Abstract
Background: In the neurosciences, the physical disector method represents an established quantitative stereological method for unbiased sampling and counting of cells in histological tissue sections of known thickness. Physical disector analyses are conventionally performed using plastic-embedded tissue samples, because plasticembedding causes a comparably low and definable shrinkage of the embedded tissue, and the thickness of thin plastic sections can be determined adequately. However, immunohistochemistry protocols often don't work satisfactorily in sections of plastic-embedded tissue. New method: Here, a new methodological approach is presented, allowing for physical disector analyses of immunohistochemically labeled cells in paraffin sections. The embedding-related tissue shrinkage is standardized by using defined tissue sample volumes and paraffin volumes, and the extent of tissue shrinkage can be determined accurately from the sample volumes prior to and after embedding. Co-embedding of polyethylene section thickness standards together with the tissue samples allows the precise determination of individual paraffin section thicknesses by spectral reflectance measurements. Results and comparison with existing method(s): The applicability of the new method is demonstrated by physical disector analysis of immunohistochemically identified somatotroph cells in paraffin sections of porcine pituitary gland tissue. With consideration of individual shrinkage factors and section thicknesses, the cell numbers and mean volumes estimated in paraffin disector sections do not significantly differ from the results obtained by analyses of plastic-embedded pituitary tissue samples of the identical animals (2.4% average difference). Conclusions: The featured method enables combination of paraffin section immunohistochemistry and physical disector analyses for unbiased quantitative stereological analyses of different cell types.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Tiermedizin > Zentrum für Klinische Tiermedizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 0165-0270 |
Sprache: | Englisch |
Dokumenten ID: | 99020 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023, 15:30 |
Letzte Änderungen: | 08. Apr. 2024, 13:56 |