Vol 27, No 5 (2024)

Objective:Gene expression profile data is a good data source for people to study tumors, but gene expression data has the characteristics of high dimension and redundancy. Therefore, gene selection is a very important step in microarray data classification.

Method:In this paper, a feature selection method based on the maximum mutual information coefficient and graph theory is proposed. Each feature of gene expression data is treated as a vertex of the graph, and the maximum mutual information coefficient between genes is used to measure the relationship between the vertices to construct an undirected graph, and then the core and coritivity theory is used to determine the feature subset of gene data.

Results:In this work, we used three different classification models and three different evaluation metrics such as accuracy, F1-Score, and AUC to evaluate the classification performance to avoid reliance on any one classifier or evaluation metric. The experimental results on six different types of genetic data show that our proposed algorithm has high accuracy and robustness compared to other advanced feature selection methods.

Conclusion:In this method, the importance and correlation of features are considered at the same time, and the problem of gene selection in microarray data classification is solved.

Background:Dominating David-derived networks are widely studied due to their fractal nature, with applications in topology, chemistry, and computer sciences. The use of molecular structure descriptors is a standard procedure that is used to correlate the biological activity of molecules with their chemical structures, which can be useful in the field of pharmacology.

Objective:This article's goal is to develop analytically closed computing formulas for eccentricitybased descriptors of the second type of dominating David-derived network. Thermodynamic characteristics, physicochemical properties, and chemical and biological activities of chemical graphs are just a few of the many properties that may be determined using these computation formulas.

Methods:Vertex sets were initially divided according to their degrees, eccentricities, and cardinalities of occurrence. The eccentricity-based indices are then computed using some combinatorics and these partitions.

Results:Total eccentricity, average eccentricity, and the Zagreb index are distance-based topological indices utilized in this study for the second type of dominating David-derived network, denoted as D2(m).

Conclusion:These calculations will assist the readers in estimating the fractal and difficult-tohandle thermodynamic and physicochemical aspects of chemical structure. Apart from configuration and impact resistance, the D2(m) design has been used for fundamental reasons in a variety of technical and scientific advancements.

Background:Vicatia thibetica de Boiss is a common Tibetan medicine used for both medicine and food, belonging to the family Apiaceae. This plant has the functions of dispelling wind, removing dampness, dispersing cold, and relieving pain. It has great development potential and application prospects in food development and medicinal value.

Methods:The related references on botany, traditional uses, phytochemistry, quantitative analysis, and pharmacology of V. thibetica de Boiss had been retrieved from both online and offline databases, including PubMed, ScienceDirect, Web of Science, Elsevier, Willy, SpringLink, SciFinder, Google Scholar, Baidu Scholar, ACS publications, SciHub, Scopus, and CNKI.

Results:V. thibetica de Boiss exerts nourishing, appetizing, and digestive effects according to the theory of Tibetan medicine. Phytochemical reports have revealed that V. thibetica de Boiss contains flavonoids, coumarins, sterols, and organic acids. Meanwhile, the quantitative analysis of the chemical constituents of V. thibetica de Boiss has been done by means of UPLC-Q-TOF-MS. It has also been found that V. thibetica de Boiss possesses multiple pharmacological activities, including anti-fatigue, anti-oxidant, anti-aging, and non-toxic activities.

Conclusion:This paper has comprehensively summarized botany, traditional uses, phytochemistry, quantitative analysis, and pharmacology of V. thibetica de Boiss. It will not only provide an important clue for further studying V. thibetica de Boiss, but also offer an important theoretical basis and valuable reference for in-depth research and exploitation of this plant in the future.

The role of medicinal plants has been advantageous due to their manifestation through various cellular and molecular mechanisms. Inhibition of the monoamine oxidase enzyme is suspected to be a highly effective treatment for various neurological illnesses like Alzheimer's disease, Parkinson’s disease, depression, social phobia, and panic disorders. The study of phytochemicals and plant extracts used as a traditional source of medication revealed that they possess the vast potential for monoamine oxidase inhibition. Thus, the article focuses on the potential use of plant extracts and phytochemicals as sources of novel MAO inhibitors for treating neurological disorders. Exhaustive literature search revealed that a variety of phytochemicals from the categories such as flavonoids, alkaloids, glycosides, alkyl phenyl ketones, coumarin derivatives and essential oils have displayed potential MAO inhibition. This review highlights the progress made in the discovery and development of plant-based MAO inhibitors and aims to provide medicinal chemists with an overview of this information to aid in the development of clinically viable drugs.

Background:Osteosarcoma is a disease that primarily affects adolescents with skeletal immaturity. LncRNAs are abnormally expressed and correlated with osteosarcoma patients' prognosis. We identified aberrant expression of LncRNA SNHG25 (small nucleolar RNA host gene 25) in osteosarcoma and analyzed the molecular mechanisms by which it regulates osteosarcoma progression.

Methods:The expression levels of SNHG25 in tumour specimens and cells were measured by RTqPCR. Loss-of-function assays were conducted to investigate the functional role of SNHG25 in vitro and in vivo. Bioinformatic predictions, dual-luciferase reporter assays, and western blotting were performed to explore the possible underlying mechanisms.

