ReviewInflammation and regeneration2025
Single-pixel imaging flow cytometry for biomedical research.
Review in Inflammation and regeneration, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
High-throughput single-cell analysis and screening have become essential tools in life science research. Imaging flow cytometry, in particular, enables large-scale image-based profiling of heterogeneous cell populations, allowing statistical analysis of cellular morphology, subcellular features, and functional responses. However, its analytical capability is often limited by the use of conventional two-dimensional (2D) image sensors. In this review, we highlight recent advances in single-pixel imaging flow cytometry, which replaces 2D image sensors with single-pixel photodetectors. This approach offers advantages in sensitivity, flexibility, and speed in imaging system design and has been implemented in various optical configurations to achieve high-throughput single-cell imaging. We first introduce its key techniques, then outline representative biomedical applications, including cancer and COVID-19 research, and finally discuss current limitations and prospects for future developments. Single-pixel imaging flow cytometry is expected to serve as a versatile platform supporting both basic and translational studies in diverse biomedical applications.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.