The formation of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) was investigated using a kinetic study approach as described by first-order, Arrhenius, and Eyring equations. Chemical model systems with different amino acid precursors (proline, phenylalanine, and glycine) were examined at different times (4, 8, 12, and 16 min) and temperatures (150, 180, 210, 240, and 270 °C). PhIP was detected using high-performance liquid chromatography equipped with fluorescence detector (HPLC-FLD). The good fit in first-order suggested that PhIP formation was influenced by the types of amino acids and PhIP concentration significantly increased with time and temperature (up to 240 °C). PhIP was detected in proline and phenylalanine model systems but not in the glycine model system. The phenylalanine model system demonstrated low activation energy (Ea) of 95.36 kJ/mol that resulted in a high rate of PhIP formation (great amount of PhIP formed). Based on the ∆S‡ values both proline and phenylalanine demonstrated bimolecular rate-limiting steps for PhIP formation. Altogether these kinetic results could provide valuable information in predicting the PhIP formation pathway.
A robust screening approach and a sparse quantitative structure-retention relationship (QSRR) model for predicting retention indices (RIs) of 169 constituents of essential oils is proposed. The proposed approach is represented in two steps. First, dimension reduction was performed using the proposed modified robust sure independence screening (MR-SIS) method. Second, prediction of RIs was made using the proposed robust sparse QSRR with smoothly clipped absolute deviation (SCAD) penalty (RSQSRR). The RSQSRR model was internally and externally validated based on [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], Y-randomization test, [Formula: see text], [Formula: see text], and the applicability domain. The validation results indicate that the model is robust and not due to chance correlation. The descriptor selection and prediction performance of the RSQSRR for training dataset outperform the other two used modelling methods. The RSQSRR shows the highest [Formula: see text], [Formula: see text], and [Formula: see text], and the lowest [Formula: see text]. For the test dataset, the RSQSRR shows a high external validation value ([Formula: see text]), and a low value of [Formula: see text] compared with the other methods, indicating its higher predictive ability. In conclusion, the results reveal that the proposed RSQSRR is an efficient approach for modelling high dimensional QSRRs and the method is useful for the estimation of RIs of essential oils that have not been experimentally tested.
Four new furanoanthraquinones, 2-hydroxymethyl-3,4-[2'-(1-hydroxy-1-methylethyl)-dihydrofurano]-8-hydroxyanthraquinone, 2-hydroxymethyl-3,4-[1'-hydroxy-2'-(1-hydroxy-1-methylethyl)-dihydrofurano]-8-hydroxyanthraquinone, 2-hydroxymethyl-3,4-[2'-1-hydroxy-1-methylethyl)-dihydrofurano]anthraquinone and 2-methyl-3,4-[2'-(1-hydroxy-1-methylethyl)-dihydrofurano] anthraquinone or capitellataquinone A-D and four known anthraquinones, rubiadin, anthragallol 2-methyl ether, alizarin 1-methyl ether and digiferruginol, together with scopoletin were isolated from the stems of Hedyotis capitellata Wall (Rubiaceae). Lucidin-3-O-beta-glucoside was isolated from the roots of the plant. Characterization of the new compounds was carried out by extensive NMR studies using FGCOSY, FGHMQC, FGHMBC and DEPT-135 in addition to other spectroscopic methods.
The X-ray single crystal analysis of isomeric ortho, meta, and para bromo-substituted α-methylsulfonyl-α-diethoxyphosphoryl acetophenones showed that this class of compound adopts synclinal (gauche) conformations for both [-P(O)(OEt)2] and [-S(O)2Me] groups, with respect to the carbonyl functional group. The phosphonate, sulfonyl, and carbonyl functional groups are joined through an intramolecular network of attractive interactions, as detected by molecular orbital calculations at the M06-2X/6-31G(d,p) level. These interactions are responsible for the more stable conformations in the gas phase, which also persist in the solid-state structures. The main structural distinction in the title compounds relates to the torsion angle of the aryl group (with respect to the carbonyl group), which gives rise to different interactions in the crystal packing, due to the different positions of the Br atom.
