Network-based gene expression biomarkers for cold and heat patterns of rheumatoid arthritis in traditional chinese medicine

Genome-wide Analysis Identified SEMA4D, Novel Candidate Gene for Temperature Sensitivity in Patients With Non-Small Cell Lung Cancer

BACKGROUND

In the era of precision medicine, individual temperature sensitivity has been highlighted. This trait has traditionally been used for cold-heat pattern identification to understand the inherent physical characteristics, which are influenced by genetic factors, of an individual. However, genome-wide association studies (GWASs) on this trait are limited.

METHODS

Using genotype data from 90 patients with advanced non-small cell lung cancer (NSCLC) and epidermal growth factor receptor mutations, we performed a GWAS to assess the association between single nucleotide polymorphisms (SNPs) and temperature sensitivity, such as cold and heat scores. The score of each participant was evaluated using self-administered questionnaires on common symptoms and a 15-item symptom-based cold-heat pattern identification questionnaire.

RESULTS

The GWAS was adjusted for confounding factors, including age and sex, and significant associations were identified for cold and heat scores: SNP rs145814326, located on the intron of SORCS2 at chromosome 4p16.1, had a P-value of 1.86 × 10-7; and SNP rs79297667, located upstream from SEMA4D at chromosome 9q22.2, had a P-value of 8.97 × 10-8. We also found that the genetic variant regulates the expression level of SEMA4D in the main tissues, including the lungs and white blood cells, in NSCLC.

CONCLUSIONS

SEMA4D was found to be significantly associated with temperature sensitivity in patients with NSCLC, suggesting an increased expression of SEMA4D in patients with higher heat scores. The potential role of temperature sensitivity as a prognostic or predictive marker of immune response in NSCLC should be further studied.

Analysis of Colorectal Carcinogenesis Paradigm between Cold Constitution and Heat Constitution: Earlier ECM Collagen Deposition

Colorectal cancer (CRC) is a common malignant tumor around the world. Studying the unique constitution of CRC patients is conducive to the application of personalized medical treatment for CRC. The most common types of constitution in CRC are cold and heat constitution. A previous study has suggested that the malignant progression in cold and heat constitution CRC are different; however, the mechanism remains unclear. The tumor microenvironment (TME) is likely to vary with each individual constitution, which may affect the tumor growth in different constitutions. The extracellular matrix (ECM), the most important component of TME, plays a critical role in disease progression and outcome in patients with CRC. Moreover, collagen, the major component of the ECM, determines the main functional characteristics of ECM and tissue fibrosis caused by collagen deposition, which is one of the signs of CRC malignant progression. This study aimed to explore the mechanisms leading to different colorectal carcinogenesis paradigms between the cold constitution and heat constitution within the context of ECM collagen deposition. We established the CRC rat models and enrolled 30 CRC patients with cold and heat constitution. The collagen-related parameters were detected by using Sirius red staining combined with polarized light microscope, and expressions of collagen (COL I and COL III) and lysyl oxidase (LOX and LOXL2) were determined using immunohistochemistry, while the mRNA levels of COL1A1, COL3A1, LOX, and LOXL2 were measured by qRT-PCR. We found that a higher degree of collagen deposition in the cold-constitution group. The results suggest cold and heat constitution may affect the colorectal carcinogenesis paradigm by influencing the early collagen deposition in colon tissue. The study may provide an effective idea for clinicians to improve the prognosis of CRC patients with different constitutions.

Unsupervised Learning and Multipartite Network Models: A Promising Approach for Understanding Traditional Medicine

The ultimate goal of precision medicine is to determine right treatment for right patients based on precise diagnosis. To achieve this goal, correct stratification of patients using molecular features and clinical phenotypes is crucial. During the long history of medical science, our understanding on disease classification has been improved greatly by chemistry and molecular biology. Nowadays, we gain access to large scale patient-derived data by high-throughput technologies, generating a greater need for data science including unsupervised learning and network modeling. Unsupervised learning methods such as clustering could be a better solution to stratify patients when there is a lack of predefined classifiers. In network modularity analysis, clustering methods can be also applied to elucidate the complex structure of biological and disease networks at the systems level. In this review, we went over the main points of clustering analysis and network modeling, particularly in the context of Traditional Chinese medicine (TCM). We showed that this approach can provide novel insights on the rationale of classification for TCM herbs. In a case study, using a modularity analysis of multipartite networks, we illustrated that the TCM classifications are associated with the chemical properties of the herb ingredients. We concluded that multipartite network modeling may become a suitable data integration tool for understanding the mechanisms of actions of traditional medicine.

