Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 Infection
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 unvaccina...
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MDPI AG
2023-02-01
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| Online Access: | https://www.mdpi.com/2076-2615/13/5/830 |
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| author | Dávid G. Horváth Zsolt Abonyi-Tóth Márton Papp Attila Marcell Szász Till Rümenapf Christian Knecht Heinrich Kreutzmann Andrea Ladinig Gyula Balka |
| author_facet | Dávid G. Horváth Zsolt Abonyi-Tóth Márton Papp Attila Marcell Szász Till Rümenapf Christian Knecht Heinrich Kreutzmann Andrea Ladinig Gyula Balka |
| author_sort | Dávid G. Horváth |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T07:33:15Z |
| format | Article |
| id | doaj.art-ba2b3c9433cc498e9bb2496bd161e901 |
| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-03-11T07:33:15Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj.art-ba2b3c9433cc498e9bb2496bd161e9012023-11-17T07:12:57ZengMDPI AGAnimals2076-26152023-02-0113583010.3390/ani13050830Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 InfectionDávid G. Horváth0Zsolt Abonyi-Tóth1Márton Papp2Attila Marcell Szász3Till Rümenapf4Christian Knecht5Heinrich Kreutzmann6Andrea Ladinig7Gyula Balka8Department of Pathology, University of Veterinary Medicine, István u. 2, 1078 Budapest, HungaryDepartment of Biostatistics, University of Veterinary Medicine, István u. 2, 1078 Budapest, HungaryCentre for Bioinformatics, University of Veterinary Medicine, István u. 2, 1078 Budapest, HungaryDepartment of Internal Medicine and Oncology, Semmelweis University, Korányi Sándor u. 2/a, 1083 Budapest, HungaryInstitute of Virology, Department of Pathobiology, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210 Vienna, AustriaUniversity Clinic for Swine, Department for Farm Animals and Veterinary Public Health, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210 Vienna, AustriaUniversity Clinic for Swine, Department for Farm Animals and Veterinary Public Health, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210 Vienna, AustriaUniversity Clinic for Swine, Department for Farm Animals and Veterinary Public Health, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210 Vienna, AustriaDepartment of Pathology, University of Veterinary Medicine, István u. 2, 1078 Budapest, HungaryReproductive 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.https://www.mdpi.com/2076-2615/13/5/830CD163digital image analysisendometriuminflammatoryPRRSVQuPath |
| spellingShingle | Dávid G. Horváth Zsolt Abonyi-Tóth Márton Papp Attila Marcell Szász Till Rümenapf Christian Knecht Heinrich Kreutzmann Andrea Ladinig Gyula Balka Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 Infection Animals CD163 digital image analysis endometrium inflammatory PRRSV QuPath |
| title | Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 Infection |
| title_full | Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 Infection |
| title_fullStr | Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 Infection |
| title_full_unstemmed | Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 Infection |
| title_short | Quantitative Analysis of Inflammatory Uterine Lesions of Pregnant Gilts with Digital Image Analysis Following Experimental PRRSV-1 Infection |
| title_sort | quantitative analysis of inflammatory uterine lesions of pregnant gilts with digital image analysis following experimental prrsv 1 infection |
| topic | CD163 digital image analysis endometrium inflammatory PRRSV QuPath |
| url | https://www.mdpi.com/2076-2615/13/5/830 |
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