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Ertürk, A.

Deep 3D histology powered by tissue clearing, omics and AI.

Nat. Methods 21, 1153-1165 (2024)
Verlagsversion DOI PMC
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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
To comprehensively understand tissue and organism physiology and pathophysiology, it is essential to create complete three-dimensional (3D) cellular maps. These maps require structural data, such as the 3D configuration and positioning of tissues and cells, and molecular data on the constitution of each cell, spanning from the DNA sequence to protein expression. While single-cell transcriptomics is illuminating the cellular and molecular diversity across species and tissues, the 3D spatial context of these molecular data is often overlooked. Here, I discuss emerging 3D tissue histology techniques that add the missing third spatial dimension to biomedical research. Through innovations in tissue-clearing chemistry, labeling and volumetric imaging that enhance 3D reconstructions and their synergy with molecular techniques, these technologies will provide detailed blueprints of entire organs or organisms at the cellular level. Machine learning, especially deep learning, will be essential for extracting meaningful insights from the vast data. Further development of integrated structural, molecular and computational methods will unlock the full potential of next-generation 3D histology.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Common Coordinate Framework; Light-sheet Microscopy; Whole-body; Cancer Metastasis; Intact-tissue; Resolution; Expression; Proteomics
Sprache englisch
Veröffentlichungsjahr 2024
HGF-Berichtsjahr 2024
ISSN (print) / ISBN 1548-7091
e-ISSN 1548-7105
Zeitschrift Nature Methods
Quellenangaben Band: 21, Heft: 7, Seiten: 1153-1165 Artikelnummer: , Supplement: ,
Verlag Nature Publishing Group
Verlagsort New York, NY
Begutachtungsstatus Peer reviewed
Institut(e) Institute for Tissue Engineering and Regenerative Medicine (ITERM)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-505800-001
Förderungen Nomis Heart Atlas Project Grant (Nomis Foundation)
European Research Council
Deutsche Forschungsgemeinschaft (German Research Foundation)
Vascular Dementia Research Foundation
DOI 10.1038/s41592-024-02327-1
WOS ID 001271440000004
Scopus ID 85198399691
PubMed ID 38997593
Erfassungsdatum 2024-07-15
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