
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T09:49:55Z
date_updated: 2023-01-30T09:49:55Z
file_id: '12446'
file_name: 2022_MolecularSystemsBio_Angermayr.pdf
file_size: 1098812
relation: main_file
success: 1
file_date_updated: 2023-01-30T09:49:55Z
has_accepted_license: '1'
intvolume: ' 18'
isi: 1
issue: '9'
keyword:
- Applied Mathematics
- Computational Theory and Mathematics
- General Agricultural and Biological Sciences
- General Immunology and Microbiology
- General Biochemistry
- Genetics and Molecular Biology
- Information Systems
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
pmid: 1
publication: Molecular Systems Biology
publication_identifier:
eissn:
- 1744-4292
publication_status: published
publisher: Embo Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Growth‐mediated negative feedback shapes quantitative antibiotic response
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: 18
year: '2022'
...
---
_id: '12262'
abstract:
- lang: eng
text: The AAA-ATPase Drg1 is a key factor in eukaryotic ribosome biogenesis that
initiates cytoplasmic maturation of the large ribosomal subunit. Drg1 releases
the shuttling maturation factor Rlp24 from pre-60S particles shortly after nuclear
export, a strict requirement for downstream maturation. The molecular mechanism
of release remained elusive. Here, we report a series of cryo-EM structures that
captured the extraction of Rlp24 from pre-60S particles by Saccharomyces cerevisiae
Drg1. These structures reveal that Arx1 and the eukaryote-specific rRNA expansion
segment ES27 form a joint docking platform that positions Drg1 for efficient extraction
of Rlp24 from the pre-ribosome. The tips of the Drg1 N domains thereby guide the
Rlp24 C terminus into the central pore of the Drg1 hexamer, enabling extraction
by a hand-over-hand translocation mechanism. Our results uncover substrate recognition
and processing by Drg1 step by step and provide a comprehensive mechanistic picture
of the conserved modus operandi of AAA-ATPases.
acknowledged_ssus:
- _id: EM-Fac
acknowledgement: "We thank M. Fromont-Racine, A. Johnson, J. Woolford, S. Rospert,
J. P. G. Ballesta and\r\nE. Hurt for supplying antibodies. The work was supported
by Boehringer Ingelheim (to\r\nD. H.), the Austrian Science Foundation FWF (grants
32536 and 32977 to H. B.), the\r\nUK Medical Research Council (MR/T012412/1 to A.
J. W.) and the German Research\r\nFoundation (Emmy Noether Programme STE 2517/1-1
and STE 2517/5-1 to F.S.). We\r\nthank Norberto Escudero-Urquijo, Pablo Castro-Hartmann
and K. Dent, Cambridge\r\nInstitute for Medical Research, for their help in cryo-EM
during early phases of this\r\nproject. This research was supported by the Scientific
Service Units of IST Austria through\r\nresources provided by the Electron Microscopy
Facility. We thank S. Keller, Institute of\r\nMolecular Biosciences (Biophysics),
University Graz for support with the quantification of\r\nthe SPR particle release
assay. We thank I. Schaffner, University of Natural Resources and\r\nLife Sciences,
Vienna for her help in early stages of the SPR experiments."
article_processing_charge: No
article_type: original
author:
- first_name: Michael
full_name: Prattes, Michael
last_name: Prattes
- first_name: Irina
full_name: Grishkovskaya, Irina
last_name: Grishkovskaya
- first_name: Victor-Valentin
full_name: Hodirnau, Victor-Valentin
id: 3661B498-F248-11E8-B48F-1D18A9856A87
last_name: Hodirnau
- first_name: Christina
full_name: Hetzmannseder, Christina
last_name: Hetzmannseder
- first_name: Gertrude
full_name: Zisser, Gertrude
last_name: Zisser
- first_name: Carolin
full_name: Sailer, Carolin
last_name: Sailer
- first_name: Vasileios
full_name: Kargas, Vasileios
last_name: Kargas
- first_name: Mathias
full_name: Loibl, Mathias
last_name: Loibl
- first_name: Magdalena
full_name: Gerhalter, Magdalena
last_name: Gerhalter
- first_name: Lisa
full_name: Kofler, Lisa
last_name: Kofler
- first_name: Alan J.
