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Vs asw 2

Manufactured by Olympus

The VS-ASW 2.9 software is a product developed by Olympus. It is a software application designed to facilitate the analysis and processing of visual data.

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3 protocols using vs asw 2

1

Histopathological Evaluation of SARS-CoV-2 Lung Damage

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Histopathology was blindly interpreted by a board-certified veterinary pathologist. The H&E slides were evaluated for morphological evidence of inflammatory-mediated pathology in the lungs, and trachea, and the reduction or absence of pathological features was used as an indicator of protection against airborne SARS-CoV-2 exposure. Each hamster was assigned a score of 0–3 based on absent, mild, moderate, or severe manifestation, of pulmonary pathology including mural bronchial inflammation, neutrophilic bronchitis, consolidating pneumonia, and interstitial alveolar thickening. The sum of all scores was then provided for each hamster. H&E-stained lung tissue slides were scanned at 20 Å~magnification using an Olympus VS120 microscope, Hamamatsu ORCA-R2 camera, and Olympus VS-ASW 2.9 software at the Experimental Pathology Facility at Colorado State University.
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2

Multimodal Visualization of Immune Markers

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Bright-field microscopy and H&E staining were used for morphological examination of Tissue-Tek-processed cryosections. Stained sections were embedded in glycerin jelly and visualized using the Olympus BX61VS microscope and VS-ASW 2.9 software. Confocal microscopy was used for fluorescence detection of CD4 and CD8 expression compared with DAPI counterstaining of nuclear DNA in tissue after fixation of 10-μm cryosections with acetone at -20°C for 10 minutes. The same staining strategy as described in section 2.8 was used, but the incubation and washing steps were extended. Processing also included initial blocking with 10% normal porcine serum. Cryosections were embedded in Mowiol medium, visualized using the Leica TCS SP5/LAS AF microsystem, and finally analyzed using ImageJ software.
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3

Quantitative Lung Histopathology Analysis

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The extent of lesion burden was analyzed by lung histopathology and expressed as the proportion of lesion area over total lung area per stained tissue section. Stained slides were blinded and analyzed by a veterinary pathologist (Dr. Brendan Podell, Colorado State University). H&E-stained sections were scanned at 20X magnification using an Olympus VS120 microscope, Hamamatsu ORCA-R2 camera, and Olympus VS-ASW 2.9 software. Visiopharm software was used for image analysis. For each tissue section, a region of interest (ROI) was generated at low magnification with a custom tissue detecting algorithm using decision forest training and classification to differentiate tissue versus background based on color and area. Lesions were identified within tissue ROIs at high magnification with an additional custom-made algorithm using decision forest training and classification based on staining intensity, color normalization and deconvolution, area, and morphological features. Percent lesion calculations were integrated into the same algorithm and calculated from tissue area and lesion area as designated by the ROI and lesions detected. Lesion identification and quantification were then reviewed and edited by a pathologist as needed.
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