LABORATOIRE DE BIOMATÉRIAUX ET PHÉNOMÈNES DE TRANSPORT

Intitulé de l’équipe de recherche :   Synthèse et caractérisation physico-chimique des biomatériaux

Acronyme et code : SCBM  C0560103

Domaine : SI/Génie des procédés et environnement

COMPOSANTE HUMAINE :

Chef d’équipe : Pr. BENKORTEBI Othmane

 

Description scientifique du programme de recherche

 

La thématique de recherche de notre équipe s’axe principalement sur les points suivants :

  1. La préparation par extraction et purification et/ou modification chimique des matériaux d’origine naturelle: végétale ou animale.
  2. La caractérisation physico-chimique de ces matériaux en utilisant les techniques appropriées: spectroscopies, microscopie électronique, .etc.
  3. Application des biomatériaux en tant que substituts tissulaires ou en tant que vecteurs pour des agents actifs de nature thérapeutique. Dans le premier cas il s’agit d’essayer de reproduire les caractéristiques fonctionnelles du tissu à remplacer en s’assurant d’une biocompatibilité acceptable et dans le second cas, fabriquer des ensembles à l’échelle microscopique ou nanométrique (microcapsules, nanoparticules) capables de porter des molécules actives, de les conduire, et ensuite de les libérer dans les sites cibles selon un processus contrôlé. La compréhension et la maîtrise des différents facteurs liés à cette opération et aux systèmes constitués par le biomatériau qui est généralement un biopolymère et l’agent actif sont toujours demandées.               
 Nom et Prénom Grade Qualité Etablissement
1 BENKORTEBI Othmane Pr. Chef d’équipe Fac. Technologie / UYFM
2 HAMADACHE Mabrouk Pr. Membre Fac. Technologie / UYFM
3 BITAM Said MCA Membre Fac. Technologie / UYFM
4 BOUKELKAL Asmaa MCA Membre Fac. Technologie / UYFM
5 ATHAMNIA Djamal MCA Membre Fac. Technologie / UYFM
6 BELAISSA Yahia MCB Membre Fac. Sciences / UYFM

publications :

N  Auteurs Titre de l’article Journal Catégorie  A+/A/B Lien sur net ou
DOI
Année de punlication
1 Yahia Belaissa et al. A new hetero-junction p -CuO/ n -ZnO for the removal of amoxicillin by photocatalysis under solar irradiation J TAIWAN INST CHEM E A https://doi.org/10.1016/j.jtice.2016.09.002 2016
2 Hamadache mabrouk et al. A Quantitative Structure Activity Relationship for acute oral toxicity ofpesticides on rats: Validation, domain of application and prediction J HAZARD MATER A+ https://doi.org/10.1016/j.jhazmat.2015.09.021 2016
3 Boukhelkhal Asmaa et al. Adsorptive removal of amoxicillin from wastewater using wheat grains:equilibrium, kinetic, thermodynamic studies and mass transfer, DESALIN WATER TREAT A https://doi.org/10.1080/19443994.2016.1166991 2016
4 Hamadache mabrouk et al. Artificial neural network-based equation to predict the toxicity of
herbicides on rats
CHEMOMETR INTELL LAB A https://doi.org/10.1016/j.chemolab.2016.03.007 2016
5 Sediri Meriem et al. Artificial Neural Networks Modeling of Dynamic Adsorption From Aqueous Solution Moroccan Journal of Chemistry B https://doi.org/10.48317/IMIST.PRSM/morjchem-v5i2.7785 2017
6 Mahammadou Harouna Bassirou et al. New approach of the fouling process modeling in tangential filtration on cake DESALIN WATER TREAT A doi: 10.5004/dwt.2017.20576 2017
7 Djamel Atsamnia et al. Prediction of the antibacterial activity of garlic extract on E. coli, S.aureus and B. subtilis by determining the diameter of the inhibitionzones using artificial neural networks LWT-FOOD SCI TECHNOL A https://doi.org/10.1016/j.lwt.2017.04.053 2017
8 Bitam Said et al. QSAR model for prediction of the therapeuticpotency of N-benzylpiperidine derivatives as AChE
inhibitors
SAR QSAR ENVIRON RES A https://doi.org/10.1080/1062936X.2017.1331467 2017
9 Hamadache mabrouk et al. Multilayer Perceptron Model for PredictingAcute Toxicity of Fungicides on Rats International Journal of Quantitative Structure-Property Relationships B https://doi.org/10.4018/IJQSPR.2018010106 2018
10 Bitam Said et al. Prediction of therapeutic potency of tacrinederivatives as BuChE inhibitors from quantitative
structure–activity relationship modelling
SAR QSAR ENVIRON RES A https://doi.org/10.1080/1062936X.2018.1423640 2018
11 Hamadache mabrouk et al. QSAR modeling in ecotoxicological risk assessment: application
to the prediction of acute contact toxicity of pesticides on bees
(Apis mellifera L.)
ENVIRON SCI POLLUT R A https://doi.org/10.1007/s11356-017-0498-9 2018
12 Boukhelkhal Asmaa et al. Use of an anionicsurfactant for the sorption of a binary mixture of antibiotics from aqueous solutions, ENVIRON TECHNOL A https://doi.org/10.1080/09593330.2018.1472301 2018
13 Mhammadou Harouna Bassirou et al. Modeling of transitional pore blockage to cake filtration and modified fouling index –Dynamical surface phenomena in membrane filtration, CHEM ENG SCI A https://doi.org/10.1016/j.ces.2018.07.054 2019
14 Mahammadou harouna Bassirou et al. New Alternative of Enhancing Hospital Hygiene Facing
Pseudomonas aeruginosa Drug Resistance Impact of Hypertonic
Saline Solutions on the Behavior of P. aeruginosa
ACS Omega B https://doi.org/10.1021/acsomega.8b02733 2019
15 Gheraba Lamia et al. Prediction of Climatic Parameters from Physicochemical Parameters using Artificial Neural Networks: Case Study of Ain Defla (Algeria) KUI B https://doi.org/10.15255/KUI.2019.004 2019
16 Bitam Said et al. 2D QSAR studies on a series of (4S,5R)-5-[3,5-bis(trifluoromethyl)phenyl]-4-methyl-1,3-oxazolidin-2-one as CETP inhibitors SAR and QSAR in Environmental Research A https://doi.org/10.1080/1062936X.2020.1765195 2020
17 S. Belmadani et al. Artificial Neural Network Models for Prediction of Density and Kinematic Viscosity of Different Systems of Biofuels and Their Blends with Diesel Fuel. Comparative Analysis. KUI B https://doi.org/10.15255/KUI.2019.053 2020
18 Rahal Sofiane et al. In silico prediction of critical micelle concentration (CMC) of classic and extended anionic surfactants from their molecular structural descriptors Arabian Journal for Science and Engineering A https://doi.org/10.1007/s13369-020-04598-0 2020
19 Mahammadou harouna Bassirou et al. Optimization of Diauxienne Growth of Pseudomonas aeruginosa in the Bioremediation of Soils Polluted by Hydrocarbons ACTA SCIENTIFIC MICROBIOLOGY A http://dx.doi.org/10.31080/ASMI.2020.03.0578

