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An Image-based fluorescence cell analyzer

ADAMII™ LS is a benchtop fluorescent intensity based cell analyzer providing versatile assays and high accurate results (similarity to flow cytometer).

KEY FEATURES & BENEFITS

- Bright field and 3 fluorescence channels (GFP/RFP/DAPI)

- Fluorescence level / Transfection efficiency / Protein expression

- Cell cycle

- Apoptosis

- Total cell counting / Viability / Cell size

- Dot plot

- 21 CFR part 11 compliance for GMP

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ADAMII™ LS,

An image-based fluorescence cell analyzer providing high-quality cell analysis with reliable results

Advantage #1

High-quality cell analysis

ADAMII^TMLS provides high reliability and utilization in cell analysis with multiple frame photographing technique. The slides used for ADAMII^TMLS are available in 1 channel and 2 channel. 1ch slide chamber holds a total of 75 frames, allowing a wide range of measurement for high accuracy.

Advantage #2

Fluorescence analyzer for various samples

- Mammalian cell containing fluorescent protein (GFP, RFP)

- Transfection efficiency

- Cell cycle with PI staining

- Apoptosis

Advantage #3

Fluorescence staining for better performance

- By counting only nucleus cells (Iymphocyte) through fluorescence staining, total cell counting becomes easier and more precise.

- ADAMII^TMLS uses Acridine Orange (AO) and DAPI reagent, which are cell permeable dye and impermeable DNA dye, respectively, for higher accuracy. Thus, it allows user to measure various reagents and cell samples.

Advantage #4

Easy and simple use

ADAMII^TMLS is designed for easy and simple process. It is an user-independent analyzer that does not require any expert to perform. ADAMII^TMLS is a maintenance-free and benchtop-sized instrument for user convenience.

Reference paper of using ADAMII™ LS

Title

Development of new TAK-285 derivatives as potent EGFR/HER2 inhibitors possessing antiproliferative effects against 22RV1 and PC3 prostate carcinoma cell lines. Journal of Enzyme Inhibition and Medicinal Chemistry, 38(1), 2202358, 2023.

Link: https://doi.org/10.1080/14756366.2023.2202358

Machine Learning-Based Approach to Developing Potent EGFR Inhibitors for Breast Cancer─ Design, Synthesis, and In Vitro Evaluation. ACS omega, 2023

Link: https://doi.org/10.1021/acsomega.3c02799