full_name: Warren, Alan J.
last_name: Warren
- first_name: Florian
full_name: Stengel, Florian
last_name: Stengel
- first_name: David
full_name: Haselbach, David
last_name: Haselbach
- first_name: Helmut
full_name: Bergler, Helmut
last_name: Bergler
citation:
ama: Prattes M, Grishkovskaya I, Hodirnau V-V, et al. Visualizing maturation factor
extraction from the nascent ribosome by the AAA-ATPase Drg1. Nature Structural
& Molecular Biology. 2022;29(9):942-953. doi:10.1038/s41594-022-00832-5
apa: Prattes, M., Grishkovskaya, I., Hodirnau, V.-V., Hetzmannseder, C., Zisser,
G., Sailer, C., … Bergler, H. (2022). Visualizing maturation factor extraction
from the nascent ribosome by the AAA-ATPase Drg1. Nature Structural & Molecular
Biology. Springer Nature. https://doi.org/10.1038/s41594-022-00832-5
chicago: Prattes, Michael, Irina Grishkovskaya, Victor-Valentin Hodirnau, Christina
Hetzmannseder, Gertrude Zisser, Carolin Sailer, Vasileios Kargas, et al. “Visualizing
Maturation Factor Extraction from the Nascent Ribosome by the AAA-ATPase Drg1.”
Nature Structural & Molecular Biology. Springer Nature, 2022. https://doi.org/10.1038/s41594-022-00832-5.
ieee: M. Prattes et al., “Visualizing maturation factor extraction from the
nascent ribosome by the AAA-ATPase Drg1,” Nature Structural & Molecular
Biology, vol. 29, no. 9. Springer Nature, pp. 942–953, 2022.
ista: Prattes M, Grishkovskaya I, Hodirnau V-V, Hetzmannseder C, Zisser G, Sailer
C, Kargas V, Loibl M, Gerhalter M, Kofler L, Warren AJ, Stengel F, Haselbach D,
Bergler H. 2022. Visualizing maturation factor extraction from the nascent ribosome
by the AAA-ATPase Drg1. Nature Structural & Molecular Biology. 29(9), 942–953.
mla: Prattes, Michael, et al. “Visualizing Maturation Factor Extraction from the
Nascent Ribosome by the AAA-ATPase Drg1.” Nature Structural & Molecular
Biology, vol. 29, no. 9, Springer Nature, 2022, pp. 942–53, doi:10.1038/s41594-022-00832-5.
short: M. Prattes, I. Grishkovskaya, V.-V. Hodirnau, C. Hetzmannseder, G. Zisser,
C. Sailer, V. Kargas, M. Loibl, M. Gerhalter, L. Kofler, A.J. Warren, F. Stengel,
D. Haselbach, H. Bergler, Nature Structural & Molecular Biology 29 (2022)
942–953.
date_created: 2023-01-16T09:59:06Z
date_published: 2022-09-12T00:00:00Z
date_updated: 2023-08-04T09:52:20Z
day: '12'
ddc:
- '570'
department:
- _id: EM-Fac
doi: 10.1038/s41594-022-00832-5
external_id:
isi:
- '000852942100004'
pmid:
- '36097293'
file:
- access_level: open_access
checksum: 2d5c3ec01718fefd7553052b0b8a0793
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T10:00:04Z
date_updated: 2023-01-30T10:00:04Z
file_id: '12447'
file_name: 2022_NatureStrucMolecBio_Prattes.pdf
file_size: 9935057
relation: main_file
success: 1
file_date_updated: 2023-01-30T10:00:04Z
has_accepted_license: '1'
intvolume: ' 29'
isi: 1
issue: '9'
keyword:
- Molecular Biology
- Structural Biology
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 942-953
pmid: 1
publication: Nature Structural & Molecular Biology
publication_identifier:
eissn:
- 1545-9985
issn:
- 1545-9993
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Visualizing maturation factor extraction from the nascent ribosome by the AAA-ATPase
Drg1
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 29
year: '2022'
...