Protein function depends greatly on its structure. Based on this principle, it is vital to study the
protein structure in order to understand its function. This study attempts to build the predicted
model of lipase gene in Rhodococcus sp. NAM81 using homology modelling method. The
predicted structure was then used to investigate the function of protein through several
bioinformatic tools. The DNA sequence of lipase gene was obtained from the Rhodococcus sp.
NAM81 genome scaffold. Blastx analysis showed 100% identity to the target enzyme andthe
appropriate template for homology modelling was determined using Blastp analysis. The 3D
protein structure was built using two homology modelling software, EsyPred3D and Swiss
Model Server. Both structures built obtained LGScore of greater than 4, which means they are
extremely good models according to ProQ validation criteria. Both structures also satisfied the
Ramachandran plot structure validation analysis. The predicted structures were 100% matched
with each other when superimposed with DaliLite pairwise. This shows that both structure
validation servers agreed on the same model. Structure analysis using ProFunc had found seven
motifs and active sites that indicate similar function of this protein with other known proteins.
Thus, this study has successfully produced a good 3D protein structure for the target enzyme.
A new optical trapping design to transport gold nanoparticles using a PANDA ring resonator system is proposed. Intense optical fields in the form of dark solitons controlled by Gaussian pulses are used to trap and transport nanoscopic volumes of matter to the desired destination via an optical waveguide. Theoretically, the gradient and scattering forces are responsible for this trapping phenomenon, where in practice such systems can be fabricated and a thin-film device formed on the specific artificial medical materials, for instance, an artificial bone. The dynamic behavior of the tweezers can be tuned by controlling the optical pulse input power and parameters of the ring resonator system. Different trap sizes can be generated to trap different gold nanoparticles sizes, which is useful for gold nanoparticle therapy. In this paper, we have shown the utility of gold nanoparticle trapping and delivery for therapy, which may be useful for cosmetic therapy and related applications.
Molecular dynamics simulation and biophysical analysis were employed to reveal the characteristics and the influence of ionic liquids (ILs) on the structural properties of DNA. Both computational and experimental evidence indicate that DNA retains its native B-conformation in ILs. Simulation data show that the hydration shells around the DNA phosphate group were the main criteria for DNA stabilization in this ionic media. Stronger hydration shells reduce the binding ability of ILs' cations to the DNA phosphate group, thus destabilizing the DNA. The simulation results also indicated that the DNA structure maintains its duplex conformation when solvated by ILs at different temperatures up to 373.15 K. The result further suggests that the thermal stability of DNA at high temperatures is related to the solvent thermodynamics, especially entropy and enthalpy of water. All the molecular simulation results were consistent with the experimental findings. The understanding of the properties of IL-DNA could be used as a basis for future development of specific ILs for nucleic acid technology.
Theoretically, Ultrasound method is an economical and environmentally friendly or "green" technology, which has been of interest for more than six decades for the purpose of enhancement of oil/heavy-oil production. However, in spite of many studies, questions about the effective mechanisms causing increase in oil recovery still existed. In addition, the majority of the mechanisms mentioned in the previous studies are theoretical or speculative. One of the changes that could be recognized in the fluid properties is viscosity reduction due to radiation of ultrasound waves. In this study, a technique was developed to investigate directly the effect of ultrasonic waves (different frequencies of 25, 40, 68 kHz and powers of 100, 250, 500 W) on viscosity changes of three types of oil (Paraffin oil, Synthetic oil, and Kerosene) and a Brine sample. The viscosity calculations in the smooth capillary tube were based on the mathematical models developed from the Poiseuille's equation. The experiments were carried out for uncontrolled and controlled temperature conditions. It was observed that the viscosity of all the liquids was decreased under ultrasound in all the experiments. This reduction was more significant for uncontrolled temperature condition cases. However, the reduction in viscosity under ultrasound was higher for lighter liquids compare to heavier ones. Pressure difference was diminished by decreasing in the fluid viscosity in all the cases which increases fluid flow ability, which in turn aids to higher oil recovery in enhanced oil recovery (EOR) operations. Higher ultrasound power showed higher liquid viscosity reduction in all the cases. Higher ultrasound frequency revealed higher and lower viscosity reduction for uncontrolled and controlled temperature condition experiments, respectively. In other words, the reduction in viscosity was inversely proportional to increasing the frequency in temperature controlled experiments. It was concluded that cavitation, heat generation, and viscosity reduction are three of the promising mechanisms causing increase in oil recovery under ultrasound.
