Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.

Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data resources might be promising to help investigate the molecular mechanisms of pain phenotypes. Here, we integrated large-scale bibliographic literatures and well-established data sources to obtain high-quality pain relevant herbal data (i.e. 426 pain related herbs with their targets). We used machine learning method to identify three distinct herb categories with their specific indications of symptoms, targets and enriched pathways, which were characterized by the efficacy of treatment to the chronic cough related neuropathic pain, the reproduction and autoimmune related pain, and the cancer pain, respectively. We further detected the novel pathophysiological mechanisms of the pain subtypes by network medicine approach to evaluate the interactions between herb targets and the pain disease modules. This work increased the understanding of the underlying molecular mechanisms of pain subtypes that herbal drugs are participating and with the ultimate aim of developing novel personalized drugs for pain disorders.

Network pharmacology based investigation into the effect and mechanism of Modified Sijunzi Decoction against the subtypes of chronic atrophic gastritis.

Chronic atrophic gastritis (CAG) is a common digestive disease without specific treatment. According to syndrome differentiation, traditional Chinese medicine (TCM) classified it into different syndromes and has achieved significant therapeutic effects. In this study, immune repertoire sequencing techniques combined with symptom scores, electronic gastroscopy as well as pathologic changes were used to evaluate the effect and the underlying mechanism of Modified Sijunzi Decoction (MSD) in treating CAG. The results showed that MSD could relieve CAG symptoms, improve pathologic changes in CAG with fatigue and tiredness symptom, but with no help in CAG with reversal heat symptom. Moreover, MSD could regulate immune disorders in CAG with fatigue and tiredness symptom, and 7 TCR biomarkers were explored in CAG patients with immune disorders. All these results indicated that MSD is effective in treating CAG patients with fatigue and tiredness symptom by tonifying the spleen qi, suggesting that CAG treatment based on syndrome differentiation is reasonable.

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome.

BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to one type of disease. Unveiling the association between depressive and the fatigue diseases provides a great opportunity to bridge the modern medicine with the traditional Chinese medicine. METHODS: In this work, 295 general participants were recruited to complete Zung Self-Rating Depression Scales and Chalder Fatigue Scales, and meanwhile, to donate plasma and urine samples for 1H NMR-metabolic profiling. Artificial intelligence methods was used to analysis the underlying association between DD and CFS. Principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyze the metabolic profiles with respect to gender and age. Variable importance in projection and t-test were employed in conjunction with the PLS-DA models to identify the metabolite biomarkers. Considering the asymmetry and complexity of the data, convolutional neural networks (CNN) model, an artificial intelligence method, was built to analyze the data characteristics between each groups. RESULTS: The results showed the gender- and age-related differences for the candidate biomarkers of the DD and the CFS diseases, and indicated the same and different biomarkers of the two diseases. PCA analysis for the data characteristics reflected that DD and CFS was separated completely in plasma metabolite. However, DD and CFS was merged into one group. LIMITATION: Lack of transcriptomic analysis limits the understanding of the association of the DD and the CFS diseases on gene level. CONCLUSION: The unmasked candidate biomarkers provide reliable evidence to explore the commonality and differences of the depressive and the fatigue diseases, and thereby, bridge over the traditional Chinese medicine with the modern medicine.

SymMap: an integrative database of traditional Chinese medicine enhanced by symptom mapping.

Recently, the pharmaceutical industry has heavily emphasized phenotypic drug discovery (PDD), which relies primarily on knowledge about phenotype changes associated with diseases. Traditional Chinese medicine (TCM) provides a massive amount of information on natural products and the clinical symptoms they are used to treat, which are the observable disease phenotypes that are crucial for clinical diagnosis and treatment. Curating knowledge of TCM symptoms and their relationships to herbs and diseases will provide both candidate leads and screening directions for evidence-based PDD programs. Therefore, we present SymMap, an integrative database of traditional Chinese medicine enhanced by symptom mapping. We manually curated 1717 TCM symptoms and related them to 499 herbs and 961 symptoms used in modern medicine based on a committee of 17 leading experts practicing TCM. Next, we collected 5235 diseases associated with these symptoms, 19 595 herbal constituents (ingredients) and 4302 target genes, and built a large heterogeneous network containing all of these components. Thus, SymMap integrates TCM with modern medicine in common aspects at both the phenotypic and molecular levels. Furthermore, we inferred all pairwise relationships among SymMap components using statistical tests to give pharmaceutical scientists the ability to rank and filter promising results to guide drug discovery. The SymMap database can be accessed at http://www.symmap.org/ and https://www.bioinfo.org/symmap.

