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Automatic quantification of mitochondrial fragmentation from two-photon microscope images of mouse brain tissue

Tutkimustuotosvertaisarvioitu

Standard

Automatic quantification of mitochondrial fragmentation from two-photon microscope images of mouse brain tissue. / Lihavainen, E.; Kislin, M.; Toptunov, D.; Khiroug, L.; S. Ribeiro, A.

julkaisussa: Journal of Microscopy: Oxford, Vuosikerta 206, Nro 3, 2015, s. 338–351.

Tutkimustuotosvertaisarvioitu

Harvard

Lihavainen, E, Kislin, M, Toptunov, D, Khiroug, L & S. Ribeiro, A 2015, 'Automatic quantification of mitochondrial fragmentation from two-photon microscope images of mouse brain tissue', Journal of Microscopy: Oxford, Vuosikerta. 206, Nro 3, Sivut 338–351. https://doi.org/10.1111/jmi.12301

APA

Lihavainen, E., Kislin, M., Toptunov, D., Khiroug, L., & S. Ribeiro, A. (2015). Automatic quantification of mitochondrial fragmentation from two-photon microscope images of mouse brain tissue. Journal of Microscopy: Oxford, 206(3), 338–351. https://doi.org/10.1111/jmi.12301

Vancouver

Author

Lihavainen, E. ; Kislin, M. ; Toptunov, D. ; Khiroug, L. ; S. Ribeiro, A. / Automatic quantification of mitochondrial fragmentation from two-photon microscope images of mouse brain tissue. Julkaisussa: Journal of Microscopy: Oxford. 2015 ; Vuosikerta 206, Nro 3. Sivut 338–351.

Bibtex - Lataa

@article{06f085078104424b82b75742842ad8ec,
title = "Automatic quantification of mitochondrial fragmentation from two-photon microscope images of mouse brain tissue",
abstract = "The morphology of mitochondria can inform about their functional state and, thus, about cell vitality. For example, fragmentation of the mitochondrial network is associated with many diseases. Recent advances in neuronal imaging have enabled the observation of mitochondria in live brains for long periods of time, enabling the study of their dynamics in animal models of diseases. To aid these studies, we developed an automatic method, based on supervised learning, for quantifying the degree of mitochondrial fragmentation in tissue images acquired via two-photon microscopy from transgenic mice, which exclusively express Enhanced cyan fluorescent protein (ECFP) under Thy1 promoter, targeted to the mitochondrial matrix in subpopulations of neurons. We tested the method on images prior to and after cardiac arrest, and found it to be sensitive to significant changes in mitochondrial morphology because of the arrest. We conclude that the method is useful in detecting morphological abnormalities in mitochondria and, likely, in other subcellular structures as well.",
keywords = "Beta regression, Image analysis, Intravital imaging, Mitochondrial fragmentation, Mitochondrial morphology, Two-photon microscopy",
author = "E. Lihavainen and M. Kislin and D. Toptunov and L. Khiroug and {S. Ribeiro}, A.",
year = "2015",
doi = "10.1111/jmi.12301",
language = "English",
volume = "206",
pages = "338–351",
journal = "Journal of Microscopy: Oxford",
issn = "0022-2720",
publisher = "Wiley",
number = "3",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Automatic quantification of mitochondrial fragmentation from two-photon microscope images of mouse brain tissue

AU - Lihavainen, E.

AU - Kislin, M.

AU - Toptunov, D.

AU - Khiroug, L.

AU - S. Ribeiro, A.

PY - 2015

Y1 - 2015

N2 - The morphology of mitochondria can inform about their functional state and, thus, about cell vitality. For example, fragmentation of the mitochondrial network is associated with many diseases. Recent advances in neuronal imaging have enabled the observation of mitochondria in live brains for long periods of time, enabling the study of their dynamics in animal models of diseases. To aid these studies, we developed an automatic method, based on supervised learning, for quantifying the degree of mitochondrial fragmentation in tissue images acquired via two-photon microscopy from transgenic mice, which exclusively express Enhanced cyan fluorescent protein (ECFP) under Thy1 promoter, targeted to the mitochondrial matrix in subpopulations of neurons. We tested the method on images prior to and after cardiac arrest, and found it to be sensitive to significant changes in mitochondrial morphology because of the arrest. We conclude that the method is useful in detecting morphological abnormalities in mitochondria and, likely, in other subcellular structures as well.

AB - The morphology of mitochondria can inform about their functional state and, thus, about cell vitality. For example, fragmentation of the mitochondrial network is associated with many diseases. Recent advances in neuronal imaging have enabled the observation of mitochondria in live brains for long periods of time, enabling the study of their dynamics in animal models of diseases. To aid these studies, we developed an automatic method, based on supervised learning, for quantifying the degree of mitochondrial fragmentation in tissue images acquired via two-photon microscopy from transgenic mice, which exclusively express Enhanced cyan fluorescent protein (ECFP) under Thy1 promoter, targeted to the mitochondrial matrix in subpopulations of neurons. We tested the method on images prior to and after cardiac arrest, and found it to be sensitive to significant changes in mitochondrial morphology because of the arrest. We conclude that the method is useful in detecting morphological abnormalities in mitochondria and, likely, in other subcellular structures as well.

KW - Beta regression

KW - Image analysis

KW - Intravital imaging

KW - Mitochondrial fragmentation

KW - Mitochondrial morphology

KW - Two-photon microscopy

U2 - 10.1111/jmi.12301

DO - 10.1111/jmi.12301

M3 - Article

VL - 206

SP - 338

EP - 351

JO - Journal of Microscopy: Oxford

JF - Journal of Microscopy: Oxford

SN - 0022-2720

IS - 3

ER -