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Cl quant software

Manufactured by Nikon
Sourced in United States

CL-Quant software is a tool developed by Nikon for analysis and quantification of microscope images. It provides functionalities for image processing, measurement, and data analysis to support research and laboratory workflows.

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10 protocols using cl quant software

1

Automated Imaging and Survival Analysis

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After transfection, the plate was inserted into BioStation CT (Nikon) which consists of cell incubator and automated imaging system. Neurons which express red fluorescence in six technical replicates were automatically imaged with 10 × objective lens every 12 h for 12 days. In each well, 4 × 4 tiled images were captured. Individual neurons were tracked by monitoring red fluorescence with the CL-Quant software (Nikon) and automated algorithm developed by Nikon. The risk of neuronal death was determined over time, and Cox proportional hazard analysis was used to estimate cumulative risk of death, or hazard ratio (HR). An open-source R package (https://cran.rproject.org/web/packages/survival/index.html) was used to perform statistical analysis and to generate Forest plot.
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2

Analyzing Proliferation and Apoptosis of DK-MG and iNSc Cells

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The proliferation ratio of DK-MG sublines (also with exogenous expression of EGFRvIII) was analyzed according to in vitro real-time observations in BioStation CT (Nikon, Tokyo, Japan) for 60 h in different cell culture conditions (serum free or 10% FBS media). Briefly, the cells were seeded onto 6-well plates in the amount of 40,000 cells per well and left to adhere for 24 h. After that, plates were placed in BioStation CT and photos were taken every 6 h. Simultaneously, an apoptosis analysis was conducted by adding CellEventTM Caspase-3/7 Green Ready ProbesTM Reagent (Thermo Fisher, Waltham, MA, USA) to the same wells and performing the observation under green fluorescent light for 96 h. The number of viable cells was calculated using CL Quant software (Nikon) from 5 visual fields. According to tools described above, the influences of 1–10 ng/mL TGFβ1 (Merck Millipore, Burlington, MA, USA), TGFβ2 (Sigma–Aldrich, St. Louis, MI, USA), TGFβ3 (Thermo Fisher Scientific, Waltham, MA, USA), and EGF (20 ng/mL, Peprotech, Waltham, MA, USA) on the proliferation ratio and apoptosis were analyzed on different cell lines: DK-MG sublines, NIH/3T3 and induced neural stem cells (iNSc). Erlotinib (10 µM, Molekula) and DMSO (vehicle, Serva) were used as controls.
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3

Cell Viability Monitoring with 5-FU

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Cells (5 × 104) were seeded in a 12-well plate and treated with 5-FU and DMSO. Cell behavior was then monitored with a BioStation CT system (Nikon) under the following conditions: picture position of tiling, 3 × 3; × 10 magnification, ch2 (Ex/Em 438/483), 800 ms of exposure time and 240 luminance; scheduling 0, 12, 36, and 60 hours. Data trimming was performed with CL-Quant software (Nikon).
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4

Automated Image-Based Cell Morphology Analysis

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All images were processed and quantified using CL-Quant software (Nikon Corporation) as previously described with some modifications [19] (link), [22] . Five original filter processes were designed: (1) background adjustment, (2) enhancement of texture, (3) cell recognition, (4) noise removal, and (5) filling the blank regions in cell objects (Fig. S1). After recognizing the cellular areas through image processing, cell numbers were measured as recognized objects. Therefore, the cell growth ratio in this study was calculated using the following formula: Cell growth ratio = object number in Time 22/object number at time 1. For morphological profiling, 14 parameters (Table S2) were measured from each recognized cellular object and their statistical profiles were calculated by collecting all measured parameter profiles from 1000 to 3000 cells in the tiling image per well. The morphological parameters were summarized as the statistical values average and standard deviation. Therefore, each condition (= 1 well) was represented by a total of 28 parameters (= 14 parameters × (mean/standard deviation)). The practical morphological parameters used for further analysis are illustrated in Figs. S2–S4.
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5

