A Quantitative Structure–Activity Relationship Study of Calpeptin (Calpain Inhibitor) as an Anticancer Agent

Calpeptin analogs show anticancer properties with inhibition of calpain. In this work, we applied a quantitative structure–activity relationship (QSAR) model on 34 calpeptin derivatives to select the most appropriate compound. QSAR was employed to generate the models and predict the more significant compounds through a series of calpeptin derivatives. The HyperChem, Gaussian 09, and Dragon software programs were used for geometry optimization of the molecules. The 2D and 3D molecular structures were drawn by ChemDraw (Ultra 16.0) and Chem3D (Pro16.0) software. The Unscrambler program was used for the analysis of data. Multiple linear regression (MLR‐MLR), partial least‐squares (MLR‐PLS1), principal component regression (MLR‐PCR), a genetic algorithm‐artificial neural networks (GA‐ANN), and a novel similarity analysis‐artificial neural network (SA‐ANN) method were used to create QSAR models. Among the three MLR models, MLR‐MLR provided better statistical parameters. The R² and RMSE of the prediction were estimated as 0.8248 and 0.26, respectively. Nevertheless, the constructed model using GA‐ANN revealed the best statistical parameters among the studied methods (R² test = 0.9643, RMSE test = 0.0155, R² train = 0.9644, RMSE train = 0.0139). The GA‐ANN model is found to be the most favorable method among the statistical methods and can be employed for designing new calpeptin analogs as potent calpain inhibitors in cancer treatment.     

Prediction of CO2 Solubility in Polymers by Radial Basis Function Artificial Neural Network Based on Chaotic Self-adaptive Particle Swarm Optimization and Fuzzy Clustering Method

To replace costly and time-consuming experimentation in laboratory, a novel solubility prediction model based on chaos theory, self-adaptive particle swarm optimization （PSO）, fuzzy c-means clustering method, and radial ba- sis function artificial neural network （RBF ANN） is proposed to predict CO2 solubility in polymers, hereafter called CSPSO-FC RBF ANN. The premature convergence problem is overcome by modifying the conventional PSO using chaos theory and self-adaptive inertia weight factor. Fuzzy c-means clustering method is used to tune the hidden centers and radial basis function spreads. The modified PSO algorithm is employed to optimize the RBF ANN connection weights. Then, the proposed CSPSO-FC RBF ANN is used to investigate solubility of CO2 in polystyrene （PS）, polypropylene （PP）, poly（butylene succinate） （PBS） and poly（butylene succinate-co-adipate） （PBSA）, respec- tively. Results indicate that CSPSO-FC RBF ANN is an effective method for gas solubility in polymers. In addition, compared with conventional RBF ANN and PSO ANN, CSPSO-FC RBF ANN shows better performance. The values of average relative deviation （ARD）, squared correlation coefficient （R2） and standard deviation （SD） are 0.1071, 0.9973 and 0.0108, respectively. Statistical data demonstrate that CSPSO-FC RBF ANN has excellent prediction capability and high-accuracy, and the correlation between prediction values and experimental data is good.     

Mixed phase Fe2O3/Mn3O4 magnetic nanocomposite for enhanced adsorption of methyl orange dye: Neural network modeling and response surface methodology optimization

In this research, a novel magnetic mesoporous adsorbent with mixed phase of Fe₂O₃/Mn₃O₄ nanocomposite was prepared by a facile precipitating method and characterized extensively. The prepared nanocomposite was used as adsorbent for toxic methyl orange (MO) dye removal from aqua matrix considering its high surface area (178.27 m²/g) with high saturation magnetization (23.07 emu/g). Maximum dye adsorption occurs at solution pH 2.0 and the electrostatic attraction between anionic form of MO dye molecules and the positively charged nanocomposite surface is the main driving force behind this adsorption. Response surface methodology (RSM) was used for optimizing the process variables and maximum MO removal of 97.67% is obtained at optimum experimental condition with contact time, adsorbent dose and initial MO dye concentration of 45 min, 0.87 g/l and 116 mg/l, respectively. Artificial neural network (ANN) model with optimum topology of 3–5–1 was developed for predicting the MO removal (%), which has shown higher predictive ability than RSM model. Maximum adsorption capacity of this nanocomposite was found to be 322.58 mg/g from Langmuir isotherm model. Kinetic studies reveal the applicability of second‐order kinetic model with contribution of intra‐particle diffusion in this process.     

