Ti2 e microscope
The Ti2-E microscope is a high-performance inverted microscope designed for a variety of laboratory applications. It features a stable and rigid frame, providing a stable platform for precise imaging and analysis. The Ti2-E is equipped with advanced optics and illumination systems, enabling clear and detailed observation of samples.
Lab products found in correlation
50 protocols using ti2 e microscope
Monitoring mast cell ROS and death
Sphere Formation Assay for Ovarian Cancer
Immunofluorescence Microscopy Procedure
Immunofluorescence Analysis of p65 and YAP
BMDMs in 6-well plates were incubated with anti-p65 antibody (1:500, 8242, Cell Signaling Technology) overnight at 4 °C. As secondary antibodies, Alexa 488 (Cell Signaling Technology) were added in well plates for 1h at room temperature, and then added Hoechst (TIANGEN) for 15 min in dark. These 6-well plates were visualized with a Nikon Ti2-E microscope (Nikon). Images were analyzed by Nikon NIS-Elements Br 3.0 software (Nikon). To quantify the nuclear translocation of p65, ten files from each group were analyzed for the p65 high positive in nuclei (%). The p65 high positive in the nuclei (%) was calculated (p65 high positive in the nuclei (%) = the number of p65 high positive in the nuclei ×100 / the number of total nuclei) 14 (link).
BMDMs on cell slides were incubated with anti-p65(1:500, 8242, Cell Signaling Technology) and anti-YAP (1:50, sc-101199, Santa Cruz) antibodies. As secondary antibodies, Alexa 594 and 488 (Cell Signaling Technology) were added for 1h at room temperature in dark, and then sections were sealed by fluorescent mounting medium with DAPI (ZSGB-BIO) in dark. These sections were visualized with a Nikon 80i microscope (Nikon). Images were analyzed with Nikon NIS-Elements Br 3.0 software (Nikon).
Co-Detection of Insulin Receptor and Keratin 5
Cyclic Immunofluorescence Imaging of FFPE TMA
Seventy five, 1000 × 1000 high quality regions were identified and extracted from the TMA images and saved as tiff images. Expert pathologists independently annotated these images. The annotations were done using Cellthon, a python based cell annotation graphical user interface (GUI) we created using Tkinter toolkit55 . Together these 75 images and their cell and nucleus annotations comprise the GIT dataset.
Fluorescence Microscopy of Cellular Membranes
Spatial Transcriptomic Analysis of Amyloid-Beta
Time-Lapse Imaging of TGF-β-Induced Cellular Changes
Quantitative Analysis of Calcification in Cells
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