Tiansi Liquid Modulates Gut Microbiota Composition and Tryptophan⁻Kynurenine Metabolism in Rats with Hydrocortisone-Induced Depression.

Tiansi Liquid is a traditional Chinese herbal medicine used to treat depression; however, the underlying mechanisms remain unclear. Here, we examined the effect of Tiansi Liquid in a rat model of hydrocortisone-induced depression using behavioral testing, 16S rRNA high-throughput pyrosequencing and high-performance liquid chromatography-mass spectrometry-based metabolomics of the tryptophan (TRP)⁻kynurenine (KYN) pathway. Tiansi Liquid significantly improved the sucrose preference and exploratory behavior of the depressive rats. The richness of intestinal mucosa samples from the model (depressive) group tended to be higher than that from the control group, while the richness was higher in the Tiansi Liquid-treated group than in the model group. Tiansi Liquid increased the relative abundance of some microbiota (Ruminococcaceae, Lactococcus, Lactobacillus, Lachnospiraceae_NK4A136_group). Metabolomics showed that Tiansi Liquid reduced the levels of tryptophan 2,3 dioxygenase, indoleamine 2,3-dioxygenase, quinoline and the KYN/TRP ratio, while increasing kynurenic acid and 5-HT levels. Correlation analysis revealed a negative relationship between the relative abundance of the Lachnospiraceae_NK4A136_group and quinoline content. Collectively, these findings suggest that Tiansi Liquid ameliorates depressive symptoms in rats by modulating the gut microbiota composition and metabolites in the TRP⁻KYN pathway.

The Effect of Chinese Herbal Medicine on Quality of Life and Exercise Tolerance in Heart Failure With Preserved Ejection Fraction: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: Chinese herbal medicine (CHM) has a good effect of alleviating symptoms and improving quality of life and exercise tolerance in patients with heart failure with preserved ejection fraction (HFpEF), but it wasn't sufficiently valued and promoted because of the lack of evidence-based medical evidence. Aim: To systematically review the effect of CHM on quality of life and exercise tolerance in patients with HFpEF. Methods: We conducted a systematic literature search for Chinese and English studies in PubMed, EMBASE, Cochrane Central Register of Controlled Trials, Chinese Biomedical Literature Database, China Knowledge Resource Integrated Database, Wanfang Data, and China Science and Technology Journal Database. Databases were searched using terms relating to or describing CHM, HFpEF and randomized controlled trials, without any exclusion criteria for other types of diseases or disorders. Literature retrieval, data extraction, and risk of bias assessments were performed independently by two investigators. Differences were resolved by consensus. RevMan 5.3.0 was used for data analysis. Quantitative synthesis was used when the included studies were sufficiently homogeneous and subgroup analyses were performed for studies with different sample sizes and blind methods. GRADEpro was used to grade the available evidence to minimize bias in our findings. Results: Seventeen studies with 2,724 patients were enrolled in this review. ROB assessments showed a relatively high selection and performance bias. Meta-analyses showed that compared with conventional western medicine, combined CHM and conventional western medicine could significantly improve 6-min walk distance (MD = 52.13, 95% CI [46.91, 57.34], P < 0.00001), and it seemed to be more effective as compared with combined placebo and conventional western medicine. Similar results were observed for quality of life and the results were better in a larger sample. The GRADEpro showed a very low to moderate level of the available evidence. Conclusion: Combined CHM and conventional western medicine might be effective to improve exercise tolerance and quality of life in HFpEF patients, but new well-designed studies with larger sample size, strict randomization, and clear description about detection and reporting processes are needed to further strengthen this evidence.

