Crosstalk between autophagy and inflammasomes in ricin-induced inflammatory injury.

Ricin (ricin toxin, RT) has the potential to cause damage to multiple organs and systems. Currently, there are no existing antidotes, vaccinations, or effective therapies to prevent or treat RT intoxication. Apart from halting protein synthesis, RT also induces oxidative stress, inflammation and autophagy. To explore the mechanisms of RT-induced inflammatory injury and specific targets of prevention and treatment for RT poisoning, we characterized the role of cross-talk between autophagy and NLRP3 inflammasome in RT-induced damage and elucidated the underlying mechanisms. We showed that RT-induced inflammation was attributed to activation of the TLR4/MyD88/NLRP3 signaling and ROS production, evidenced by increased ASC speck formation and attenuated TXNIP/TRX-1 interaction, as well as pre-treatment with MCC950, MyD88 knockdown and NAC significantly reduced IL-1ß, IL-6 and TNF-α mRNA expression. In addition, autophagy is also enhanced in RT-triggered MLE-12 cells. RT elevated the levels of ATG5, p62 and Beclin1 protein, provoked the accumulation of LC3 puncta detected by immunofluorescence staining. Treatment with rapamycin (Rapa) reversed the RT-caused TLR4/MyD88/NLRP3 signaling activation, ASC specks formation as well as the levels of IL-1ß, IL-6 and TNF-α mRNA. In conclusion, RT promoted NLRP3 inflammasome activation and autophgay. Inflammation induced by RT was attenuated by autophagy activation, which suppressed the NLRP3 inflammasome. These findings suggest Rapa as a potential therapeutic drug for the treatment of RT-induced inflammation-related diseases.

[Discovery and application of traditional Chinese medicine efficacy markers based on systematic traditional Chinese medicine].

The quality marker(Q-marker) of traditional Chinese medicine(TCM) is a new concept of TCM quality control proposed in recent years. It is a hot issue in the research of modern Chinese medicine. The TCM efficacy is a high-level summary of the TCM therapeutic effect under the guidance of TCM theory. On this basis, it is of considerable significance to explore the TCM efficacy marker for the TCM modernization. However, the traditional research strategy based on the single herb and decoction piece in macro TCM level, or the drug research strategy based on the biological effect of the targets, is quite different from the characteristics of multiple components of TCM, as well as the weak and low-selective effect of Chinese medicine ingredients on targets. Therefore, how to select representative ingredients to characterize the TCM overall efficacy is a problematic point in establishing TCM efficacy markers. In this paper, the concept and method of Q-marker were introduced into the study of Chinese medicine efficacy. The research method for systematic TCM was used to systematically discuss the connotation of TCM efficacy markers, the principles of discovery and determination, common research ideas and techniques by taking the representative research results as an example. This study provides new ideas for the research and discovery of TCM efficacy markers.

[Study on components efficacy of Salviae Miltiorrhizae Radix et Rhizoma based on systematic traditional Chinese medicine].

This paper aimed to establish efficacy systems of tanshinones and salvianolic acids, two representative substances in Salviae Miltiorrhizae Radix et Rhizoma by using literature mining and biological network construction, based on systematic traditional Chinese medicine theory. The systematic study on the efficacy of traditional Chinese medicine was carried out from the basic unit, the structure and relationship between the basic units, the boundary of the research object and the function of the system, so as to explain the overall efficacy of the two kinds of components at the molecular level. Firstly, we collected the elements of the efficacy systems of these two kinds of components by literature mining, and defined their boundaries based on biological processes. After that, the structure of the efficacy systems was clarified according to the relationship in the KEGG database. Finally, the function of the efficacy systems was analyzed from the level of pharmacology, pharmacodynamics, and efficacy, revealing the scientific connotation of traditional Chinese medicine efficacy system. The results showed that there were 201 targets(elements), 12 target sets(boundary), and 12 pathway networks(structure) in salvianolic acids' efficacy system. Meanwhile, there were 189 targets(elements), 11 target sets(boundary), and 11 pathway networks(structure) in tanshinones' efficacy system. The results suggested that the functions of salvia-nolic acids' and tanshinones' efficacy systems were different in pharmacology and pharmacodynamics from aspects of elements, boundary, relationship and structure, but they were same in functional level as both of them could promote blood circulation, remove blood stasis, clear away heart-fire, relieve restlessness, and soothe the nerves. Based on systematic traditional Chinese medicine, we constructed the efficacy system of two representative components in Salviae Miltiorrhizae Radix et Rhizoma in this paper, elucidated the overall efficacy and builded the bridge between reductionism and holism in traditional Chinese medicine.

