Glutathione (GSH), the most abundant nonprotein thiol found in living organisms, are involved in the etiology and progression of many human diseases including cancer. So, monitoring changes of cellular GSH levels has an important guiding significance. To date, however, majority of probes can only qualitatively detect GSH in living cells. Herein, with coumarin as the read-out fluorophore and Michael addition as the sensing mechanism, six fluorescent probes were designed and synthesized. Among them, RP-2 exhibited a reversible and extremely fast response toward GSH (half time: ∼3 s), which endowed RP-2 the capacity of real-time imaging. Among the reversible probes based on Michael addition, RP-2 had both the largest forward and reverse rate constants thus far. The reaction between RP-2 and GSH was studied in detail by density functional theory and fluorescence spectroscopy. Real-time imaging of GSH levels in living cells was achieved with a temporal resolution of seconds. To simplify the processing of images, a program was developed and validated. RP-2 was expected to serve as a new fluorescent imaging tool to understand the function of intracellular GSH in the future.
Sequential DNA detection is a fundamental issue for elucidating the interactive relationships among complex gene systems. Here, a sequential logic DNA gate was achieved by utilizing the two-ring DNA structure, with the ability to recognize "before" and "after" triggering sequences of DNA signals. By taking advantage of a "loop-open" mechanism, separations of two-ring DNAs were controlled. Three triggering pathways with different sequential DNA treatments were distinguished by comparing fluorescent outputs. Programmed nanoparticle arrangement guided by "interlocked" two-ring DNA was also constructed to demonstrate the achievement of designed nanostrucutres. Such sequential logic DNA operation may guide future molecular sensors to monitor more complex gene network in biological systems.
Interior design is the core step of interior decoration, and it determines the overall layout and style of furniture. Traditional interior design is usually laborious and time‐consuming work carried out by professional designers and cannot always meet clients' personalized requirements. With the development of computer graphics, computer vision and machine learning, computer scientists have carried out much fruitful research work in computer‐aided personalized interior design (PID). In general, personalization research in interior design mainly focuses on furniture selection and floor plan preparation. In terms of the former, personalized furniture selection is achieved by selecting furniture that matches the resident's preference and style, while the latter allows the resident to personalize their floor plan design and planning. Finally, the automatic furniture layout task generates a stylistically matched and functionally complete furniture layout result based on the selected furniture and prepared floor plan. Therefore, the main challenge for PID is meeting residents' personalized requirements in terms of both furniture and floor plans. This paper answers the above question by reviewing recent progress in five separate but correlated areas, including furniture style analysis, furniture compatibility prediction, floor plan design, floor plan analysis and automatic furniture layout. For each topic, we review representative methods and compare and discuss their strengths and shortcomings. In addition, we collect and summarize public datasets related to PID and finally discuss its future research directions.
Herein, we have developed a rapid and enzyme-free nucleic acid amplification detection method that combined the exponential self-assembly of four DNA hairpins and the FRET pair Cy3 and Cy5. This strategy was very ingenious and rapid, and could detect nucleic acids at concentrations as low as 10 pM in 15 min in biological fluids.
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