Identification of Characteristic Autoantibodies Associated With Deficiency Pattern in Traditional Chinese Medicine of Rheumatoid Arthritis Using Protein Chips

Background: Rheumatoid arthritis (RA) is an autoimmune disease. Based on traditional Chinese medicine (TCM) theory, deficiency pattern (DP) which leads to specific treatment principles in clinical management is a crucial pattern diagnosis among RA patients, and autoantibodies have potential implications in TCM pattern classification. The purpose of this study was to identify specific RA DP-associated autoantibodies.

Methods: RA DP patients, RA nondeficiency pattern (NDP) patients and healthy controls (HCs) were recruited for this study. Then, clinical data and sera from all subjects were collected. After that, the sera were probed with protein chips, which were constructed by known RA related autoantigens, to screen for DP-associated candidate autoantibodies. Lastly, candidate autoantibodies were validated via enzyme-linked immunosorbent assay (ELISA) and function was evaluated by network analysis.

Results: Protein chips results showed that RA patients have higher levels of anti-vascular endothelial growth factor (VEGF) A165 antibodies than HC (P < 0.005); anti-VEGFA165 antibodies levels of patients with RA DP were lower than patients with RA NDP (P < 0.05). The results of the ELISA also showed statistically significant differences in anti-VEGFA165 antibodies between the RA and HC group (P < 0.0001); and there were statistically significant differences in anti-VEGFA165 antibodies between the RA DP and RA NDP group (P < 0.05). Network analysis results suggested IL-6 signaling pathway has a significant effect on VEGFA165 in RA patients.

Conclusion: Autoantibodies identification in RA using protein chips help in understanding DP in TCM. Discovery of anti-VEGFA165 antibodies may provide the possibility for clinical precision treatment.

MicroRNA-5195-3p enhances the chemosensitivity of triple-negative breast cancer to paclitaxel by downregulating EIF4A2

Background

Chemotherapy based on paclitaxel (PTX) is the standard treatment for a range of cancers, including triple-negative breast cancer (TNBC), but the increasing development of resistance has reduced/has negatively impacted its clinical utility. A previous study demonstrated that miR-5195-3p could suppress lung cancer cell growth. This study was designed to investigate whether miR-5195-3p attenuates chemoresistance to PTX by regulating target genes in TNBC cells.

Methods

The study used both PTX-resistant tumor tissues and PTX-resistant TNBC cell lines. The expression of miR-5195-3p was determined using quantitative real-time PCR. Cell viability, cell cycle distribution and apoptosis were analyzed using CCK-8 and flow cytometry assays. The target genes of miR-5195-3p were predicted with bioinformatics analysis and confirmed using the luciferase reporter assay.

Results

MiR-5195-3p expression was lower in PTX-resistant tumor tissues and PTX-resistant TNBC cell lines. Upregulation of miR-5195-3p enhanced the sensitivity of PTX-resistant TNBC cells to PTX treatment. EIF4A2 was confirmed as a potential target of miR-5195-3p. EIF4A2 knockdown imitated the effects of miR-5195-3p on chemosensitivity, while restoration of EIF4A2 rescued them.

Conclusion

These data demonstrate that miR-5195-3p might be a potential therapeutic target to reverse chemoresistance in TNBC through its targeting of EIF4A2.

