An ethnobotanical survey of medicinal plants of Laos toward the discovery of bioactive compounds as potential candidates for pharmaceutical development

Context: An ethnobotany-based approach in the selection of raw plant materials to study was implemented. Objective: To acquire raw plant materials using ethnobotanical field interviews as starting point to discover new bioactive compounds from medicinal plants of the Lao People’s Democratic Republic. Methods: Using semi-structured field interviews with healers in the Lao PDR, plant samples were collected, extracted, and bio-assayed to detect bioactivity against cancer, HIV/AIDS, TB, malaria. Plant species demonstrating activity were recollected and the extracts subjected to a bioassay-guided isolation protocol to isolate and identify the active compounds. Results: Field interviews with 118 healers in 15 of 17 provinces of Lao PDR yielded 753 collections [573 species] with 955 plant samples. Of these 955, 50 extracts demonstrated activity in the anticancer, 10 in the anti-HIV, 30 in the anti-TB, and 52 in the anti-malarial assay. Recollection of actives followed by bioassay-guided isolation processes yielded a series of new and known in vitro-active anticancer and antimalarial compounds from 5 species. Discussion: Laos has a rich biodiversity, harboring an estimated 8,000-11,000 species of plants. In a country highly dependent on traditional medicine for its primary health care, this rich plant diversity serves as a major source of their medication. Conclusion: Ethnobotanical survey has demonstrated the richness of plant-based traditional medicine of Lao PDR, taxonomically and therapeutically. Biological assays of extracts of half of the 955 samples followed by in-depth studies of a number of actives have yielded a series of new bioactive compounds against the diseases of cancer and malaria

Social Network Analysis of Co-fired Fuzzy Rules

Abstract. The popularity of modern online social networks has grown up so quickly in the last few years that, nowadays, social network analysis has become one of the hottest research lines in the world. It is important to highlight that social network analysis is not limited to the analysis of networks connecting peo-ple. Indeed, it is strongly connected with the classical methods widely recognized in the context of graph theory. Thus, social network analysis is applied to many different areas like for instance economics, bibliometrics, and so on. This contri-bution shows how it can also be successfully applied in the context of designing interpretable fuzzy systems. The key point consists of looking at the rule base of a fuzzy system as a fuzzy inference-gram (fingram), i.e., as a social network made of nodes representing fuzzy rules. In addition, nodes are connected through edges that represent the interaction between rules, at inference level, in terms of co-fired rules, i.e., rules fired at the same time by a given input vector. In short, fingram analysis consists of studying the interaction among nodes in the network for the purpose of understanding the structure and behavior of the fuzzy rule base under consideration. It is based on the basic principles of social network analysis which have been properly adapted to the design of fuzzy systems.