[Modular pharmacology: research progress and development of analysis platform].

Based on the systematic deconstruction of multi-dimensional and multi-target biological networks, modular pharmacology explains the complex mechanism of diseases and the interactions of multi-target drugs. It has made progress in the fields of pathogenesis of disease, biological basis of disease and traditional Chinese medicine(TCM) syndrome, pharmacological mechanism of multi-target herbs, compatibility of formulas, and discovery of new drug of TCM compound. However, the complexity of multi-omics data and biological networks brings challenges to the modular deconstruction and analysis of the drug networks. Here, we constructed the "Computing Platform for Modular Pharmacology" online analysis system, which can implement the function of network construction, module identification, module discriminant analysis, hub-module analysis, intra-module and inter-module relationship analysis, and topological visualization of network based on quantitative expression profiles and protein-protein interaction(PPI) data. This tool provides a powerful tool for the research on complex diseases and multi-target drug mechanisms by means of modular pharmacology. The platform may have broad range of application in disease modular identification and correlation mechanism, interpretation of scientific principles of TCM, analysis of complex mechanisms of TCM and formulas, and discovery of multi-target drugs.

Whole brain morphologic features improve the predictive accuracy of IDH status and VEGF expression levels in gliomas.

Glioma is a systemic disease that can induce micro and macro alternations of whole brain. Isocitrate dehydrogenase and vascular endothelial growth factor are proven prognostic markers and antiangiogenic therapy targets in glioma. The aim of this study was to determine the ability of whole brain morphologic features and radiomics to predict isocitrate dehydrogenase status and vascular endothelial growth factor expression levels. This study recruited 80 glioma patients with isocitrate dehydrogenase wildtype and high vascular endothelial growth factor expression levels, and 102 patients with isocitrate dehydrogenase mutation and low vascular endothelial growth factor expression levels. Virtual brain grafting, combined with Freesurfer, was used to compute morphologic features including cortical thickness, LGI, and subcortical volume in glioma patient. Radiomics features were extracted from multiregional tumor. Pycaret was used to construct the machine learning pipeline. Among the radiomics models, the whole tumor model achieved the best performance (accuracy 0.80, Area Under the Curve 0.86), while, after incorporating whole brain morphologic features, the model had a superior predictive performance (accuracy 0.82, Area Under the Curve 0.88). The features contributed most in predicting model including the right caudate volume, left middle temporal cortical thickness, first-order statistics, shape, and gray-level cooccurrence matrix. Pycaret, based on morphologic features, combined with radiomics, yielded highest accuracy in predicting isocitrate dehydrogenase mutation and vascular endothelial growth factor levels, indicating that morphologic abnormalities induced by glioma were associated with tumor biology.

Miao medicine Gu Yan Xiao tincture inhibits mTOR to stimulate chondrocyte autophagy in a rabbit model of osteoarthritis.

ETHNOPHARMACOLOGICAL RELEVANCE: The Gu Yan Xiao tincture, a blend of traditional Chinese herbs, is traditionally used for osteoarthritis and related pain. This study investigated its mechanism of action in order to rationalize and validate its therapeutic use. AIM OF THE STUDY: This study analyzed, in a rabbit model of knee osteoarthritis, whether and how Gu Yan Xiao tincture exerts therapeutic benefits by modulating chondrocyte autophagy. MATERIALS AND METHODS: The active constituents within the GYX tincture were identified using liquid chromatography-mass spectrometry. The rabbit model was established by injecting animals with type II collagenase intra-articularly, and the effects of topically applied tincture were examined on osteoarthritis lesions of the knee using histopathology, micro-computed tomography and x-ray imaging. Effects of the tincture were also evaluated on levels of inflammatory cytokines, matrix metalloproteases, and autophagy in chondrocytes. As a positive control, animals were treated with sodium diclofenac. RESULTS: The tincture mitigated the reduction in joint space, hyperplasia of the synovium and matrix metalloproteases in serum that occurred after injection of type II collagenase in rabbits. These therapeutic effects were associated with inhibition of mTOR and activation of autophagy in articular chondrocytes. Inhibiting mTOR with rapamycin potentiated the therapeutic effects of the tincture, while inhibiting autophagy with 3-methyladenine antagonized them. CONCLUSIONS: Gu Yan Xiao tincture mitigates tissue injury in a rabbit model of osteoarthritis, at least in part by inhibiting mTOR and thereby promoting autophagy in chondrocytes. These results rationalize the use of the tincture not only against osteoarthritis but also potentially other diseases involving inhibition of autophagy in bones and joints.