Protective effect of Traditional Chinese medicine Shuangwu Zhentong Capsule on collagen-induced arthritis in rats and possible mechanisms

The aim of this study was to investigate the protective effect of Traditional Chinese medicine Shuangwu Zhentong Capsule (SZC) on collagen-induced arthritis (CIA) and the possible mechanisms. Sixty rats were randomly divided into control and model: low-, medium-, and high-dose SZC and prednisone acetate (PA) groups, with 10 rats in each group. The CIA model was established in later 5 groups. The rats in low-, medium-, and high-dose SZC groups were intragastricallly administered with SZC, with dose of 0.5, 1, and 2 g/kg, respectively. The PA group was intragastricallly administered with 5 mg/kg PA. The treatment was performed for 3 weeks. Before treatment and after treatment, the paw swelling degree and polyarthritis index score of rats were measured. At the end of experiment, the serum tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and nitric oxide (NO) levels were determined. The expressions of Ras and Raf-1 protein in synovial tissue were detected. Results showed that, after treatment, compared with model group, in high-dose SZC and PA groups, the paw swelling degree, polyarthritis index score, serum TNF-α, IL-1β and NO levels, and synovial tissue Ras and Raf-1 protein levels were significantly decreased, respectively ( P < 0.05). In conclusion, SZC has obvious protective effects on CIA in rats. The mechanisms may be related to its resistance of inflammatory reaction and down-regulation of Ras and Raf-l protein expressions in synovial tissue.

Deciphering Potential Correlations between New Biomarkers and Pattern Classification in Chinese Medicine by Bioinformatics: Two Examples of Rheumatoid Arthritis

Biological complexity and the need for personalized medicine means that biomarker development has become increasingly challenging. Thus, new paradigms for research need to be created that bring together a different classifier of individuals. One potential solution is collaboration between biomarker development and Chinese medicine pattern classification. In this article, two examples of rheumatoid arthritis are discussed, including a new biomarker candidate casein kinase 2 interacting protein 1 (CKIP-1) and a micro RNA 214. The authors obtained a "snapshot" of pattern classification with disease in biomarker identification. Bioinformatics analyses revealed underlying biological functions of two biomarker candidates, in varying degrees, are correlated with Chinese medicine pattern of rheumatoid arthritis. The authors' initial attempt can provide a new window for studying the win-win potential correlation between the biomarkers and pattern classification in Chinese medicine.

Clinical Efficacy of Acupuncture on Rheumatoid Arthritis and Associated Mechanisms: A Systemic Review

OBJECTIVE

The objective of this review is to investigate the detailed existing scientific information about the clinical efficacy of acupuncture on rheumatoid arthritis (RA) conditions and to reveal the proposed mechanisms.

METHODS

We searched the PubMed, EMBASE, Cochrane, AMED (Allied and Complementary Medicine), NCCAM (The National Center for Complementary and Alternative Medicine), and CNKI (China National Knowledge Infrastructure) databases to identify relevant monographs and related references from 1974 to 2018. Chinese journals and theses/dissertations were hand searched.

RESULTS

43 studies were recruited. Each research was analyzed for study design, subject characteristics, intervention, selected acupoints, assessment parameters, proposed mechanisms, and results/conclusions.

CONCLUSIONS

In our review, we concluded that acupuncture alone or combined with other treatment modalities is beneficial to the clinical conditions of RA without adverse effects reported and can improve function and quality of life and is worth trying. Several important possible mechanisms were summarized including anti-inflammatory effect, antioxidative effect, and regulation of immune system function. However, there is still inconsistency regarding the clinical efficacy and lack of well-designed human/animal double-blinded RCTs. Future discussion for further agreement on taking traditional Chinese medicine (TCM) theory into consideration as much as possible is a top priority.

