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Latifa Bulbul,S. M. Kamruzzaman,Md. Mostafizur Rahman 경희대학교 융합한의과학연구소 2017 Oriental Pharmacy and Experimental Medicine Vol.17 No.4
The present study was investigated the brain antioxidant status and the memory enhancing efficiency of methanolic extract of Aegiceras corniculatum (AC) leaves in mice. The effects of 7-day oral administration of extracts at doses of 50 and 100 mg/kg BW were examined in both adult and aged group of mice. The memory enhancing activity was assessed by passive avoidance (PA) test and Morris water maze test (MWM). Amnesia was induced by scopolamine in MWM test. Both groups were subdivided into three groups (n = 10/groups) for PA test and five groups (n = 5/groups) for MWM test. Instantly after experiment, mice brain homogenates were subjected to determination of acetyl cholinesterase (AChE), superoxide dismutase (SOD), catalase (CAT), thiobarbituric acid reactive substances (TBARS), glutathione peroxidase (GPx), glutathione reductase (GR), glutathione S-transferase (GST), reduced glutathione (GSH) and reactive oxygen species (ROS). In PA test, both doses were significantly increased step through and escape latencies in both group of mice, whereas in MWM test, AC extract also significantly attenuated the effects of scopolamine compared to negative control animals in respective models. Additionally, the highest levels of SOD, CAT, GSH and GST were observed in the aged groups, whereas GR and GSHpx were observed in the adult groups. Moreover, AChE, TBARS and ROS levels were significantly decreased in both groups of mice in a dose-dependent manner. Histopathological analysis also showed the protected effect of AC. These findings together that A. corniculatum has potent antioxidant properties, capable of enhancing cognitive function in both adult and aged mice.
Latifa Ould Larbi,Lazreg Hadji,Mohamed Ait Amar Meziane,E.A. Adda Bedia 한국풍공학회 2018 Wind and Structures, An International Journal (WAS Vol.27 No.4
In this paper, a simple first-order shear deformation theory is presented for dynamic behavior of functionally graded beams. Unlike the existing first-order shear deformation theory, the present one contains only three unknowns and has strong similarities with the classical beam theory in many aspects such as equations of motion, boundary conditions, and stress resultant expressions. Equations of motion and boundary conditions are derived from Hamilton’s principle. Analytical solutions of simply supported FG beam are obtained and the results are compared with Euler-Bernoulli beam and the other shear deformation beam theory results. Comparison studies show that this new first-order shear deformation theory can achieve the same accuracy of the existing first-order shear deformation theory.
Latifa Khaouane,Chérif Si-Moussa,Salah Hanini,Othmane Benkortbi 한국생물공학회 2012 Biotechnology and Bioprocess Engineering Vol.17 No.5
This study aims at optimizing the culture conditions (agitation speed, temperature and pH) of the Pleuromutilin production by Pleurotus mutilus. A hybrid methodology including a central composite design (CCD),an artificial neural network (ANN), and a particle swarm optimization algorithm (PSO) was used. Specifically, the CCD and ANN were used for conducting experiments and modeling the non-linear process, respectively. The PSO was used for two purposes: Replacing the standard back propagation in training the ANN (PSONN) and optimizing the process. In comparison to the response surface methodology (RSM) and to the Bayesian regularization neural network (BRNN), PSONN model has shown the highest modeling ability. Under this hybrid approach (PSONN-PSO), the optimum levels of culture conditions were: 242 rpm agitation speed; temperature 26.88 and pH 6.06. A production of 10,074 ± 500 μg/g, which was in very good agreement with the prediction (10,149 μg/g),was observed in verification experiment. The hybrid PSONN-PSO gave a yield of 27.5% greater than that obtained by the hybrid BRNN-PSO. This work shows that the combination of PSONN with the generic PSO algorithm has a good predictability and a good accuracy for bio-process optimization. This hybrid approach is sufficiently general and thus can be helpful for modeling and optimization of other industrial bio-processes.