Effects of Qijian mixture on type 2 diabetes assessed by metabonomics, gut microbiota and network pharmacology.

Qijian mixture, a new traditional Chinese medicine (TCM) formula comprising of Astragalus membranaceus, Ramulus euonymi, Coptis chinensis and Pueraria lobata, was designed to ameliorate the type 2 diabetes (T2D), and its safety and efficacy were evaluated in the research by metabonomics, gut microbiota and system pharmacology. To study the hypoglycemic effect of Qijian mixture, male KKay mice (28-30 g, 8-9 week) and C57/BL6 mice (18-19 g, 8-9 week) were used. Thirty KKay diabetic mice were randomly distributed into 5 groups, abbreviated as Model group (Model), Low Qijian Mixture group (QJM(L)), High Qijian Mixture group (QJM(H)), Chinese Medicine (Gegen Qinlian Decoction) Positive group (GGQL), and Western Medicine (Metformin hydrochloride) Positive group (Metformin). C57/BL6 was considered as the healthy control group (Control). Moreover, a system pharmacology approach was utilized to assess the physiological targets involved in the action of Qijian mixture. There was no adverse drug reaction of Qijian mixture in the acute toxicity study and HE result, and, compared with Model group, Qijian mixture could modulate blood glycemic level safely and effectively. Qijian Mixture was lesser effective than metformin hydrochloride; however, both showed similar hypoglycemic trend. Based on 1H NMR based metabonomics study, the profoundly altered metabolites in Qijian mixture treatment group were identified. Qijian mixture-related 55 proteins and 4 signaling pathways, including galactose metabolism, valine, leucine and isoleucine degradation metabolism, aminoacyl-tRNA biosynthesis metabolism and alanine, aspartate and glutamate metabolism pathways, were explored. The PCoA analysis of gut microbiota revealed that Qijian mixture treatment profoundly enriched bacteroidetes. In addition, the system pharmacology paradigm revealed that Qijian mixture acted through TP53, AKT1 and PPARA proteins. It was concluded that Qijian mixture effectively alleviated T2D, and this effect was linked with the altered features of the metabolite profiles and the gut microbiota.

Mechanism of Chinese Medicine Herbs Effects on Chronic Heart Failure Based on Metabolic Profiling.

Chronic heart failure (CHF) is a major public health problem in huge population worldwide. The detailed understanding of CHF mechanism is still limited. Zheng (syndrome) is the criterion of diagnosis and therapeutic in Traditional Chinese Medicine (TCM). Syndrome prediction may be a better approach for understanding of CHF mechanism basis and its treatment. The authors studied disturbed metabolic biomarkers to construct a predicting mode to assess the diagnostic value of different syndrome of CHF and explore the Chinese herbal medicine (CHM) efficacy on CHF patients. A cohort of 110 patients from 11 independent centers was studied and all patients were divided into 3 groups according to TCM syndrome differentiation: group of Qi deficiency syndrome, group of Qi deficiency and Blood stasis syndrome, and group of Qi deficiency and Blood stasis and Water retention syndrome. Plasma metabolomic profiles were determined by UPLC-TOF/MS and analyzed by multivariate statistics. About 6 representative metabolites were highly possible to be associated with CHF, 4, 7, and 5 metabolites with Qi deficiency syndrome, Qi deficiency and Blood stasis syndrome, and Qi deficiency and Blood stasis and Water retention syndrome (VIP > 1, p < 0.05). The diagnostic model was further constructed based on the metabolites to diagnose other CHF patients with satisfying sensitivity and specificity (sensitivity and specificity are 97.1 and 80.6% for CHF group vs. NH group; 97.1 and 80.0% for QD group vs. NH group; 97.1 and 79.5% for QB group vs. NH group; 97.1 and 88.9% for QBW group vs. NH group), validating the robustness of plasma metabolic profiling to diagnostic strategy. By comparison of the metabolic profiles, 9 biomarkers, 2-arachidonoylglycerophosphocholine, LysoPE 16:0, PS 21:0, LysoPE 20:4, LysoPE 18:0, linoleic acid, LysoPE 18:2, 4-hydroxybenzenesulfonic acid, and LysoPE 22:6, may be especially for the effect of CHM granules. A predicting model was attempted to construct and predict patient based on the related symptoms of CHF and the potential biomarkers regulated by CHM were explored. This trial was registered with NCT01939236 (https://clinicaltrials.gov/).