Understanding Chinese Medicine Patterns of Rheumatoid Arthritis and Related Biomarkers

Background: A considerable number of Rheumatoid Arthritis (RA) patients only experience side effects from treatment, with little to no actual pain relief. The combination of disease diagnosis in biomedicine and multi-disciplinary integrative approaches such as Chinese Medicine (CM), can help to identify different functional diagnosis of RA in the context of biomarker discovery. We aimed to analyse CM patterns in RA and their biomarker profiles. Methods: Four electronic databases (web of science, CINAHL, Scopus and PubMed) were searched. The reference list of all identified reports and articles were searched for additional studies. All study designs were included and no date limits were set. Studies were considered if they were published in English and explored the possible biomarkers profiles in RA patients, classified according to the American College of Rheumatology and categorized in CM as either cold, heat/hot or deficiency patterns. Methodological quality of included studies was assessed using checklists adapted from the ©Critical Appraisal Skills Programme by two independent reviewers. A narrative synthesis was conducted, using thematic analysis. Results: A total of 10 articles were included. The studies examined 77 healthy volunteers and 1150 RA patients categorized as cold, heat/hot or deficiency pattern and related biomarkers were identified individually or concomitantly. Conclusions: CM pattern differentiation based on clinical signs and symptoms showed a diverse range of biomolecules, proteins and genes from RA patients correlated well with cold, heat/hot or deficiency phenotype-based CM patterns and could be used as diagnostic biomarkers for early detection, disease monitoring and therapeutic targets.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

Prediction of cold and heat patterns using anthropometric measures based on machine learning

OBJECTIVE

To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures can improve the predictive power to diagnose these patterns.

METHODS

Based on a total of 4,859 subjects (3,000 women and 1,859 men), statistical analyses using binary logistic regression were performed to assess the significance of the difference and the predictive power of each anthropometric measure, and binary logistic regression and Naive Bayes with the variable selection technique were used to assess the improvement in the predictive power of the patterns using the combined measures.

RESULTS

In women, the strongest indicators for determining the cold and heat patterns among anthropometric measures were body mass index (BMI) and rib circumference; in men, the best indicator was BMI. In experiments using a combination of measures, the values of the area under the receiver operating characteristic curve in women were 0.776 by Naive Bayes and 0.772 by logistic regression, and the values in men were 0.788 by Naive Bayes and 0.779 by logistic regression.

CONCLUSIONS

Individuals with a higher BMI have a tendency toward a heat pattern in both women and men. The use of a combination of anthropometric measures can slightly improve the diagnostic accuracy. Our findings can provide fundamental information for the diagnosis of cold and heat patterns based on body shape for personalized medicine.

Isoorientin from Gypsophila elegans induces apoptosis in liver cancer cells via mitochondrial-mediated pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Gypsophila elegans has been used as a traditional herbal medicine for treating immune disorders and chronic liver diseases in China. The aim of this study is to isolate an active ingredient from this herb and investigate its anti-tumor activity.

MATERIALS AND METHODS

An active ingredient was isolated from the ethanol extract using bioassay-guided screening. And its anti-tumor activity was analyzed by testing the cytotoxicity, lactate dehydrogenase (LDH) release, clonogenecity and migration in HepG2 cells. To investigate its potential mechanism, cell apoptosis, cell cycle arrest, reactive oxygen species (ROS), cytochrome c, mitochondria membrane potential (MMP) and caspase level were determined in liver cancer cell line HepG2.

RESULTS

A flavonoid glycoside, i.e., G. elegans isoorientin (GEI), was isolated from this herb and identified as Isoorientin-2″-O-α-l-arabinopyranosyl. Our results showed that GEI significantly inhibited the viability and proliferation of HepG2 cells in a dose- and time-dependent manner, and its cytotoxic effect was also confirmed by the elevated level of LDH. GEI treatment could markedly inhibit the clonogenicity and migration of HepG2 cells. Moreover, GEI induced remarkable apoptotic death of HepG2 cells through cell cycle arrest at G1 phase via the regulation of cell cycle-related genes, such as cyclin D, cyclin E and CDK2. Further study showed that GEI treatment significantly elevated ROS formation, followed by attenuation of MMP via up-regulation of Bax and down-regulation of Bcl-2, accompanied by cytochrome c release to the cytosol. In addition, GEI treatment resulted in a significant dose-dependent increase in caspase-3 and -9 proteolytic activities.

