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This study aims to optimize chitin extraction conditions by reducing water and chemical consumption using a two-level factorial design approach. Two variables were studied for the demineralization process: the volume of hydrochloric acid (400 to 500 mL) and the demineralization time (1 to 1.5 hours) at room temperature. For deproteinization, the variables examined were NaOH concentration (0.6 to 1 mol/L) and deproteinization time (1 to 1.5 hours) at 70-80°C. The ash and protein contents were measured to evaluate the efficiency of the demineralization and deproteinization processes, respectively. Minitab 18 software was used for the experimental design.The results showed that the best conditions for extracting high-quality chitin are a demineralization time of 1 hour, an HCl volume of 500 mL, a NaOH concentration of 1 M, and a deproteinization time of 1 hour. These optimal conditions reduce the amount of water, time, and chemicals required for chitin extraction. Compared to previous studies, we significantly reduced the amount of water and chemicals as well as the extraction duration.These results are innovative as they offer a more efficient and sustainable solution for chitin extraction, thus filling a gap in current research by proposing an optimized method. By providing these new data and demonstrating their effectiveness, our research makes a significant contribution to improving chitin extraction techniques, addressing an unmet need in the industrial field.

Diabetes is one of the most common diseases worldwide, and its prevalence rate continues to rise. This increase is due to factors related to nutrition and lifestyle on the one hand, and to genetic factors on the other hand, thus creating a real public health problem. Therefore, it is crucial to identify diabetes early in order to allow rapid treatment, capable of slowing down the progression of the disease. The objective of this work is to propose an automatic diabetes prediction system based on the following machine learning techniques: SVM, KNN, Decision Tree and Logistic Regression. Using risk factors specific to the Algerian environment, we constructed a new dataset that includes 823 patients, with 418 being diabetic and 405 being non-diabetic. In order to choose the relevant features and identify the most informative risk factors, we combined several feature extraction methods such as ANalysis Of Variance (ANOVA), Recursive Feature Elimination (RFE) and we used also the features proposed by the Pima Indian Diabetes Dataset (PIDD). The results of this study provided valuable information on the comparative performance of different machine learning models in the prediction of diabetes, as well as on the importance of the selected characteristics. [JJCIT 2023; 9(4.000): 377-394]

This study evaluates the physicochemical properties, phenolic and flavonoid content, antioxidant activity, and molecular docking interactions of honey from eastern Morocco. Analysis confirmed compliance with European Commission standards, with moisture content ranging from 15.39% to 19.74% and pH between 3.79 and 4.94. Carob honey exhibited the highest protein content (0.42%), polyphenol concentration (720.16 mg gallic acid/kg), flavonoid content (90.5 mg catechin/kg), and antioxidant activity (63.5% DPPH inhibition). Strong correlations were observed between phenolic and flavonoid content and antioxidant properties. Molecular docking identified ethyl phenylacetate and thymol as key compounds with significant interactions with cytochrome c peroxidase, suggesting potential therapeutic effects. DFT calculations supported these findings, indicating these compounds may enhance antioxidant activity. The study highlights the exceptional quality and antioxidant capacity of honey from eastern Morocco, reflecting its unique floral sources and potential as a natural source of antioxidants with therapeutic benefits.

The aims of this study were to determine the polyphenolic profile, to estimate the total phenolic and flavonoid contents, and to evaluate the antioxidant and antidiabetic activities of the extract of Pistacia lentiscus leaves, and the hydroacetonic mixture was employed as an alternative for common solvents in the extraction process. In order to explain the antidiabetic activity, molecular docking has been performed on the main constituents of the leaf extract. The characterization of the extract has been performed by high-performance liquid chromatography (HPLC) leading to the detection of 20 compounds of which gallic acid, ellagic acid, catechin, kaempferol, and quercetin 3-glucoside were identified using authentic standards. The total phenolic and flavonoid contents, assessed using the Folin–Ciocalteu and quercetin methods, were 394.5 ± 0.08 mg gallic acid equivalent/g dry extract (mg GAE/g DE) and 101.2 ± 0.095 mg quercetin equivalent/g dry extract (mg QE/g DE), respectively. On the other hand, the antioxidant activity of leaf extract, quantified by determining the ability to neutralize the free radical DPPH and β-carotene/linoleate model system, reached the values of 0.0027 ± 0.002 mg/mL and 0.128 ± 0.04 mg/mL, respectively. Regarding the antidiabetic activity, based on the inhibition of pancreatic α-amylase activity, a significant inhibition of about 68.20% with an IC50 value of 0.266 mg/mL had been observed. This finding is consistent with the molecular docking study of the main phenolic compounds of the extracts, where a remarkable binding affinity against α-amylase was observed, with values of −7.631 (kcal/mol), −6.818 (kcal/mol), and −5.517 (kcal/mol) for the major compounds catechin, quercetin-3-glucoside, and gallic acid, respectively.

En la actualidad, el interés por la educación emocional desde la orientación educativa se halla en constante crecimiento. Esta da respuesta a las necesidades que presenta el alumnado inmerso en el contexto educativo, desarrollando así sus competencias emocionales y sociales y potenciando su adaptación al medio, así como su desarrollo integral. Esto, sumado a la necesidad de hacer frente a la discriminación por religión, cultura u orientación sexual, hace que en el presente artículo se aborde un recurso web denominado Smart Emotion indicado para alumnado, familias y docentes de Educación Secundaria Obligatoria. A través de este recurso se trabaja la inteligencia emocional a través de cuatro enfoques diferentes (diversidad afectivo-sexual, sostenibilidad, paz y derechos humanos e igualdad de género) y ofreciendo directrices tanto a discentes como a docentes.

Introduction: Myelodysplastic syndromes (MDS) are a group of haematological disorders, whose diagnosis is based mainly on cytological studies of blood and marrow cells and cytogenetic analysis. Moreover, national epidemiological data on MDS are very scarce, especially in Maghreb countries where the population is on average younger than in Europe or the USA. The objective of the present study was to describe demographic and clinical features and the overall survival of patients with MDS in Algeria. Materials and Methods: This study is retrospective and national multicenter (n=19 centres), performed between 2014 to 2019. The evaluation was performed using EPI-INFO and SPSS version 21 software. Survival data were calculated using the Kaplan-Meier method and comparison of survival curves using the Log Rank test. Univariate and multivariate analysis of survival was performed using the Cox regression method. The study has been approved by the Ethical and Scientific Council of the participating hospitals. The closing date of the study is 31/12/2019. Results: A total of 670 patients with newly diagnosed MDS have been identified. The average number of new cases was 112/year, with an annual progression rate of 19%. Demographics show a slight female predominance (M/F of 317/353=0, 89; sex ratio F/M=1.11). The median follow-up was 29,3 months (range, 1 to 77 months). The overall median age was 69 years (range 16-96). The crude mean annual incidence rate was 0, 38 per 100,000 inhabitants aged ≥15 years old and it was 0, 17/100,000 in men and 0, 21/100,000 in women. Overall survival was 39 months. According to the IPSS score, the high-risk forms are low and their overall survival was 15 months. The rate of transformation into acute myeloid leukaemia (AML) is 32%. Conclusion: This national epidemiological survey shows an annual progression rate of 19% and an increase in incidence from 0.007/100.000 in 2005 to 0.45/100.000 in 2019.