Cell Migration Dynamics Analysis

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SOX10-NL positive (and NGFR-positive) and SOX10-NL negative (and NGFR-negative) cells were sorted and seeded onto fibronectin-coated tissue culture dishes for 24 hours. After cells were attached, time-lapse phase contrast images (magnification 10x, 5x5 tiles) were taken at 10 min intervals for 24 hours using BioStation CT (Nikon) at 37°C with 5% CO2. Cell migration rate was measured by tracking analysis using CL-Quant software (Nikon) for initial 12 hours with time-lapse images.
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6

Quantitative Analysis of Colony Morphology

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In Exp. 1 and Exp. 2, images were processed by MetaMorph. In Exp. 1 and Exp. 2, images were preprocessed that were binarized successive segment of the 20 pixel under 89 brightness value by the original program written in C language. After this process, images were processed through “Close filter”, “binarization filter”, and “Close-Open filter” (MetaMorph) for all field of images. In Exp. 3, imaged were binarized the colony area (MetaMorph) which was segmented manually by regions tool (MetaMorph). All colonies recognized in each image were measured with 9 morphology parameters (Supplementary information Fig. S2). The 9 parameters were selected from 44 morphology parameters in MetaMorph to escape from multicollinearity. Moreover, 9 parameters were chosen because most of them were related to the morphological characteristic features which related to the conventionally described irregular colony morphology. For quantification of immunohistochemical staining result (SSEA4 and TRA-1-60), fluorescent images were quantified by CL-Quant software (Nikon Corp.). Stained colonies in the images were recognized by soft-matching algorithm following the manufactures' protocol, and the intensity of each colony was measured, and calculated as “total intensity/total pixel area in a colony”.
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7

High-Throughput Live-Cell Imaging of Motor Neurons

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Dissociated MNs were plated in complete MN media at a density of 50, 25, and 12.5 K cells/well in the inner 60 wells of borate/poly-ornithine/laminin/fibronectin coated 96-well plates (Greiner). Outer wells were filled with water to avoid evaporation effects. A total of 3 days after plating, 3/4 of the media was removed and replaced with fresh complete MN media. A total of 6 days after plating, and before treatment, the MN culture plate was entered into the Nikon BioStation CT for an initial image acquisition. A 10x objective was used to acquire phase images across the plate with a 4 × 4 stitched tiling capture area equivalent to 3.08 mm × 3.08 mm per well. After an initial image acquisition, the plate was removed, and MN culture media was replaced with stressor media as indicated in ER stressor assays methods section. The plate was then returned to the Nikon BioStation CT for image acquisition every 6 h for 48 h. Final images were then saved as time-lapse video files using CL-Quant software (Nikon) and FIJI/ImageJ was used to select and crop a region of interest for representative video files.
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8

Noninvasive Cell Growth Analysis

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Noninvasive cell growth
and morphology analyses of live cells were performed using 10×
and 20× phase contrast objectives in a BioStation CT using the
automatic Z-focus.40 After attachment,
BEAS-2B cells were treated with Puff EC fluids (0.1–10%) or
with WS-23 (0.045–4.5 mg/mL) solutions dissolved in cell culture
medium. Images were taken every 2 h for 48 h to collect time-lapse
data for analysis. Evaluation of BEAS-2B growth and morphology was
compared in control and treated groups using Nikon CL Quant software
(Melville, NY).40 −42 (link) Data from the treated groups were normalized to untreated
controls.
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9

Automated Imaging of Tracked Neurons

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After transfection, the plate was inserted into BioStation CT (Nikon) which consists of a cell incubator and automated imaging system. Six technical replicates (wells) of neurons were automatically imaged with the 10x objective lens every 12 h for 14 consecutive days. In each well, 4 × 4 tiled images were captured. Individual neurons were tracked by monitoring red fluorescence with the CL-Quant software (Nikon) and Algorithm 3 developed by Nikon. A cell ID number was given to each cell body and tracked during the imaging period.
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10

Quantitative Image Analysis Workflow

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All images were processed and quantitated using the CL-Quant software (Nikon Corporation). Five original filter processes were designed: (1) background adjustment, (2) cell recognition, (3) noise removal, (4) filling in blank regions in cell objects, and (5) removal of incomplete cells in peripheral areas of images (Suppl. Fig. S1). All acquired images were subjected to these processes. All processes were applied to both cell types (1321N1 and PC12), except that process 2 was customized for each cell line.
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