Spinal CX3CL1/CX3CR1 may not directly participate in the development of morphine tolerance in rats

CX3CL1 (fractalkine), the sole member of chemokine CX3C family, is implicated in inflammatory and neuropathic pain via activating its receptor CX3CR1 on neural cells in spinal cord. However, it has not been fully elucidated whether CX3CL1 or CX3CR1 contributes to the development of morphine tolerance. In this study, we found that chronic morphine exposure did not alter the expressions of CX3CL1 and CX3CR1 in spinal cord. And neither exogenous CX3CL1 nor CX3CR1 inhibitor could affect the development of morphine tolerance. The cellular localizations of spinal CX3CL1 and CX3CR1 changed from neuron and microglia, respectively, to all the neural cells during the development of morphine tolerance. A microarray profiling revealed that 15 members of chemokine family excluding CX3CL1 and CX3CR1 were up-regulated in morphine-treated rats. Our study provides evidence that spinal CX3CL1 and CX3CR1 may not be involved in the development of morphine tolerance directly

Glutathione-Stabilized Copper Nanoclusters as a Switch-Off Fluorescent Sensor for Sensing of Quercetin in Tea Samples

Quercetin, a natural polyphenolic flavonoid with antioxidant and anti-allergic properties, is extensively found in foods and holds significant importance for human health. In this study, a simple switch-off fluorescent sensor based on copper nanoclusters (Cu NCs) was proposed for the sensitive determination of quercetin. Glutathione acted as the reducing and protective agent in the synthesized process of Cu NCs via a facile, green one-pot method. As anticipated, the glutathione-capped Cu NCs (GSH-Cu NCs) exhibited favorable water solubility and ultrasmall size. The fluorescence property of GSH-Cu NCs was further enhanced with Al3+ ion through the aggregation-induced emission effect. When quercetin was present in the sample solution, the system exhibited effective fluorescence quenching, which was attributed to the internal filter effect. The GSH-Cu NCs/Al3+-based fluorescent sensor showed a good linear relationship to quercetin in the concentration range from 0.1 to 60 μM. A detection limit of 24 nM was obtained. Moreover, the constructed sensor was employed for the successful determination of quercetin in tea samples

In situ synthesis of a Prussian blue nanoparticles/graphdiyne oxide nanocomposite with high stability and electrocatalytic activity

Herein we report an in situ synthesis of Prussian blue nanoparticles (PB) on graphdiyne oxide (GDYO) which acts as an excellent substrate. The hybrid was then used as an electrode with high electrochemical catalytic activity towards hydrogen peroxide. The PB/GDYO hybrid was prepared by simply adding FeCl3 to GDYO solution, and then mixing with Fe(CN)63− at room temperature. The GDYO was able to anchor PB in nanoparticle form and stabilize it in neutral and weakly basic solutions. The hybrid was investigated by transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy and electrochemical measurements. The PB/GDYO hybrid showed high electrochemical catalytic activity and stability for the detection of hydrogen peroxide. Keywords: Prussian blue, Graphdiyne oxide, In-situ synthesis, Electrocatalytic activity, Hydrogen peroxid

A Maritime Traffic Network Mining Method Based on Massive Trajectory Data

Intelligent ships are the future direction of maritime transportation. Route design and route planning of intelligent ships require high-precision, real-time maritime traffic network information, which changes dynamically as the traffic environment changes. At present, there is a lack of high-precision and accurate information extraction methods for maritime traffic networks. Based on the massive trajectory data of vessels, the adaptive waypoint extraction model (ANPG) is proposed to extract the critical waypoints on the traffic network, and the improved kernel density estimation method (KDE-T) is constructed to mine the spatial–temporal characteristics of marine lanes. Then, an automatic traffic network generation model (NNCM), based on the pix2pix network, is put forward to reconstruct the maritime traffic network. NNCM has been tested on the historical trajectory data of Humen waters and Dongping waters in China, the experimental results show that the NNCM model improves the extraction accuracy by 13% and 33% compared to the geometric analysis method and density clustering method. It is of great significance to improve the navigation accuracy of intelligent ships. This method can also provide important technical support for waterway design and monitoring and maritime traffic supervision.</jats:p