An Integrative Metabolomic and Network Pharmacology Study Revealing the Regulating Properties of Xihuang Pill That Improves Anlotinib Effects in Lung Cancer

Jiawei Danxuan Koukang Alleviates Arecoline Induced Oral Mucosal Lesions: Network Pharmacology and the Combined Ultra-High Performance Liquid Chromatography (UPLC) and Mass Spectrometry (MS)

Purpose

Arecoline is one of the main toxic components of arecoline to cause oral mucosal lesions or canceration, which seriously affects the survival and life quality of patients. This study analyzed the mechanism of Jiawei Danxuan Koukang (JDK) in alleviating arecoline induced oral mucosal lesions, to provide new insights for the treatment of oral submucosal fibrosis (OSF) or cancerosis.

Methods

Metabolomics was applied to analyze the composition of JDK and serum metabolites. The active ingredients of JDK were analyzed by the combined ultra-high performance liquid chromatography and mass spectrometry. The target network of JDK, metabolites and OSF was analyzed by network pharmacology, and molecular docking. Oral mucosal lesions and fibrosis were analyzed by HE and Masson staining. Cell differentiation, proliferation and apoptosis were detected. The expressions of α-SMA, Collagen I, Vimentin, Snail, E-cadherin, AR and NOTCH1 were detected by Western blot.

Results

Arecoline induced the gradual atrophy and thinning of rat oral mucosal, collagen accumulation, the increase expressions of fibrosis-related proteins and Th17/Treg ratio. JDK inhibited arecoline-induced oral mucosal lesions and inflammatory infiltration. Arecoline induced changes of serum metabolites in Aminoacyl-tRNA biosynthesis, Alanine, aspartate and glutamate metabolism and Arginine biosynthesis pathways, which were reversed by M-JDK. Quercetin and AR were the active ingredients and key targets of JDK, metabolites and OSF interaction. Arecoline promoted the expression of AR protein, and the proliferation of oral fibroblasts. Quercetin inhibited the effect of arecoline on oral fibroblasts, but was reversed by AR overexpression. Arecoline induced NOTCH1 expression in CAL27 and SCC-25 cells, and promoted cell proliferation, but was reversed by M-JDK or quercetin.

Conclusion

JDK improved the arecoline-induced OSF and serum metabolite functional pathway. Quercetin targeted AR protein to improve arecoline-induced OSF. JDK and quercetin inhibited arecoline-induced NOTCH1 protein expression in CAL27 and SCC-25 cells to play an anti-oral cancer role.

Meta-analysis of the efficacy and safety of Xihuang Pills/capsules in adjuvant treatment of uterine cervical neoplasms

BACKGROUND

Xihuang Pills/Capsules have a longstanding history of utilization in traditional Chinese medicine (TCM) for treating cancer. Nevertheless, a comprehensive investigation is required regarding the specific impacts and safety of Xihuang Pills/Capsules in individuals with uterine cervical neoplasms. Thus, conducting a meta-analysis is essential to evaluate the clinical effectiveness of combining Xihuang Pills/Capsules with Western medicine in patients with cervical neoplasms.

METHODS

The research involved searching 5 English and 4 Chinese databases for randomized controlled trials (RCTs) investigating the use of Xihuang Pills/Capsules in conjunction with Western medicine for treating uterine cervical neoplasms. Subsequently, statistical analysis was carried out using Review Manager software (version 5.3).

RESULTS

This research encompassed 10 RCTs involving 937 patients. The findings revealed that the combination of Xihuang Pills/Capsules with Western medicine treatment led to improvements in various aspects of the patients' condition. Specifically, there was an enhancement in the short-term efficacy rate (risk ratio [RR] = 1.14, 95% confidence interval [CI]: 1.06-1.22, P = .0003), Karnofsky performance score (KPS) (mean difference [MD] = 5.90, 95% CI: 0.54-11.26, P = .03), survival rates, CD3+, CD3 + CD4+, CD3 + CD8+, CD3-CD56 + cells, and immunoglobulin M in patients with uterine cervical neoplasms. Moreover, the combination treatment resulted in a reduction of adverse reactions, including gastrointestinal reactions (RR = 0.52, 95% CI: 0.42-0.64, P < .00001), radiation proctitis (RR = 0.47, 95% CI: 0.33-0.68, P < .0001), myelosuppression (RR = 0.41, 95% CI: 0.26-0.64, P < .0001), as well as carcinoembryonic antigen (CEA) and squamous cell carcinoma antigen (SCC-Ag) levels. Additionally, the treatment exhibited an inhibitory effect on white blood cells (WBCs) and platelets (PLTs).

CONCLUSION

The amalgamation of Xihuang Pills/Capsules with conventional anti-tumor therapy proves to be both effective and safe in the treatment of cervical neoplasms. However, further validation through high-quality RCTs is necessary to substantiate these findings.

