Hand-foot-and-mouth disease (HFMD), with poorly understood pathogenesis, has become a major public health threat across Asia Pacific. In order to characterize the metabolic changes of HFMD and to unravel the regulatory role of clinical intervention, we have performed a metabolomics approach in a clinical trial. In this study, metabolites profiling was performed by liquid chromatography/quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) platform from the HFMD clinical patient samples. The outcome of this study suggested that 31 endogenous metabolites were mainly involved and showed marked perturbation in HFMD patients. In addition, combination therapy intervention showed normalized tendency in HFMD patients in differential pathway. Taken together, these results indicate that metabolomics approach can be used as a complementary tool for the detection and the study of the etiology of HFMD.

Androgens have been linked to the onset, severity, and progression of rheumatoid arthritis (RA). In traditional Chinese medicine (TCM), the most common pattern in RA is kidney deficiency, which partly corresponds to a low sex hormone state. In this study, TCM kidney deficiency was induced in male Sprague-Dawley rats with castration surgery, and a TCM preparation, Yi Shen Juan Bi Pill (YJB), was used to treat collagen induced arthritis (CIA) rats with castration. Metabolomic technique was used to evaluate the pharmacological mechanism in castrated CIA rats treated by YJB. The results showed that castration significantly increased the severity of the arthritis in rats but was ameliorated by YJB. Its pharmacological mechanism was partially associated with lipid metabolites involving free fatty acid (FFA) and lysophosphatidylcholine (LPC). In conclusion, the experimental results demonstrate the protective effect of YJB on the TCM kidney deficiency pattern induced by androgen deficiency in CIA rats and support that YJB should be used for the clinical treatment of RA with TCM kidney deficiency pattern.

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.

Wang-Bi Capsule (WB), a traditional Chinese medicine- (TCM-) based herbal formula, is currently used in clinic for the treatment of rheumatoid arthritis (RA) with positive clinical effects. However, its pharmacological mechanism of action in RA is still obscure. Therefore, this study established a collagen-induced arthritis (CIA) mice model to examine the efficacy of WB by using arthritis score, histological analysis, and micro-CT examination. Proinflammatory cytokines expression, osteoclast number, OPG/RANKL system, and NF-κB activation were then detected to further investigate the mechanism of WB in RA treatment. The results indicated that WB could alleviate the erythema and swelling of paws in CIA mice. It also inhibited the infiltration of inflammatory cells and bone destruction and increased bone density in joints of CIA mice. Mechanistic studies showed that WB treatment decreased the production of IL-1β, IL-6, and TNF-α in serum and joints of CIA mice. Moreover, it reduced the osteoclast number, increased OPG level, decreased RANKL level, and inhibited the activation of NF-κB in joints of CIA mice. In conclusion, this study demonstrated that WB could effectively alleviate disease progression of CIA mice by decreasing the IL-1β, IL-6, and TNF-α levels, modulating the OPG/RANKL system, and inhibiting the activation of NF-κB.

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.

IN TRADITIONAL CHINESE MEDICINE (TCM), PATIENTS WITH RHEUMATOID ARTHRITIS (RA) CAN BE CLASSIFIED INTO TWO MAIN PATTERNS: cold-pattern and heat-pattern. This paper identified the network-based gene expression biomarkers for both cold- and heat-patterns of RA. Gene expression profilings of CD4+ T cells from cold-pattern RA patients, heat-pattern RA patients, and healthy volunteers were obtained using microarray. The differentially expressed genes and related networks were explored using DAVID, GeneSpring software, and the protein-protein interactions (PPI) method. EIF4A2, CCNT1, and IL7R, which were related to the up-regulation of cell proliferation and the Jak-STAT cascade, were significant gene biomarkers of the TCM cold pattern of RA. PRKAA1, HSPA8, and LSM6, which were related to fatty acid metabolism and the I-κB kinase/NF-κB cascade, were significant biomarkers of the TCM heat-pattern of RA. The network-based gene expression biomarkers for the TCM cold- and heat-patterns may be helpful for the further stratification of RA patients when deciding on interventions or clinical trials.

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.

The potential toxicity of herbal drugs, particularly drug-induced liver injury (DILI), has received extensive attention as the use of Chinese herbal medicine has rapidly increased globally. As a classic Chinese patent medicine, Zhuang Gu Guan Jie Wan (ZGGJW) has been brought into focus recently because of its satisfactory therapeutic effects on osteoarthritis (OA) as well as its unanticipated side effects. This study aimed to decipher the puzzling phenomenon of liver injury developing in response to ZGGJW that varies by the subtype of OA. Normal, anterior cruciate ligament transaction (ACLT) and partial medial meniscectomy (MMx) induced OA and ovariectomy combined with ACLT and partial MMx induced rat models were used and treated orally with ZGGJW or distilled water for 30 days. The results from histopathology, biochemistry, and immunohistochemistry showed that ZGGJW induced liver injury, increased the level of malondialdehyde (MDA), and decreased the levels of total antioxidation capability (T-AOC), superoxide dismutase (SOD), interleukin-22 (IL-22), and signal transducer and activator of transcription factor 3 (STAT3) in the liver of normal rats, while liver injury was alleviated and showed different tendencies in the above markers for ACLT and partial MMx induction rats and ovariectomy combined with ACLT and partial MMx induction rats after ZGGJW treatment. In the OA disease states, hepatic injury induced by ZGGJW could be associated with an impairment in antioxidant capacity and the high levels of IL-22 and STAT3 after ZGGJW treatment may be responsible for the slight hepatic injury of ZGGJW based on the subtype of OA. This study provides a novel approach to better understanding of the risks and limitations when using potentially toxic Chinese patent medicine in clinical applications.

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.