Cortical myelin and thickness mapping provide insights into whole-brain tumor burden in diffuse midline glioma.

Systemic infiltration is a hallmark of diffuse midline glioma pathogenesis, which can trigger distant disturbances in cortical structure. However, the existence and effects of these changes have been underexamined. This study aimed to investigate whole-brain cortical myelin and thickness alternations induced by diffuse midline glioma. High-resolution T1- and T2-weighted images were acquired from 90 patients with diffuse midline glioma with H3 K27-altered and 64 patients with wild-type and 86 healthy controls. Cortical thickness and myelin content was calculated using Human Connectome Project pipeline. Significant differences in cortical thickness and myelin content were detected among groups. Short-term survival prediction model was constructed using automated machine learning. Compared with healthy controls, diffuse midline glioma with H3 K27-altered patients showed significantly reduced cortical myelin in bilateral precentral gyrus, postcentral gyrus, insular, parahippocampal gyrus, fusiform gyrus, and cingulate gyrus, whereas diffuse midline glioma with H3 K27 wild-type patients exhibited well-preserved myelin content. Furtherly, when comparing diffuse midline glioma with H3 K27-altered and diffuse midline glioma with H3 K27 wild-type, the decreased cortical thickness in parietal and occipital regions along with demyelination in medial orbitofrontal cortex was observed in diffuse midline glioma with H3 K27-altered. Notably, a combination of cortical features and tumor radiomics allowed short-term survival prediction with accuracy 0.80 and AUC 0.84. These findings may aid clinicians in tailoring therapeutic approaches based on cortical characteristics, potentially enhancing the efficacy of current and future treatment modalities.

Arginine Biosynthesis Pathway Found to Play a Key Role in the Neuroprotective Effect of Liu-Wei-Luo-Bi (LWLB) Granules in Diabetic db/db Mice with Peripheral Neuropathy Using an Untargeted Metabolomics Strategy.

Aim: Liu-Wei-Luo-Bi (LWLB) granules was a Chinese compound prescription for treating diabetic peripheral neuropathy (DPN). The aim of this study was to investigate the effect of LWLB granules on diabetic mice with peripheral neuropathy and to elucidate the potential mechanism based on an untargeted metabolomics approach. Methods: One hundred forty db/db mice were randomly divided into seven groups: the Control group, DPN group, Mudan (MD) granules group, Epalrestat (Epa) group, and the LWLB low, medium, or high dose (LW-l, LW-m, or LW-h) group. After 12 weeks of treatment, body weight, blood glucose, mechanical pain threshold, motor conduction velocity (MCV), sensory conduction velocity (SCV), and Pathological Organization of the Sciatic and Caudal Nerves in mice were measured. Serum samples were collected for untargeted metabolomics analysis using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) and multivariate statistics. Disease-related pathways were screened out with function enrichment analyses of candidate biomarkers. Results: LWLB granules can improve the peripheral neuropathy of type 2 diabetic mice with peripheral nerve conduction disorders, mainly through significantly improving the nerve conduction velocity (P < 0.05) and lowering the mechanical pain threshold (P < 0.05). A total of 43 metabolites were identified as potential biomarkers related to the therapeutic effect of LWLB granules. Fifty, 4, and 26; 23, 4, and 22; and 24, 1, and 16 biomarkers were discovered in the LW-l, LW-m, and LW-h groups at the 4th, 6th, and 12th weeks, respectively. Five, three, seven, five, and four metabolic pathways were found in MD, Epa, LW-l, LW-m, and LW-h groups, respectively. The arginine biosynthesis pathway is the overlapping pathway in LW-l, LW-m, and LW-h groups. Conclusion: LWLB granules have an obvious neuroprotective effect on diabetic peripheral neuropathy, and the metabolism mechanism of LWLB is mainly related to the arginine biosynthesis pathway on diabetic db/db mice with peripheral neuropathy.

Mother-child dyad support needs to be expressed by mothers diagnosed with breast cancer.

