Cell refractive index is a key biophysical parameter, which has been extensively studied. It is correlated with other cell biophysical properties including mechanical, electrical and optical properties, and not only represents the intracellular mass and concentration of a cell, but also provides important insight for various biological models. Measurement techniques developed earlier only measure the effective refractive index of a cell or a cell suspension, providing only limited information on cell refractive index and hence hindering its in-depth analysis and correlation. Recently, the emergence of microfluidic, photonic and imaging technologies has enabled the manipulation of a single cell and the 3D refractive index of a single cell down to sub-micron resolution, providing powerful tools to study cells based on refractive index. In this review, we provide an overview of cell refractive index models and measurement techniques including microfluidic chip-based techniques for the last 50 years, present the applications and significance of cell refractive index in cell biology, hematology, and pathology, and discuss future research trends in the field, including 3D imaging methods, integration with microfluidics and potential applications in new and breakthrough research areas.

In this paper, for the first time, an on-chip optofluidic imaging system is innovated to measure the biophysical signatures of single waterborne bacteria, including both their refractive indices and morphologies (size and shape), based on immersion refractometry. The key features of the proposed optofluidic imaging platform include (1) multiple sites for single-bacterium trapping, which enable parallel measurements to achieve higher throughput, and (2) a chaotic micromixer, which enables efficient refractive index variation of the surrounding medium. In the experiments, the distinctive refractive index of Echerichia coli, Shigella flexneri and Vibrio cholera are measured with a high precision of 5 × 10(-3) RIU. The developed optofluidic imaging system has high potential not only for building up a database of biophysical signatures of waterborne bacteria, but also for developing single-bacterium detection in treated water that is in real-time, label-free and low cost.

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