Integrating network pharmacology and pharmacological evaluation to reveal the therapeutic effects and potential mechanism of S-allylmercapto-N-acetylcysteine on acute respiratory distress syndrome.

In this research, we sought to examine the effectiveness of S-allylmercapto-N-acetylcysteine (ASSNAC) on LPS-provoked acute respiratory distress syndrome (ARDS) and its potential mechanism based on network pharmacology. To incorporate the effective targets of ASSNAC against ARDS, we firstly searched DisGeNET, TTD, GeneCards and OMIM databases. Then we used String database and Cytoscape program to create the protein-protein interaction network. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis both identified the potential pathways connected to genes. Cytoscape software was used to build the network of drug-targets-pathways and the SwissDock platform was applied to dock the molecule of ASSNAC with the key disease targets. Correspondingly, an ARDS model was established by instillation of LPS in mice to confirm the underlying action mechanism of ASSNAC on ARDS as indicated by the network pharmacology analysis. Results exhibited that 27 overlapping targets, including TLR4, ICAM1, HIF1A, MAPK1, NFKB1, and others, were filtered out. The in vivo experiments showed that ASSNAC alleviated LPS-induced lung injury by downregulating levels of pro-inflammatory mediators and lung dry-wet ratio. Also, ASSNAC attenuated oxidative stress evoked by LPS via diminishing MDA production and SOD consumption as well as upregulating HO-1 level through Nrf2 activation. Results from western blot, quantitative real-time PCR and immunohistochemistry suggested that ASSNAC developed its therapeutic effects by regulating TLR4/MyD88/NF-κB signaling pathway. In conclusion, our research presented the efficacy of ASSNAC against ARDS. Furthermore, the mechanism of ASSNAC on ARDS was clarified by combining network pharmacology prediction with experimental confirmation.

Detection of chlorophyll fluorescence parameters of potato leaves based on continuous wavelet transform and spectral analysis.

The tuber development and nutrient transportation of potato crops are closely related to canopy photosynthesis dynamics. Chlorophyll fluorescence parameters of photosystem II, especially the maximum quantum yield of primary photochemistry (Fv/Fm), are intrinsic indicators for plant photosynthesis. Rapid detection of Fv/Fm of leaves by spectroscopy method instead of time-consuming pulse amplitude modulation technique could help to indicate potato development dynamics and guide field management. Accordingly, this study aims to extract fluorescence signals from hyperspectral reflectance to detect Fv/Fm. Hyperspectral imaging system and closed chlorophyll fluorescence imaging system were applied to collect the spectral data and values of Fv/Fm of 176 samples. The spectral data were decomposed by continuous wavelet transform (CWT) to obtain wavelet coefficients (WFs). Three mother wavelet functions including second derivative of Gaussian (gaus2), biorthogonal 3.3 (bior3.3) and reverse biorthogonal 3.3 (rbio3.3) were compared and the bior3.3 showed the best correlation with Fv/Fm. Two variable selection algorithms were used to select sensitive WFs of Fv/Fm including Monte Carlo uninformative variables elimination (MC-UVE) algorithm and random frog (RF) algorithm. Then the partial least squares (PLS) regression was used to establish detection models, which were labeled as bior3.3-MC-UVE-PLS and bior3.3-RF-PLS, respectively. The determination coefficients of prediction set of bior3.3-MC-UVE-PLS and bior3.3-RF-PLS were 0.8071 and 0.8218, respectively, and the root mean square errors of prediction set were 0.0181 and 0.0174, respectively. The bior3.3-RF-PLS had the best detection performance and the corresponding WFs were mainly distributed in the bands affected by fluorescence emission (650-800 nm), chlorophyll absorption and reflection. Overall, this study demonstrated the potential of CWT in fluorescence signals extraction and can serve as a guide in the quick detection of chlorophyll fluorescence parameters.