System Pharmacology-Based Dissection of the Synergistic Mechanism of Huangqi and Huanglian for Diabetes Mellitus.

The rapidly increasing diabetes mellitus (DM) is becoming a major global public health issue. Traditional Chinese medicine (TCM) has a long history of the treatment of DM with good efficacy. Huangqi and Huanglian are one of the most frequently prescribed herbs for DM, and the combination of them occurs frequently in antidiabetic formulae. However, the synergistic mechanism of Huangqi (Radix Astragali) and Huanglian (Rhizoma Coptidis) has not been clearly elucidated. To address this problem, a feasible system pharmacology model based on chemical, pharmacokinetic and pharmacological data was developed via network construction approach to clarify the synergistic mechanisms of these two herbs. Forty-three active ingredients of Huangqi (mainly astragalosides and isoflavonoids) and Huanglian (primarily isoquinoline alkaloids) possessing favorable pharmacokinetic profiles and biological activities were selected, interacting with 50 DM-related targets to provide potential synergistic therapeutic actions. Systematic analysis of the constructed networks revealed that these targets such as GLUT2, NOS2, PTP1B, and IGF1R were mainly involved in PI3K-Akt signaling pathway, insulin resistance, insulin signaling pathway, and HIF-1 signaling pathway, and were mainly located in retina, pancreatic islet, smooth muscle, immunity-related organ tissues, and whole blood. The contribution index of every active ingredient also indicated five compounds, including berberine (BBR), astragaloside IV (AIV), quercetin, palmatine, and astragalus polysaccharides, as the principal components of this herb combination. These results successfully explained the polypharmcological and synergistic mechanisms underlying the efficiency of Huangqi and Huanglian for the treatment of DM and its complications.

Drug-symptom networking: Linking drug-likeness screening to drug discovery.

Understanding the relationships between drugs and symptoms has broad medical consequences, yet a comprehensive description of the drug-symptom associations is currently lacking. Here, 1441 FDA-approved drugs were collected, and PCA was used to extract 122 descriptors which explained 91% of the variance. Then, a k-means++ method was employed to partition the drug dataset into 3 clusters, and 3 corresponding SVDD models (drug-likeness screening models) were constructed with an overall accuracy of up to 95.6%. Furthermore, 6878 herbal molecules from the TcmSP™ database were screened by the above 3 SVDD model to obtain 5309 candidate drug molecules with highly accept classification of 77.19%. To assess the accuracy of the SVDD models, 8559 herbal molecule-symptom co-occurrences were mined from Pubmed abstracts, involving 697 herbal molecules and 314 symptoms. Most of the 697 herbal molecules could be found in the accepted SVDD data (5309 molecules), showing the potential of the SVDD for the screening of drug candidates. Moreover, a herbal molecule-herbal molecule network and a herbal molecule-symptom were constructed. Overall, the results provided a new drug-likeness screening approach independent to abnormal training data, and the comprehensive collection of herbal molecule-symptom associations formed a new data resource for systematic characterization of the symptom-oriented medicines.

Triptolide treatment reduces Alzheimer's disease (AD)-like pathology through inhibition of BACE1 in a transgenic mouse model of AD.

