ReviewNature reviews. Chemistry2026
Molecular rotor-based probes for protein monitoring in biomedical research.
Review in Nature reviews. Chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
8 authors.
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Abstract
As the fundamental executors of biological function, proteins are frequently dysregulated or differentially expressed in disease states, making them valuable biomarkers and/or therapeutic targets. Conventional approaches to monitoring the presence and activity of these proteins - including enzyme-linked immunosorbent assay, western blotting and mass spectrometry - have limited ability to provide real-time information on living cells. Fluorescence imaging overcomes these limitations by enabling selective, non-invasive and dynamic protein analysis. Molecular rotor fluorophores offer unique advantages owing to their high sensitivity to microenvironmental changes and tunable photophysical properties. Notably, these molecular rotor scaffolds can be functionalized into targeting probes that become highly emissive upon binding to specific proteins via the restriction of intramolecular rotation. Here, we introduce molecular rotor-based probes and outline their design principles and detection mechanisms. We highlight their applications in disease diagnosis and biological research, and we discuss the current challenges and prospects for clinical translation.
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Registered trials
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.