Integrated metabolomics, network pharmacology and biological verification to reveal the mechanisms of Nauclea officinalis treatment of LPS-induced acute lung injury

BACKGROUND

Acute lung injury (ALI) is a severe inflammatory disease, underscoring the urgent need for novel treatments. Nauclea officinalis Pierre ex Pitard (Danmu in Chinese, DM) is effective in treating inflammatory respiratory diseases. However, there is still no evidence of its protective effect against ALI.

METHODS

Metabolomics was applied to identify the potential biomarkers and pathways in ALI treated with DM. Further, network pharmacology was introduced to predict the key targets of DM against ALI. Then, the potential pathways and key targets were further verified by immunohistochemistry and western blot assays.

RESULTS

DM significantly improved lung histopathological characteristics and inflammatory response in LPS-induced ALI. Metabolomics analysis showed that 16 and 19 differential metabolites were identified in plasma and lung tissue, respectively, and most of these metabolites tended to recover after DM treatment. Network pharmacology analysis revealed that the PI3K/Akt pathway may be the main signaling pathway of DM against ALI. The integrated analysis of metabolomics and network pharmacology identified 10 key genes. These genes are closely related to inflammatory response and cell apoptosis of lipopolysaccharide (LPS)-induced ALI in mice. Furthermore, immunohistochemistry and western blot verified that DM could regulate inflammatory response and cell apoptosis by affecting the PI3K/Akt pathway, and expression changes in Bax and Bcl-2 were also triggered.

CONCLUSION

This study first integrated metabolomics, network pharmacology and biological verification to investigate the potential mechanism of DM in treating ALI, which is related to the regulation of inflammatory response and cell apoptosis. And the integrated analysis can provide new strategies and ideas for the study of traditional Chinese medicines in the treatment of ALI.

Metabolomics Combined with Network Pharmacology-Based Strategy to Reveal the Underlying Mechanism of Zhenhuang Submicron Emulsion in Treating Oropharyngeal Mucositis Complications of Radiation Therapy for Head and Neck Cancer

Introduction

Head and neck tumors account for more than 6% of all cancers. The primary treatment for tumors of the head and neck is radiation therapy, which can induce oropharyngeal mucositis as a side effect. At present, there is no widely available therapeutic for the treatment of oropharyngeal mucositis in clinical practice. Based on the traditional prescription Liushen Wan, the pathogenesis and pathology, we developed a new Chinese medicine prescription and made Zhenhuang submicron emulsion (ZHSE) spray, which has an efficacious therapeutic effect for oropharyngeal mucositis. However, its mechanism is unclear.

Methods

This research explored the mechanism behind the modulatory effects of ZHSE by a strategy of metabolomics and network pharmacology. Multivariate data analyses, including unsupervised principal component analysis (PCA) and supervised orthogonal partial least squares discriminant analysis (OPLS-DA), were performed. Potential biomarkers were identified depending on the mass-charge ratio of the selected compound. Statistical and pathway enrichment analysis was performed in the KEGG pathway database. Network pharmacology combining metabolomic analyses was conducted to illustrate the key targets and pathways.

Results

Critical metabolic pathways were investigated, 56f biomarkers were enriched and key metabolites such as linoleic acid, 9,10-epoxyoctadecenoic acid, acetoacetic acid and citric acid were identified. A complex network of “compound-target-potential metabolite” interactions was drawn to illuminate the regulation of chemical constituents on key metabolites. These findings manifest that ZHSE regulates endogenous metabolite disorders during the treatment of oropharyngeal mucositis by various constituents, interacting with multiple targets associated with inflammation and pain.

Conclusion

In this work, we determined several critical biomarkers and metabolic pathways and identified the possible regulatory mechanism by which ZHSE functions in the treatment of oropharyngeal mucositis. This study provides a new perspective on integrating metabolomics and network pharmacology for exploring improved therapy for head and neck tumors based on the traditional classic prescription of LSW.

Practical Implementation of Artificial Intelligence-Based Deep Learning and Cloud Computing on the Application of Traditional Medicine and Western Medicine in the Diagnosis and Treatment of Rheumatoid Arthritis

Rheumatoid arthritis (RA), an autoimmune disease of unknown etiology, is a serious threat to the health of middle-aged and elderly people. Although western medicine, traditional medicine such as traditional Chinese medicine, Tibetan medicine and other ethnic medicine have shown certain advantages in the diagnosis and treatment of RA, there are still some practical shortcomings, such as delayed diagnosis, improper treatment scheme and unclear drug mechanism. At present, the applications of artificial intelligence (AI)-based deep learning and cloud computing has aroused wide attention in the medical and health field, especially in screening potential active ingredients, targets and action pathways of single drugs or prescriptions in traditional medicine and optimizing disease diagnosis and treatment models. Integrated information and analysis of RA patients based on AI and medical big data will unquestionably benefit more RA patients worldwide. In this review, we mainly elaborated the application status and prospect of AI-assisted deep learning and cloud computation-oriented western medicine and traditional medicine on the diagnosis and treatment of RA in different stages. It can be predicted that with the help of AI, more pharmacological mechanisms of effective ethnic drugs against RA will be elucidated and more accurate solutions will be provided for the treatment and diagnosis of RA in the future.