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In cell developer v1.9.2 analysis software

Manufactured by GE Healthcare

The IN Cell Developer V1.9.2 is a software application designed for image analysis. It provides tools for the processing and quantification of images captured using IN Cell Analyzer instruments.

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2 protocols using in cell developer v1.9.2 analysis software

1

High-throughput 3D Spheroid Imaging and Analysis

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PANC1 and SNC12 spheres were generated in 1536-well in black, clear bottom microtiter plates (catalog number 3836, Corning) as described above. Once spheres were formed, they were stained with Hoechst dye 33342 (Invitrogen, Carlsbad, CA, USA), at a concentration of 1:1000 and PI (Invitrogen) at a concentration of 1:500 and incubated for 2 h at room temperature. The spheres were then imaged with an IN Cell 2000 (GE Healthcare, Marlborough, MA, USA) using a 10 × 0.45 NA lens. Spheres were imaged with three channels; brightfield, DAPI (350/50 excitation, 455/50 emission), and PI (Texas Red; 579/34 excitation, 624/40 emission) at 50, 100, and 25 ms exposures, respectively. Images were analyzed using GE's IN Cell Developer V1.9.2 analysis software (GE Healthcare). Briefly, the DAPI channel was used to identify two classes of spheroids (large and small) using an intensity segmentation algorithm (objects greater than 255 RFU). Large spheroids were categorized as having an area of 200 μm2 or more, whereas small spheroids and individual cells were categorized as having an area of <200 μm2. PI objects were also identified with intensity segmentation (>215 RFU) and size criteria (>6 μm2). PI-positive objects in within DAPI spheroids were calculated using standard Developer target linking.
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2

High-throughput Neurite Outgrowth Quantification

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NSCs were seeded in 384-well plates under the same condition as described above. After 4 week differentiation, neuronal cells were stained with anti-β-III Tubulin antibody and Hoechst 33342 nuclear dye as described in the immunofluorescence staining section. Fluorescence imaging was performed in the IN Cell 2200 imaging system with a 40× objective lens using standard FITC and DAPI filter sets. Images were analyzed using INCell Developer V1.9.2 analysis software (GE Healthcare). Briefly, the DAPI channel was used to identify nuclei using an intensity segmentation algorithm (objects greater than 650 RFU ranging in size from 5 to 75µm). β-III Tubulin (FITC) stained neurites were also identified by intensity segmentation (greater than 1150 RFU) with a post processing sieve to remove debris objects less than 2µm in size. Mean neurite length, measured in microns, was averaged to the number of nuclei per image.
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