 

2020
20 H. Maouz et al. QSPR studies of carbonyl, hydroxyl, polyene indices, and viscosity average molecular weight of polymers under photostabilization using ANN and MLR approaches KUI B https://doi.org/10.15255/KUI.2019.022 2020
21 Imane Khezrane et al. Use of hydrocarbons sludge as a substrate for the production of biosurfactants by Pseudomonas aeruginosa ATCC 27853 Environmental monitoring and assessment A https://doi.org/10.1007/s10661-020-08269-3 2020
22 Laidi Maamar et al. CMC OF DIVERSE GEMINI SURFACTANTS MODELING USING A HYBRID APPROACH COMBINING SVR-DA Chemical Industry & Chemical Engineering Quarterly A https://doi.org/10.2298/CICEQ200907048L 2021
23 M. Hammoudi et al. Optimisation of the Microencapsulation of an Active Ingredient by Crosslinking and the Coating Method to Target Colon Diseases KUI B https://doi.org/10.15255/KUI.2020.056 2021
24 K. Otmanine et al. Preventive Activity of Giner (Zingiber officinale) Against Myelotoxicity and Hepatotoxicity Induced by Cyclohexatriene and Identification of the Most Active … KUI B https://doi.org/10.15255/KUI.2020.062 2021
25 OMARI Souhila et al. Response surface methodology for the study of interactions between components in a micellar system formulation Journal of the Serbian Chemical Society A https://doi.org/10.2298/JSC210216033O 2021
26 Yahia Belaissa et al. A new hybrid process for Amoxicillin elimination by combination of adsorption and photocatalysis on (CuO/AC) under solar irradiation Journal of Molecular Structure A https://doi.org/10.1016/j.molstruc.2022.132769 2022
27 Mohamed Sannad et al. A numerical simulation under milk fouling in a plate heat exchanger in the presence of a porous medium Journal of Advanced Research in Fluid Mechanics and Thermal Sciences B https://doi.org/10.37934/arfmts.91.1.117 2022
28 Djamel Atsamnia et al. Comparative Therapeutic Properties of Garlic Extract and Metformin on Hyperglycaemia, Hypercholesterolaemia, and Hypertriglyceridaemia in Alloxan-induced Type1-like Diabetic Rats KUI B https://doi.org/10.15255/KUI.2021.035 2022
29 Abd Elaziz Sarrai et al. Modeling and optimization of Tylosin adsorption using dehydrated wheat bran: adsorption behaviors, kinetic and thermodynamic studies Reaction Kinetics, Mechanisms, and Catalysis  A https://doi.org/10.1007/s11144-022-02241-7 2022
30 Imane Euldji et al. QSPR Modelling of the Solubility of Drug and Drug‐like Compounds in Supercritical Carbon Dioxide Molecular Informatics A https://doi.org/10.1002/minf.202200026 2022
31 Yahia Belaissa et al. Removal of amoxicillin in aqueous solutions by a chemical activated carbons derived from Jujube nuts: adsorption behaviors, kinetic and thermodynamic studies Reaction Kinetics, Mechanisms, and Catalysis  A https://doi.org/10.1007/s11144-022-02159-0 2022
32 Mohamed Kouider Amar et al. Rheological and structural study of solid lipid microstructures stabilized within a lamellar gel network Journal of Pharmaceutical Innovation A https://doi.org/10.1007/s12247-022-09642-0 2022
33 OMARI Souhila et al. Synthesis and characterization of activated carbon from red pumpkin skin for the removal of ionic dyes Water Practice & Technology B https://doi.org/10.2166/wpt.2022.038 2022
34 Bitam Said et al. 2D-QSAR, docking, molecular dynamics, studies of PF-07321332 analogues to identify alternative inhibitors against 3CLpro enzyme in SARS-CoV disease Journal of Biomolecular Structure and Dynamics A https://doi.org/10.1080/07391102.2022.2113822 2023