The complex pathogenesis of Alzheimer's disease (AD) involves multiple contributing factors, including amyloid ß (Aß) peptide accumulation, inflammation and oxidative stress. Effective therapeutic strategies for AD are still urgently needed. Triptolide is the major active compound extracted from Tripterygium wilfordii Hook.f., a traditional Chinese medicinal herb that is commonly used to treat inflammatory diseases. The 5-month-old 5XFAD mice, which carry five familial AD mutations in the ß-amyloid precursor protein (APP) and presenilin-1 (PS1) genes, were treated with triptolide for 8 weeks. We observed enhanced spatial learning performances, and attenuated Aß production and deposition in the brain. Triptolide also inhibited the processing of amyloidogenic APP, as well as the expression of ßAPP-cleaving enzyme-1 (BACE1) both in vivo and in vitro. In addition, triptolide exerted anti-inflammatory and anti-oxidative effects on the transgenic mouse brain. Triptolide therefore confers protection against the effects of AD in our mouse model and is emerging as a promising therapeutic candidate drug for AD.

Evaluation and SAR analysis of the cytotoxicity of tanshinones in colon cancer cells.

AIM: This study was designed to evaluate the anti-cancer actions of tanshinone I and tanshinone IIA, and six derivatives of tanshinone IIA on normal and cancerous colon cells. Structure activity relationship (SAR) analysis was conducted to delineate the significance of the structural modifications of tanshinones for improved anti-cancer action. METHOD: Tanshinone derivatives were designed and synthesized according to the literature. The cytotoxicity of different compounds on colon cancer cells was determined by the MTT assay. Apoptotic activity of the tanshinones was measured by flow cytometry (FCM). RESULTS: Tanshinone I and tanshinone IIA both exhibited significant cytotoxicity on colon cancer cells. They are more effective in p53(+/+) colon cancer cell line. It was also noted that the anti-cancer activity of tanshinone I was more potent and selective. Two of the derivatives of tanshinone IIA (N1 and N2) also exhibited cytotoxicity on colon cancer cells. CONCLUSION: The anti-colon cancer activity of tanshinone I was more potent and selective than tanshinone IIA, and is p53 dependent. The derivatives obtained by structural modifications of tanshinone IIA exhibited lower cytotoxicity on both normal and colon cancer cells. From steric and electronic characteristics point of view, it was concluded that structural modifications of ring A and furan or dihydrofuran ring D on the basic structure of tanshinones influences the activity. An increase of the delocalization of the A and B rings could enhance the cytotoxicity of such compounds, while a non-planar and small sized D ring region would provide improved anti-cancer activity.

Profiling of differentially expressed genes in roots of Robinia pseudoacacia during nodule development using suppressive subtractive hybridization.

BACKGROUND: Legume-rhizobium symbiosis is a complex process that is regulated in the host plant cell through gene expression network. Many nodulin genes that are upregulated during different stages of nodulation have been identified in leguminous herbs. However, no nodulin genes in woody legume trees, such as black locust (Robinia pseudoacacia), have yet been reported. METHODOLOGY/PRINCIPAL FINDINGS: To identify the nodulin genes involved in R. pseudoacacia-Mesorhizobium amorphae CCNWGS0123 symbiosis, a suppressive subtractive hybridization approach was applied to reveal profiling of differentially expressed genes and two subtracted cDNA libraries each containing 600 clones were constructed. Then, 114 unigenes were identified from forward SSH library by differential screening and the putative functions of these translational products were classified into 13 categories. With a particular interest in regulatory genes, twenty-one upregulated genes encoding potential regulatory proteins were selected based on the result of reverse transcription-polymerase chain reaction (RT-PCR) analysis. They included nine putative transcription genes, eight putative post-translational regulator genes and four membrane protein genes. The expression patterns of these genes were further analyzed by quantitative RT-PCR at different stages of nodule development. CONCLUSIONS: The data presented here offer the first insights into the molecular foundation underlying R. pseudoacacia-M. amorphae symbiosis. A number of regulatory genes screened in the present study revealed a high level of regulatory complexity (transcriptional, post-transcriptional, translational and post-translational) that is likely essential to develop symbiosis. In addition, the possible roles of these genes in black locust nodulation are discussed.