Logic Programming and Artificial Neural Networks in Pharmacological Screening of Schinus Essential Oils

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Antioxidant,antimicrobial and toxicological properties of Schinus molle L. essential oils

Ethnopharmacological relevance: Schinus molle L. has been used in folk medicine as antibacterial, antiviral, topical antiseptic, antifungal, antioxidant, anti-inflammatory, anti-tumoural as well as antispasmodic and analgesic; however, there are few studies of pharmacological and toxicological properties of S. molle essential oils. Aim of the study: The aim of this study was to evaluate the antioxidant and antimicrobial activities of S. molle leaf and fruit essential oils, correlated with their chemical composition and evaluate their acute toxicity. Materials and methods: The chemical composition of S. molle leaf and fruit essential oils were evaluated by GC-FID and GC-MS. Antioxidant properties were determined using the 2,2-diphenyl-1-picryl-hydrazyl (DPPH) free radical and β-carotene/linoleic acid methods. Antimicrobial properties were evaluated by the agar disc diffusion method and minimal inhibitory concentration assay. Toxicity in Artemia salina and acute toxicity with behavioural screening in mice were evaluated. Results: The dominant compounds found in leaf and fruit essential oils (EOs) were monoterpene hydrocarbons, namely -phellandrene, β-phellandrene, β-myrcene, limonene and α-pinene. EOs showed low scavenging antioxidant activity by the DPPH free radical method and a higher activity by the β-carotene/linoleic acid method. Antimicrobial activity of EOs was observed for Gram+, Gram– pathogenic bacteria and food spoilage fungi. EOs showed cytotoxicity for Artemia salina and lower toxicity in Swiss mice. Conclusions: The result showed that EOs of leaves and fruits of S. molle demonstrated antioxidant and antimicrobial properties, suggesting their potential use in food or pharmaceutical industries.

ANTIOXIDANT, ANTIMICROBIAL AND TOXICOLOGICAL PROPERTIES OF SCHINUS MOLLE L. ESSENTIAL OILS

Schinus molle L. is commonly known as pink pepper or American pepper, of Anacardiaceae family, from subtropical regions of South America, introduced and naturalized in South Europe, including Portugal. In folk medicine, plant extracts and essential oil has related as having antibacterial, antiviral, antifungal, anti-inflammatory, antitumoral, antispasmodic, analgesic and antidepressive properties. The aim of present study was to evaluate the chemical composition and biological activities of essential oil extracted from leaves and fruits of S. molle. For this purpose, the essential oils were analyzed by gas chromatography (GC/FID) and antioxidant properties were evaluated by the free radical DPPH and by system β-carotene/linoleic acid methods. The antimicrobial activities were screened against pathogenic bacteria and fungi and food spoiling fungi by the disc diffusion assay and minimal inhibitory concentration (MIC) was determined for sensitive strains. Toxicity of essential oils were carried out by the brine shrimp mortality test (EC50) and acute lethal dose (DL50) determination after oral administration in Swiss mice The major components in leaf essential oil were α-phellandrene, β-phellandrene and limonene, while myrcene, α-phellandrene and 1,8-cineole are the main components in the fruit essential oil. The essential oils of leaf and fruit of S. molle showed antioxidant activity through the two mechanisms: the ability to capture free radicals and protection of lipid peroxidation. These oils exhibited also a broad microbial activity spectrum, against pathogenic bacteria Gram-positive and Gram-negative and Candida spp. The fruit essential oil showed high cytotoxicity against Artemia salina. Essential oils of leaves and fruits of S. molle showed significant antioxidant and microbial properties, so the studies continue to clarify more in deep its toxicity, including hepatotoxicity and nephrotoxicity, and to evaluate its medicinal or nutraceutical potential.

An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach

Plants of genus Schinus are native South America and introduced in Mediterranean countries, a long time ago. Some Schinus species have been used in folk medicine, and Essential Oils of Schinus spp. (EOs) have been reported as having antimicrobial, anti-tumoural and anti-inflammatory properties. Such assets are related with the EOs chemical composition that depends largely on the species, the geographic and climatic region, and on the part of the plants used. Considering the difficulty to infer the pharmacological properties of EOs of Schinus species without a hard experimental setting, this work will focus on the development of an Artificial Intelligence grounded Decision Support System to predict pharmacological properties of Schinus EOs. The computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters to the handling of incomplete, unknown, or even self-contradictory information. New clustering methods centered on an analysis of attribute’s similarities were used to distinguish and aggregate historical data according to the context under which it was added to the Case Base, therefore enhancing the prediction process.