CONCLUSION

The present study demonstrates that the ability of GEI to induce apoptosis against HepG2 cells mediated by mitochondrial-mediated pathway.

Cleistopholine isolated from Enicosanthellum pulchrum exhibits apoptogenic properties in human ovarian cancer cells

BACKGROUND

Cleistopholine is a natural alkaloid present in plants with numerous biological activities. However, cleistopholine has yet to be isolated using modern techniques and the mechanism by which this alkaloid induces apoptosis in cancer cells remains to be elucidated.

HYPOTHESIS/PURPOSE

This study aims to isolate cleistopholine from the roots of Enicosanthellum pulchrum by using preparative-HPLC technique and explore the mechanism by which this alkaloid induces apoptosis in human ovarian cancer (CAOV-3) cells in vitro from 24 to 72 h. This compound may be developed as an anticancer agent that induces apoptosis in ovarian cancer cells.

STUDY DESIGN/METHODS

Cytotoxicity was assessed via the cell viability assay and changes in cell morphology were observed via the acridine orange/propidium iodide (AO/PI) assay. The involvement of apoptotic pathways was evaluated through caspase analysis and multiple cytotoxicity assays. Meanwhile, early and late apoptotic events via the Annexin V-FITC and DNA laddering assays, respectively. The mechanism of apoptosis was explored at the molecular level by evaluating the expression of specific genes and proteins. In addition, the proliferation of CAOV-3-cells treated with cleistopholine was analysed using the cell cycle arrest assay.

RESULTS

The IC50 of cleistopholine (61.4 µM) was comparable with that of the positive control cisplatin (62.8 µM) at 24 h of treatment. Apoptos is was evidenced by cell membrane blebbing, chromatin compression and formation of apoptotic bodies. The initial phase of apoptosis was detected at 24 h by the increase in Annexin V-FITC binding to cell membranes. A DNA ladder was formed at 48 h, indicating DNA fragmentation in the final phase of apoptosis. The mitochondria participated in the process by stimulating the intrinsic pathway via caspase 9 with a reduction in mitochondrial membrane potential (MMP) and an increase in cytochrome c release. Cell death was further validated through the mRNA and protein overexpression of Bax, caspase 3 and caspase 9 in the treated cells compared with the untreated cells. In contrast, Bcl-2, Hsp70 and survivin decreased in expression upon cleistopholine treatment. Cell cycle was arrested at the G0/G1 phase and cell population percentage significantly increased to 43.5%, 45.4% and 54.3% in time-dependent manner in the cleistopholine-treated CAOV-3 cells compared with the untreated cells at 24, 48 and 72 h respectively.

CONCLUSION

The current study indicated that cleistopholine can be a potential candidate as a new drug to treat ovarian cancer disease.

Piperine derivatives as potential inhibitors of Survivin: An in silico molecular docking

Targeting Survivin, as an inhibitor of apoptosis and a regulator of cell division, has become a worldwide controversial issue. Piperine as a pungent alkaloid has been identified as the most potent adjuvant at enhancing the efficacy of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-based therapies in triple-negative breast cancer (TNBC) cells in vitro and in vivo, which might be mediated through inhibition of Survivin. In this work, the binding energies, inhibition constants and binding modes of a group of previously synthesized Piperine derivatives at the binding site of Survivin have been studied using molecular docking tools and the best compounds with minimum binding energies are proposed as potential drugs for the inhibition of Survivin. A comprehensive SAR analysis has been done on the results that can be used for designing new Piperine analogs with higher efficacy. Molecular docking computations also show that the studied compounds can bind to BIR domain of Survivin in the same binding site as that of Smac/DIABLO with a suitable binding energy. This binding may result in the segregation of Smac/DIABLO in the cytosol and subsequently free Smac/DIABLO molecules could be available for binding with inhibitors of apoptosis to initiate caspase mediated apoptosis.

