In Vitro Effects of Tartary Buckwheat-Derived Nanovesicles on Gut Microbiota.

Evidence suggests that plant-derived nanovesicles may play a significant role in human health. Tartary buckwheat has several physiological activities; however, its underlying health-promoting mechanism remains unclear. In this study, first, Tartary buckwheat-derived nanovesicles (TBDNs) were collected, their structures were analyzed, and microRNA sequencing was performed. Next, target prediction and functional verification were conducted. Finally, the effects of TBDNs on gut microbiota and short-chain fatty acid levels were evaluated. The average size of TBDNs was 141.8 nm diameter. Through the sequencing analyses, 129 microRNAs, including 11 novel microRNAs were identified. Target gene prediction showed that some microRNAs could target functional genes in Escherichia coli and Lactobacillus rhamnosus-related physiological processes. TBDNs significantly promoted the growth of E. coli and L. rhamnosus, enhanced the diversity of fecal microorganisms and increased the short-chain fatty acid levels. These findings provided a new nutritional perspective for Tartary buckwheat and were conducive to promote the development and utilization of Tartary buckwheat.

Method for Ferrite Nanomaterials-Mediated Cellular Magnetic Hyperthermia.

Magnetic hyperthermia (MH) mediated by magnetic nanoparticles is one of the most promising antitumor modalities. The past several decades have witnessed great progress for MH antitumor therapy in scientific trials and clinic applications since it was initially advanced by Gilchrist et al. The ultimate object of MH in vivo is to efficiently kill cancer cells, and hence, it is of great importance to develop an optimized cellular MH method to evaluate the therapeutic efficiency in vitro. In this study, we systematically studied the considerable affecting factors of cancer cell-killing efficiency during the cellular MH process, including the region of cell vessel positioned inside the alternating magnetic field copper coil, the magnetic field amplitude, the types of cancer cells, etc. Taking all these into account, we introduced a method for standardizing the cellular MH process to evaluate the cell-killing efficiency.

[Study on the polarized reflectance-hyperspectral information fusion technology of tomato leaves nutrient diagnoses].

With 25%, 50%, 75%, 100% and 150%, five levels of, nitrogen (N), phosphorus (P) and potassium (K) nutrition stress samples cultivated in Venlo type greenhouse soilless cultivation mode as the research object, polarized reflectance spectra and hyperspectral images of different nutrient deficiency greenhouse tomato leaves were acquired by using polarized reflectance spectroscopy system developed by our own research group and hyperspectral imaging system respectively. The relationship between a certain number of changes in the bump and texture of non-smooth surface of the nutrient stress leaf and the level of polarization reflected radiation was clarified by scanning electron microscopy (SEM). On the one hand, the polarization spectrum was converted into the degree of polarization through Stokes equation, and the four polarization characteristics between the polarization spectroscopy and reference measurement values of N, P and K respectively were extracted. On the other hand, the four characteristic wavelengths of N, P, K hyperspectral image data were determined respectively through the principal component analysis, followed by eight hyperspectral texture features extracted corresponding to the four characteristic wavelengths through correlation analysis. Polarization characteristics and hyperspectral texture features combined with each characteristics of N, P, K were extracted. These 12 characteristic variables were normalized by maximum-minimum value method. N, P, K nutrient levels quantitative diagnostic models were established by SVR. Results of models are as follows: the correlation coefficient of nitrogen r = 0.961 8, root mean square error RMSE= 0.451; correlation coefficient of phosphorus r = 0.916 3, root mean square error RMSE = 0.620; correlation coefficient of potassium r = 0.940 6, root mean square error RMSE = 0.494. The results show that high precision tomato leaves nutrition prediction model could be built by using polarized reflectance spectroscopy combined with high spectral information fusion technology and achieve good diagnoses effect. It has a great significance for the improvement of model accuracy and the development of special instruments. The research provides a new idea for the rapid detection of tomato nutrient content.

[Study on the polarized reflectance characteristics of single greenhouse tomato nutrient deficiency leaves].

In order to improve accuracy of quantitative analysis model for the greenhouse tomato nitrogen, phosphorus and potassium nutrient stress, and explore the advantages of polarization non-destructive detection in single-leaf plants scale, polarized reflectance characteristics of greenhouse nutrient deficiency tomato leaves in different growing seasons and different deficiency extents were both examined via means of polarized reflectance spectroscopy system, which was self-developed by the research group. The main factors with effects on the polarized reflectance characteristics of tomato leaves were discussed, such as incident zenith angle, azimuth angle, detection zenith angle, light source polarizer degree, and detector polarizer degree. Experiments were carried out to verify the optimum level of above five parameters by means of range analysis of orthogonal experiments, through that way we can know the best angle combination of five parameters. Based on the above analysis, the angle combination and sorting of detecting tomato nutrients deficiency leaves via means of polarization spectroscopy system were obtained as follows: incident zenith angle 60 degrees, light source polarizer degree 0 degrees, detection zenith angle 45 degrees, detector polarizer degree 45 degrees and azimuth angle 180 degrees. At the same time, both the spectra of nitrogen, phosphorus and potassium deficiency leaves in different growth stages and different deficiency extent leaves were compared with each other. Results show that there is a positive correlation between the greenhouse nutrient deficiency tomato leaves growth cycle and tomato leaves polarized reflectance spectra. Nutrient excess or nutrient deficiency can both lead to polarized reflectance decline and polarized reflectance decline extent of greenhouse tomato leaves is more obvious during the fruiting and harvest period. This paper has a certain theoretical and practical significance in the research on nutrition rapid detection on the plant single leaf scale by means of polarized reflectance spectrum.