AIMS AND OBJECTIVES: To investigate the support needs identified by Taiwanese breast cancer diagnosed mothers for themselves and their 6-12-year-old children for implementation in a support group. BACKGROUND: Mothers with dependent children are burdened with diverse child-centered concerns while battling breast cancer. A better understanding of the concomitant support needs of mothers and their children can yield tailored support for ill mothers and their children. DESIGN: A qualitative descriptive study employing content analysis of collected data. METHODS: Between February and June of 2020, semi-structured individual interviews were conducted with 20 mothers who had been diagnosed with breast cancer in the last 2 years. Qualitative content analysis was used. This study followed the COREQ guidelines. RESULTS: Ill mothers favoured a hybrid format for support groups, consisting of mother-only, child-only, and mother-child group sessions. The content analysis yielded four themes for mother-only group sessions: (1) learning to reach out to children; (2) dealing with negative emotions; (3) how to say goodbye to children; and (4) resetting for the future. Three themes related to child-only group sessions emerged: (1) emotional and health education; (2) getting along with a sick mother; and (3) preparing for uncertainty. The core theme for mother-child group sessions was relationship enhancement. CONCLUSION: The findings revealed that mother-reported support needs of ill mothers and their children included support for improving children's emotional well-being and mothers' emotional coping, preparing for uncertainty, and promoting intimacy in the mother-child relationship. RELEVANCE TO CLINICAL PRACTICE: A relation-focused approach to psychosocial support group development that allows mother-child mutual influences on each other's coping to be addressed bilaterally is suggested. PATIENT OR PUBLIC CONTRIBUTION: Mothers diagnosed with breast cancer were interviewed for data collection and invited to review and validate the synthesised data for enhancing the credibility of the study.

Energy saving and emission reduction fiscal policy and corporate green technology innovation.

With the increasing prominence of resource and environmental issues, countries around the world are paying more and more attention to the concept of sustainable development. Under this concept, China started to implement a pilot project of "National Comprehensive Demonstration City of Energy Saving and Emission Reduction Fiscal Policy" in 2011 to protect resources and environment through green and low-carbon development. This paper aims to investigate whether and how the pilot policy induces corporate green technology innovation. Based on the data on Chinese listed firms from 2008 to 2019 and the relevant theories of economics, management and organizational psychology, we find that the pilot policy can promote corporate green technology innovation. This indicates that the pilot policy, as an external force, will encourage firms to improve their adaptability through green technology innovation which is one type of organizational change, thus improving their organizational effectiveness. The heterogeneity analyses reveal that the promotion effect of the pilot policy on green innovation is stronger among firms in high-carbon industries, firms in the mature stage and firms that are not state-owned. The mechanism tests find that the credit allocation effect and innovation compensation effect generated by the pilot policy are the key channels to promote green technology innovation. In addition to enriching the research on the evaluation of the effects of the pilot policy, our paper also expands the literature on organizational psychology and organizational change from the perspective of corporate green innovation, offers practical implications for the low-carbon transition of manufacturing industries under the emission peak and carbon neutrality targets, and provides insights for other emerging economies to achieve better resource and environmental protection through the energy saving and emission reduction fiscal policy.

Modular networks and genomic variation during progression from stable angina pectoris through ischemic cardiomyopathy to chronic heart failure.

BACKGROUND: Analyzing disease-disease relationships plays an important role for understanding etiology, disease classification, and drug repositioning. However, as cardiovascular diseases with causative links, the molecular relationship among stable angina pectoris (SAP), ischemic cardiomyopathy (ICM) and chronic heart failure (CHF) is not clear. METHODS: In this study, by integrating the multi-database data, we constructed paired disease progression modules (PDPMs) to identified relationship among SAP, ICM and CHF based on module reconstruction pairs (MRPs) of K-value calculation (a Euclidean distance optimization by integrating module topology parameters and their weights) methods. Finally, enrichment analysis, literature validation and structural variation (SV) were performed to verify the relationship between the three diseases in PDPMs. RESULTS: Total 16 PDPMs were found with K > 0.3777 among SAP, ICM and CHF, in which 6 pairs in SAP-ICM, 5 pairs for both ICM-CHF and SAP-CHF. SAP-ICM was the most closely related by having the smallest average K-value (K = 0.3899) while the maximum is SAP-CHF (K = 0.4006). According to the function of the validation gene, inflammatory response were through each stage of SAP-ICM-CHF, while SAP-ICM was uniquely involved in fibrosis, and genes were related in affecting the upstream of PI3K-Akt signaling pathway. 4 of the 11 genes (FLT1, KDR, ANGPT2 and PGF) in SAP-ICM-CHF related to angiogenesis in HIF-1 signaling pathway. Furthermore, we identified 62.96% SVs were protein deletion in SAP-ICM-CHF, and 53.85% SVs were defined as protein replication in SAP-ICM, while ICM-CHF genes were mainly affected by protein deletion. CONCLUSION: The PDPMs analysis approach combined with genomic structural variation provides a new avenue for determining target associations contributing to disease progression and reveals that inflammation and angiogenesis may be important links among SAP, ICM and CHF progression.

