The synthesis, structures and properties of five Cd(II) coordination networks: [Cd(bpdc5, are reported. Complexes 1 and 2 show the pcu and fsd topologies with 2-and 3-fold interpenetrating modes, respectively, and complex 4 exhibits a 2-fold 2D A 2D parallel interpenetration network containing a rotaxane-like motif. Complex 3 is a 1D A 2D polycatenane derived from the helical channels, and the 2D layers are further mutually interdigitated, whereas complex 5 is a 2D A 3D polycatenane based on the undulating sql sheets. These five complexes show different thermal and luminescent properties and the CO 2 capture is preferable to N 2 in the gas sorption for the desolvated product of 1.
Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termed flimGANE (fluorescence lifetime imaging based on Generative Adversarial Network Estimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is up to 2,800 times faster than the gold standard time-domain maximum likelihood estimation (TD_MLE) and that flimGANE provides a more accurate analysis of low-photon-count histograms in barcode identification, cellular structure visualization, Förster resonance energy transfer characterization, and metabolic state analysis in live cells. With its advantages in speed and reliability, flimGANE is particularly useful in fundamental biological research and clinical applications, where high-speed analysis is critical.
In this work, a deep learning-based method, STED-flimGANE, is introduced to achieve enhanced STED imaging resolution under a low STED-beam power and photon-starved conditions.
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