001     284075
005     20260122140425.0
024 7 _ |a 10.1002/smtd.202401050
|2 doi
024 7 _ |a pmid:40509616
|2 pmid
037 _ _ |a DZNE-2026-00083
041 _ _ |a English
082 _ _ |a 620
100 1 _ |a Rogler, Teresa S
|0 0009-0008-5943-407X
|b 0
245 _ _ |a 3D Quantification of Viral Transduction Efficiency in Living Human Retinal Organoids.
260 _ _ |a Weinheim
|c 2025
|b WILEY-VCH Verlag GmbH & Co. KGaA
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1769086917_9322
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a The development of therapeutics builds on testing their efficiency in vitro. To optimize gene therapies, for example, fluorescent reporters expressed by treated cells are typically utilized as readouts. Traditionally, their global fluorescence signal has been used as an estimate of transduction efficiency. However, analysis in individual cells within a living 3D tissue remains a challenge. Readout on a single-cell level can be realized via fluorescence-based flow cytometry at the cost of tissue dissociation and loss of spatial information. Complementary, spatial information is accessible via immunofluorescence of fixed samples. Both approaches impede time-dependent studies on the delivery of the vector to the cells. Here, quantitative 3D characterization of viral transduction efficiencies in living retinal organoids is introduced. The approach combines quantification of gene delivery efficiency in space and time, leveraging human retinal organoids, engineered adeno-associated virus (AAV) vectors, confocal live imaging, and deep learning-based image segmentation. The integration of these tools in an organoid imaging and analysis pipeline allows quantitative testing of future treatments and other gene delivery methods. It has the potential to guide the development of therapies in biomedical applications.
536 _ _ |a 353 - Clinical and Health Care Research (POF4-353)
|0 G:(DE-HGF)POF4-353
|c POF4-353
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
650 _ 7 |a 3D segmentation
|2 Other
650 _ 7 |a adeno‐associated virus
|2 Other
650 _ 7 |a gene therapy
|2 Other
650 _ 7 |a retinal organoids
|2 Other
650 _ 7 |a transduction efficiency
|2 Other
700 1 _ |a Salbaum, Katja A
|b 1
700 1 _ |a Brinkop, Achim T
|0 0000-0002-1682-4720
|b 2
700 1 _ |a Sonntag, Selina M
|0 0000-0003-3326-1285
|b 3
700 1 _ |a James, Rebecca
|b 4
700 1 _ |a Shelton, Elijah R
|0 0000-0001-9311-1567
|b 5
700 1 _ |a Thielen, Alina
|b 6
700 1 _ |a Rose, Roland
|b 7
700 1 _ |a Babutzka, Sabrina
|0 P:(DE-HGF)0
|b 8
700 1 _ |a Klopstock, Thomas
|0 P:(DE-2719)2810704
|b 9
700 1 _ |a Michalakis, Stylianos
|0 0000-0001-5092-9238
|b 10
700 1 _ |a Serwane, Friedhelm
|0 0000-0001-6943-8244
|b 11
773 _ _ |a 10.1002/smtd.202401050
|g p. 2401050
|0 PERI:(DE-600)2884448-8
|n 2
|p 2401050
|t Small Methods
|v 10
|y 2025
|x 2366-9608
856 4 _ |u https://pub.dzne.de/record/284075/files/DZNE-2026-00083.pdf
|y Restricted
856 4 _ |u https://pub.dzne.de/record/284075/files/DZNE-2026-00083.pdf?subformat=pdfa
|x pdfa
|y Restricted
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 8
|6 P:(DE-HGF)0
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 9
|6 P:(DE-2719)2810704
913 1 _ |a DE-HGF
|b Gesundheit
|l Neurodegenerative Diseases
|1 G:(DE-HGF)POF4-350
|0 G:(DE-HGF)POF4-353
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Clinical and Health Care Research
|x 0
915 _ _ |a DEAL Wiley
|0 StatID:(DE-HGF)3001
|2 StatID
|d 2024-12-18
|w ger
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b SMALL METHODS : 2022
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2024-12-18
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2024-12-18
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-18
915 _ _ |a IF >= 10
|0 StatID:(DE-HGF)9910
|2 StatID
|b SMALL METHODS : 2022
|d 2024-12-18
920 1 _ |0 I:(DE-2719)1111015
|k Clinical Research (Munich)
|l Clinical Research (Munich)
|x 0
980 _ _ |a journal
980 _ _ |a EDITORS
980 _ _ |a VDBINPRINT
980 _ _ |a I:(DE-2719)1111015
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21