Predicting and verifying outcome of Tripterygium wilfordii Hook F. based therapy in rheumatoid arthritis: from open to double-blinded randomized trial

Tripterygium wilfordii Hook F. (TwHF) based therapy has been proved as effective in treating rheumatoid arthritis (RA), yet the predictors to its response remains unclear. A two-stage trial was designed to identify and verify the baseline symptomatic predictors of this therapy. 167 patients with active RA were enrolled with a 24-week TwHF based therapy treatment and the symptomatic predictors were identified in an open trial; then in a randomized clinical trial (RCT) for verification, 218 RA patients were enrolled and classified into predictor positive (P+) and predictor negative (P−) group, and were randomly assigned to accept the TwHF based therapy and Methotrexate and Sulfasalazine combination therapy (M&S) for 24 weeks, respectively. Five predictors were identified (diuresis, excessive sweating, night sweats for positive; and yellow tongue-coating, thermalgia in the joints for negative). In the RCT, The ACR 20 responses were 82.61% in TwHF/P+ group, significantly higher than that in TwHF/P− group (P = 0.0001) and in M&S/P+ group (P < 0.05), but not higher than in M&S/P− group. Similar results were yielded in ACR 50 yet not in ACR 70 response. No significant differences were detected in safety profiles among groups. The identified predictors enable the TwHF based therapy more efficiently in treating RA subpopulations.

ZHENG May Contribute to Obesity Phenotypes Based on Body Composition: A Pilot Study on the Traditional Chinese Medicine Approach

Objective. Obesity therapy needs new approaches to complement current phenotyping systems. This study aims to assess associations between the Traditional Chinese Medicine (TCM) ZHENG and obesity phenotypes. Methods. We assessed medical history and habitual physical activity and measured body composition, fasting plasma glucose and insulin, and lipids. We collected TCM data through face-to-face interview. ZHENG elements (essentials and locations) were identified by TCM practitioner. Primary ZHENG was assessed by cluster analysis. Results. In 140 consecutive subjects enrolled in a university clinic (body mass index (BMI): 39.9 ± 5.8 kg/m2), ZHENG essentials were identified as “QiXu,” “Re,” “YinXu,” and “TanShi” (totally 86.8%). Locations were “Shen,” “Wei,” “Pi,” and “Gan” (totally 91.8%). Four types of primary ZHENG were identified: A (37.1% of subjects), B (16.5%), C (35.7%), and D (10.7%). Subjects in type D showed elevated BMI, total fat mass (FM), FM index, trunk FM, and less physical activity, as compared with others. Subjects in type B changed regional body composition (reduced trunk FM% and elevated appendicular FM%). Biological parameters did not differ across primary ZHENG clusters. Conclusions. Obesity phenotypes based on body composition differ according to ZHENG in obese patients. This study is a first step toward understanding the contribution of TCM to obesity phenotyping.

Pharmacological tools for the development of traditional Chinese medicine

Pharmacology as a modern science was introduced in China approximately 150 years ago, and has been used since then to study traditional Chinese medicine (TCM). Pharmacology has experienced its own development over this time and continues to provide new tools for the study of TCM. In the present review, three models for the pharmacological study of TCM are considered: (i) chemistry-focused study; (ii) target-directed study; and (iii) systems-biology-based study. These approaches correspond to recent developments in pharmacology, and in particular to new tools available to the field. Representative achievements and the pharmacological tools used to study TCM are reviewed. Pharmacology has played, and will continue to play, an indispensable role in elucidating the chemical basis, biological targets, and mechanisms of action of TCM medicines, and in developing a scientific basis for the theory of TCM.

Rheumatoid arthritis with deficiency pattern in traditional chinese medicine shows correlation with cold and hot patterns in gene expression profiles

