Title
Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 Infection
Language
English
Description (en)
Reproductive disorders caused by porcine reproductive and respiratory syndrome virus-1 are not yet fully characterized. We report QuPath-based digital image analysis to count inflammatory cells in 141 routinely, and 35 CD163 immunohistochemically stained endometrial slides of vaccinated or unvaccinated pregnant gilts inoculated with a high or low virulent PRRSV-1 strain. To illustrate the superior statistical feasibility of the numerical data determined by digital cell counting, we defined the association between the number of these cells and endometrial, placental, and fetal features. There was strong concordance between the two manual scorers. Distributions of total cell counts and endometrial and placental qPCR results differed significantly between examiner1's endometritis grades. Total counts' distribution differed significantly between groups, except for the two unvaccinated. Higher vasculitis scores were associated with higher endometritis scores, and higher total cell counts were expected with high vasculitis/endometritis scores. Cell number thresholds of endometritis grades were determined. A significant correlation between fetal weights and total counts was shown in unvaccinated groups, and a significant positive correlation was found between these counts and endometrial qPCR results. We revealed significant negative correlations between CD163+ counts and qPCR results of the unvaccinated group infected with the highly virulent strain. Digital image analysis was efficiently applied to assess endometrial inflammation objectively.
Keywords (en)
Pathology; Biomarkers; Insights; Strains; Type-1
DOI
10.3390/ani13050830
Author of the digital object
Dávid G  Horváth  (University of Veterinary Medicine, Budapest)
Gyula  Balka  (University of Veterinary Medicine, Budapest)
Andrea  Ladinig  (University of Veterinary Medicine, Vienna)
Heinrich  Kreutzmann  (University of Veterinary Medicine, Vienna)
Christian  Knecht  (University of Veterinary Medicine, Vienna)
Till  Rümenapf  (University of Veterinary Medicine, Vienna)
Attila Marcell  Szász  (Semmelweis University)
Zsolt  Abonyi-Tóth  (University of Veterinary Medicine, Budapest)
Márton  Papp  (University of Veterinary Medicine, Budapest)
Format
application/pdf
Size
5.3 MB
Licence Selected
CC BY 4.0 International
Type of publication
Article
Name of Publication (en)
Animals
Pages or Volume
18
Volume
13
Number
5
Publisher
MDPI
Publication Date
2023
Content
Details
Object type
PDFDocument
Format
application/pdf
Created
13.04.2023 03:24:55
This object is in collection
Metadata
Veterinärmedizinische Universität Wien (Vetmeduni) | Veterinärplatz 1 | 1210 Wien - Österreich | T +43 1 25077-0 | Web: vetmeduni.ac.at