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Artemisia Capillaris (AC) and Alisma Rhizome (AR) are natural products for the treatment of liver disorders in oriental medicine clinics. Here, we report metabolomic changes in the evaluation of the treatment effects of AC and AR on fatty livers in diabetic mice, along with a proposition of the underlying metabolic pathway. Hydrophobic and hydrophilic metabolites extracted from mouse livers were analyzed using HPLC-QTOF and CE-QTOF, respectively, to generate metabolic profiles. Statistical analysis of the metabolites by PLS-DA and OPLA-DA fairly discriminated between the diabetic, and the AC- and AR-treated mice groups. Various PEs mostly contributed to the discrimination of the diabetic mice from the normal mice, and besides, DG (18:1/16:0), TG (16:1/16:1/20:1), PE (21:0/20:5), and PA (18:0/21:0) were also associated with discrimination by s-plot. Nevertheless, the effects of AC and AR treatment were indistinct with respect to lipid metabolites. Of the 97 polar metabolites extracted from the CE-MS data, 40 compounds related to amino acid, central carbon, lipid, purine, and pyrimidine metabolism, with $p$ values less than 0.05, were shown to contribute to liver dysregulation. Following treatment with AC and AR, the metabolites belonging to purine metabolism preferentially recovered to the metabolic state of the normal mice. The AMP/ATP ratio of cellular energy homeostasis in AR-treated mice was more apparently increased ($p<0.05$) than that of AC-treated mice. On the other hand, amino acids, which showed the main alterations in diabetic mice, did not return to the normal levels upon treatment with AR or AC. In terms of metabolomics, AR was a more effective natural product in the treatment of liver dysfunction than AC. These results may provide putative biomarkers for the prognosis of fatty liver disorder following treatment with AC and AR extracts.

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. These variants may lead to immune escape or drug resistance. Natural products may be appropriate for this need due to their cost efficiency, fewer side effects, and antiviral activities. Considering these circumstances, there is a need to develop or discover more compounds that have potential to target SARS-CoV-2. 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.

Chronic respiratory diseases are long-term conditions affecting the airways and other lung components that are characterized by a high prevalence, disability rate, and mortality rate. Further optimization of their treatment is required. Natural products, primarily extracted from organisms, possess specific molecular and structural formulas as well as distinct chemical and physical properties. These characteristics grant them the advantages of safety, gentleness, accessibility, and minimal side effects. The numerous advances in the use of natural products for treating chronic respiratory diseases have provided a steady source of motivation for new drug research and development. In this paper, we introduced the pathogenesis of chronic respiratory diseases and natural products. Furthermore, we classified natural products according to their mechanism for treating chronic respiratory diseases and describe the ways in which these products can alleviate the pathological symptoms. Simultaneously, we elaborate on the signal transduction pathways and biological impacts of natural products’ targeting. Additionally, we present future prospects for natural products, considering their combination treatment approaches and administration methods. The significance of this review extends to both the research on preventing and treating chronic respiratory diseases, as well as the advancement of novel drug development in this field.

Let be the class of all algebraic probability spaces. A "natural product" is, by definition, a map which is required to satisfy all the canonical axioms of Ben Ghorbal and Schürmann for "universal product" except for the commutativity axiom. We show that there exist only five natural products, namely tensor product, free product, Boolean product, monotone product and anti-monotone product. This means that, in a sense, there exist only five universal notions of stochastic independence in noncommutative probability theory.

It is known that there are exactly five natural products, which are universal products fulfilling two normalization conditions simultaneously. We classify universal products without these extra conditions. We find a two-parameter deformation of the Boolean product, which we call (r, s)-products. Our main result states that, besides degnerate cases, these are the only new universal products. Furthermore, we introduce a GNS-construction for not necessarily positive linear functionals on algebras and study the GNS-construction for (r, s)-product functionals.

Ligand-protein inverse docking has recently been introduced as a computer method for identification of potential protein targets of a drug. A protein structure database is searched to find proteins to which a drug can bind or weakly bind. Examples of potential applications of this method in facilitating drug discovery include: (1) identification of unknown and secondary therapeutic targets of a drug, (2) prediction of potential toxicity and side effect of an investigative drug, and (3) probing molecular mechanism of bioactive herbal compounds such as those extracted from plants used in traditional medicines. This method and recent results on its applications in solving various drug discovery problems are reviewed.

Naturally occurring molecules offer intricate structures and functionality that are the basis of modern medicinal chemistry, but are under-represented in materials science. Herein, we review recent literature describing the use of abundant and relatively inexpensive, natural products for the synthesis of ligands for luminescent organometallic complexes used for organic light emitting diodes (OLEDs) and related technologies. These ligands are prepared from the renewable starting materials caffeine, camphor, pinene and cinchonine and, with the exception of caffeine, impart performance improvements to the emissive metal complexes and resulting OLED devices, with emission wavelengths that span the visible spectrum from blue to red. The advantages of these biologically-derived molecules include improved solution processibility and phase homogeneity, brighter luminescence, higher quantum efficiencies and lower turn-on voltages. While nature has evolved these carbon-skeletons for specific purposes, they also offer some intriguing benefits in materials science and technology.

The dopamine (DA) metabolism changes are significant in Parkinson’s disease (PD). Levels of monoamine oxidases (MAOs) play a critical role in DA metabolism and oxidative damage. Increased levels of the MAO-B enzyme in the elderly raise oxidative damage and enhance neurodegenerative processes. Inhibiting MAO-B as an attractive target would be the best method for treating and understanding Parkinson’s disease. This study aimed to recognize a suitable inhibitor for the MAO-B enzyme using computational biology and compared it with Safinamide as a positive control. We used various computational biology techniques such as binding free energy, virtual screening, molecular dynamics (MD), and docking considerations to achieve the goal. To obtain a potent inhibitor, 41,852 compounds were taken from the Zinc database. After preparing compounds and the MAO-B enzyme, screening was performed using AutoDock Vina software. After screening, a potent natural inhibitor (ZINC00261335) was picked, and then, subsequent MD simulations for both ZINC00261335 and Safinamide were conducted via GROMACS software. The stability of the MAO-B_ZINC00261335 complex was excellent during the simulation, and the results of MM-PBSA analysis explicated that ZINC00261335 with ($-$118.353kJmol${}^{-1}$) is more potent than Safinamide ($-$89.305kJmol${}^{-1}$). Ultimately, the ADME study (lipophilicity, drug similarity and pharmacokinetic parameters) for ZINC00261335 was revealed, which is acceptable for human use. This study indicates that ZINC00261335 is a suitable MAO-B inhibitor and a great candidate for more laboratory studies.

Skincare is one of the most important issues in the process of adapting to the changing and developing society of today’s women and men. In addition to being an area where women show more interest, a certain segment of men, if not most, care about skincare as well. In this chapter, while examining the products of some brands used for skincare, the authors has tried to find the most harmless of them. Step-wise Weight Assessment Ratio Analysis (SWARA), Additive Ratio Assessment (ARAS), and Complex Proportional Assessment (COPRAS) were used to select the most harmless skincare product. While SWARA was used to find the criteria weights, ARAS and COPRAS rules were applied to determine such a product, and the two methods were compared. Through the combination of these methods, skincare products of various brands were evaluated and determined to be the most harmless one. Pairwise combination of the three quantitative methods is a unique approach developed for the purpose of this study and it offers an objective assessment of various decision alternatives.