Uncovering Mechanism and Efficacy of Salvia Miltiorrhiza-Safflower in Cerebral Ischemia-Reperfusion Injury.

Cerebral ischemia (CI) is the main cause of stroke morbidity and disability. This study aims to identify the early molecular regulation responsible for the therapeutic effectiveness of the Herb pair Danshen-Honghua (DH) for CI. The major targets of DH were identified by searching the public database of traditional Chinese medicine (TCM). In addition, GeneCards, Disgenet, and GeneMap databases in OMIM were used to determine the disease targets of CI. A total of 88 common targets of DH and CI were selected, a protein-protein interaction (PPI) network was established by Cytoscape, and 19 core targets were screened. These genes were primarily enriched in biological processes including wound healing, reaction to oxidative stress, and response to peptides, lipid and atherosclerosis, Age-rage signaling pathway, and TNF signaling pathway by KEGG and GO enrichments. The effective components of DH had stable binding to these key targets by molecular docking. Finally, it was verified that the mechanism of DH on CI treatment may be related to the activation of the TNF-α/JNK signaling pathway by establishing the middle cerebral artery occlusion (MCAO) rat model.

Multi-target meridians classification based on the topological structure of anti-cancer phytochemicals using deep learning.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese medicine (TCM) meridian is the key theoretical guidance of prescription against tumor in clinical practice. However, there is no scientific and systematic verification of therapeutic action of herbs under meridians context. Several studies have determined the Chinese herbal medicine (CHM) phytochemicals for intrinsic attribute or meridians classification based on artificial intelligence (AI) tools. However, it is challenging to represent the complex molecular structures with large heterogeneity through the current technologies. In addition, the multiple correspondence between herbs and meridians has not been paid much attention. AIM OF THE STUDY: We aim to develop an AI framework to classify multi-target meridians through the topological structure of phytochemicals. MATERIALS AND METHODS: A total of 354 anti-cancer herbs, their corresponding TCM meridians and 5471 ingredient compounds were collected from public databases of CancerHSP, ETCM, and Hit 2.0. The statistical analysis of herbal and compound datasets, clustering analysis of the associated cancers, and correlational analysis of meridian tropism were preliminary conducted. Then a deep learning (DL) hybrid model named GRMC consisting of graph convolutional network (GCN) and recurrent neural network (RNN) was employed to generate the meridian multi-label sequences based on molecular graph. RESULTS: The curing herbs against tumors have tight relationships to lung, liver, stomach, and spleen meridians. These herbs behave different properties in curing certain cancer. Certain cancer types have co-occurrence such as ovarian, bladder and cervical cancer. Compounds have multitarget meridians with characteristics of higher-order correlations. Compared with the other state-of-the-art algorithms on the datasets and previous methods dealing with conventional fixed fingerprints of herbal compounds, the proposed GRMC has superior overall performance on testing dataset with the one error of 0.183, hamming loss of 0.112, mean averaged accuracy (MAA) of 0.855, mean averaged precision (MAP) of 0.891, mean averaged recall (MAR) of 0.812, and mean averaged F1 score (MAF) of 0.849. CONCLUSIONS: The proposed method can predict multi-targeted meridians through neural graph features in herbal compounds and outperforms several comparison methods. It could provide a basis for understanding the molecular scientific evidence of TCM meridians.

Allele-specific expression and chromatin accessibility contribute to heterosis in tea plants (Camellia sinensis).

Heterosis is extensively used to improve crop productivity, yet its allelic and chromatin regulation remains unclear. Based on our resolved genomes of the maternal TGY and paternal HD, we analyzed the contribution of allele-specific expression (ASE) and chromatin accessibility of JGY and HGY, the artificial hybrids of oolong tea with the largest cultivated area in China. The ASE genes (ASEGs) of tea hybrids with maternal-biased were mainly related to the energy and terpenoid metabolism pathways, whereas the ASEGs with paternal-biased tend to be enriched in glutathione metabolism, and these parental bias of hybrids may coordinate and lead to the acquisition of heterosis in more biological pathways. ATAC-seq results showed that hybrids have significantly higher accessible chromatin regions (ACRs) compared with their parents, which may confer broader and stronger transcriptional activity of genes in hybrids. The number of ACRs with significantly increased accessibility in hybrids was much greater than decreased, and the associated alleles were also affected by differential ACRs across different parents, suggesting enhanced positive chromatin regulation and potential genetic effects in hybrids. Core ASEGs of terpene and purine alkaloid metabolism pathways with significant positive heterosis have greater chromatin accessibility in hybrids, and were potentially regulated by several members of the MYB, DOF and TRB families. The binding motif of CsMYB85 in the promoter ACR of the rate-limiting enzyme CsDXS was verified by DAP-seq. These results suggest that higher numbers and more accessible ACRs in hybrids contribute to the regulation of ASEGs, thereby affecting the formation of heterotic metabolites.