Modular Screening Reveals Driver Induced Additive Mechanisms of Baicalin and Jasminoidin on Cerebral Ischemia Therapy.

Combination therapy with increased efficacy and reduced toxicity plays a crucial role in treating complex diseases, such as stroke, but it remains an insurmountable barrier to elucidate the mechanisms of synergistic effects. Here, we present a Driver-induced Modular Screening (DiMS) strategy integrated synergistic module and driver gene identification to elucidate the additive mechanisms of Baicalin (BA) and Jasminoidin (JA) on cerebral ischemia (CI) therapy. Based on anti-ischemia genomic networks BA, JA, and their combination (BJ), we obtained 4, 3, and 9 On-modules of BA, JA, and BJ by modular similarity analysis. Compared with the monotherapy groups, four additive modules (Add-module, BJ_Mod-4, 7, 9, and 13), 15 driver genes of BJ were identified by modular similarity and network control methods, and seven driver proteins (PAQR8, RhoA, EMC10, GGA2, VIPR1, FAM120A, and SEMA3F) were validated by animal experiments. The functional analysis found neuroprotective roles of the Add-modules and driver genes, such as the Neurotrophin signaling pathway and FoxO signaling pathway, which may reflect the additive mechanisms of BJ. Moreover, such a DiMS paradigm provides a new angle to explore the synergistic mechanisms of combination therapy and screen multi-targeted drugs for complex diseases.

Deciphering potential pharmacological mechanisms of Danhong injection to treat chronic stable angina based on drug response-related modules and genes.

ETHNOPHARMACOLOGICAL RELEVANCE: Danhong injection (DHI), a traditional Chinese medicine (TCM) injection that has been widely used to treat coronary heart disease and angina pectoris. However, its underlying pharmacological mechanisms have not been fully elucidated. Not all patients benefit from DHI to the same extent. We attempted to explore the characteristics of potential therapeutic targets in different responsive populations. AIM OF THE STUDY: This study aimed to reveal the potential molecular mechanisms of DHI in treating chronic stable angina and identify potential therapeutic targets for DHI. MATERIALS AND METHODS: Based on a previous phase IV clinical trial of DHI in treating chronic stable angina, drug response modules were identified through structural entropy and similarity. Drug response-related genes were screened out based on the correlations between drug response module/module-related genes and clinical features and were assessed using a random forest model. Further validation was conducted using a hypoxia/reoxygenation (H/R) model. RESULTS: Seven DHI-related response modules were identified. Eight drug response-related genes were screened out, and principal component analysis showed that DHI responders were distinguished from responders in the control group based on their expression values. The combination of the two most important genes, SHC4 and PIP5K1P1, discriminated between responders and nonresponders with an area under the receiver operating characteristic curve (AUC) of 0.714; however, no significant difference was found in the AUC between the combination and a single gene. Reverse transcription-polymerase chain reaction showed that middle-dose DHI treatment significantly decreased SHC4 mRNA expression compared with that in the H/R group (P = 0.026), a finding consistent with our previous analysis of differentially expressed genes. CONCLUSIONS: DHI comprehensively exerted a therapeutic effect by acting on multiple response modules related to angina pectoris and drug response-related genes. Our findings indicate that the dimensionality reduction strategy based on the target network-drug response module-therapeutic targets can contribute to revealing the mechanism of action of TCM compounds and guiding precise clinical medication.

