The goal of this thesis was to understand and quantify to what extent plants are used for the treatment of mental and folk illnesses such as susto and mal aire in the Neotropics and to investigate the anxiolytic and antiepileptic potential of previously unstudied Neotropical members of the genera Piper and Peperomia.
Firstly, the literature was reviewed and a regression analysis method was used in order to quantitatively determine which plant families are preferred for the treatment of mental, behavioral and neurological health disorders in the Neotropics. This analysis identified Piperaceae, among others, as an important taxonomic group for the treatment of such disorders. Following that lead, a botanical survey was conducted in Peru, where 47 species of Piperaceae and 21 plants traditionally used for folk illnesses by the Yanesha of Peru, an Amazonian ethnic group, were collected. In order to target potential anxiolytic and antiepileptic plants, two high throughput bioassays were used to evaluate the extracts’ in vitro activity on the γ-aminobutyric acid (GABA) system. Plant extracts in general demonstrated moderate to high affinity to the GABA-BZD receptor. Additionally, extracts demonstrated low to moderate activity in the inhibition of the GABA-T enzyme, with a few plants exhibiting promising activity. Plants selected by the Yanesha showed comparable activity to the other Piperaceae plants with Piper cremii being the most active plant in the GABAA assay, and Drymaria cordata in the GABA-T assay. Finally, four phytochemicals from Piper tuerckheimii, a plant regarded as one of the most effective traditional remedy for the treatment of epilepsy and susto by the Q’eqchi’ Maya of Belize presented, were isolated for the first time.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OOU-OLD./20437 |
| Date | 23 November 2011 |
| Creators | Picard, Gabriel |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
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