---
_id: '12264'
abstract:
- lang: eng
text: Reproductive isolation (RI) is a core concept in evolutionary biology. It
has been the central focus of speciation research since the modern synthesis and
is the basis by which biological species are defined. Despite this, the term is
used in seemingly different ways, and attempts to quantify RI have used very different
approaches. After showing that the field lacks a clear definition of the term,
we attempt to clarify key issues, including what RI is, how it can be quantified
in principle, and how it can be measured in practice. Following other definitions
with a genetic focus, we propose that RI is a quantitative measure of the effect
that genetic differences between populations have on gene flow. Specifically,
RI compares the flow of neutral alleles in the presence of these genetic differences
to the flow without any such differences. RI is thus greater than zero when genetic
differences between populations reduce the flow of neutral alleles between populations.
We show how RI can be quantified in a range of scenarios. A key conclusion is
that RI depends strongly on circumstances—including the spatial, temporal and
genomic context—making it difficult to compare across systems. After reviewing
methods for estimating RI from data, we conclude that it is difficult to measure
in practice. We discuss our findings in light of the goals of speciation research
and encourage the use of methods for estimating RI that integrate organismal and
genetic approaches.
acknowledgement: 'We are grateful to the participants of the ESEB satellite symposium
‘Understanding reproductive isolation: bridging conceptual barriers in speciation research’ in 2021 for the interesting discussions that helped us clarify the thoughts presented in this article. We thank Roger
Butlin, Michael Turelli and two anonymous reviewers for their thoughtful comments
on this manuscript. We are also very grateful to Roger Butlin and the Barton Group
for the continued conversa-tions about RI. In addition, we thank all participants
of the speciation survey. Part of this work was funded by the Austrian Science Fund
FWF (grant P 32166)'
article_processing_charge: Yes (via OA deal)
article_type: review
author:
- first_name: Anja M
full_name: Westram, Anja M
id: 3C147470-F248-11E8-B48F-1D18A9856A87
last_name: Westram
orcid: 0000-0003-1050-4969
- first_name: Sean
full_name: Stankowski, Sean
id: 43161670-5719-11EA-8025-FABC3DDC885E
last_name: Stankowski
- first_name: Parvathy
full_name: Surendranadh, Parvathy
id: 455235B8-F248-11E8-B48F-1D18A9856A87
last_name: Surendranadh
orcid: 0000-0001-6395-386X
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: Westram AM, Stankowski S, Surendranadh P, Barton NH. What is reproductive isolation?
Journal of Evolutionary Biology. 2022;35(9):1143-1164. doi:10.1111/jeb.14005
apa: Westram, A. M., Stankowski, S., Surendranadh, P., & Barton, N. H. (2022).
What is reproductive isolation? Journal of Evolutionary Biology. Wiley.
https://doi.org/10.1111/jeb.14005
chicago: Westram, Anja M, Sean Stankowski, Parvathy Surendranadh, and Nicholas H
Barton. “What Is Reproductive Isolation?” Journal of Evolutionary Biology.
Wiley, 2022. https://doi.org/10.1111/jeb.14005.
ieee: A. M. Westram, S. Stankowski, P. Surendranadh, and N. H. Barton, “What is
reproductive isolation?,” Journal of Evolutionary Biology, vol. 35, no.
