The American journal of Chinese medicine
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Review
Ginsenoside Rg5: A Review of Anticancer and Neuroprotection with Network Pharmacology Approach.
Ginsenoside Rg5 (G-Rg5) is a rare ginsenoside isolated from ginseng (Panax ginseng C. A. Meyer), and this compound is increasingly known for its potent pharmacological activities. ⋯ Likewise, molecular docking of the related proteins was performed, and the binding energies were all less than [Formula: see text]7.0[Formula: see text]kJ/mol, indicating that these proteins had excellent binding capacity with G-Rg5. The network pharmacology results revealed many potential G-Rg5 mechanisms, which need to be further explored. We expect that the network pharmacology approach and molecular docking techniques can help us gain a deeper understanding of the therapeutic mechanisms of different ginsenosides and even the ginseng plant, for further developing their therapeutic potential as well as clinical applications.
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Diabetic nephropathy (DN) is a common microvascular complication of diabetes mellitus (DM), which can lead to renal failure in diabetic patients. At present, the first-line drugs for DN are mainly the renin-angiotensin system (RAS) inhibitors or angiotensin receptor blockers, and the latest approved aldosterone receptor antagonist finerenone, which delay the progression of DN to end-stage renal disease (ESRD), but the therapeutic effect is still not ideal. ⋯ In recently years, the therapeutic effects and mechanisms of TCM prescription, Chinese herbal medicine, and its active components on DN have received extensive attention in new drug development. This paper reviews the research progress of the mechanism of TCM on DN.
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Machine learning (ML), as a branch of artificial intelligence, acquires the potential and meaningful rules from the mass of data via diverse algorithms. Owing to all research of traditional Chinese medicine (TCM) belonging to the digitalization of clinical records or experimental works, a massive and complex amount of data has become an inextricable part of the related studies. It is thus not surprising that ML approaches, as novel and efficient tools to mine the useful knowledge from data, have created inroads in a diversity of scopes of TCM over the past decade of years. ⋯ The eight common applied fields are divided into two parts: one for TCM, such as the diagnosis of diseases, the determination of syndromes, and the analysis of prescription, and the other for the related researches of Chinese herbal medicine, such as the quality control, the identification of geographic origins, the pharmacodynamic material basis, the medicinal properties, and the pharmacokinetics and pharmacodynamics. Additionally, this paper discusses the function and feature difference among ML approaches when they are applied to the corresponding fields via comparing their principles. The specificity of each approach to its applied fields has also been affirmed, whereby laying a foundation for subsequent studies applying ML approaches to TCM.
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Coronavirus disease 2019 (COVID-19) is currently a worldwide pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, there are no drugs that can specifically combat SARS-CoV-2. Besides, multiple SARS-CoV-2 variants are circulating globally. ⋯ Therefore, we searched for articles on natural products describing anti-SARS-CoV-2 activities by targeting the SARS-CoV-2 life cycle and the cytokine storm in COVID-19 from academic databases. We reviewed anti-SARS-CoV-2 activities of natural products, especially those that target the SARS-CoV-2 life cycle (angiotensin-converting enzyme 2, transmembrane serine protease 2, cathepsin L, 3CL protease, PL protease, RNA-dependent RNA polymerase, and helicase) and cytokine storm in COVID-19. This review may provide a repurposed approach for the discovery of specific medications using natural products to treat COVID-19 through targeting the SARS-CoV-2 life cycle and the cytokine storm in COVID-19.
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Currently, there is a lack of adequate methods to assess insomnia objectively. This study addresses the usefulness of tongue features and oral microbial profile as a potential diagnostic biomarker of insomnia. One hundred insomniac patients and 20 healthy control subjects were selected. ⋯ On the other hand, the oral microbial communities of the insomniac patients revealed greater alpha and beta diversities in the non-coating group vs. the thick-coating group. The alpha and beta diversities were higher in orotype1 than orotype2. Collectively, this study highlighted that the lightness of tongue body and tongue coating as well as oral microbial profiles of SR1, Actinobacteria, Clostridia and Lachnospiraceae_unclassified could be considered potential biomarkers of insomnia.