[Study on efficacy markers of heat-clearing and detoxifying effect of Lonicerae Japonicae Flos based on systematic traditional Chinese medicine].

Lonicerae Japonicae Flos has a long history of heat-clearing and detoxifying effect. The description of its efficacy in Chinese Pharmacopoeia of past dynasties is relatively stable, and it is an excellent carrier for the study of efficacy markers. Guided by the theory of systematic traditional Chinese medicine, heat-clearing and detoxifying effect efficacy system of Lonicerae Japonicae Flos was taken as an example in this study to clarify the elements(active ingredients) of Lonicerae Japonicae Flos in heat-clearing and detoxifying efficacy system, determine the boundary(signal pathway), establish the structure(system dynamics model), identify the system functions corresponding to pharmacology, efficacy and effects(heat-clearing and detoxifying effect), and explore the application of system dynamics model in the discovery of efficacy markers of traditional Chinese medicine. In this paper, the dynamic models of interleukin 1(IL-1) and interleukin 6(IL-6) in vivo were established to predict the expression of related factors in IL-1 and IL-6 signaling pathways of different components and their combinations in Lonicerae Japonicae Flos by dynamic network, so as to find the effective markers of heat-clearing and detoxification of Lonicerae Japonicae Flos. The results showed that the lower the concentration of chlorogenic acid, the higher the inhibition rate of Jun N-terminal kinase(JNK) at downstream of IL-1 by the combination of chlorogenic acid and linalool; the higher the concentration of luteolin in IL-6 pathway, the higher the inhibition rate of C-reactive protein(CRP) at downstream of IL-6 by the combination of chlorogenic acid and luteolin. It revealed that the potential efficacy markers of Lonicerae Japonicae Flos in heat-clearing and detoxifying effect based on IL-1 signaling pathway were chlorogenic acid and linalool, and the potential efficacy markers of Lonicerae Japonicae Flos in heat-clearing and detoxifying effect based on IL-6 signaling pathway were chlorogenic acid and luteolin. This study provided methodological guidance for the discovery of efficacy markers of traditional Chinese medicine.

A Network Pharmacology Approach to Explore the Mechanisms of Qishen Granules in Heart Failure.

This study aimed to investigate the intrinsic mechanisms of Qishen granules (QSG) in the treatment of HF, and to provide new evidence and insights for its clinical application. Information on QSG ingredients was collected from Traditional Chinese medicine systems pharmacology (TCMSP), TCM@Taiwan, TCMID, and Batman, and input into SwissTargetPrediction to identify the compound targets. HF-related targets were detected from Therapeutic Target Database (TTD), Disgenet-Gene, Drugbank database, and Online Mendelian Inheritance in Man (OMIM) database. The overlap targets of QSG and HF were identified for pathway enrichment analysis by utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The protein-protein interaction (PPI) network of QSG-HF was constructed, following by the generation of core targets, construction of core modules, and KEGG analysis of the core functional modules. There were 1909 potential targets predicted from the 243 bioactive compounds in QSG which shared 129 common targets with HF-related targets. KEGG pathway analysis of common targets indicated that QSG could regulated 23 representative pathways. In the QSG-HF PPI network analysis, 10 key targets were identified, including EDN1, AGT, CREB1, ACE, CXCR4, ADRBK1, AGTR1, BDKRB1, ADRB2, and F2. Further cluster and enrichment analysis suggested that neuroactive ligand-receptor interaction, cGMP-PKG signaling pathway, renin secretion, vascular smooth muscle contraction, and the renin-angiotensin system might be core pathways of QSG for HF. Our study elucidated the possible mechanisms of QSG from a systemic and holistic perspective. The key targets and pathways will provide new insights for further research on the pharmacological mechanism of QSG.

Correction: Hou, J., et al. Anti-Inflammatory Effects of Aurantio-Obstusin From Seed of Cassia obtusifolia L. Through Modulation of the NF-κB Pathway. Molecules 2018, 23, 3093.

