Purpose Heavy metals are toxic pollutants released into the environment as a result of different industrial activities. Biosorption of heavy metals from aqueous solutions is a new technology for the treatment of industrial wastewater. The aim of the present research is to highlight the basic biosorption theory to heavy metal removal. Materials and methods Heterogeneous cultures mostly dried anaerobic bacteria, yeast (fungi), and protozoa were used as low-cost material to remove metallic cations Pb(II), Cr(III), and Cd(II) from synthetic wastewater. Competitive biosorption of these metals was studied. Results The main biosorption mechanisms were complexation and physical adsorption onto natural active functional groups. It is observed that biosorption of these metals was a surface process. The main functional groups involved in these processes were hydroxyl (–OH) and carboxylic groups (C=O) with 37, 52, and 31 and 21, 14, and 34 % removal of Pb(II), Cr(III), and Cd(II), respectively. Langmuir was the best model for a single system. While extended Langmuir was the best model for binary and ternary metal systems. The maximum uptake capacities were 54.92, 34.78, and 29.99 mg/g and pore diffusion coefficients were 7.23, 3.15, and 2.76 × 10−11 m2/s for Pb(II), Cr(III), and Cd(II), respectively. Optimum pH was found to be 4. Pseudo-second-order was the best model to predict the kinetic process. Biosorption process was exothermic and physical in nature. Conclusions Pb(II) offers the strongest component that is able to displace Cr(III) and Cd(II) from their sites, while Cd(II) ions are the weakest adsorbed component.
The ligand Schiff base [(E)-3-(2-hydroxy-5-methylbenzylideneamino)- 1- phenyl-1H-pyrazol-5(4H) –one] with some metals ion as Mn(II); Co(II); Ni(II); Cu(II); Cd(II) and Hg(II) complexes have been preparation and characterized on the basic of mass spectrum for L, elemental analyses, FTIR, electronic spectral, magnetic susceptibility, molar conductivity measurement and functions thermodynamic data study (∆H°, ∆S° and ∆G°). Results of conductivity indicated that all complexes were non electrolytes. Spectroscopy and other analytical studies reveal distorted octahedral geometry for all complexes. The antibacterial activity of the ligand and preparers metal complexes was also studied against gram and negative bacteria.
The ligand Schiff base [(E)-3-(2-hydroxy-5-methylbenzylideneamino)- 1- phenyl-1H-pyrazol-5(4H) –one] with some metals ion as Mn(II); Co(II); Ni(II); Cu(II); Cd(II) and Hg(II) complexes have been preparation and characterized on the basic of mass spectrum for L, elemental analyses, FTIR, electronic spectral, magnetic susceptibility, molar conductivity measurement and functions thermodynamic data study (∆H°, ∆S° and ∆G°). Results of conductivity indicated that all complexes were non electrolytes. Spectroscopy and other analytical studies reveal distorted octahedral geometry for all complexes. The antibacterial activity of the ligand and preparers metal complexes was also studied against gram and negative bacteria.
The research includes synthesis and identification of novel three amino acids ligands complexes of some heavy metal (II) ions by using the amino acids like glycine, L-alanine and L-valine. New metal mixed ligand complexes with amino acids are prepared the reaction by reacting the three amino acids with the metals(II) chloride by using 50% ethanolic solution and 50% distall water in the molar ratio [1:1:1:1] ( M:Gly:Ala:Val) except for Co(II) and Ni(II) complexes were found after diagnosis the coordination with both Lalanine and L-valine. The prepared complexes identified by using physical properties, flame atomic absorption and conductivity measurements, in addition, mass, FT.IR and UV.vis spectrum as well magnetic moment data. The general
... Show MoreStudy the role of CoQ10 and IGFBP-1 in obese male patients with diabetic mellitus type 2. ELISA method was used to assay Serum CoQ10 and IGFBP-1. Blood was taken with drawn sample from 30 obese normal patients with age range (40-60) years, 30 diabetic patients with age range (40-60) years at duration of disease (1-5) years and 30 normal healthy patients. The mean difference between T2DM according to CoQ10 (12.5±1.1) was decreased than the mean of IFG (21.8±3.2) (P 0.002) and the mean difference between T2DM according to IGFBPs (0.65±0.06) was decreased than the mean of IFG (3.2±0.3) (P 0.000). While no significant difference between mean age of DM2 patients (55.5±1.06), and IFG (55.6±0.9) (p 0.90), no significant difference bet
... Show MoreGestational diabetes mellitus is glucose intolerance of varying degree with onset or first detection duringpregnancy,it can causelong and short term morbidities in both the mother and the child, such as shoulder dystocia,preeclampsia, and high blood pressure. The most powerful endogenous vasoconstrictor peptide, urotensin II, andits receptor are involved in the etiology of gestational diabetes mellitus.Aim of the study: The study’s goal was to see if there is a link between Urotensin II levels and insulin resistancein pregnant women with gestational diabetes.Patients and method: A case-control study that was conducted in obstetrics and gynecology department atBaghdad Teaching hospital from the first of January 2019 to the end of D
... Show MoreBackground: Bone mineral density has been assessed using Dual-Energy X-Ray Absorptiometry. Bone mineral density is measured according to the results of the Dual-Energy X-Ray Absorptiometry examination of the vertebral column and pelvis. Although diabetes mellitus type II (DM) is known to affect bone mineral density, at the present time this particular relationship is not clear. Objective: The aim of current study was to evaluate the effects of type II diabetes mellitus on bone mineral density of the upper and lower limbs as well as gender differences. Patients and Methods: This study involved 165 patients complaining of bone pain (85 males and 80 females), 85 patients of who suffered from diabetes, involving both genders. In addition,
... Show MoreIn this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and
... Show More