In our precious study, the correlation between cold and hot patterns in traditional Chinese medicine (TCM) and gene expression profiles in rheumatoid arthritis (RA) has been explored. Based on TCM theory, deficiency pattern is another key pattern diagnosis among RA patients, which leads to a specific treatment principle in clinical management. Therefore, a further analysis was performed aiming at exploring the characteristic gene expression profile of deficiency pattern and its correlation with cold and hot patterns in RA patients by bioinformatics analysis approach based on gene expression profiles data detected with microarray technology. The TCM deficiency pattern-related genes network comprises 7 significantly, highly connected regions which are mainly involved in protein transcription processes, protein ubiquitination, toll-like receptor activated NF- κ B regulated gene transcription and apoptosis, RNA clipping, NF- κ B signal, nucleotide metabolism-related apoptosis, and immune response processes. Toll-like receptor activated NF- κ B regulated gene transcription and apoptosis pathways are potential specific pathways related to TCM deficiency patterns in RA patients; TCM deficiency pattern is probably related to immune response. Network analysis can be used as a powerful tool for detecting the characteristic mechanism related to specific TCM pattern and the correlations between different patterns.

Navigating traditional chinese medicine network pharmacology and computational tools

The concept of "network target" has ushered in a new era in the field of traditional Chinese medicine (TCM). As a new research approach, network pharmacology is based on the analysis of network models and systems biology. Taking advantage of advancements in systems biology, a high degree of integration data analysis strategy and interpretable visualization provides deeper insights into the underlying mechanisms of TCM theories, including the principles of herb combination, biological foundations of herb or herbal formulae action, and molecular basis of TCM syndromes. In this study, we review several recent developments in TCM network pharmacology research and discuss their potential for bridging the gap between traditional and modern medicine. We briefly summarize the two main functional applications of TCM network models: understanding/uncovering and predicting/discovering. In particular, we focus on how TCM network pharmacology research is conducted and highlight different computational tools, such as network-based and machine learning algorithms, and sources that have been proposed and applied to the different steps involved in the research process. To make network pharmacology research commonplace, some basic network definitions and analysis methods are presented.

Microarray analysis reveals the molecular basis of antiarthritic activity of huo-luo-xiao-ling dan

Rheumatoid arthritis (RA) is a chronic inflammatory disease of autoimmune origin. Huo-luo-xiao-ling dan (HLXL) is an herbal mixture that has been used in traditional Chinese medicine over several decades to treat chronic inflammatory diseases including RA. However, the mechanism of the anti-arthritic action of this herbal remedy is poorly understood at the molecular level. In this study, we determined by microarray analysis the effects of HLXL on the global gene expression profile of the draining lymph node cells (LNC) in the rat adjuvant arthritis (AA) model of human RA. In LNC restimulated in vitro with the disease-related antigen mycobacterial heat-shock protein 65 (Bhsp65), 84 differentially expressed genes (DEG) (64 upregulated and 20 downregulated) versus 120 DEG (94 upregulated and 26 downregulated) were identified in HLXL-treated versus vehicle (Water)-treated rats, respectively, and 62 DEG (45 upregulated and 17 downregulated) were shared between the two groups. The most affected pathways in response to HLXL treatment included immune response, inflammation, cellular proliferation and apoptosis, and metabolic processes, many of which are directly relevant to arthritis pathogenesis. These results would advance our understanding of the mechanisms underlying the anti-arthritic activity of HLXL.

Differences of excess and deficiency zheng in patients with chronic hepatitis B by urinary metabonomics

Traditional Chinese medicine (TCM) physicians stratify patients with the same disease into different subtypes in order to guide the appropriate treatment, which is called Zheng (TCM syndrome) classification. Excess and deficiency ZHENG is a couple of basic ZHENGs of maladjusted body nature, reflecting the struggling state of human body and pathogenic factor and is important and prevalently exists in the ZHENG classification of many diseases. The present work using chronic hepatitis B (CHB) as an entry point explored the substance connotation of excess and deficiency ZHENG with the metabonomic technology based on gas chromatography-mass spectrometry (GC-MS). The different substantial basis of two ZHENGs suggested that CHB patients could be categorized into two groups with diverse pathogenesis. The differential metabolites and disturbed pathways compared to not-obvious ZHENG characters patients (without ZHENG group/WZ) were selected in both of the two ZHENGs. The ROC analysis demonstrated that five metabolites had a greater potential to be the clinic biomarkers of EZ or DZ. And excess ZHENG revealed a higher level of immune function than deficiency ZHENG. We are eager to transform the concept of traditional excess and deficiency ZHENGs to modern therapeutic approaches, with the prospect to help to promote personalized medicine.

