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Review

New Possibilities for Evaluating the Development of Age-Related Pathologies Using the Dynamical Network Biomarkers Theory

by
Kazutaka Akagi
1,*,
Keiichi Koizumi
1,2,
Makoto Kadowaki
1,
Isao Kitajima
1 and
Shigeru Saito
1
1
Research Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, Japan
2
Division of Presymptomatic Disease, Institute of Natural Medicine, University of Toyama, Toyama 930-0194, Japan
*
Author to whom correspondence should be addressed.
Cells 2023, 12(18), 2297; https://doi.org/10.3390/cells12182297
Submission received: 20 August 2023 / Revised: 12 September 2023 / Accepted: 15 September 2023 / Published: 17 September 2023
(This article belongs to the Special Issue The Role of Cellular Senescence in Health, Disease, and Aging)
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Abstract

Aging is the slowest process in a living organism. During this process, mortality rate increases exponentially due to the accumulation of damage at the cellular level. Cellular senescence is a well-established hallmark of aging, as well as a promising target for preventing aging and age-related diseases. However, mapping the senescent cells in tissues is extremely challenging, as their low abundance, lack of specific markers, and variability arise from heterogeneity. Hence, methodologies for identifying or predicting the development of senescent cells are necessary for achieving healthy aging. A new wave of bioinformatic methodologies based on mathematics/physics theories have been proposed to be applied to aging biology, which is altering the way we approach our understand of aging. Here, we discuss the dynamical network biomarkers (DNB) theory, which allows for the prediction of state transition in complex systems such as living organisms, as well as usage of Raman spectroscopy that offers a non-invasive and label-free imaging, and provide a perspective on potential applications for the study of aging.
Keywords: dynamical network biomarkers theory; Raman spectroscopy; aging; resilience dynamical network biomarkers theory; Raman spectroscopy; aging; resilience
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MDPI and ACS Style

Akagi, K.; Koizumi, K.; Kadowaki, M.; Kitajima, I.; Saito, S. New Possibilities for Evaluating the Development of Age-Related Pathologies Using the Dynamical Network Biomarkers Theory. Cells 2023, 12, 2297. https://doi.org/10.3390/cells12182297

AMA Style

Akagi K, Koizumi K, Kadowaki M, Kitajima I, Saito S. New Possibilities for Evaluating the Development of Age-Related Pathologies Using the Dynamical Network Biomarkers Theory. Cells. 2023; 12(18):2297. https://doi.org/10.3390/cells12182297

Chicago/Turabian Style

Akagi, Kazutaka, Keiichi Koizumi, Makoto Kadowaki, Isao Kitajima, and Shigeru Saito. 2023. "New Possibilities for Evaluating the Development of Age-Related Pathologies Using the Dynamical Network Biomarkers Theory" Cells 12, no. 18: 2297. https://doi.org/10.3390/cells12182297

APA Style

Akagi, K., Koizumi, K., Kadowaki, M., Kitajima, I., & Saito, S. (2023). New Possibilities for Evaluating the Development of Age-Related Pathologies Using the Dynamical Network Biomarkers Theory. Cells, 12(18), 2297. https://doi.org/10.3390/cells12182297

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