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Abstract The SQUAMOSA promoter-binding protein-like (SPL) family play a key role in guiding the switch of plant growth from juvenile to adult phases. Populus euphratica Oliv. exhibit typical heterophylly, and is therefore an ideal model for studying leaf shape development. To investigate the role and regulated networks of SPLs in the morphogenesis of P. euphratica heteromorphic leaves. In this study, 33 P. euphratica SPL (PeuSPL) genes were identified from P. euphratica genome and transcriptome data. Phylogenetic analysis depicted the classification of these SPL genes into two subgroups. The expression profiles and regulatory networks of P. euphratica SPL genes analysis displayed that major P. euphratica SPL family members gradually increases from linear to broad-ovate leaves, and they were involved in the morphogenesis regulation, stress response, transition from vegetative to reproductive growth, photoperiod, and photosynthesis etc. 14 circRNAs, and 33 lncRNAs can promote the expression of 12 of the P. euphratica SPLs by co-decoying miR156 in heteromorphic leaf morphogenesis. However, it was found that the effect of PeuSPL2-4 and PeuSPL9 in leaf shape development was contrasting to their homologous genes of Arabidopsis. Therefore, it was suggested that the SPL family were evolutionarily conserved for regulation growth, but were varies in different plant for regulation of the organ development.

Natural products (NPs) have historically played a primary role in the discovery of small-molecule drugs. However, due to the advent of other methodologies and the drawbacks of NPs, the pharmaceutical industry has largely declined in interest regarding the screening of new drugs from NPs since 2000. There are many technical bottlenecks to quickly obtaining new bioactive NPs on a large scale, which has made NP-based drug discovery very time-consuming, and the first thorny problem faced by researchers is how to dereplicate NPs from crude extracts. Remarkably, with the rapid development of omics, analytical instrumentation, and artificial intelligence technology, in 2012, an efficient approach, known as tandem mass spectrometry (MS/MS)-based molecular networking (MN) analysis, was developed to avoid the rediscovery of known compounds from the complex natural mixtures. Then, in the past decade, based on the classical MN (CLMN), feature-based MN (FBMN), ion identity MN (IIMN), building blocks-based molecular network (BBMN), substructure-based MN (MS2LDA), and bioactivity-based MN (BMN) methods have been presented. In this paper, we review the basic principles, general workflow, and application examples of the methods mentioned above, to further the research and applications of these methods. [ABSTRACT FROM AUTHOR]

To explore the mechanism of Shouhui Tongbian Capsules in treating constipation by means of network pharmacology and molecular docking approach. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) and Bioinfoematics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine(BATMAN) were applied to obtain chemical components and potential targets of eight herbs in Shouhui Tongbian Capsules according to the screening principles of oral availability(OB)≥30% and drug-like property(DL)≥0.18. Disease targets relating to constipation were screened out through GeneCards, PharmGkb and other databases, drug targets were integrated with disease targets, and intersection targets were exactly the potential action targets of Shouhui Tongbian Capsules for treating constipation; PPI network of potential targets was constructed using STRING platform, and GO(gene ontology) analysis and KEGG(Kyoto encyclopedia of genes and genomes) pathway data were obtained to conduct enrichment analysis and predict its mechanism of action. Cytoscape 3.6.1 was used to construct a network of "medicinal materials-chemical components-drug targets", and the network topology analysis was carried out on the PPI network to obtain its main components and key targets. Molecular docking between components and key targets of Shouhui Tongbian Capsules verified the accuracy of network pharmacological analysis results. The PPI network analysis showed 92 chemical components, including quercetin, stigmaste-rol, aloe-emodin, rhein, and key targets for instance AKT1, MAPK1, IL6, JUN, TNF and TP53. The enrichment analysis of KEGG screened out 157 signal pathways(P<0.01), mainly involving interleukin 17 signaling pathway, AGE-RAGE signaling pathway in diabetic complications, thyroid hormone signaling pathway. Quercetin, resveratrol and lysine with top degree value had a rational conformation in docking site of protein crystal complexes. This study preliminarily showed that various active ingredients in Shouhui Tongbian Capsules could regulate multiple signaling pathways, increase intestinal smoothness and peristalsis function, ensure smooth intestinal lumen, and play a role in treating constipation by acting on key targets, such as AKT1, MAPK1, IL6 and JUN.