Traditional chinese medicine-based network pharmacology could lead to new multicompound drug discovery

Current strategies for drug discovery have reached a bottleneck where the paradigm is generally “one gene, one drug, one disease.” However, using holistic and systemic views, network pharmacology may be the next paradigm in drug discovery. Based on network pharmacology, a combinational drug with two or more compounds could offer beneficial synergistic effects for complex diseases. Interestingly, traditional chinese medicine (TCM) has been practicing holistic views for over 3,000 years, and its distinguished feature is using herbal formulas to treat diseases based on the unique pattern classification. Though TCM herbal formulas are acknowledged as a great source for drug discovery, no drug discovery strategies compatible with the multidimensional complexities of TCM herbal formulas have been developed. In this paper, we highlighted some novel paradigms in TCM-based network pharmacology and new drug discovery. A multiple compound drug can be discovered by merging herbal formula-based pharmacological networks with TCM pattern-based disease molecular networks. Herbal formulas would be a source for multiple compound drug candidates, and the TCM pattern in the disease would be an indication for a new drug.

Bridging the traditional Chinese medicine pattern classification and biomedical disease diagnosis with systems biology

Being the unique core of traditional Chinese medicine (TCM), pattern classification exerts a direct effect on the efficacy and safety of herbal interventions. In this article, the authors integrated the pattern classification and disease diagnosis with many approaches from systems biology. Integration of pattern classification with biomedical diagnosis by systems biology is not only a new direction of personalized medicine development, but also provides a new drug development model. In the further study, the pattern classifications of major diseases will be the focus of research.

Understanding the molecular mechanism of interventions in treating rheumatoid arthritis patients with corresponding traditional chinese medicine patterns based on bioinformatics approach

Better effectiveness would be achieved when interventions are used in treating patients with a specific traditional Chinese medicine (TCM) pattern. In this paper, the effectiveness in treating rheumatoid arthritis (RA) patients in a randomized clinical trial as reanalyzed after the patients were classified into different TCM patterns and the underlying mechanism of how the TCM pattern influences the clinical effectiveness of interventions (TCM and biomedicine therapy) was explored. The pharmacological networks of interventions were builtup with protein and protein interaction analyses based on all the related targeted proteins obtained from PubChem. The underlying mechanism was explored by merging the pharmacological networks with the molecular networks of TCM cold and hot patterns in RA. The results show that the TCM therapy is better in treating the RA patients with TCM hot pattern, and the biomedical therapy is better in the RA patients with cold pattern. The pharmacological network of TCM intervention is merged well with the molecular network of TCM hot pattern, and the pharmacological network of biomedical therapy is merged well with the network of cold pattern. The finding indicates that molecular network analysis could give insight into the full understanding of the underlying mechanism of how TCM pattern impacts the efficacy.

Traditional chinese medicine zheng in the era of evidence-based medicine: a literature analysis

Zheng, which is also called a syndrome or pattern, is the basic unit and a key concept of traditional Chinese medicine (TCM) theory. Zheng can be considered a further stratification of patients when it is integrated with biomedical diagnoses in clinical practice to achieve higher efficacies. In an era of evidence-based medicine, confronted with the vast and increasing volume of TCM data, there is an urgent need to explore these resources effectively using techniques of knowledge discovery in databases. The application of effective data mining in the analysis of multiple extensively integrated databases can supply new information about TCM Zheng research. In this paper, we screened the published literature on TCM Zheng-related studies in the SinoMed and PubMed databases with a novel data mining approach to obtain an overview of the Zheng research landscape in the hope of contributing to a better understanding of TCM Zheng in the era of evidence-based medicine. In our results, contrast was found in Zheng in different studies, and several determinants of Zheng were identified. The data described in this paper can be used to assess Zheng research studies based on the title and certain characteristics of the abstract. These findings will benefit modern TCM Zheng-related studies and guide future Zheng study efforts.