The Synergistic Effects of Astragalus mongholicus and Salvia miltiorrhiza on Coronary Heart Disease Identified by Network Pharmacology and Experiment.

BACKGROUND AND PURPOSE: Two Chinese herbal medicines Huang Qi (HQ, Astragalus mongholicus) and Dan Shen (DS, Salvia miltiorrhiza) are often combined to treat coronary heart disease (CHD). The purpose of this study was to identify the underlying synergistic effects and mechanisms of HQ and DS against CHD. METHODS: The active components and targets of HQ and DS, CHD-related genes, and the biological progression were analysed by network pharmacology. The myocardial infarction (MI) rat model was established by ligating the left anterior descending coronary artery. Cardiac function was detected by ultrasonic electrocardiography. The MI size, fibrosis, cardiac hypertrophy, lipid metabolism, blood viscosity, and coagulation indexes were analysed by histological staining or chemical methods, respectively. RESULTS: A total of 170 shared and specific seed genes of HQ and DS against CHD were identified. The shared and specific biological processes of HQ and DS against CHD were obtained. The LVEF and LVFS values significantly increased, the myocardium infarct size and fibrosis significantly decreased, the values of lipid metabolism indexes and blood viscosity indexes significantly reduced in the HQ + DS treatment group vs HQ or DS single treatment (P < 0.05); the LVEDd, LVEDs, and the CSA values significantly reduced in HQ single and HQ + DS treatment groups vs MI group (P < 0.05); the coagulation index (APTT, PT, TT, and FIB) values decreased significantly in the DS single and HQ + DS treatment groups vs MI group (P < 0.05). CONCLUSION: In MI rats, HQ and DS exhibited synergistic effects on improving cardiac function, reducing MI size, fibrosis, regulating hyperlipidaemia, and maintaining circulatory system homeostasis; HQ had the specific advantage of alleviating cardiac remodelling; DS had the specific advantage of regulating hypercoagulability. This study revealed that HQ and DS not only exerted synergistic effects but also exhibited complementary effects on CHD.

Prediction of hepatocellular carcinoma risk in patients with chronic liver disease from dynamic modular networks.

BACKGROUND: Discovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease. METHODS: In this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs. RESULTS: We found the total of 13 oncogenic allosteric modules (OAMs) among chronic hepatitis B (CHB), cirrhosis and HCC network used SimiNEF. We obtained the 11 highly correlated gene pairs involving 15 genes (r > 0.8, P < 0.001) from the 12 OAMs (the out-of-bag (OOB) classification error rate < 0.5) partial consistent with those in independent clinical microarray data, then a three-gene set (cyp1a2-cyp2c19-il6) was optimized to distinguish HCC from non-tumor liver tissues using random forests with an average area under the curve (AUC) of 0.973. Furthermore, we found significant inhibitory effect on the tumor growth of Bel-7402, Hep 3B and Huh7 cell lines in zebrafish treated with the compounds affected those three genes. CONCLUSIONS: These findings indicated that the sequential AMs-based approach could detect HCC risk in the patients with chronic liver disease and might be applied to any time-dependent risk of cancer.

Uncovering the protective mechanism of Huoxue Anxin Recipe against coronary heart disease by network analysis and experimental validation.

Coronary heart disease (CHD) is a leading cause of death and disability worldwide. Huoxue Anxin Recipe (HAR) is a novel Chinese Herbal Medicine formula of that has been used to treat CHD for several decades. Our previous study found that HAR had anti-oxidative effects, and could promote myocardial angiogenesis and improve cardiac function following myocardial infarction (MI) in rats. However, the active compounds, potential targets, and biological processes related to HAR have not been systematically investigated. Here, network pharmacology and experimental validation were used to study the protective mechanisms of HAR against CHD. We identified 124 active components, 124 verified targets, and 111 predictive targets. A total of 1192 genes related to CHD were identified by cDNA microarray and database analysis. A total of 47 putative targets of HAR against CHD were identified, including 32 verified targets and 15 predictive targets. ClueGo enrichment analysis identified 49 biological processes involved in the anti-CHD effects of HAR. Among them, the negative regulation of blood coagulation and regulation of collagen biosynthetic process were experimentally validated. After constructing a protein-protein interaction network and clustering with MECODE and ClusterONE, 162 key proteins (from ClueGo and clustering) were used to construct an internal interaction network. Complement C3 (C3), Fibrinogen alpha (FGA), Fibrinogen gamma (FGG), interleukin-6 (IL6), and Apolipoprotein A1 (APOA1) were the top 5 hub proteins identified by cytoHubber analysis. HAR limited the concentrations of C3, FGA, FGG, and IL6 and increased APOA1 levels. The results indicated that HAR could down-regulate blood coagulation, regulate collagen biosynthesis, inhibit peroxidation and inflammation injury, and promote cholesterol efflux. HAR could be a potential source of novel and effective drugs for CHD.

