Near-Infrared Fluorescence Probe with a New Recognition Moiety for the Specific Detection of Cysteine to Study the Corresponding Physiological Processes in Cells, Zebrafish, and Arabidopsis thaliana.

Cysteine (Cys), as one of the biological thiols, is related to many physiological and pathological processes in humans and plants. Therefore, it is necessary to develop a sensitive and selective method for the detection and imaging of Cys in biological organisms. In this work, a novel near-infrared (NIR) fluorescent probe, Probe-Cys, was designed by connecting furancarbonyl, as a new recognition moiety, with Fluorophore-OH via the decomposition of IR-806. The use of the furan moiety is anticipated to produce more effective fluorescence quenching because of the electron-donating ability of the O atom. Probe-Cys has outstanding properties, such as a new recognition group, an emission wavelength in the infrared region at 710 nm, a linear range (0-100 µM), a low detection limit of 0.035 µM, good water solubility, excellent sensitivity, and selectivity without the interference of Hcy, GSH, and HS-. More importantly, Probe-Cys could achieve the detection of endogenous Cys by reacting with the stimulant 1,4-dimercaptothreitol (DTT) and the inhibitor N-ethylmaleimide (NEM) in HepG2 cells and zebrafish. Ultimately, it was successfully applied to obtain images of Arabidopsis thaliana, revealing that the content of Cys in the meristematic zone was higher than that in the elongation zone, which was the first time that the NIR fluorescence probe was used to obtain images of Cys in A. thaliana. The superior properties of the probe exhibit its great potential for use in biosystems to explore the physiological and pathological processes associated with Cys.

Single-Channel Blind Image Separation Based on Transformer-Guided GAN.

Blind source separation (BSS) has been a great challenge in the field of signal processing due to the unknown distribution of the source signal and the mixing matrix. Traditional methods based on statistics and information theory use prior information such as source distribution independence, non-Gaussianity, sparsity, etc. to solve this problem. Generative adversarial networks (GANs) learn source distributions through games without being constrained by statistical properties. However, the current blind image separation methods based on GANs ignores the reconstruction of the structure and details of the separated image, resulting in residual interference source information in the generated results. This paper proposes a Transformer-guided GAN guided by an attention mechanism. Through the adversarial training of the generator and the discriminator, U-shaped Network (UNet) is used to fuse the convolutional layer features to reconstruct the structure of the separated image, and Transformer is used to calculate the position attention and guide the detailed information. We validate our method with quantitative experiments, showing that it outperforms previous blind image separation algorithms in terms of PSNR and SSIM.

Rapid and visual evaluation the internal corruption of meat tissue by a designed near-infrared fluorescence probe with a broad pH response range.

Rapid and visual evaluation the internal corruption of meat tissue is closely related to public health. The pH change caused by glycolysis and amino acid decomposition is an important indicator of meat freshness. Herein, we designed a pH-responsive NIR fluorescent probe (Probe-OH) based on protonation/deprotonation for monitoring the internal corruption of meat tissue. Probe-OH was synthesized by a stable hemicyanine skeleton with phenolic hydroxyl group, which exhibited excellent performances such as high selectivity, high sensitivity, fast response time (60 s), a broad pH-responsive range of 4.0-10.0, and superior spatio-temporal sampling ability. In addition, we conducted a paper chip platform to measure pH value in different meat samples (pork and chicken), which is convenient to evaluate pH value of meat by observing the color changes of paper strips. Furthermore, in combination with the NIR advantages of fluorescence imaging, Probe-OH was successfully applied to assess the freshness of pork and chicken breasts, and the structural changes of muscle tissue can be clearly observed under confocal microscope. The results of Z-axis scanning showed that Probe-OH could penetrate into the interior to monitor the internal corruption of meat tissue, the fluorescence intensity changes with scanning height in the meat tissue section, and reaches its maximum at 50 µm. To the best of our knowledge, there have been no reports of fluorescence probe being used to image the inside of meat tissue section so far. It is expected that we can provide a new rapid, sensitive, near-infrared fluorescence method for assessment of the freshness in the internal organization of meat.