9. Wiley, pp. 1143–1164, 2022.
ista: Westram AM, Stankowski S, Surendranadh P, Barton NH. 2022. What is reproductive
isolation? Journal of Evolutionary Biology. 35(9), 1143–1164.
mla: Westram, Anja M., et al. “What Is Reproductive Isolation?” Journal of Evolutionary
Biology, vol. 35, no. 9, Wiley, 2022, pp. 1143–64, doi:10.1111/jeb.14005.
short: A.M. Westram, S. Stankowski, P. Surendranadh, N.H. Barton, Journal of Evolutionary
Biology 35 (2022) 1143–1164.
corr_author: '1'
date_created: 2023-01-16T09:59:24Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2025-04-15T08:20:40Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1111/jeb.14005
external_id:
isi:
- '000849851100002'
pmid:
- '36063156'
file:
- access_level: open_access
checksum: f08de57112330a7ee88d2e1b20576a1e
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T10:05:31Z
date_updated: 2023-01-30T10:05:31Z
file_id: '12448'
file_name: 2022_JourEvoBiology_Westram.pdf
file_size: 3146793
relation: main_file
success: 1
file_date_updated: 2023-01-30T10:05:31Z
has_accepted_license: '1'
intvolume: ' 35'
isi: 1
issue: '9'
keyword:
- Ecology
- Evolution
- Behavior and Systematics
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 1143-1164
pmid: 1
project:
- _id: 05959E1C-7A3F-11EA-A408-12923DDC885E
grant_number: P32166
name: Snapdragon Speciation
publication: Journal of Evolutionary Biology
publication_identifier:
eissn:
- 1420-9101
issn:
- 1010-061X
publication_status: published
publisher: Wiley
quality_controlled: '1'
related_material:
record:
- id: '12265'
relation: other
status: public
scopus_import: '1'
status: public
title: What is reproductive isolation?
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 35
year: '2022'
...
---
_id: '12265'
acknowledgement: We are very grateful to the authors of the commentaries for the interesting
discussion and to Luke Holman for handling this set of manuscripts. Part of this
work was funded by the Austrian Science Fund FWF (grant P 32166).
article_processing_charge: Yes (via OA deal)
article_type: letter_note
author:
- first_name: Anja M
full_name: Westram, Anja M
id: 3C147470-F248-11E8-B48F-1D18A9856A87
last_name: Westram
orcid: 0000-0003-1050-4969
- first_name: Sean
full_name: Stankowski, Sean
id: 43161670-5719-11EA-8025-FABC3DDC885E
last_name: Stankowski
- first_name: Parvathy
full_name: Surendranadh, Parvathy
id: 455235B8-F248-11E8-B48F-1D18A9856A87
last_name: Surendranadh
orcid: 0000-0001-6395-386X
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: 'Westram AM, Stankowski S, Surendranadh P, Barton NH. Reproductive isolation,
speciation, and the value of disagreement: A reply to the commentaries on ‘What
is reproductive isolation?’ Journal of Evolutionary Biology. 2022;35(9):1200-1205.
doi:10.1111/jeb.14082'
apa: 'Westram, A. M., Stankowski, S., Surendranadh, P., & Barton, N. H. (2022).
Reproductive isolation, speciation, and the value of disagreement: A reply to
the commentaries on ‘What is reproductive isolation?’ Journal of Evolutionary
Biology. Wiley. https://doi.org/10.1111/jeb.14082'
chicago: 'Westram, Anja M, Sean Stankowski, Parvathy Surendranadh, and Nicholas
H Barton. “Reproductive Isolation, Speciation, and the Value of Disagreement:
A Reply to the Commentaries on ‘What Is Reproductive Isolation?’” Journal of
Evolutionary Biology. Wiley, 2022. https://doi.org/10.1111/jeb.14082.'
ieee: 'A. M. Westram, S. Stankowski, P. Surendranadh, and N. H. Barton, “Reproductive
isolation, speciation, and the value of disagreement: A reply to the commentaries
on ‘What is reproductive isolation?,’” Journal of Evolutionary Biology,
vol. 35, no. 9. Wiley, pp. 1200–1205, 2022.'
ista: 'Westram AM, Stankowski S, Surendranadh P, Barton NH. 2022. Reproductive isolation,
speciation, and the value of disagreement: A reply to the commentaries on ‘What
is reproductive isolation?’ Journal of Evolutionary Biology. 35(9), 1200–1205.'
mla: 'Westram, Anja M., et al. “Reproductive Isolation, Speciation, and the Value
of Disagreement: A Reply to the Commentaries on ‘What Is Reproductive Isolation?’”
