Recent developments in our understanding of the implications of traditional African medicine on drug metabolism

Traditional Medicinal Plants as a Source of Antituberculosis Drugs: A System Review

Medicinal plants are the chief components in the different oriental formulations in different traditional medical systems worldwide. As a thriving source of medicine, the medicinal plants with antituberculosis (TB) properties inspire the pharmacists to develop new drugs based on their active components or semimetabolites. In the present review, the anti-TB medicinal plants were screened from the scientific literatures, based on the botanical classification and the anti-TB activity. The obtained anti-TB medicinal plants were categorized into three different categories, viz., 159 plants critically examined with a total 335 isolated compounds, 131 plants with their crude extracts showing anti-TB activity, and 27 plants in literature with the prescribed formula by the traditional healers. Our systemic analysis on the medicinal plants can assist the discovery of novel and more efficacious anti-TB drugs.

Anticancer Potential of Sutherlandia frutescens and Xysmalobium undulatum in LS180 Colorectal Cancer Mini-Tumors

Colorectal cancer remains to be one of the leading causes of death worldwide, with millions of patients diagnosed each year. Although chemotherapeutic drugs are routinely used to treat cancer, these treatments have severe side effects. As a result, the use of herbal medicines has gained increasing popularity as a treatment for cancer. In this study, two South African medicinal plants widely used to treat various diseases, Sutherlandia frutescens and Xysmalobium undulatum, were evaluated for potential activity against colorectal cancer. This potential activity for the treatment of colorectal cancer was assessed relative to the known chemotherapeutic drug, paclitaxel. The cytotoxic activity was considered in an advanced three-dimensional (3D) sodium alginate encapsulated LS180 colorectal cancer functional spheroid model, cultured in clinostat-based rotating bioreactors. The LS180 cell mini-tumors were treated for 96 h with two concentrations of each of the crude aqueous extracts or paclitaxel. S. frutescens extract markedly decreased the soluble protein content, while decreasing ATP and AK per protein content to below detectable limits after only 24 h exposure. X. undulatum extract also decreased the soluble protein content, cell viability, and glucose consumption. The results suggested that the two phytomedicines have potential to become a source of new treatments against colorectal cancer.

Antiretroviral and cytotoxic activities of Tityus obscurus synthetic peptide

New drugs are constantly in demand, and nature's biodiversity is a rich source of new compounds for therapeutic applications. Synthetic peptides based on the transcriptome analysis of scorpion venoms of Tityus obscurus, Opisthacanthus cayaporum, and Hadrurus gertschi were assayed for their cytotoxic and antiretroviral activity. The Tityus obscurus scorpion-derived synthetic peptide (FFGTLFKLGSKLIPGVMKLFSKKKER), in concentrations ranging from 6.24 to 0.39 μM, proved to be the most active one against simian immunodeficiency virus (SIV) replication in the HUT-78 cell line and in primary human leukocytes, with the lowest toxicity for these cells. The immune cellular response evaluated in primary human leukocytes treated with the most promising peptide and challenged with SIV infection exhibited production of cytokines such as interleukin (IL)-4, IL-6, IL-8, IL-10, and interferon-γ, which could be involved in cell defense mechanisms to overcome viral infection through proinflammatory and anti-inflammatory pathways, similar to those evoked for triggering the mechanisms exerted by antiviral restriction factors.

Characterization of an Alginate Encapsulated LS180 Spheroid Model for Anti-colorectal Cancer Compound Screening

Colorectal cancer is one of the leading causes of cancer-related deaths. A main problem for its treatment is resistance to chemotherapy, requiring the development of new drugs. The success rate of new candidate cancer drugs in clinical trials remains dismal. Three-dimensional (3D) cell culture models have been proposed to bridge the current gap between in vitro chemotherapeutic studies and the human in vivo, due to shortcomings in the physiological relevance of the commonly used two-dimensional cell culture models. In this study, LS180 colorectal cancer cells were cultured as 3D sodium alginate encapsulated spheroids in clinostat bioreactors. Growth and viability were evaluated for 20 days to determine the ideal experimental window. The 3- (4,5- dimethylthiazol- 2- yl)-2,5-diphenyltetrazolium bromide assay was then used to establish half maximal inhibitory concentrations for the standard chemotherapeutic drug, paclitaxel. This concentration was used to further evaluate the established 3D model. During model characterization and evaluation soluble protein content, intracellular adenosine triphosphate levels, extracellular adenylate kinase, glucose consumption, and P-glycoprotein (P-gp) gene expression were measured. Use of the model for chemotherapeutic treatment screening was evaluated using two concentrations of paclitaxel, and treatment continued for 96 h. Paclitaxel caused a decrease in cell growth, viability, and glucose consumption in the model. Furthermore, relative expression of P-gp increased compared to the untreated control group. This is a typical resistance-producing change, seen in vivo and known to be a result of paclitaxel treatment. It was concluded that the LS180 sodium alginate encapsulated spheroid model could be used for testing new chemotherapeutic compounds for colorectal cancer.

A systematic literature review and classification of knowledge discovery in traditional medicine

INTRODUCTION AND OBJECTIVE

Despite the importance of machine learning methods application in traditional medicine there is a no systematic literature review and a classification for this field. This is the first comprehensive literature review of the application of data mining methods in traditional medicine.

METHOD

We reviewed 5 database between 2000 to 2017 based on the Kitchenham systematic review methodology. 502 articles were identified and reviewed for their relevance to application of machine learning methods in traditional medicine, 42 selected papers were classified and categorized on four dimension; 1) application domain of data mining techniques in traditional medicine; 2) the data mining methods most frequently used in traditional medicine; 3) main strength and limitation of data mining techniques in traditional medicine; 4) the performance evaluation methods in data mining methods in traditional medicine.

RESULT

The result obtained showed that main application domain of data mining techniques in traditional medicine was related to syndrome differentiation. Bayesian Networks (BNs), Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) were recognized as being the methods most frequently applied in traditional medicine. Furthermore, each data mining techniques has its own strength and limitations when applied in traditional medicine. Single scaler methods were frequently used for performance evaluation of data mining methods.

CONCLUSION

Machine learning methods have become an important research field in traditional medicine. Our research provides information about this methods by examining the related articles.