The authors wish to make the following correction to their paper [...].

[Nature-effect relationship research of traditional Chinese medicine for promoting blood circulation and removing blood stasis based on nature combination].

The efficacy of traditional Chinese medicine is the therapeutic effect of the drug on the body. The nature of traditional Chinese medicine is a further generalization of the effect of efficacy,and there is an intrinsic relationship between efficacy and nature of traditional Chinese medicine. In this study,the nature-effect relationship is found on the whole level,through the research mode of " nature combination-targets of traditional Chinese medicine-modules of protein interaction network-efficiency". The results showed that the warm-pungent-liver protein interaction network mainly participated in lipid catabolic process,blood coagulation,platelet activation,heme oxidation,platelet degranulation,apoptotic process,acute inflammatory response to exert the effect of anti-tumor,antithrombotic,anti-myocardial ischemia and anti-inflammatory.

Anti-Inflammatory Effects of Aurantio-Obtusin from Seed of Cassia obtusifolia L. through Modulation of the NF-κB Pathway.

Aurantio-obtusin, an anthraquinone compound, isolated from dried seeds of Cassia obtusifolia L. (syn. Senna obtusifolia; Fabaceae) and Cassia tora L. (syn. Senna tora). Although the biological activities of Semen Cassiae have been reported, the anti-inflammatory mechanism of aurantio-obtusin, its main compound, on RAW264.7 cells, remained unknown. We investigated the anti-inflammatory effect of aurantio-obtusin on lipopolysaccharide- (LPS)-induced RAW264.7 cells in vitro and elucidated the possible underlying molecular mechanisms. Nitric oxide production (NO) and prostaglandin E2 (PGE2) were measured by the Griess colorimetric method and enzyme-linked immunosorbent assay (ELISA), respectively. Protein expression levels of cyclooxygenase 2 (COX-2) were monitored by cell-based ELISA. Interleukin 6 (IL-6) and tumor necrosis factor-alpha (TNF-α) synthesis were analyzed using ELISA. The mRNA expression of nitric oxide synthase (iNOS), COX-2, and the critical pro-inflammatory cytokines (IL-6 and TNF-α) were detected by quantitative real-time PCR. Aurantio-obtusin significantly decreased the production of NO, PGE2, and inhibited the protein expression of COX-2, TNF-α and IL-6, which were similar to those gene expression of iNOS, COX-2, TNF-α and IL-6 (p < 0.01). Consistent with the pro-inflammatory gene expression, the Aurantio-obtusin efficiently reduced the LPS-induced activation of nuclear factor-κB in RAW264.7 cells. These results suggested that aurantio-obtusin may function as a therapeutic agent and can be considered in the further development of treatments for a variety of inflammatory diseases. Further studies may provide scientific evidence for the use of aurantio-obstusin as a new therapeutic agent for inflammation-related diseases.

Using Coexpression Protein Interaction Network Analysis to Identify Mechanisms of Danshensu Affecting Patients with Coronary Heart Disease.

Salvia miltiorrhiza, known as Danshen, has attracted worldwide interest for its substantial effects on coronary heart disease (CHD). Danshensu (DSS) is one of the main active ingredients of Danshen on CHD. Although it has been proven to have a good clinical effect on CHD, the action mechanisms remain elusive. In the current study, a coexpression network-based approach was used to illustrate the beneficial properties of DSS in the context of CHD. By integrating the gene expression profile data and protein-protein interactions (PPIs) data, two coexpression protein interaction networks (CePIN) in a CHD state (CHD CePIN) and a non-CHD state (non-CHD CePIN) were generated. Then, shared nodes and unique nodes in CHD CePIN were attained by conducting a comparison between CHD CePIN and non-CHD CePIN. By calculating the topological parameters of each shared node and unique node in the networks, and comparing the differentially expressed genes, target proteins involved in disease regulation were attained. Then, Gene Ontology (GO) enrichment was utilized to identify biological processes associated to target proteins. Consequently, it turned out that the treatment of CHD with DSS may be partly attributed to the regulation of immunization and blood circulation. Also, it indicated that sodium/hydrogen exchanger 3 (SLC9A3), Prostaglandin G/H synthase 2 (PTGS2), Oxidized low-density lipoprotein receptor 1 (OLR1), and fibrinogen gamma chain (FGG) may be potential therapeutic targets for CHD. In summary, this study provided a novel coexpression protein interaction network approach to provide an explanation of the mechanisms of DSS on CHD and identify key proteins which maybe the potential therapeutic targets for CHD.

