Establishment of an AI-supported scoring system for neuroglial cells
The feasibility of a computer-aided scoring system based on artificial intelligence to detect and classify morphological changes in neuroglial cells was assessed in this study. The system was applied to hippocampal organotypic slice cultures (OHC) from 5 to 7 day-old wild-type and TNF-overexpressing...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-06-01
|
| Series: | Frontiers in Cellular Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fncel.2025.1584422/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849423118322368512 |
|---|---|
| author | Annika Bitsch Manfred Henrich Svenja Susanne Erika Körber Kathrin Büttner Christiane Herden Christiane Herden |
| author_facet | Annika Bitsch Manfred Henrich Svenja Susanne Erika Körber Kathrin Büttner Christiane Herden Christiane Herden |
| author_sort | Annika Bitsch |
| collection | DOAJ |
| description | The feasibility of a computer-aided scoring system based on artificial intelligence to detect and classify morphological changes in neuroglial cells was assessed in this study. The system was applied to hippocampal organotypic slice cultures (OHC) from 5 to 7 day-old wild-type and TNF-overexpressing mice in order to analyze effects of a proinflammtory stimulus such as TNF. The area fraction of cells, cell number, number of cell processes and area of the cell nucleus were used as target variables. Immunfluorescence labeling was used to visualize neuronal processes (anti-neurofilaments), microglia (anti-Iba1) and astrocytes (anti-GFAP). The analytic system was able to reliably detect differences in the applied target variables such as the increase in neuronal processes over a period of 14 days in both mouse lines. The number of microglial projections and the microglial cell number provided reliable information about activation level. In addition, the area of microglial cell nuclei was suitable for classification of microglia into activity levels. This scoring system was supported by description of morphology, using the automatically created cell masks. Therefore, this scoring system is suitable for morphological description and linking the morphology with the respective cellular activity level employing analyses of large data sets in a short time. |
| format | Article |
| id | doaj-art-4d87da8b21644c059f86fda9211173a2 |
| institution | Kabale University |
| issn | 1662-5102 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cellular Neuroscience |
| spelling | doaj-art-4d87da8b21644c059f86fda9211173a22025-08-20T03:30:45ZengFrontiers Media S.A.Frontiers in Cellular Neuroscience1662-51022025-06-011910.3389/fncel.2025.15844221584422Establishment of an AI-supported scoring system for neuroglial cellsAnnika Bitsch0Manfred Henrich1Svenja Susanne Erika Körber2Kathrin Büttner3Christiane Herden4Christiane Herden5Institute of Veterinary Pathology, Justus Liebig University Giessen, Gießen, GermanyInstitute of Veterinary Pathology, Justus Liebig University Giessen, Gießen, GermanyInstitute of Veterinary Pathology, Justus Liebig University Giessen, Gießen, GermanyBiomathematics and Data Processing Group of the Department of Veterinary Medicine, Justus Liebig University Giessen, Gießen, GermanyInstitute of Veterinary Pathology, Justus Liebig University Giessen, Gießen, GermanyCenter of Mind, Brain and Behaviour, Justus Liebig University Giessen, Gießen, GermanyThe feasibility of a computer-aided scoring system based on artificial intelligence to detect and classify morphological changes in neuroglial cells was assessed in this study. The system was applied to hippocampal organotypic slice cultures (OHC) from 5 to 7 day-old wild-type and TNF-overexpressing mice in order to analyze effects of a proinflammtory stimulus such as TNF. The area fraction of cells, cell number, number of cell processes and area of the cell nucleus were used as target variables. Immunfluorescence labeling was used to visualize neuronal processes (anti-neurofilaments), microglia (anti-Iba1) and astrocytes (anti-GFAP). The analytic system was able to reliably detect differences in the applied target variables such as the increase in neuronal processes over a period of 14 days in both mouse lines. The number of microglial projections and the microglial cell number provided reliable information about activation level. In addition, the area of microglial cell nuclei was suitable for classification of microglia into activity levels. This scoring system was supported by description of morphology, using the automatically created cell masks. Therefore, this scoring system is suitable for morphological description and linking the morphology with the respective cellular activity level employing analyses of large data sets in a short time.https://www.frontiersin.org/articles/10.3389/fncel.2025.1584422/fullneuroglial cellsneuronal projectionsmicrogliaastrocytesartificial intelligence based scoring systemsmorphological complexity |
| spellingShingle | Annika Bitsch Manfred Henrich Svenja Susanne Erika Körber Kathrin Büttner Christiane Herden Christiane Herden Establishment of an AI-supported scoring system for neuroglial cells Frontiers in Cellular Neuroscience neuroglial cells neuronal projections microglia astrocytes artificial intelligence based scoring systems morphological complexity |
| title | Establishment of an AI-supported scoring system for neuroglial cells |
| title_full | Establishment of an AI-supported scoring system for neuroglial cells |
| title_fullStr | Establishment of an AI-supported scoring system for neuroglial cells |
| title_full_unstemmed | Establishment of an AI-supported scoring system for neuroglial cells |
| title_short | Establishment of an AI-supported scoring system for neuroglial cells |
| title_sort | establishment of an ai supported scoring system for neuroglial cells |
| topic | neuroglial cells neuronal projections microglia astrocytes artificial intelligence based scoring systems morphological complexity |
| url | https://www.frontiersin.org/articles/10.3389/fncel.2025.1584422/full |
| work_keys_str_mv | AT annikabitsch establishmentofanaisupportedscoringsystemforneuroglialcells AT manfredhenrich establishmentofanaisupportedscoringsystemforneuroglialcells AT svenjasusanneerikakorber establishmentofanaisupportedscoringsystemforneuroglialcells AT kathrinbuttner establishmentofanaisupportedscoringsystemforneuroglialcells AT christianeherden establishmentofanaisupportedscoringsystemforneuroglialcells AT christianeherden establishmentofanaisupportedscoringsystemforneuroglialcells |