Doudach Latifa,Mrabti Hanae Naceiri,Al-Mijalli Samiah Hamad,Kachmar Mohamed Reda,Benrahou Kaoutar,Assaggaf Hamza,Qasem Ahmed,Abdallah Emad Mohamed,Rajab Bodour Saeed,Harraqui Khouloud,Mekkaoui Mouna,B 대한약침학회 2023 Journal of pharmacopuncture Vol.26 No.1
Objectives: Moroccan Arbutus unedo is an essential medicinal plant; however, little is known about the biological properties of its leaves mentioned in Moroccan traditional medicine. Methods: Various standard experiments were performed to evaluate the phytochemical, antidiabetic, antioxidant, antibacterial, and acute and sub-chronic toxicity characteristics of A. unedo leaves. Results: Phytochemical screening led to the identification of several phytochemical classes, including tannins, flavonoids, terpenoids, and anthraquinones, with high concentrations of polyphenols (31.83 ± 0.29 mg GAEs/g extract) and flavonoids (16.66 ± 1.47 mg REs/g extract). Further, the mineral analysis revealed high levels of calcium and potassium. A. unedo extract demonstrated significant antioxidant and anti-diabetic activities by inhibiting α-amylase (1.350 ± 0.32 g/mL) and α-glucosidase (0.099 ± 1.21 g/mL) compared to the reference drug Acarbose. Also, the methanolic extract of the plant exhibited significantly higher antibacterial activity than the aqueous extract. Precisely, three of the four examined bacterial strains exhibited substantial susceptibility to the methanolic extract . Minimum bactericidal concentration (MBC)/minimum inhibitory concentration (MIC) values indicated that A. unedo harbor abundant bactericidal compounds. For toxicological studies, mice were administered with A. unedo aqueous extract at single doses of 2,000 and 5,000 mg/kg. They did not exhibit significant abnormal behavior, toxic symptoms, or death during the 14-day acute toxicity test and the 90-day sub-chronic toxicity test periods. The general behavior, body weight, and hematological and biochemical status of the rats were assessed, revealing no toxicological symptoms or clinically significant changes in biological markers observed in the mice models, except hypoglycemia, after 90 days of daily dose administration. Conclusion: The study highlighted several biological advantages of A. unedo leaves without toxic effects in short-term application. Our findings suggest that conducting more comprehensive and extensive in vivo investigations is of utmost importance to identify molecules that can be formulated into pharmaceuticals in the future.
Larbi, Latifa Ould,Hadji, Lazreg,Meziane, Mohamed Ait Amar,Adda Bedia, E.A. Techno-Press 2018 Wind and Structures, An International Journal (WAS Vol.27 No.4
In this paper, a simple first-order shear deformation theory is presented for dynamic behavior of functionally graded beams. Unlike the existing first-order shear deformation theory, the present one contains only three unknowns and has strong similarities with the classical beam theory in many aspects such as equations of motion, boundary conditions, and stress resultant expressions. Equations of motion and boundary conditions are derived from Hamilton's principle. Analytical solutions of simply supported FG beam are obtained and the results are compared with Euler-Bernoulli beam and the other shear deformation beam theory results. Comparison studies show that this new first-order shear deformation theory can achieve the same accuracy of the existing first-order shear deformation theory.
Epidemiology and risk factors of voluntary pesticide poisoning in Morocco (2008-2014)
Zineb Nabih,Latifa Amiar,Zakaria Abidli,Maria Windy,Abdelmajid Soulaymani,Abdelrhani Mokhtari,Rachida Soulaymani-Bencheikh 한국역학회 2017 Epidemiology and Health Vol.39 No.-
OBJECTIVES: To determine the epidemiological profile and risk factors of voluntary poisoning by pesticides. METHODS: A retrospective analysis was conducted of all cases of voluntary poisoning by pesticides registered at the Anti-Poison and Pharmacovigilance Center of Morocco between January 2008 and December 2014. RESULTS: During the study period, 2,690 cases of acute pesticide poisoning were registered. The region of Rabat-Salé-Zemmour-Zaer accounted for the largest proportion, with 598 cases. The average age of the patients was 24.63±10.29 years. The sex ratio (female-to-male) was 0.45. Adults and teenagers were most affected by this type of poisoning, with 1,667 cases (62.0%) and 806 cases (30.0%), respectively. Suicide attempts accounted for 98.4% of the cases (2,469 cases). Pesticide poisoning occurred more often in urban zones (64.8%). Insecticides were incriminated in 14.0% of cases, with a mortality rate of 4.2%. Among the 1,635 patients for whom the outcomes were known, 154 died, corresponding to a mortality rate of 5.7%. CONCLUSIONS: Voluntary intoxication by pesticides presents a real scourge that affects public health, and in this study, we developed an epidemiological profile of this phenomenon. Nevertheless, this study has limitations in that it did not evaluate the impact of the socioeconomic and psychological factors that are important contributors to this type of poisoning.
Yamina Ammi,Latifa Khaouane,Salah Hanini 한국화학공학회 2015 Korean Journal of Chemical Engineering Vol.32 No.11
This work investigates the use of neural networks in modeling the rejection processes of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes. Three feed-forward neural network (NN) models, characterized by a similar structure (eleven neurons for NN1 and NN2 and twelve neurons for NN3 in the input layer, one hidden layer and one neuron in the output layer), are constructed with the aim of predicting the rejection of organic compounds (neutral and ionic). A set of 956 data points for NN1 and 701 data points for NN2 and NN3 were used to test the neural networks. 80%, 10%, and 10% of the total data were used, respectively, for the training, the validation, and the test of the three models. For the most promising neural network models, the predicted rejection values of the test dataset were compared to measured rejections values; good correlations were found (R= 0.9128 for NN1, R=0.9419 for NN2, and R=0.9527 for NN3). The root mean squared errors for the total dataset were 11.2430% for NN1, 9.0742% for NN2, and 8.2047% for NN3. Furthermore, the comparison between the predicted results and QSAR models shows that the neural network models gave far better.