Automated quantification of avian influenza virus antigen in different organs.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
16 Apr 2024
16 Apr 2024
Historique:
received:
10
08
2023
accepted:
08
04
2024
medline:
17
4
2024
pubmed:
17
4
2024
entrez:
16
4
2024
Statut:
epublish
Résumé
As immunohistochemistry is valuable for determining tissue and cell tropism of avian influenza viruses (AIV), but time-consuming, an artificial intelligence-based workflow was developed to automate the AIV antigen quantification. Organ samples from experimental AIV infections including brain, heart, lung and spleen on one slide, and liver and kidney on another slide were stained for influenza A-matrixprotein and analyzed with QuPath: Random trees algorithms were trained to identify the organs on each slide, followed by threshold-based quantification of the immunoreactive area. The algorithms were trained and tested on two different slide sets, then retrained on both and validated on a third set. Except for the kidney, the best algorithms for organ selection correctly identified the largest proportion of the organ area. For most organs, the immunoreactive area assessed following organ selection was significantly and positively correlated to a manually assessed semiquantitative score. In the validation set, intravenously infected chickens showed a generally higher percentage of immunoreactive area than chickens infected oculonasally. Variability between the slide sets and a similar tissue texture of some organs limited the ability of the algorithms to select certain organs. Generally, suitable correlations of the immunoreactivity data results were achieved, facilitating high-throughput analysis of AIV tissue tropism.
Identifiants
pubmed: 38627481
doi: 10.1038/s41598-024-59239-5
pii: 10.1038/s41598-024-59239-5
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
8766Subventions
Organisme : EC | Directorate-General for Employment, Social Affairs and Inclusion | European Social Fund (Fondo Social Europeo)
ID : 100380880
Informations de copyright
© 2024. The Author(s).
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