Results:SNHG25 was highly expressed in osteosarcoma cells and tissues. The Kaplan–Meier curve showed that the survival rate of patients with high SNHG25 expression was significantly lower than those with low SNHG25 expression. Functional studies have indicated that inhibition of SNHG25 suppresses cell proliferation, migration, and invasion, while promoting apoptosis. SNHG25 knockdown suppresses osteosarcoma tumour growth in vivo. SNHG25 functions as a sponge for miR-497-5p in osteosarcoma cells. The level of SNHG25 was negatively correlated with that of miR-497-5p. The proliferation, invasion, and migration of osteosarcoma cells were restored by transfection of the miR-497-5p inhibitor in the SNHG25 knockdown group

Conclusion:SNHG25 was determined to function as an oncogene by promoting osteosarcoma cell proliferation, invasion, and migration through the miR-497-5p/SOX4 axis. Upregulation of SNHG25 expression indicated poor prognosis in patients with osteosarcoma, which showed that SNHG25 may serve as a potential therapeutic target and prognostic biomarker in osteosarcoma.

Introduction:Cervical cancer is one of the malignant cancers with high mortality among women worldwide. Although vaccines and early detection have reduced cervical cancer mortality, it remains a malignancy with a high mortality rate in women.

Objective:We aimed to develop a novel integrated strategy that combines metabolomics with network pharmacology to explore the therapeutic mechanisms of naringin in cervical cancer. The mechanism of naringin intervention in cervical cancer was initially clarified by metabolomics and network pharmacology.

Methods:The method of LC-MS and network pharmacology for the detection and identification of potential biomarkers and the mechanisms of action of naringin was used. The metabolites were detected and identified based on ultra-high-performance liquid chromatography coupled with Quadrupole- Exactive Orbitrap MS (UHPLC-Q-Exactive Orbitrap MS) and followed by the network pharmacology analysis.

Results:In network pharmacology, naringin played a synergetic role through regulatory shared pathways, such as steroid hormone biosynthesis, sphingolipid signaling pathway and arachidonic acid metabolism, etc. Besides, the metabolomics analysis showed that 20 differential metabolites and 10 metabolic pathways were mainly involved in the therapeutic effect of naringin on cervical cancer. The result showed that naringin treatment for cervical cancer mainly occurs through the following metabolic pathways: amino acid metabolism and arachidonic acid metabolism.

Conclusion:This work provided valuable information and a scientific basis for further studies of naringin in the treatment of cervical cancer.

Background:Fuzi-Gancao herb couple is one of the most common herb couples involved in the TCM formula, which was used for the treatment of chronic diseases. The herb couple has a hepatoprotective effect. However, its main components and therapeutic mechanism are not yet clear. This study aims to elucidate the therapeutic effect and mechanism of the Fuzi-Gancao herb couple on NAFLD from animal experiments, network pharmacology, and molecular docking.

Methods:60 Male C57BL/6 mice (20 g ± 2 g) were randomly divided into six groups including the blank group (n=10) and NALFD group (n=50). The mice of the NALFD group were fed with a high-fat diet for 20 weeks to establish the NAFLD model and the NALFD mice were randomly divided into five groups including positive group (berberine), model group and F-G groups with three dosages (0.257, 0.514, 0.771 g/kg) (n=10). After 10 weeks of administration, the serum was collected for the analysis of ALT, AST, LDL-c, HDL-c, and TC, and liver tissues were collected for pathological analysis. The TCMAS database was used to collect the main components and targets of the Fuzi-Gancao herb couple. The GeneCards database was used to collect NAFLD-related targets, and the key targets were obtained by intersecting with herbal targets. The diseasecomponent- target relationship diagram was constructed by Cytoscape 3.9.1. The obtained key targets were imported into the String database to obtain the PPI network, and imported into the DAVID database for KEGG pathway analysis and GO analysis. Finally, the key targets and key gene proteins were imported into Discovery Studio 2019 for molecular docking verification.

Results:In this study, H-E staining indicated the pathological changes of liver tissue in Fuzi- Gancao groups were significantly improved, and the levels of AST, ALT, TC, HDL-c, and LDL-c in serum of Fuzi-Gancao groups decreased in a dose-dependent manner, compared with the model group. 103 active components and 299 targets in the Fuzi-Gancao herb couple were confirmed in the TCMSP database and 2062 disease targets in NAFLD were obtained. 142 key targets and 167 signal pathways were screened, such as the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, IL-17 signaling pathway, TNF signaling pathway, and so on. The main bioactive ingredients of Fuzi-Gancao herb couple in the treatment of NAFLD are quercetin, kaempferol, naringenin, inermine, (R)-norcoclaurine, isorhamnetin, ignavine, 2,7-Dideacetyl-2,7- dibenzoyl-taxayunnanine F, glycyrol mainly involving IL6, AKT1, TNF, TP53, IL1B, VEGFA and other core targets. Molecular docking analysis indicated that there is a good affinity between the key components and the key targets.

Conclusion:This study preliminarily explained the main components and mechanism of the Fuzi- Gancao herb couple in the treatment of NAFLD and provided an idea for subsequent research.