SYSTCM: A systemic web platform for objective identification of pharmacological effects based on interplay of "traditional Chinese Medicine-components-targets".

Mechanism analysis is essential for the use and promotion of Traditional Chinese Medicine (TCM). Traditional methods of network analysis relying on expert experience lack an explanatory framework, prompting the application of deep learning and machine learning for objective identification of TCM pharmacological effects. A dataset was used to construct an interacted network graph between 424 molecular descriptors and 465 pharmacological targets to represent the relationship between components and pharmacological effects. Subsequently, the optimal identification model of pharmacological effects (IPE) was established through convolution neural networks of GoogLeNet structure. The AUC values are greater than 0.8, MCC values are greater than 0.7, and ACC values are greater than 0.85 across various test datasets. Subsequently, 18 recognition models of TCM efficacy (RTE) were created using support vector machines (SVM). Integration of pharmacological effects and efficacies led to the development of the systemic web platform for identification of pharmacological effects (SYSTCM). The platform, comprising 70,961 terms, including 636 Traditional Chinese Medicines (TCMs), 8190 components, 40 pharmacological effects, and 18 efficacies. Through the SYSTCM platform, (1) Total 100 components were predicted from TCMs with anti-inflammatory pharmacological effects. (2) The pharmacological effects of complete constituents were predicted from Coptidis Rhizoma (Huang Lian). (3) The principal components, pharmacological effects, and efficacies were elucidated from Salviae Miltiorrhizae radix et rhizome (Dan Shen). SYSTCM addresses subjectivity in pharmacological effect determination, offering a potential avenue for advancing TCM drug development and clinical applications. Access SYSTCM at http://systcm.cn.

Revealing active constituents within traditional Chinese Medicine used for treating bacterial pneumonia, with emphasis on the mechanism of baicalein against multi-drug resistant Klebsiella pneumoniae.

ETHNOPHARMACOLOGICAL RELEVANCE: The emergence of antibiotic-resistant bacteria has rendered it more challenging to treat bacterial pneumonia. Traditional Chinese medicine (TCM) has superior efficacy in the treatment of pneumonia, and it has the unique advantage of antibacterial resistance against multi-drug resistant (MDR) bacteria, but the medication rule and pharmacological mechanism of its antibacterial activity are not clear. AIM OF THE STUDY: This study aims to reveal Chinese medication patterns in treating bacterial pneumonia to select bioactive constituents in core herbs, predict their pharmacological mechanisms and further explore their antibacterial ability against clinically isolated MDR Klebsiella pneumoniae (KP) and their antibacterial mechanisms. MATERIALS AND METHODS: The high-frequency medicinal herbs to treat lung diseases were first screened from Pharmacopoeia of the People's Republic of China (ChP.), and then bioactive compounds in core herbs and targets for compounds and disease were collected. Potential targets, signaling pathways, and drugs' core components were determined by constructing protein-protein interaction network, enrichment analysis and "component-target-pathway-disease" network were mapped by Cytoscape 3.8.2, and the potential therapeutic value of selected core components was verified by comparing the disease targets in the GEO database with the herbal component targets in the ITCM database. The clinically isolated KP were screened by drug sensitivity tests with meropenem (MEM), polymyxin E (PE), and tigecycline and biofilm-forming assay; broth microdilution, chessboard methods and biofilm morphology and permeability experiments were employed to determine the antibacterial, bactericidal and biofilm inhibition ability of selected bioactive constituents alone and in combination with antibiotics; The mechanism of bioactive components on quorum sensing (QS) genes LuxS and LuxR was predicted by molecular docking and tested by RT-PCR. RESULTS: The 13 core Chinese medicines were obtained by mining ChP., and 615 potential targets of core herbal medicine were screened, and the PI3K-Akt signaling pathway might play crucial roles in the therapeutic process. In-vitro experiments revealed that the selected core compounds, including forsythoside B, baicalin, baicalein, and forsythin, all have antibacterial activity, in which baicalein had the strongest ability and a synergistic effect in combination with MEM or PE. Their synergy exhibited a stronger effect on biofilms of MDR KP, inhibiting biofilm formation, disrupting formed biofilms, and removing the residual structures of dead bacteria. Baicalein was predicted to have stable binding capacity to LuxS and LuxR genes by molecular docking, and RT-PCR results verified that the combination of baicalein with MEM or PE was effective in inhibiting the expression of QS genes (LuxS and LuxR) and consequently suppressing biofilm formation. CONCLUSION: The core Chinese herbal medicine in the ChP. to treat lung diseases has a multi-component, multi-target, and multi-pathway synergy to improve bacterial pneumonia. Experimental studies have confirmed that the bioactive compound baicalein was able to combat MDR KP alone and synergistic with MEM or PE, inhibited and disrupted biofilms via regulating LuxS and LuxR genes, and further disturbed quorum sensing system to promote the therapeutic efficacy, which provides a new pathway and rationale for treating MDR KP-induced bacterial pneumonia.