Journal of Evolutionary Biology, vol. 35, no. 9, Wiley, 2022, pp. 1200–05,
doi:10.1111/jeb.14082.'
short: A.M. Westram, S. Stankowski, P. Surendranadh, N.H. Barton, Journal of Evolutionary
Biology 35 (2022) 1200–1205.
corr_author: '1'
date_created: 2023-01-16T09:59:37Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2025-04-15T08:20:40Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1111/jeb.14082
external_id:
isi:
- '000849851100009'
file:
- access_level: open_access
checksum: 27268009e5eec030bc10667a4ac5ed4c
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T10:14:09Z
date_updated: 2023-01-30T10:14:09Z
file_id: '12449'
file_name: 2022_JourEvoBiology_Westram_Response.pdf
file_size: 349603
relation: main_file
success: 1
file_date_updated: 2023-01-30T10:14:09Z
has_accepted_license: '1'
intvolume: ' 35'
isi: 1
issue: '9'
keyword:
- Ecology
- Evolution
- Behavior and Systematics
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 1200-1205
project:
- _id: 05959E1C-7A3F-11EA-A408-12923DDC885E
grant_number: P32166
name: Snapdragon Speciation
publication: Journal of Evolutionary Biology
publication_identifier:
eissn:
- 1420-9101
issn:
- 1010-061X
publication_status: published
publisher: Wiley
quality_controlled: '1'
related_material:
record:
- id: '12264'
relation: other
status: public
scopus_import: '1'
status: public
title: 'Reproductive isolation, speciation, and the value of disagreement: A reply
to the commentaries on ‘What is reproductive isolation?’'
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 35
year: '2022'
...
---
_id: '12268'
abstract:
- lang: eng
text: The complexity of the microenvironment effects on cell response, show accumulating
evidence that glioblastoma (GBM) migration and invasiveness are influenced by
the mechanical rigidity of their surroundings. The epithelial–mesenchymal transition
(EMT) is a well-recognized driving force of the invasive behavior of cancer. However,
the primary mechanisms of EMT initiation and progression remain unclear. We have
previously showed that certain substrate stiffness can selectively stimulate human
GBM U251-MG and GL15 glioblastoma cell lines motility. The present study unifies
several known EMT mediators to uncover the reason of the regulation and response
to these stiffnesses. Our results revealed that changing the rigidity of the mechanical
environment tuned the response of both cell lines through change in morphological
features, epithelial-mesenchymal markers (E-, N-Cadherin), EGFR and ROS expressions
in an interrelated manner. Specifically, a stiffer microenvironment induced a
mesenchymal cell shape, a more fragmented morphology, higher intracellular cytosolic
ROS expression and lower mitochondrial ROS. Finally, we observed that cells more
motile showed a more depolarized mitochondrial membrane potential. Unravelling
the process that regulates GBM cells’ infiltrative behavior could provide new
opportunities for identification of new targets and less invasive approaches for
treatment.
acknowledgement: "The research leading to these results has received funding from
AIRC under IG 2021 - ID. 26328 project – P.I. Cortese Barbara and AIRC under MFAG
2015 - ID. 16803 project – “P.I. Cortese Barbara”. The authors are also grateful
to the ”Tecnopolo per la medicina di precisione” (TecnoMed Puglia) - Regione Puglia:
DGR n.2117 del 21/11/2018, CUP: B84I18000540002 and “Tecnopolo di Nanotecnologia
e Fotonica per la medicina di precisione” (TECNOMED) - FISR/MIUR-CNR: delibera CIPE
n.3449 del 7-08-2017, CUP: B83B17000010001.\r\nWe thank Dr. Francesca Pagani for
useful technical support. We thank also Irene Iacuitto, Giovanna Loffredo and Manuela
Marchetti for practical administrative support."