Nitrate concentration in groundwater is influenced by complex and interrelated variables, leading to great difficulty during the modeling process. The objectives of this study are (1) to evaluate the performance of two artificial intelligence (AI) techniques, namely artificial neural networks and support vector machine, in modeling groundwater nitrate concentration using scant input data, as well as (2) to assess the effect of data clustering as a pre-modeling technique on the developed models' performance. The AI models were developed using data from 22 municipal wells of the Gaza coastal aquifer in Palestine from 2000 to 2010. Results indicated high simulation performance, with the correlation coefficient and the mean average percentage error of the best model reaching 0.996 and 7 %, respectively. The variables that strongly influenced groundwater nitrate concentration were previous nitrate concentration, groundwater recharge, and on-ground nitrogen load of each land use land cover category in the well's vicinity. The results also demonstrated the merit of performing clustering of input data prior to the application of AI models. With their high performance and simplicity, the developed AI models can be effectively utilized to assess the effects of future management scenarios on groundwater nitrate concentration, leading to more reasonable groundwater resources management and decision-making.
Combined computational and experimental strategies for the systematic design of chemical sensor arrays using carbonitrile neutral receptors are presented. Binding energies of acetonitrile, n-pentylcarbonitrile and malononitrile with Ca(II), Mg(II), Be(II) and H⁺ have been investigated with the B3LYP, G3, CBS-QB3, G4 and MQZVP methods, showing a general trend H⁺ > Be(II) > Mg(II) > Ca(II). Hydrogen bonding, donor-acceptor and cation-lone pair electron simple models were employed in evaluating the performance of computational methods. Mg(II) is bound to acetonitrile in water by 12.5 kcal/mol, and in the gas phase the receptor is more strongly bound by 33.3 kcal/mol to Mg(II) compared to Ca(II). Interaction of bound cations with carbonitrile reduces the energies of the MOs involved in the proposed σ-p conjugated network. The planar malononitrile-Be(II) complex possibly involves a π-network with a cationic methylene carbon. Fabricated potentiometric chemical sensors show distinct signal patterns that can be exploited in sensor array applications.
A kinetic model incorporating adsorption, desorption and biodegradation processes was developed to describe the bioregeneration of granular activated carbon (GAC) loaded with 4-chlorophenol (4-CP) and 2,4-dichlorophenol (2,4-DCP), respectively, in simultaneous adsorption and biodegradation processes. The model was numerically solved and the results showed that the kinetic model was well-fitted (R(2)>0.83) to the experimental data at different GAC dosages and at various initial 4-CP and 2,4-DCP concentrations. The rate of bioregeneration in simultaneous adsorption and biodegradation processes was influenced by the ratio of initial chlorophenol concentration to GAC dosage. Enhancement in the rate of bioregeneration was achieved by using the lowest ratio under either one of the following experimental conditions: (1) increasing initial chlorophenol concentration at constant GAC dosage and (2) increasing GAC dosage at constant initial chlorophenol concentration. It was found that the rate enhancement was more pronounced under the second experimental condition.
Optimization of thermo-alkaline disintegration of sewage sludge for enhanced biogas yield was carried out using response surface methodology (RSM) and Box-Behnken design of experiment. The individual linear and quadratic effects as well as the interactive effects of temperature, NaOH concentration and time on the degree of disintegration were investigated. The optimum degree of disintegration achieved was 61.45% at 88.50 °C, 2.29 M NaOH (24.23%w/w total solids) and 21 min retention time. Linear and quadratic effects of temperature are most significant in affecting the degree of disintegration. The coefficient of determination (R(2)) of 99.5% confirms that the model used in predicting the degree of disintegration process has a very good fitness with the experimental variables. The disintegrated sludge increased the biogas yield by 36%v/v compared to non-disintegrated sludge. The RSM with Box-Behnken design is an effective tool in predicting the optimum degree of disintegration of sewage sludge for increased biogas yield.
