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A main determinant of the spatial resolution of live-cell super-resolution (SR) microscopes is the maximum photon flux that can be collected. To further increase the effective resolution for a given photon flux, we take advantage of a priori knowledge about the sparsity and continuity of biological structures to develop a deconvolution algorithm that increases the resolution of SR microscopes nearly twofold. Our method, sparse structured illumination microscopy (Sparse-SIM), achieves ~60-nm resolution at a frame rate of up to 564 Hz, allowing it to resolve intricate structures, including small vesicular fusion pores, ring-shaped nuclear pores formed by nucleoporins and relative movements of inner and outer mitochondrial membranes in live cells. Sparse deconvolution can also be used to increase the three-dimensional resolution of spinning-disc confocal-based SIM, even at low signal-to-noise ratios, which allows four-color, three-dimensional live-cell SR imaging at ~90-nm resolution. Overall, sparse deconvolution will be useful to increase the spatiotemporal resolution of live-cell fluorescence microscopy. The resolution of fluorescence microscopy is increased by incorporating prior information into deconvolution algorithms.

The spatial resolutions of live-cell super-resolution microscopes are limited by the maximum collected photon flux. Taking advantage of a priori knowledge of the sparsity and continuity of biological structures, we develop a deconvolution algorithm that further extends the resolution of super-resolution microscopes under the same photon budgets by nearly twofold. As a result, sparse structured illumination microscopy (Sparse-SIM) achieves ~60 nm resolution at a 564 Hz frame rate, allowing it to resolve intricate structural intermediates, including small vesicular fusion pores, ring-shaped nuclear pores formed by different nucleoporins, and relative movements between the inner and outer membranes of mitochondria in live cells. Likewise, sparse deconvolution can be used to increase the three-dimensional resolution and contrast of spinning-disc confocal-based SIM (SD-SIM), and operates under conditions with the insufficient signal-to-noise-ratio, all of which allows routine four-color, three-dimensional, ~90 nm resolution live-cell super-resolution imaging. Overall, sparse deconvolution may be a general tool to push the spatiotemporal resolution limits of live-cell fluorescence microscopy.

With the growth of the Internet and the advancements in modern communication systems, sending data over the Internet or other media is now a commonplace practice. Consequently, it has become an important issue to secure the confidentiality and integrity of data because the data are sent via the Internet as a primary method of communication. This paper proposes a steganographic method based on the vector quantization coding compression algorithm with elastic indicators, which also incorporates a keystream to enhance security. Our experimental results have shown that the proposed method performs more effectively compared to the method proposed by Lee et al. in 2013.

Membrane voltage is an important biophysical signal that underlies intercellular electrical communications. A fluorescent voltage indicator is presented that enables the investigation of electrical signaling at high spatial resolution. The method is built upon the site-specific modification of microbial rhodopsin proteins with organic fluorophores, resulting in a hybrid indicator scaffold that is one of the most sensitive and fastest orange-colored voltage indicators developed to date. We applied this technique to optically map electrical connectivity in cultured cells, which revealed gap junction-mediated long-range coupling that spanned over hundreds of micrometers.

With the continued expansion of the Internet and increased means of communication, it is inevitable that we send data via the Internet or other such media. The important issue of maintaining the confidentiality and integrity of such data when using the Internet as a primary mode of communication also continues to grow in scale. In this paper, we therefore propose an information-hiding method based on the vector quantization (VQ) compression algorithm with elastic indicators; further, we present our design for a key stream to enhance security. Our experimental results have shown that our proposed method performs better as compared to the method introduced by Lee et al. in 2013.