

A core‐shell‐shell Yb3⁺/Er3⁺ UCNP architecture is engineered to balance energy migration and back energy transfer, yielding more than a tenfold enhancement in single‐particle brightness. Leveraging these optimized probes, it achieves long‐term, high‐resolution single‐particle tracking in live neurons, uncovering coordinated transport mechanisms of motor proteins. Abstract Lanthanide‐doped upconversion nanoparticles (UCNPs) are promising bioimaging probes due to their exceptional photostability and minimal background interference. However, their limited single‐particle brightness has hindered broader applications. The study addresses this challenge by enhancing energy migration (EM) between sensitizer Yb3+ to improve energy transfer efficiency to emitter Er3+. Nanoparticles are designed with a sensitizer/emitter‐segregated core‐shell‐shell architecture (NaLu0.9Er0.1F4@NaYbF4@NaLuF4) to inhibit back energy transfer (BET) and then increased Yb3+ doping levels (NaLu0.9‐xYbxEr0.1F4@NaYbF4@NaLuF4) to enhance EM into the core. UCNPs with an alloy‐core of NaYb0.9Er0.1F4 exhibited the brightest upconversion luminescence, achieving over a tenfold enhancement compared to NaLu0.9Er0.1F4‐core counterparts, highlighting the importance of EM. Further optimization of the Yb3+/Er3+ ratio and inert shell thickness (NaLuF4) maximized single‐particle brightness. These optimized UCNPs enabled long‐term tracking of axonal transport in live dorsal root ganglion (DRG) neurons. Using a Bayesian Hidden Markov Model, it quantitatively characterized resolved heterogeneous motion states and annotated trajectories with local spatiotemporal dynamics of retrograde, anterograde, and diffusive motions. The analysis revealed a kinesin‐dynein coordination mechanism, where anterograde motion facilitates retrograde activation. It also examined the effects of inhibitors and stimulants on transport behavior. These findings establish upconversion single‐particle tracking (uSPT) as a powerful tool for long‐term, real‐time monitoring of neuronal activities. A core-shell-shell Yb 3 ⁺/Er 3 ⁺ UCNP architecture is engineered to balance energy migration and back energy transfer, yielding more than a tenfold enhancement in single-particle brightness. Leveraging these optimized probes, it achieves long-term, high-resolution single-particle tracking in live neurons, uncovering coordinated transport mechanisms of motor proteins. Abstract Lanthanide-doped upconversion nanoparticles (UCNPs) are promising bioimaging probes due to their exceptional photostability and minimal background interference. However, their limited single-particle brightness has hindered broader applications. The study addresses this challenge by enhancing energy migration (EM) between sensitizer Yb 3+ to improve energy transfer efficiency to emitter Er 3+. Nanoparticles are designed with a sensitizer/emitter-segregated core-shell-shell architecture (NaLu 0.9 Er 0.1 F 4 @NaYbF 4 @NaLuF 4 ) to inhibit back energy transfer (BET) and then increased Yb 3+ doping levels (NaLu 0.9-x Yb x Er 0.1 F 4 @NaYbF 4 @NaLuF 4 ) to enhance EM into the core. UCNPs with an alloy-core of NaYb 0.9 Er 0.1 F 4 exhibited the brightest upconversion luminescence, achieving over a tenfold enhancement compared to NaLu 0.9 Er 0.1 F 4 -core counterparts, highlighting the importance of EM. Further optimization of the Yb 3+ /Er 3+ ratio and inert shell thickness (NaLuF 4 ) maximized single-particle brightness. These optimized UCNPs enabled long-term tracking of axonal transport in live dorsal root ganglion (DRG) neurons. Using a Bayesian Hidden Markov Model, it quantitatively characterized resolved heterogeneous motion states and annotated trajectories with local spatiotemporal dynamics of retrograde, anterograde, and diffusive motions. The analysis revealed a kinesin-dynein coordination mechanism, where anterograde motion facilitates retrograde activation. It also examined the effects of inhibitors and stimulants on transport behavior. These findings establish upconversion single-particle tracking (uSPT) as a powerful tool for long-term, real-time monitoring of neuronal activities. Advanced Science, Volume 12, Issue 43, November 20, 2025.
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