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Tma software

Manufactured by Olympus
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Sourced in United Kingdom

The TMA software is a digital pathology tool designed for the analysis and quantification of tissue microarray (TMA) data. It provides a streamlined workflow for managing and analyzing TMA samples, enabling researchers to extract valuable insights from their tissue samples.

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Lab products found in correlation

Dotslide system, by Olympus (1 mentions)

2 protocols using tma software

1

Glioma Immunostaining Quantification

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The TMAs were scanned using the Olympus dotSlide system (×20 objective) and TMA software (Olympus, UK). Image analysis of the immunostaining was performed with ImageJ (Wayne Rasband, National Institutes of Health (NIH), Bethesda, MD, version 1.47g) to obtain protein load defined as the percentage area of the image stained. The use of protein load as the standard quantification measure for all immunostaining in human glioma samples provided consistency within the measurement allowing fair comparisons between sample groups.
Noorani I., Petty G., Grundy P.L., Sharpe G., Willaime‐Morawek S., Harris S., Thomas G.J., Nicoll J.A, & Boche D. (2015). Novel association between microglia and stem cells in human gliomas: A contributor to tumour proliferation?. The Journal of Pathology: Clinical Research, 1(2), 67-75.
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2

Immunostaining Quantification in Glioma

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The TMAs were scanned at magnification × 20 using the Olympus dotSlide system and TMA software (Olympus, UK). Digital image analysis of the immunostaining was performed with Fiji/ImageJ (Wayne Rasband, National Institutes of Health, Bethesda, MD, USA, version 1.49u44 (link)) to obtain protein load. For each antibody, a threshold was determined to quantify the percentage image area immunostained by the antibody and expressed as protein load (%). The use of protein load as the standard quantification measure for all immunostaining in human glioma samples provided consistency within the measurement allowing fair comparisons between regions.
Noorani I., Sidlauskas K., Pellow S., Savage R., Norman J.L., Chatelet D.S., Fabian M., Grundy P., Ching J., Nicoll J.A, & Boche D. (2023). Clinical impact of anti-inflammatory microglia and macrophage phenotypes at glioblastoma margins. Brain Communications, 5(3), fcad176.
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