Genome Analysis Reveals a Synergistic Mechanism of Ursodeoxycholic Acid and Jasminoidin in Mice Brain Repair After Ischemia/Reperfusion: Crosstalk Among Muti-Pathways.

Studies have shown that combination drug therapy which corresponding treatment involves multiple genes and targets is more effective against cerebral ischemia. To identify the synergistic mechanism of ursodeoxycholic acid and jasminoidin based on differential pathway network, which protect against brain ischemia-reperfusion injury. Totally 115 mice with focal cerebral ischemia-reperfusion injury were allocated into five groups: sham, vehicle, ursodeoxycholic acid (UA), jasminoidin (JA), and JA and UA combination group (JU). The differentially expressed genes identified by microarray which consisted of 11,644 complementary DNAs were loaded to the GeneGo MetaCore™ software to analyze the enriched pathways and processes among different groups. Of the top 10 pathways and process networks, 5, 6, and 3 overlapping pathways as well as 5, 3, and 4 overlapping process networks were observed between UA and JA, UA and JU, and JA and JU, respectively. Of these, three pathways and three process networks overlapped across the three groups. Interestingly, four representative pathways and six process networks were only noted in the JU group. Gene Ontology process analysis showed 2 processes were shared by all three treatment groups in the top 10 processes. The UA and JA combination resulted in synergistic effects through affecting multi-signal transduction pathways, different locations in the same pathway, and the new signaling pathway emerged in drug combination group, those together may enhance the treatment of cerebral ischemia-reperfusion injury through promoting neural cell apoptosis, decreasing calcium levels, inhibiting inflammation, and protecting neurons.

Mining the Synergistic Core Allosteric Modules Variation and Sequencing Pharmacological Module Drivers in a Preclinical Model of Ischemia.

Identifying the variation of core modules and hubs seems to be critical for characterizing variable pharmacological mechanisms based on topological alteration of disease networks. We first identified a total of eight core modules by using an approach of multiple modular characteristic fusing (MMCF) from different targeted networks in ischemic mice. Interestingly, the value of module disturbance intensity (MDI) increased in drug combination group. Second, we redefined a weak allosteric module and a strong allosteric module. Then, we identified 15 pharmacological module drivers (PMDs) by leave-one-out screening with a cutoff of two folds, which were at least, in part, validated by expression and variation of topological contribution. Finally, we revealed the fusional and emergent variation of PMD in core modules contributing to multidimensional synergistic mechanism in ischemic mice and rats. Our findings provide a new set of drivers that might promote the pharmacological modular flexibility and offer a potential avenue for disease treatment.

Entropy-based divergent and convergent modular pattern reveals additive and synergistic anticerebral ischemia mechanisms.

Module-based network analysis of diverse pharmacological mechanisms is critical to systematically understand combination therapies and disease outcomes. We first constructed drug-target ischemic networks in baicalin, jasminoidin, ursodeoxycholic acid, and their combinations baicalin and jasminoidin as well as jasminoidin and ursodeoxycholic acid groups and identified modules using the entropy-based clustering algorithm. The modules 11, 7, 4, 8 and 3 were identified as baicalin, jasminoidin, ursodeoxycholic acid, baicalin and jasminoidin and jasminoidin and ursodeoxycholic acid-emerged responsive modules, while 12, 8, 15, 17 and 9 were identified as disappeared responsive modules based on variation of topological similarity, respectively. No overlapping differential biological processes were enriched between baicalin and jasminoidin and jasminoidin and ursodeoxycholic acid pure emerged responsive modules, but two were enriched by their co-disappeared responsive modules including nucleotide-excision repair and epithelial structure maintenance. We found an additive effect of baicalin and jasminoidin in a divergent pattern and a synergistic effect of jasminoidin and ursodeoxycholic acid in a convergent pattern on "central hit strategy" of regulating inflammation against cerebral ischemia. The proposed module-based approach may provide us a holistic view to understand multiple pharmacological mechanisms associated with differential phenotypes from the standpoint of modular pharmacology.

Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks.

Targeting modules or signalings may open a new path to understanding the complex pharmacological mechanisms of reversing disease processes. However, determining how to quantify the structural alteration of these signalings or modules in pharmacological networks poses a great challenge towards realizing rational drug use in clinical medicine. Here, we explore a novel approach for dynamic comparative and quantitative analysis of the topological structural variation of modules in molecular networks, proposing the concept of allosteric modules (AMs). Based on the ischemic brain of mice, we optimize module distribution in different compound-dependent modular networks by using the minimum entropy criterion and then calculate the variation in similarity values of AMs under various conditions using a novel method of SimiNEF. The diverse pharmacological dynamic stereo-scrolls of AMs with functional gradient alteration, which consist of five types of AMs, may robustly deconstruct modular networks under the same ischemic conditions. The concept of AMs can not only integrate the responsive mechanisms of different compounds based on topological cascading variation but also obtain valuable structural information about disease and pharmacological networks beyond pathway analysis. We thereby provide a new systemic quantitative strategy for rationally determining pharmacological mechanisms of altered modular networks based on topological variation.

System-wide assembly of pathways and modules hierarchically reveal metabolic mechanism of cerebral ischemia.

The relationship between cerebral ischemia and metabolic disorders is poorly understood, which is partly due to the lack of comparative fusing data for larger complete systems and to the complexity of metabolic cascade reactions. Based on the fusing maps of comprehensive serum metabolome, fatty acid and amino acid profiling, we identified 35 potential metabolic biomarkers for ischemic stroke. Our analyses revealed 8 significantly altered pathways by MetPA (Metabolomics Pathway Analysis, impact score >0.10) and 15 significantly rewired modules in a complex ischemic network using the Markov clustering (MCL) method; all of these pathways became more homologous as the number of overlapping nodes was increased. We then detected 24 extensive pathways based on the total modular nodes from the network analysis, 12 of which were new discovery pathways. We provided a new perspective from the viewpoint of abnormal metabolites for the overall study of ischemic stroke as well as a new method to simplify the network analysis by selecting the more closely connected edges and nodes to build a module map of stroke.

[Module-based analysis: deciphering pathological and pharmacological mechanisms of complex diseases and multi-target drugs].

A complex disease is rarely a consequence of abnormality in a single gene. It is known that many drugs exhibit a therapeutic effect by acting on multiple targets, produce synergies to intervene the occurrence and development of diseases. Unlike the traditional methods which act on single molecule or pathway, this disease-drug target network constructed with high throughput data vividly showed the complex relationship between drugs, their targets and diseases. However, the networks are usually extremely complex. In order to reduce the complexity, it is necessary to deconstruct the network and identify module structures. In this study, framework of module analysis was summarized from four aspects: module concept, structure and identification methods, importance of disease-drug module identification, and its application. Module-based analysis provides a new perspective for deciphering the drug intervention mechanisms for complex diseases, and provides new ideas and pathways to reveal the mechanisms of multi-target and multi-component drugs.

[Situation analysis for drug clinical trial institutions].

Drug clinical trial is an important link in the chain of new drug research and development. The results of drug discovery and development directly depend on the extent of standardization of clinical trials. Therefore, improving the quality of drug clinical trials is of great importance, and drug clinical trial institutions play a crucial role in the quality management of drug clinical trials. After years of development, the overall level of drug clinical trials has advanced rapidly in China, and a large number of clinical trials of traditional Chinese medicine have also been carried out. However, there is still a big gap between our country and developed countries. Therefore, for the construction and management of Chinese drug clinical trial institutions, there is still a long way to go. This study aims to analyze the current development of drug clinical trial institutions in China and explore the existing problems from three aspects, including current situations of institutional organization and management, regional and professional distributions, and quality control. And some suggestions are put forward finally, including support of traditional Chinese medicine, introduction of drug-risk management system, and construction of information management.