Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject’s phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

Renal fibrosis (RF) is the end stage of several chronic kidney diseases. Its series of changes include excessive accumulation of extracellular matrix, epithelial-mesenchymal transition (EMT) of renal tubular cells, fibroblast activation, immune cell infiltration, and renal cell apoptosis. RF can eventually lead to renal dysfunction or even renal failure. A large body of evidence suggests that natural products in traditional Chinese medicine (TCM) have great potential for treating RF. In this article, we first describe the recent advances in RF treatment by several natural products and clarify their mechanisms of action. They can ameliorate the RF disease phenotype, which includes apoptosis, endoplasmic reticulum stress, and EMT, by affecting relevant signaling pathways and molecular targets, thereby delaying or reversing fibrosis. We also present the roles of nanodrug delivery systems, which have been explored to address the drawback of low oral bioavailability of natural products. This may provide new ideas for using natural products for RF treatment. Finally, we provide new insights into the clinical prospects of herbal natural products.

Natural products derived from herbal medicine are a fruitful source of lead compounds because of their structural diversity and potent bioactivities. However, despite the success of active compounds derived from herbal medicine in drug discovery, some approaches cannot effectively elucidate the overall effect and action mechanism due to their multi-component complexity. Fortunately, mass spectrometry-based metabolomics has been recognized as an effective strategy for revealing the effect and discovering active components, detailed molecular mechanisms, and multiple targets of natural products. Rapid identification of lead compounds and isolation of active components from natural products would facilitate new drug development. In this context, mass spectrometry-based metabolomics has established an integrated pharmacology framework for the discovery of bioactivity-correlated constituents, target identification, and the action mechanism of herbal medicine and natural products. High-throughput functional metabolomics techniques could be used to identify natural product structure, biological activity, efficacy mechanisms, and their mode of action on biological processes, assisting bioactive lead discovery, quality control, and accelerating discovery of novel drugs. These techniques are increasingly being developed in the era of big data and use scientific language to clarify the detailed action mechanism of herbal medicine. In this paper, the analytical characteristics and application fields of several commonly used mass spectrometers are introduced, and the application of mass spectrometry in the metabolomics of traditional Chinese medicines in recent years and its active components as well as mechanism of action are also discussed.

Animal models play a crucial role in studying the pathogenesis of diseases, developing new drugs, identifying disease risk markers, and improving means of prevention and treatment. However, modeling diabetic kidney disease (DKD) has posed a challenge for scientists. Although numerous models have been successfully developed, none of them can encompass all the key characteristics of human DKD. It is essential to choose the appropriate model according to the research needs, as different models develop different phenotypes and have their limitations. This paper provides a comprehensive overview of biochemical and histological phenotypes, modeling mechanisms, advantages and limitations of DKD animal models, in order to update relevant model information and provide insights and references for generating or selecting the appropriate animal models to fit different experimental needs.

Citri Reticulatae Pericarpium (CRP), also known as “chenpi”, is the most common qi-regulating drug in traditional Chinese medicine. It is often used to treat cough and indigestion, but in recent years, it has been found to have multi-faceted anti-cancer effects. This article reviews the pharmacology of CRP and the mechanism of the action of flavonoids, the key components of CRP, against cancers including breast cancer, lung cancer, prostate cancer, hepatic carcinoma, gastric cancer, colorectal cancer, esophageal cancer, cervical cancer, bladder cancer and other cancers with a high diagnosis rate. Finally, the specific roles of CRP in important phenotypes such as cell proliferation, apoptosis, autophagy and migration–invasion in cancer were analyzed, and the possible prospects and deficiencies of CRP as an anticancer agent were evaluated.