PuSH - Publikationsserver des Helmholtz Zentrums München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Yang, L. ; Liu, Q. ; Kumar, P. ; Sengupta, A. ; Farnoud, A. ; Shen, R. ; Trofimova, D.* ; Ziegler, S.* ; Davoudi, N.* ; Doryab, A. ; Yildirim, A.Ö. ; Diefenbacher, M. ; Schiller, H. ; Razansky, D.* ; Piraud, M. ; Burgstaller, G. ; Kreyling, W.G. ; Isensee, F.* ; Rehberg, M. ; Stöger, T. ; Schmid, O.

LungVis 1.0: An automatic AI-powered 3D imaging ecosystem unveils spatial profiling of nanoparticle delivery and acinar migration of lung macrophages.

Nat. Commun. 15:10138 (2024)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Targeted (nano-)drug delivery is essential for treating respiratory diseases, which are often confined to distinct lung regions. However, spatio-temporal profiling of drugs or nanoparticles (NPs) and their interactions with lung macrophages remains unresolved. Here, we present LungVis 1.0, an AI-powered imaging ecosystem that integrates light sheet fluorescence microscopy with deep learning-based image analysis pipelines to map NP deposition and dosage holistically and quantitatively across bronchial and alveolar (acinar) regions in murine lungs for widely-used bulk-liquid and aerosol-based delivery methods. We demonstrate that bulk-liquid delivery results in patchy NP distribution with elevated bronchial doses, whereas aerosols achieve uniform deposition reaching distal alveoli. Furthermore, we reveal that lung tissue-resident macrophages (TRMs) are dynamic, actively patrolling and redistributing NPs within alveoli, contesting the conventional paradigm of TRMs as static entities. LungVis 1.0 provides an advanced framework for exploring pulmonary delivery dynamics and deepening insights into TRM-mediated lung immunity.
Impact Factor
Scopus SNIP
Altmetric
14.700
0.000
Tags
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern

Zusatzinfos bearbeiten
Eigene Tags bearbeiten
Privat
Eigene Anmerkung bearbeiten
Privat
Auf Publikationslisten für
Homepage nicht anzeigen
Als besondere Publikation
markieren
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter In-vivo; Particle-size; Translocation; Deposition; Visualization; Nanomaterials; Persistence; Clearance; System
Sprache englisch
Veröffentlichungsjahr 2024
HGF-Berichtsjahr 2024
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Zeitschrift Nature Communications
Quellenangaben Band: 15, Heft: 1, Seiten: , Artikelnummer: 10138 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Lung Health and Immunity (LHI)
Helmholtz Artifical Intelligence Cooperation Unit (HAICU)
Institute of Epidemiology (EPI)
German Center for Lung Research (DZL)
POF Topic(s) 30202 - Environmental Health
30205 - Bioengineering and Digital Health
80000 - German Center for Lung Research
Forschungsfeld(er) Lung Research
Enabling and Novel Technologies
Genetics and Epidemiology
PSP-Element(e) G-505000-008
G-505000-001
G-501600-001
G-530001-001
G-505000-007
G-501694-001
G-501693-001
G-501600-014
G-504000-010
G-501800-810
Förderungen Helmholtz Incubator on Information and Data Science
Helmholtz Imaging
Helmholtz AI through a HGF research grant
EU
EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
DOI 10.1038/s41467-024-54267-1
WOS ID 001366217500024
Scopus ID 85210528194
PubMed ID 39604430
Erfassungsdatum 2024-12-05
[➜Korrektur melden]