Regulating the Polypyrrole Ion-Selective Membrane and Au Solid Contact Layer to Improve the Performance of Nitrate All-Solid Ion-Selective Electrodes.

With polymerization duration and Au3+ concentration of the electrolyte regulated, a desirable nitrate-doped polypyrrole ion-selective membrane (PPy(NO3-)-ISM) and Au solid contact layer of anticipate surface morphology were obtained, and the performance of nitrate all-solid ion-selective electrodes (NS ISEs) was improved. It was found that the roughest PPy(NO3-)-ISM remarkably increases the actual contact surface area of the PPy(NO3-)-ISMs with nitrate solution, which leads to better adsorption of NO3- ions upon the PPy(NO3-)-ISMs, and produces a larger number of electrons. The most hydrophobic Au solid contact layer avoids the formation of the aqueous layer at the interface between the PPy(NO3-)-ISM and Au solid contact layer, and ensures unimpeded transporting of the produced electrons. The PPy-Au-NS ISE for polymerization duration 1800 s and at Au3+ concentration 2.5 mM of the electrolyte displays an optimal nitrate potential response, including a Nernstian slope of 54.0 mV/dec, LOD of 1.1 × 10-4 M, rapid average response time less than 1.9 s, and long-term stability of more than 5 weeks. This indicates that the PPy-Au-NS ISE is an effective working electrode for the electrochemical determination of NO3- concentration.

Characterization of donkey-meat flavor profiles by GC-IMS and multivariate analysis.

The distinctive flavor compounds of donkey meat are unknown. Accordingly, in the present study, the volatile compounds (VOCs) in the meat from SanFen (SF) and WuTou (WT) donkeys were comprehensively analyzed by gas chromatography-ion mobility spectrometry (GC-IMS) combined with multivariate analysis. A total of 38 VOCs, of which 33.33% were ketones, 28.89% were alcohols, 20.00% were aldehydes, and 2.22% were heterocycles, were identified. Ketones and alcohols were significantly more abundant for SF than for WT, whereas aldehydes showed the opposite trend. The donkey meats from the two strains were well differentiated using topographic plots, VOC fingerprinting, and multivariate analysis. A total of 17 different VOCs were identified as potential markers for distinguishing the different strains, including hexanal-m, 3-octenal, oct-1-en-3-ol, and pentanal-d. These results indicate that GC-IMS combined with multivariate analysis is a convenient and powerful method for characterizing and discriminating donkey meat.

Investigation on the surface morphologies of reduced graphene oxide coating on the interfacial characteristics and electro-catalytic capacity of enzymatic glucose sensors.

In this study, reduced graphene oxide (rGO) were subject to ultrasonic treatment to acquire varied morphologies, and the enzymatic glucose sensors were constructed by coating the rGO onto indium tin oxide electrodes and physically linking glucose oxidase to the rGO coatings. The effects of the surface morphologies of the rGO coatings on the interfacial characteristics and the electro-catalytic capacity of the enzymatic glucose sensors were systematically investigated. It turns out that, the rGO coating with a rough surface is more hydrophilic, and exhibits uniform glucose oxidase adsorption and higher electron migration rate at the solid/liquid interface between the analytical liquid and the working electrode. As a result, the corresponding glucose sensor shows excellent electro-catalytic capacity towards glucose with a broader linear range of 0-10.0 mM, a higher sensitivity of 38.9µA·mM-1·cm-2, and a lower detection limit of 0.1µM (signal-to-noise ratio of 3). Additionally, the as-prepared glucose sensor exhibits excellent accuracy for detecting actual blood samples as well as superior resistance to interference from other substances (such as L-phenylalanine, urea, ascorbic acid, uric acid, NaCl, and KCl). These results establish the theoretical and experimental foundation for the application of rGO coating in the field of biosensors.

Correction to: A method of VR­EEG scene cognitive rehabilitation training.

[This corrects the article DOI: 10.1007/s13755-020-00132-6.].

A method of VR-EEG scene cognitive rehabilitation training.

Virtual reality technology can intuitively provide patients of neuropsychological diseases with an almost real environment for cognitive rehabilitation training . In this paper, virtual reality technology is used to construct specific scenes that are universal and related to MCI patients to restore and train patients' scene memory cognitive ability to help patients strengthen or gradually restore scene memory cognitive ability. The construction of virtual reality scenes with different contents such as life, environment, transportation and tourism, real-time detection is carried out in combination with EEG signals of patients in different scenes. The experimental results of the analysis of EEG signals of patients shows that memory rehabilitation training is strengthened by using specific stimulation scenes.