35 N. Ghalem et al. A new comprehensive model of thermal conductivity for hydrofluoroolefins refrigerants using feed-forward back-propagation neural networks Thermophysics and Aeromechanics B https://doi.org/10.1134/S086986432302018X 2023
36 Imane Euldji et al. A new hybrid quantitative structure property relationships-support vector regression (QSPR-SVR) approach for predicting the solubility of drug compounds in supercritical carbon … AIChE journal A https://doi.org/10.1002/aic.18115 2023
37 Achouak Madani et al. In silico prediction of the inhibition of new molecules on SARS-CoV-2 3CL protease by using QSAR: PSOSVR approach Brazilian Journal of Chemical Engineering A https://doi.org/10.1007/s43153-023-00332-z 2023
38 Widad Benmouloud et al. Machine learning approach for the prediction of surface tension of binary mixtures containing ionic liquids using σ‐profile descriptors International Journal of Quantum Chemistry A https://doi.org/10.1002/qua.27026 2023
39 Yahia Belaissa et al. Methylene blue Photo-degradation on the Hetero-junction system α-Fe2O3 / BaTiO3 under sunlight Journal of Photochemistry and Photobiology A: Chemistry A https://doi.org/10.1016/j.jphotochem.2023.114634 2023
40 Rahal Sofiane et al. Remediation of crude oil polluted soil using washing process with surfactant in batch reactor Algerian Journal of Environmental Science and TechnologyVol.9 n°2 B 2023
41 H. Fodil Cherif et al. Thermodynamic and kinetic study of the improvement of the adsorption efficiency of Hexavalent chromium (VI) ions by encapsulated modified prickly pear peel Algerian Journal of Environmental Science and Technology

Vol.9 n°3

B 2023
42 Imane Euldji et al. Hybrid Improved Grey Wolf Support Vector Regression Algorithm for Modeling Solubilities of APIs in Pure Ionic Liquids: σ-Profile Descriptors Journal of Chemical Information and Modeling A https://doi.org/10.1021/acs.jcim.3c01876 2024
43 Nada Boukelkal et al. QSPR for the prediction of critical micelle concentration of different classes of surfactants using machine learning algorithms Journal of Molecular Graphics and Modelling A https://doi.org/10.1016/j.jmgm.2024.108757 2024
44 Bitam Said et al. Targeting bladder cancer with Trigonella foenum-graecum: a computational study using network pharmacology and molecular docking Journal of Biomolecular Structure and Dynamics A https://doi.org/10.1080/07391102.2023.2217926 2024
  Auteurs Titre du chapitre Livre   Lien sur net ouDOI Editeur
45 Mabrouk Hamadache et al. QSAR Approaches and Ecotoxicological Risk Assessment Ecotoxicological QSARs   https://doi.org/10.1007/978-1-0716-0150-1_25 Humana, New York, NY
46 Mabrouk Hamadache et al. Contribution of Chemometric Modeling to Chemical Risks Assessment for Aquatic Plants: State‐of‐the‐Art Chemometrics and Cheminformatics in Aquatic Toxicology   https://doi.org/10.1002/9781119681397.ch20 John Wiley & Sons, Inc
47 Hamadache M.et al. Environmental Toxicity of Pesticides, and Its Modeling by QSAR Approaches: In: Roy K. (eds) Advances in QSAR Modeling. Challenges and Advances in Computational Chemistry and Physics, Advances in QSAR modeling. Callenges and Advances..   https://doi.org/10.1007/978-3-319-56850-8_13 Springer International Publishing