In this study, palm oil mill effluent (POME) was solubilized by batch thermo-alkaline pre-treatments. A three-factor central composite design (CCD) was applied to identify the optimum COD solubilization condition. The individual and interactive effects of three factors, temperature, NaOH concentration and reaction time, on solubilization of POME were evaluated by employing response surface methodology (RSM). The experimental results showed that temperature, NaOH concentration and reaction time all had an individual significant effect on the solubilization of POME. But these three factors were independent, or there was insignificant interaction on the response. The maximum COD solubilization of 82.63% was estimated under the optimum condition at 32.5 degrees C, 8.83g/L of NaOH and 41.23h reaction time. The confirmation experiment of the predicted optimum conditions verified that the RSM with the central composite design was useful for optimizing the solubilization of POME.
Zeolites P in sodium (NaP) and potassium (KP) forms were used as adsorbents for the removal of calcium (Ca2+) and zinc (Zn2+) cations from aqueous solutions. Zeolite KP was prepared by ion exchange of K+ with Na+ which neutralizes the negative charge of the zeolite P framework structure. The ion exchange capacity of K+ on zeolite NaP was determined through the Freundlich isotherm equilibrium study. Characterization of zeolite KP was determined using infrared spectroscopy and X-ray diffraction (XRD) techniques. From the characterization, the structure of zeolite KP was found to remain stable after the ion exchange process. Zeolites KP and NaP were used for the removal of Ca and Zn from solution. The amount of Ca2+ and Zn2+ in aqueous solution before and after the adsorption by zeolites was analysed using the flame atomic absorption spectroscopy method. The removal of Ca2+ and Zn2+ followed the Freundlich isotherm rather than the Langmuir isotherm model. This result also revealed that zeolite KP adsorbs Ca2+ and Zn2+ more than zeolite NaP and proved that modification of zeolite NaP with potassium leads to an increase in the adsorption efficiency of the zeolite. Therefore, the zeolites NaP and KP can be used for water softening (Ca removal) and reducing water pollution/toxicity (Zn removal).
Recently, the increased demand of fructooligosaccharides (FOS) as a functional food has alarmed researchers to screen and identify new strains capable of producing fructosyltransferase (FTase). FTase is the enzyme that converts the substrate (sucrose) to glucose and fructose. The characterization of complex sugar such as table sugar, brown sugar, molasses, etc. will be carried out and the sugar that contained the highest sucrose concentration will be selected as a substrate. Eight species of macro-fungi will be screened for its ability to produce FTase and only one strain with the highest FTase activity will be selected for further studies. In this work, neural networks (NN) have been chosen to model the process based on their excellent 'resume' in coping with nonlinear process. Bootstrap re-sampling method has been utilized in re-sampling the data in this work. This method has successfully modeled the process as shown in the results.
A poly(vinyl alcohol) (PVA) hydrogel composite scaffold containing N,O-carboxymethylated chitosan (NOCC) was tested to assess its potential as a scaffold for cartilage tissue engineering in a weight-bearing environment. The mechanical properties under unconfined compression for different hydration periods were investigated. The effect of supplementing PVA with NOCC (20wt.% PVA:5vol.% NOCC) produced a porosity of 43.3% and this was compared against a non-porous PVA hydrogel (20g PVA: 100ml of water, control). Under non-hydrated conditions, the porous PVA-NOCC hydrogel behaved in a similar way to the control non-porous PVA hydrogel, with similar non-linear stress-strain response under unconfined compression (0-30% strain). After 7days' hydration, the porous hydrogel demonstrated a reduced stiffness (0.002kPa, at 25% strain), resulting in a more linear stiffness relationship over a range of 0-30% strain. Poisson's ratio for the hydrated non-porous and porous hydrogels ranged between 0.73 and 1.18, and 0.76 and 1.33, respectively, suggesting a greater fluid flow when loaded. The stress relaxation function for the porous hydrogel was affected by the hydration period (from 0 to 600s); however the percentage stress relaxation regained by about 95%, after 1200s for all hydration periods assessed. No significant differences were found between the different hydration periods between the porous hydrogels and control. The calculated aggregate modulus, H(A), for the porous hydrogel reduced drastically from 10.99kPa in its non-hydrated state to about 0.001kPa after 7days' hydration, with the calculated shear modulus reducing from 30.92 to 0.14kPa, respectively. The porous PVA-NOCC hydrogel conformed to a biphasic, viscoelastic model, which has the desired properties required for any scaffold in cartilage tissue engineering.
