Lonicerae Japonicae Flos has been used as a tea and medicine for more than 1,500 years. It has the functions of clearing heat, detoxification, and is often used to treat carbuncle, furuncle, throat arthralgia, erysipelas, heat-toxic blood dysentery, febrile fever. This paper summarizes the botany, ethnopharmacology, chemical composition and pharmacological action of Lonicerae Japonicae Flos from 1986 to 2022, and looks forward to the future research direction of Lonicerae Japonicae Flos. At present, the components isolated from Lonicerae Japonicae Flos include essential oils, organic acids, flavonoids, iridoids, saponins and other compounds. It has the effects of anti-inflammation, anti-virus, anti-bacteria, anti-oxidation, anti-tumor, protect liver and galltesticles, hypotensive, hypolipidemic, anti-thrombosis, anti-allergy, immune regulation and so on. It is often used in clinical treatment of diarrhea, hematochezia, febrile disease, exogenous wind-heat, and cold, swelling and toxin of carbuncle, sore throat and so on. The comprehensive evaluation of the quality of Lonicerae Japonicae Flos and the understanding of multi-target network pharmacology also need to be studied. As a kind of health food with high value, LJF is worthy of further promotion and development.

Bupleuri Radix (BR) is the dry root of Bupleurum chinense DC. and Bupleurum scorzonerifolium Willd. It has the functions of evacuation and antipyretic, soothing liver and relieving depression and often used to treat cold fever, chest and rib swelling pain, irregular menstruation, uterine prolapse, rectocele and other diseases. In this paper, the botany, traditional application, phytochemistry, pharmacology and toxicity of BR were reviewed. On the basis of limited literature, the analytical method, quality control, processing method, processing effect and pharmacokinetics of BR were summarized and analyzed for the first time. This review makes an in-depth discussion on the shortcomings of the current research on BR, and puts forward its own views and solutions. This has never been summarized in the previous review of BR. It is of great practical significance for future scholars to find a breakthrough point in the study of BR. So far, its mechanism has not been satisfactorily explained. Moreover, the comprehensive quality evaluation and multi-target network pharmacology of BR need to be further studied. In the future, more in vitro and in vivo experiments are needed to give full play to the therapeutic potential of BR.

Codonopsis Radix, a traditional Chinese medicine in China, has great medicinal and scientific value. Moreover, it can also be used as a health product in daily diet. This paper reviews the botany, ethnopharmacology, phytochemistry, analysis method and quality control, processing methods, pharmacological effects, pharmacokinetics and toxicity related to Codonopsis Radix. The information of Codonopsis Radix is obtained from scientific databases (such as Baidu Scholar, CNKI, Google Scholar, PubMed, Science Direct, Web of Science, and SciFinder Scholar), Chinese herbal classics, Chinese Pharmacopoeia, PhD and MSc dissertations, and so on. The chemical components mainly include alkaloids, alkynes and polyacetylenes, flavonoids, lignans, steroids, terpenoids, organic acids, volatile oils, saccharides and other components, which have a wide range of neuroprotective effects, protection of gastrointestinal mucosa and anti-ulcer, regulation of body immunity, anti-tumor, endocrine regulation, improvement of hematopoietic function, cardiovascular protection, anti-aging and antioxidant effects. In conclusion, this paper summarizes in depth the shortcomings of the current research on Codonopsis Radix and proposes corresponding solutions. At the same time, this paper provides theoretical support for further research on the biological function and potential clinical efficacy of Codonopsis Radix.

Farfarae Flos (FF) is the dried flower bud of Tussilago farfara L, which has antitussive, expectorant, and anti-inflammatory effects. However, little research on the main active composition of FF has been reported. The purpose of this study is to find the main active compounds responsible for the three pharmacological effects (i.e., antitussive, expectorant, and anti-inflammatory effects) of Farfarae Flos, based on the spectrum–effect relationship combined with chemometrics. First, this study uses the UPLC-QDA method to establish the chromatography fingerprint of Farfarae Flos, which is combined with chemometrics to analyze 18 batches of samples. Then, we study the antitussive, expectorant, and anti-inflammatory effects of Farfarae Flos. Finally, the spectrum–effect relationship between the fingerprint and the three pharmacological effects are studied by grey correlation analysis and partial least squares regression. The results show that four, four, and three main active constituents were found for the antitussive, expectorant, and anti-inflammatory pharmacological effects, respectively. In conclusion, we found the main active compounds corresponding to the main pharmacodynamic effects of Farfarae Flos. To our knowledge, this is the first time that spectrum–effect relationships in FF have been established using both raw and processed samples, which provides an experimental basis for further studies on the pharmacodynamic material basis of Farfarae Flos, as well as providing reference for the comprehensive evaluation of Farfarae Flos quality and the development of substitute resources.

The incidence of hepatocellular carcinoma (HCC) has been increasing in recent years. With the development of various detection technologies, machine learning is an effective method to screen disease characteristic genes. In this study, weighted gene co-expression network analysis (WGCNA) and machine learning are combined to find potential biomarkers of liver cancer, which provides a new idea for future prediction, prevention, and personalized treatment. In this study, the “limma” software package was used. P < .05 and log2 |fold-change| > 1 is the standard screening differential genes, and then the module genes obtained by WGCNA analysis are crossed to obtain the key module genes. Gene Ontology and Kyoto Gene and Genome Encyclopedia analysis was performed on key module genes, and 3 machine learning methods including lasso, support vector machine-recursive feature elimination, and RandomForest were used to screen feature genes. Finally, the validation set was used to verify the feature genes, the GeneMANIA (http://www.genemania.org) database was used to perform protein–protein interaction networks analysis on the feature genes, and the SPIED3 database was used to find potential small molecule drugs. In this study, 187 genes associated with HCC were screened by using the “limma” software package and WGCNA. After that, 6 feature genes (AADAT, APOF, GPC3, LPA, MASP1, and NAT2) were selected by RandomForest, Absolute Shrinkage and Selection Operator, and support vector machine-recursive feature elimination machine learning algorithms. These genes are also significantly different on the external dataset and follow the same trend as the training set. Finally, our findings may provide new insights into targets for diagnosis, prevention, and treatment of HCC. AADAT, APOF, GPC3, LPA, MASP1, and NAT2 may be potential genes for the prediction, prevention, and treatment of liver cancer in the future.