APPLICATION NOTES

COUNTING CELLS OF DIFFERENT TYPES IN A CO-CULTURE

Counting things is a typical task in cell-based assays. Various methods exist, depending on the setting; most are expensive, labor-intensive, and time-consuming.

Here, we demonstrate how image-based counting cells of different types in a co-culture can be made cheap fast and robust, and above-all, accessible to everyone, using dot-placing and automated image analysis and data management.

(fluorescent background image: Anne Carpenter and David Logan, licensed under CC BY 3.0 re-normalized, added indicators and text)

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LABEL-FREE QUANTIFICATION OF NEURITES

Characterizing the state of the neurite network in 2D cell culture offers a sensitive readout of potentially neurotoxic properties of novel drug substances. Together with the group of Stefan Schildknecht from Hochschule Albstadt-Sigmaringen, we illustrate a label-free method to quantify the presence of neurites.

• Sensitive quantification of subtle phenotypes
• No prior knowledge in data science necessary

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LABEL-FREE CELL DETECTION OF LIPID INCLUSIONS

Using the example of lipid inclusions in HepG2 cells from the group of Stefan Schildknecht from Hochschule Albstadt-Sigmaringen, we demonstrate how the VAIDR system can turn a human observation into a quantitative, robust analytical method.

• Robust quantification of effects that are difficult to tackle with traditional image analysis
• Works without the need for fluorescence

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LABEL-FREE CELL COUNTING IN iPSC PRODUCTION

Accurate label-free quantification of cell growth over time is crucial for successful maintenance, expansion and quality control of iPSCs. In this Application Note, we show how this can be achieved in a simple and cost-effective manner by utilizing the AI-based analysis capabilities of the VAIDR-system.

• Less effort – cell counting integrated in expansion workflow
• Better quality control through unbiased AI-driven analysis
• Robust starting point for subsequent differentiation

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VAIDR ANALYZING NEURONAL PRECURSOR CELLS ON EXTRACELLULAR MATRIX

AI-ASSISTED IMAGING ACCELERATES SELECTION OF OPTIMAL CELL CULTURE MATRICES

Selecting an optimal extracellular matrix (ECM) product is essential for successful culture of primary cells, stem cells and their derivatives. Together with our partners at denovoMATRIX, we demonstrate how quick and objective ECM-selection can be achieved by combining the VAIDR and screenMATRIX technologies.

• Robust quantification of growth behavior
• Detection of desirable/undesirable phenotypes
• Label-free, cost-effective workflow

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AI-ASSISTED IMAGING MAKES CELL HEALTH QUANTIFICATION MORE SENSITIVE AND EFFICIENT

In cell cultivation for in-vitro experiments or for cell therapies, consistent cell health is a critical success factor. It is therefore desirable to establish a tight control on cell health during production. Together with our partners from acCELLerate GmbH, we demonstrate how a sensitive, label-free cell health quantification method can be easily established for live THP-1 cells using the VAIDR system. In contrast to established methods for cell viability measurement, we show that even subtle, early signs of diminishing cell health can be quantified reliably, opening the path towards overall improved performance in manufacture of high-value cell products.

• Non-invasive
• Cost-efficient
• Quantitative & robust

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