Previously, direct-proportional length-based DNA computing (DPLB-DNAC) for solving weighted graph problems has been reported. The proposed DPLB-DNAC has been successfully applied to solve the shortest path problem, which is an instance of weighted graph problems. The design and development of DPLB-DNAC is important in order to extend the capability of DNA computing for solving numerical optimization problem. According to DPLB-DNAC, after the initial pool generation, the initial solution is subjected to amplification by polymerase chain reaction and, finally, the output of the computation is visualized by gel electrophoresis. In this paper, however, we give more attention to the initial pool generation of DPLB-DNAC. For this purpose, two kinds of initial pool generation methods, which are generally used for solving weighted graph problems, are evaluated. Those methods are hybridization-ligation and parallel overlap assembly (POA). It is found that for DPLB-DNAC, POA is better than that of the hybridization-ligation method, in terms of population size, generation time, material usage, and efficiency, as supported by the results of actual experiments.
A lipase catalysed enantioselective hydrolysis process under in situ racemization of the remaining (R)-ibuprofen ester substrate with sodium hydroxide as the catalyst was developed for the production of S-ibuprofen from (R,S)-ibuprofen ester in isooctane. Detailed investigations on parameters study indicated that 0.5 M NaOH, addition of 20% (v/v) co-solvent (dimethyl sulphoxide), operating temperature of 45 degrees C, and 40 mmol/L substrate gave 86% conversion and 99.4% optical purity of S-ibuprofen in dynamic kinetic resolution. Meanwhile, in common enzymatic kinetic resolution process, only 42% conversion of the racemate and 93% enantiomeric excess of the product was obtained which are of lower values as compared to dynamic kinetic resolution. The S-ibuprofen produced during each process was evaluated and approximately 50% increment in concentration of S-acid product was produced when dynamic kinetic resolution was applied into the process.
Kinetics of production of biodiesel by enzymatic methanolysis of vegetable oils using lipase has been investigated. A mathematical model taking into account the mechanism of the methanolysis reaction starting from the vegetable oil as substrate, rather than the free fatty acids, has been developed. The kinetic parameters were estimated by fitting the experimental data of the enzymatic reaction of sunflower oil by two types of lipases, namely, Rhizomucor miehei lipase (RM) immobilized on ion-exchange resins and Thermomyces lanuginosa lipase (TL) immobilized on silica gel. There was a good agreement between the experimental results of the initial rate of reaction and those predicted by the proposed model equations, for both enzymes. From the proposed model equations, the regions where the effect of alcohol inhibition fades, at different substrate concentrations, were identified. The proposed model equation can be used to predict the rate of methanolysis of vegetable oils in a batch or a continuous reactor and to determine the optimal conditions for biodiesel production.
In this work, the potential of CO₂ mineral carbonation of brucite (Mg(OH)2) derived from the Mount Tawai peridotite (forsterite based (Mg)₂SiO4) to produce thermodynamically stable magnesium carbonate (MgCO3) was evaluated. The effect of three main factors (reaction temperature, particle size, and water vapor) were investigated in a sequence of experiments consisting of aqueous acid leaching, evaporation to dryness of the slurry mass, and then gas-solid carbonation under pressurized CO2. The maximum amount of Mg converted to MgCO₃ is ~99%, which occurred at temperatures between 150 and 175 °C. It was also found that the reduction of particle size range from >200 to <75 µm enhanced the leaching rate significantly. In addition, the results showed the essential role of water vapor in promoting effective carbonation. By increasing water vapor concentration from 5 to 10 vol %, the mineral carbonation rate increased by 30%. This work has also numerically modeled the process by which CO₂ gas may be sequestered, by reaction with forsterite in the presence of moisture. In both experimental analysis and geochemical modeling, the results showed that the reaction is favored and of high yield; going almost to completion (within about one year) with the bulk of the carbon partitioning into magnesite and that very little remains in solution.