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Biology subjects

Saimi, D.

Publications and source records attributed to Saimi, D..

2 recordsLinked to original sources

Ratio-preserving super-resolution FLIM for quantitative live-cell lifetime imaging

Super-resolution (SR) fluorescence lifetime imaging promises nanoscale maps of molecular environment and function, but photon-limited acquisition and computational reconstruction can distort lifetime estimates, particularly for ratio-derived frequency-domain measurements under SR conditions. Here we introduce structured-illumination frequency-domain FLIM (SIM-fdFLIM), an SR lifetime imaging platform that combines commercial dual-tap fdFLIM detection with ratio-preserving reconstruction. SIM-fdFLIM uses direct-current (DC)-stabilized lifetime estimation to improve reconstruction robustness under low signal-to-noise conditions, followed by ratio-domain integrated variational estimation (RIVE) to correct channel misregistration and suppress noise amplification after SR reconstruction. The method achieves ~100 nm spatial resolution in lifetime maps and enables live-cell imaging at 2.8 Hz over a 56 x 56 {micro}m2 field of view. Across representative fluorophore standards, RIVE reduces lifetime standard deviation by approximately threefold relative to non-RIVE SIM-fdFLIM while preserving mean lifetime agreement with calibrated widefield fdFLIM. In living cells, SIM-fdFLIM resolves mitochondrial cristae-scale lifetime heterogeneity, mitochondrion-to-mitochondrion functional dynamics, nanoscale lipid-environment variations and perturbation-sensitive organelle-contact signatures. These results establish SIM-fdFLIM as a ratio-preserving platform for quantitative SR lifetime imaging, extending live-cell FLIM into a regime that combines nanoscale spatial resolution, Hz-rate acquisition, and preserved lifetime fidelity.

bioengineering↗

Physics-Driven Zero-Shot Reconstruction of Isotropic 3D Fluorescence Microscopy under Undersampled Acquisition

Three-dimensional (3D) imaging represents the development of next generation of fluorescence microscopy. However, routine axial down-sampling makes isotropic resolution unrealistic. Here, we propose DeepUI, a physical zero-shot framework designed to achieve isotropic 3D fluorescence images from a low axial sampling rate. DeepUI fully leverages the intrinsic characteristics of 3D images through physics-guided degradation, which incorporates spatial-frequency joint learning to generate a scaled optical transfer function, combined with noise degradation and an up-sampling branch. Typically requiring just 5 minutes for training and 0.5 minutes for high-throughput and fast prediction, we demonstrate the superior performance of DeepUI to get isotropic results, and the exclusivity to axial down-sampling conditions, even in more challenging conditions, including defocused background, noise, and resolution blur.

bioinformatics↗