article_number: '983507'
article_processing_charge: No
article_type: original
author:
- first_name: Bernadette
full_name: Basilico, Bernadette
id: 36035796-5ACA-11E9-A75E-7AF2E5697425
last_name: Basilico
orcid: 0000-0003-1843-3173
- first_name: Ilaria Elena
full_name: Palamà, Ilaria Elena
last_name: Palamà
- first_name: Stefania
full_name: D’Amone, Stefania
last_name: D’Amone
- first_name: Clotilde
full_name: Lauro, Clotilde
last_name: Lauro
- first_name: Maria
full_name: Rosito, Maria
last_name: Rosito
- first_name: Maddalena
full_name: Grieco, Maddalena
last_name: Grieco
- first_name: Patrizia
full_name: Ratano, Patrizia
last_name: Ratano
- first_name: Federica
full_name: Cordella, Federica
last_name: Cordella
- first_name: Caterina
full_name: Sanchini, Caterina
last_name: Sanchini
- first_name: Silvia
full_name: Di Angelantonio, Silvia
last_name: Di Angelantonio
- first_name: Davide
full_name: Ragozzino, Davide
last_name: Ragozzino
- first_name: Mariafrancesca
full_name: Cascione, Mariafrancesca
last_name: Cascione
- first_name: Giuseppe
full_name: Gigli, Giuseppe
last_name: Gigli
- first_name: Barbara
full_name: Cortese, Barbara
last_name: Cortese
citation:
ama: Basilico B, Palamà IE, D’Amone S, et al. Substrate stiffness effect on molecular
crosstalk of epithelial-mesenchymal transition mediators of human glioblastoma
cells. Frontiers in Oncology. 2022;12. doi:10.3389/fonc.2022.983507
apa: Basilico, B., Palamà, I. E., D’Amone, S., Lauro, C., Rosito, M., Grieco, M.,
… Cortese, B. (2022). Substrate stiffness effect on molecular crosstalk of epithelial-mesenchymal
transition mediators of human glioblastoma cells. Frontiers in Oncology.
Frontiers Media. https://doi.org/10.3389/fonc.2022.983507
chicago: Basilico, Bernadette, Ilaria Elena Palamà, Stefania D’Amone, Clotilde Lauro,
Maria Rosito, Maddalena Grieco, Patrizia Ratano, et al. “Substrate Stiffness Effect
on Molecular Crosstalk of Epithelial-Mesenchymal Transition Mediators of Human
Glioblastoma Cells.” Frontiers in Oncology. Frontiers Media, 2022. https://doi.org/10.3389/fonc.2022.983507.
ieee: B. Basilico et al., “Substrate stiffness effect on molecular crosstalk
of epithelial-mesenchymal transition mediators of human glioblastoma cells,” Frontiers
in Oncology, vol. 12. Frontiers Media, 2022.
ista: Basilico B, Palamà IE, D’Amone S, Lauro C, Rosito M, Grieco M, Ratano P, Cordella
F, Sanchini C, Di Angelantonio S, Ragozzino D, Cascione M, Gigli G, Cortese B.
2022. Substrate stiffness effect on molecular crosstalk of epithelial-mesenchymal
transition mediators of human glioblastoma cells. Frontiers in Oncology. 12, 983507.
mla: Basilico, Bernadette, et al. “Substrate Stiffness Effect on Molecular Crosstalk
of Epithelial-Mesenchymal Transition Mediators of Human Glioblastoma Cells.” Frontiers
in Oncology, vol. 12, 983507, Frontiers Media, 2022, doi:10.3389/fonc.2022.983507.
short: B. Basilico, I.E. Palamà, S. D’Amone, C. Lauro, M. Rosito, M. Grieco, P.
Ratano, F. Cordella, C. Sanchini, S. Di Angelantonio, D. Ragozzino, M. Cascione,
G. Gigli, B. Cortese, Frontiers in Oncology 12 (2022).
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