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ID 69996
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Wang, Zheyi Department of Cardiovascular Physiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
Naruse, Keiji Department of Cardiovascular Physiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University ORCID Kaken ID publons researchmap
Takahashi, Ken Department of Cardiovascular Physiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University ORCID Kaken ID publons researchmap
Abstract
For more than a century, pathology has served as a cornerstone of modern medicine, relying primarily on static microscopic assessment of tissue morphology—such as H&E staining—which remains the “gold standard” for disease diagnosis. However, this conventional paradigm provides only a snapshot of disease states and often fails to capture their dynamic evolution and complex functional mechanisms. Moreover, animal models are constrained by marked interspecies differences, creating a persistent gap in translational research. To overcome these limitations, we propose the concept of New Pathophysiology, a research framework that transcends purely morphological descriptions and aims to resolve functional dynamics in real time. This approach integrates Organ-on-a-Chip (OOC) technology, multi-omics analyses, and artificial intelligence to reconstruct the entire course of disease initiation and to enable personalized medicine. In this review, we first outline the foundations and limitations of traditional pathology and animal models. We then systematically summarize more than one hundred existing OOC disease models across multiple organs—including the kidney, liver, and brain. Finally, we elaborate on how OOC technologies are reshaping the study of key pathological processes such as inflammation, metabolic dysregulation, and fibrosis by converting them into dynamic, mechanistic disease models, and we propose future perspectives in the field. This review adopts a relatively uncommon classification strategy based on pathological mechanisms (mechanism-based), rather than organ-based categorization, allowing readers to recognize shared principles underlying different diseases. Moreover, the focus of this work is not on emphasizing iteration or replacement of existing approaches, but on preserving past achievements from a historical perspective, with an emphasis on overcoming current limitations and enabling new advances.
Keywords
new pathophysiology
organ-on-a-chip/OOC
dynamic disease modeling
histopathology
large-model analysis
personalized medicine
Published Date
2026-01-21
Publication Title
Pathophysiology
Volume
volume33
Issue
issue1
Publisher
MDPI AG
Start Page
10
ISSN
1873-149X
Content Type
Journal Article
language
English
OAI-PMH Set
岡山大学
Copyright Holders
© 2026 by the authors.
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DOI
Related Url
isVersionOf https://doi.org/10.3390/pathophysiology33010010
License
https://creativecommons.org/licenses/by/4.0/
Citation
Wang, Z.; Naruse, K.; Takahashi, K. Bridging the Gap Between Static Histology and Dynamic Organ-on-a-Chip Models. Pathophysiology 2026, 33, 10. https://doi.org/10.3390/pathophysiology33010010