A Discovery Strategy for Active Compounds of Chinese Medicine Based on the Prediction Model of Compound-Disease Relationship.

An accurate characterization of diseases and compounds is the key to predicting the compound-disease relationship (CDR). However, due to the difficulty of a comprehensive description of CDR, the accuracy of traditional drug development models for large-scale CDR prediction is usually unsatisfactory. In order to solve this problem, we propose a new method that integrates the molecular descriptors of compounds and the symptom descriptors of diseases to build a CDR two-dimensional matrix to predict candidate active compounds. The Matlab software draws grayscale images of CDRs, which are used as a benchmark dataset for training convolutional neural network (CNN) models. The trained model is used to predict candidate antitumor active compounds. Among the AlexNet and GoogLeNet models, we selected the GoogLeNet model for the prediction of active compounds in Chinese medicine, and its Acc, Sen, Pre, F-measure, MCC, and AUC are 0.960, 0.956, 0.965, 0.960, 0.920, and 0.964, respectively. In the prediction results of compounds, 1624 candidate CDRs were found in 124 Chinese medicines. Among them, we obtained 31 features of candidate antitumor active compounds. This method provides new insights for the discovery of candidate active compounds in Chinese medicine.

Exploring the mechanism of Yixinyin for myocardial infarction by weighted co-expression network and molecular docking.

Yixinyin, the traditional Chinese medicine, has the effects of replenishing righteous qi, and promoting blood circulation to eliminate blood stagnation. It is often used to treat patients with acute myocardial infarction (MI). The purpose of our study is to explore the key components and targets of Yixinyin in the treatment of MI. In this study, we analyzed gene expression data and clinical information from 248 samples of MI patients with the GSE34198, GSE29111 and GSE66360 data sets. By constructing a weighted gene co-expression network, gene modules related to myocardial infarction are obtained. These modules can be mapped in Yixinyin PPI network. By integrating differential genes of healthy/MI and unstable angina/MI, key targets of Yixinyin for the treatment of myocardial infarction were screened. We validated the key objectives with external data sets. GSEA analysis is used to identify the biological processes involved in key targets. Through molecular docking screening, active components that can combine with key targets in Yixinyin were obtained. In the treatment of myocardial infarction, we have obtained key targets of Yixinyin, which are ALDH2, C5AR1, FOS, IL1B, TLR2, TXNRD1. External data sets prove that they behave differently in the healthy and MI (P < 0.05). GSEA enrichment analysis revealed that they are mainly involved in pathways associated with myocardial infarction, such as viral myocarditis, VEGF signaling pathway and type I diabetes mellitus. The docking results showed that the components that can be combined with key targets in YixinYin are Supraene, Prostaglandin B1, isomucronulatol-7,2'-di-O-glucosiole, angusifolin B, Linolenic acid ethyl ester, and Mandenol. For that matter, they may be active ingredients of Yixinyin in treating MI. These findings provide a basis for the preliminary research of myocardial infarction therapy in traditional Chinese medicine and provide ideas for the design of related drugs.

Mechanism of tanshinones and phenolic acids from Danshen in the treatment of coronary heart disease based on co-expression network.

