The aim of this study was to devise a model that predicts the inhibition zone diameter using artificial neural networks. The concentration, temperature and the exposure time of our extract were taken as input variables. The neural architecture model 3-13-3 and a learning algorithm Quasi-Newton (BFGS) revealed a positive correlation between the experimental results and those artificially predicted, which were measured according to a mean squared error (RMSE) and an R 2 coefficient of E.coli (RMSE=1.28; R 2 =0,96), S.aureus (RMSE=1.46; R 2 =0,97) and B.subtilis (RMSE=1.88; R 2 =0,96) respectively. Based on these results, an external and an internal model validation were attained. A neuronal mathematical equation was created to predict the inhibition diameters for experimental data not included in the basic learning. Consequently, a good correlation was observed between the values predicted by the equation and those obtained experimentally, as demonstrated by the R 2 and RMSE values. The results regarding the sensitivity analysis showed that the concentration was the most determinant parameter compared to Temperature and Time variables. Ultimately, the model developed in this study will be used reliably to predict the variation of garlic extract's inhibition diameter.

The aim of this study was to prepare microcapsules based on a natural polymer chitosan solution (high degree of deacetylation (DDA), low molecular weight (MW), and low viscosity)/sodium alginate in the presence of a crosslinking agent (glutaraldehyde), in order to encapsulate and vectorise the active principle towards the diseased organ (colon), without being diffused into other levels of the digestive tract, to increase the therapeutic effectiveness of treatment by chemotherapy and to reduce undesirable effects. The method of preparation of the microcapsules obtained from the sodium alginate/chitosan solution/active ingredients system was examined by conventional optical microscopy. In addition, an in vitro study was carried out on the active ingredients’ release profiles, depending on the pH simulating the gastric and intestinal media for the seven systems proposed. It should be mentioned that, in the basic medium (pH(colon) = 8), the release of the active ingredients is of the utmost importance. Nevertheless, control of this release can be improved by a crosslinking agent and the coating method. The dry [sodium alginate / chitosan solution / active ingredients + crosslinking 2 %] formulation coated with non-crosslinked chitosan (Formulation 7) is the standard formula that meets all the criteria from our earlier work, with a core release rate of 67 %. The PSD was unimodal, with sizes ranging from 750 µm to 900 µm.

The current pilot study was conducted to compare the triple effect of garlic extract and metformin on hyperglycaemia, hypercholesterolaemia, and hypertriglyceridaemia in alloxan-induced type 1-like diabetic rats. Wistar rats were randomly divided into four groups. Control group included normal rats. The second group included alloxan-induced type 1-like diabetic rats, receiving no treatment. The other two groups of diabetic rats were orally treated with 0.75 g of garlic extract per kg of body weight and 0.05 of metformin g per kg of body weight respectively for four weeks. The pharmacological impact of garlic compounds on serum glucose and lipids as opposed to the glucose-lowering and lipid-lowering was highlighted in these experiments. These results revealed that garlic extract has a triple action on hyperglycaemia, hypertriglyceridemia, and hypercholesterolemia. Its effect on hyperglycaemia is long lasting, and more pronounced compared to the metformin. Interestingly, it had a regulatory effect on glycaemia as highlighted in the control group.