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Super-resolution imaging has rapidly emerged as an optical microscopy technique, offering advantages of high optical resolution over the past two decades; achieving improved imaging resolution requires significant efforts in developing super-resolution imaging agents characterized by high brightness, high contrast and high sensitivity to fluorescence switching. Apart from technical requirements in optical systems and algorithms, super-resolution imaging relies on fluorescent dyes with special photophysical or photochemical properties. The concept of aggregation-induced emission (AIE) was proposed in 2001, coinciding with unprecedented advancements and innovations in super-resolution imaging technology. AIE probes offer many advantages, including high brightness in the aggregated state, low background signal, a larger Stokes shift, ultra-high photostability, and excellent biocompatibility, making them highly promising for applications in super-resolution imaging. In this review, we summarize the progress in implementation methods and provide insights into the mechanism of AIE-based super-resolution imaging, including fluorescence switching resulting from photochemically-converted aggregationinduced emission, electrostatically controlled aggregation-induced emission and specific bindingregulated aggregation-induced emission. Particularly, the aggregation-induced emission principle has been proposed to achieve spontaneous fluorescence switching, expanding the selection and application scenarios of super-resolution imaging probes. By combining the aggregation-induced emission principle and specific molecular design, we offer some comprehensive insights to facilitate the applications of AIEgens (AIE-active molecules) in super-resolution imaging. [ABSTRACT FROM AUTHOR]

Bone marrow mesenchymal stem cells (BMSCs) are considered the most important seed cells in bone tissue engineering. The present study aimed to investigate the potential of rabbit BMSCs in osteogenesis after the transfection of human BMP-2 and EGFP recombinant adenovirus. Rabbit BMSCs were isolated and the surface stem cell makers, including CD29, CD44 and CD45 were detected by flow cytometry. The expression of BMP-2 mRNA and protein in BMSCs were detected by reverse transcription-quantitative polymerase chain reaction and western blot analysis, respectively. After an induction with osteogenic medium, the alkaline phosphatase (ALK) activity at 7 days, the type I collagen at 14 days, and the calcium nodules at 21 days were performed using an ALK activity kit, immunohistochemical staining and alizarin red S staining, respectively. The expression levels of proteins related to the Wnt signaling pathway were detected by western blot analysis. The positive rates of CD29, CD44 and CD45 were 62.92±1.99, 93.55±0.99 and 0.21±0.12%. The expression of BMP-2 mRNA and protein was significantly upregulated in Ad-BMP-2/EGFP transfected BMSCs. Furthermore, Ad-BMP-2/EGFP induced ALP activity, promoted the production of type I collagen and calcium nodule formation in rabbit BMSCs. The levels of β-catenin, cyclin D1, Runx2 and c-myc were upregulated in Ad-hBMP-2/EGFP transfected BMSCs, while the level of GSK3β was significantly decreased. Results also indicated that the overexpression of BMP-2 by Ad-hBMP-2/EGFP enhanced the osteogenic differentiation ability of cultured rabbit BMSCs via stimulating the Wnt signaling pathway with the accumulation of β-catenin and suppression of GSK3β. The Ad-hBMP-2/EGFP transfected rabbit BMSCs are expected to be a good seed cell in bone tissue engineering. [ABSTRACT FROM AUTHOR]

Compound-Gaussian model with the inverse Gaussian texture (IG–CG) is recognized to be one of the best models to characterize high-resolution sea clutter at low grazing angles. The model parameters are often estimated by the second- and fourth-order amplitude sample moments, which are of low precision and easily interfered by outliers of high power such as returns of ships and reefs and sea spikes. In this letter, an iterative maximum likelihood (ML) estimator and an outlier-robust bipercentile estimator are proposed and are compared with the moment-based estimator. The experimental results show that the iterative ML estimator is better in performance than the moment-based estimator when samples are without outliers and the bipercentile estimator behaves better when samples contain a small number of outliers. [ABSTRACT FROM PUBLISHER]