BACKGROUND: The tanshinones and phenolic acids in Salvia miltiorrhiza (also named Danshen) have been confirmed for the treatment of coronary heart disease (CHD), but the action mechanisms remain elusive. METHODS: In the current study, the co-expression protein interaction network (Ce-PIN) was used to illustrate the differences between the tanshinones and phenolic acids of Danshen in the treatment of CHD. By integrating the gene expression profile data and protein-protein interactions (PPIs) data, the Ce-PINs of tanshinones and phenolic acids were constructed. Then, the Ce-PINs were analyzed by gene ontology enrichment analyzed based on the optimal algorithm. RESULTS: It turned out that Danshen is able to treat CHD by regulating the blood circulation, immune response and lipid metabolism. However, phenolic acids may regulate the blood circulation by Extracellular calcium-sensing receptor (CaSR), Endothelin-1 receptor (EDNRA), Endothelin-1 receptor (EDNRB), Kininogen-1 (KNG1), tanshinones may regulate the blood circulation by Guanylate cyclase soluble subunit alpha-1 (GUCY1A3) and Guanylate cyclase soluble subunit beta-1 (GUCY1B3). In addition, both the phenolic acids and tanshinones may regulate the immune response or inflammation by T-cell surface glycoprotein CD4 (CD4), Receptor-type tyrosine-protein phosphatase C (PTPRC). CONCLUSION: Through the same targets of the same biological process and different targets of the same biological process, the tanshinones and phenolic acids synergistically treat coronary heart disease.

Tumor microenvironment characterization in head and neck cancer identifies prognostic and immunotherapeutically relevant gene signatures.

The tumor microenvironment (TME) is of great clinical significance for predicting the therapeutic effect of tumors. Nonetheless, there was no systematic analysis of cellular interactions in the TME of head and neck cancer (HNSC). This study used gene expression data from 816 patients with HNSC to analyze the scores of 22 immune cells. On this basis, we have established a novel TMEscore-based prognostic risk model. The relationship between TMEscore and clinical and genomic characteristics was analyzed. The sample was divided into risk-H and risk-L groups based on the prognosis risk model of TMEscore, with significant differences in overall survival between the two groups (log rank p < 0.001). In terms of clinical features, the TMEscore is closely related to the T staging, Grade, and HPV. As for genomic characteristics, the genomic features of the Risk-H samples are a low expression of immune-related genes and high-frequency mutations of TP53 and CEP152. This model was validated in an external test set, in which the prognosis for Risk-H group and Risk-L group was also significantly different (log rank p = 0.017). A quantitative method of TME infiltration pattern is established, which may be a potential predictor of HNSC prognosis.

A strategy to improve the identification reliability of the chemical constituents by high-resolution mass spectrometry-based isomer structure prediction combined with a quantitative structure retention relationship analysis: Phthalide compounds in Chuanxiong as a test case.

High-resolution mass spectrometry (HRMS) provides a powerful tool for the rapid analysis and identification of compounds in herbs. However, the diversity and large differences in the content of the chemical constituents in herbal medicines, especially isomerisms, are a great challenge for mass spectrometry-based structural identification. In the current study, a new strategy for the structural characterization of potential new phthalide compounds was proposed by isomer structure predictions combined with a quantitative structure-retention relationship (QSRR) analysis using phthalide compounds in Chuanxiong as an example. This strategy consists of three steps. First, the structures of phthalide compounds were reasonably predicted on the basis of the structure features and MS/MS fragmentation patterns: (1) the collected raw HRMS data were preliminarily screened by an in-house database; (2) the MS/MS fragmentation patterns of the analogous compounds were summarized; (3) the reported phthalide compounds were identified, and the structures of the isomers were reasonably predicted. Second, the QSRR model was established and verified using representative phthalide compound standards. Finally, the retention times of the predicted isomers were calculated by the QSRR model, and the structures of these peaks were rationally characterized by matching retention times of the detected chromatographic peaks and the predicted isomers. A multiple linear regression QSRR model in which 6 physicochemical variables were screened was built using 23 phthalide standards. The retention times of the phthalide isomers in Chuanxiong were well predicted by the QSRR model combined with reasonable structure predictions (R2=0.955). A total of 81 peaks were detected from Chuanxiong and assigned to reasonable structures, and 26 potential new phthalide compounds were structurally characterized. This strategy can improve the identification efficiency and reliability of homologues in complex materials.