Asparagopsis armata and Sphaerococcus coronopifolius as a natural source of antimicrobial compounds.

Methanol, n-hexane and dichloromethane extracts of twelve marine macro-algae (Rhodophyta, Chlorophyta and Heterokontophyta divisions) from Peniche coast (Portugal) were evaluated for their antibacterial and antifungal activity. The antibacterial activity was evaluated by disc diffusion method against Bacillus subtilis (gram positive bacteria) and Escherichia coli (gram negative bacteria). Saccharomyces cerevisiae was used as a model for the antifungal activity by evaluating the growth inhibitory activity of the extracts. The high antibacterial activity was obtained by the Asparagopsis armata methanolic extract (10 mm-0.1 mg/disc), followed by the Sphaerococcus coronopifolius n-hexane extract (8 mm-0.1 mg/disc), and the Asparagopsis armata dichloromethane extract (12 mm-0.3 mg/disc) against Bacillus subtilis. There were no positive results against Escherichia coli. Sphaerococcus coronopifolius revealed high antifungal potential for n-hexane (IC50 = 40.2 µg/ml), dichloromethane (IC50 = 78.9 µg/ml) and methanolic (IC50 = 55.18 µg/ml) extracts against Saccharomyces cerevisiae growth. The antifungal potency of the Sphaerococcus coronopifolius extracts was similar with the standard amphotericin B. Asparagopsis armata and Sphaerococcus coronopifolius reveal to be interesting sources of natural compounds with antimicrobial properties.

Fuzzy obesity index (MAFOI) for obesity evaluation and bariatric surgery indication.

BACKGROUND: The Miyahira-Araujo Fuzzy Obesity Index (MAFOI) for being used as an alternative in bariatric surgery indication (BSI) is validated in this paper. The search for a more accurate method to evaluate obesity and to indicate a better treatment is important in the world health context. Body mass index (BMI) is considered the main criteria for obesity treatment and BSI. Nevertheless, the fat excess related to the percentage of Body Fat (%BF) is actually the principal harmful factor in obesity disease that is usually neglected. The aim of this research is to validate a previous fuzzy mechanism by associating BMI with %BF that yields the Miyahira-Araujo Fuzzy Obesity Index (MAFOI) for obesity evaluation, classification, analysis, treatment, as well for better indication of surgical treatment. METHODS: Seventy-two patients were evaluated for both BMI and %BF. The BMI and %BF classes are aggregated yielding a new index (MAFOI). The input linguistic variables are the BMI and %BF, and the output linguistic variable is employed an obesity classification with entirely new types of obesity in the fuzzy context, being used for BSI, as well. RESULTS: There is gradual and smooth obesity classification and BSI criteria when using the Miyahira-Araujo Fuzzy Obesity Index (MAFOI), mainly if compared to BMI or %BF alone for dealing with obesity assessment, analysis, and treatment. CONCLUSION: The resulting fuzzy decision support system (MAFOI) becomes a feasible alternative for obesity classification and bariatric surgery indication.