Cell proliferation is a measurement of cell growth and defined as the balance between cell divisions and cell loss through cell death.
Cell proliferation assays are widely applied in biological sciences to understand the growth pattern of cultured cells and to assess the in vitro safety and efficacy of drugs over time.
Kinetic Assessment of Cell Proliferation
Traditional methods are end-point assays that often assess cell proliferation indirectly, or based on cell confluence measurements only. HoloMonitor® offers a convenient assay that automatically presents kinetic cell proliferation data. Cell proliferation is directly determined; both by cell counting and by confluence assessment.
Automatic cell proliferation presentation
Result presentation (left) and video showing frequent cell divisions.
All data can easily be exported to Excel by only a click, see green arrow in the image above. Example showing Excel export outcome.
Key References Cell Proliferation
General Cytotoxicity and Its Application in Nanomaterial AnalysisIntechOpen (2018)Read more
Review describing and comparing various assays used to study biocompatibility and cytotoxicity of nanomaterials. Holographic phase imaging is pointed out as an excellent tool for cell morphometric characterisation and cell migration studies, and the authors conclude that the interest in the use of DH microscopy in research is constantly increasing.
Label-free High Temporal Resolution Assessment of Cell Proliferation Using Digital Holographic MicroscopyCytometry Part A (2017)Read more
The authors have developed a robust and label-free kinetic cell proliferation assay with high temporal resolution for adherent cells using HoloMonitor M4. Only two image processing settings were adjusted between cell lines, making the assay practical, user friendly, and free of user bias. In the recorded time-lapse image sequences, individual cells were automatically identified to provide detailed growth curves and growth rate data of cell number, confluence, and average cell volume. The results demonstrate how these parameters facilitate a deeper understanding of cell processes than what is achievable with current single-parameter and end-point methods.