Bulk Gas‐Phase Acidity

The capability of a gaseous Brønsted acid HB to deliver protons to a base is usually described by the gas‐phase acidity (GA) value of the acid. However, GA values are standard Gibbs energy differences and refer to individual gas pressures of 1 bar for acid HB, base B^?, and proton H⁺. We show that the GA value is not suited to describe the bulk acidity of a gaseous acid. Here the pressure dependence of the activities of HB, H(HB)_n⁺, and B(HB)_m^? that result from gaseous autoprotolysis have to be considered. In this work, the pressure‐dependent absolute chemical potential of the proton in the representative gaseous proton acids CH₄, NH₃, H₂O, HF, and HCl was worked out and the general theory to describe bulk gas phase acidity—that can directly be compared with solution acidity—was developed.     

Production and Physico-chemical Characterization of a Biosurfactant Produced by <Emphasis Type="Italic">Pseudomonas aeruginosa</Emphasis> OBP1 Isolated from Petroleum Sludge

Pseudomonas aeruginosa strain OBP1, isolated from petroleum sludge, was used to produce biosurfactant from a modified mineral salt medium with 2% n-hexadecane as sole source of carbon. The crude biosurfactant was fractionated using TLC and HPLC. Using FTIR spectroscopy, ¹H NMR, and LC-MS analyses, the chemical structure of the purified fraction of crude biosurfactant was identified as rhamnolipid species. The LC-MS spectra show that monorhamnolipid (l-rhamnopyranosyl-β-hydroxydecanoyl-β- hydroxydecanoate, Rha-C₁₀-C₁₀) was produced in abundance with the predominant congener [M–H]⁻ ions for l-rhamnopyranosyl-l-rhamnopyranosyl-3-hydroxydecanoyl-3-hydroxydecanoate (Rha-Rha-C₁₀-C₁₀). Seven different carbon substrates and five nitrogen sources were examined for their effect on rhamnolipid production. Using n-hexadecane (20 g/l) as carbon substrate and urea along with (NH₄)₂SO₄ (2 g/l each) as nitrogen source was found to be the best, with a maximum yield of 4.8 g/l. The biosurfactant reduced the surface tension of water to 31.1 mNm⁻¹ with a critical micelle concentration of 45 mg/l. The biosurfactant showed a better emulsifying activity against a variety of hydrocarbon and achieved a maximum emulsion index of 82% for diesel. The purified biosurfactant showed a significant antibacterial activity against Staphylococcus aureus at a minimum inhibitory concentration of 8 μg/ml.     

Zymomonas mobilis as catalyst for the biotechnological production of sorbitol and gluconic acid

The conversion of glucose and fructose into gluconic acid (GA) and sorbitol (SOR) was conducted in a batch reactor with free (CTAB-treated or not) or immobilized cells of Zymomonas mobilis. High yields (more than 90%) of gluconic acid and sorbitol were attained at initial substrate concentration of 600 g/L (glucose plus fructose at 1:1 ratio), using cells with glucose-fructose-oxidoreductase activity of 75 U/L. The concentration of the products varied hyperbolically with time according to the equations (GA)=t(GA)_max/(W_GA +t), (SOR)=t (SOR)_max/(W_Sor+t), v_GA=[W_GA (GA)_max]/(W_GA+t)² and V_SOR=[W_SOR (SOR)_max]/(W_SOR+t)². Taking the test carried out with free CTAB-treated cells as an example, the constant parameters were (GA)_max= 541 g/L, (SOR)_max=552 g/L, W_GA=4.8h, W_SOR=4.9h, υ_GA=112.7 g/L· and υ_SOR=112.7 g/L·.     

A sequential injection electronic tongue employing the transient response from potentiometric sensors for anion multidetermination

Intelligent and automatic systems based on arrays of non-specific-response chemical sensors were recently developed in our laboratory. For multidetermination applications, the normal choice is an array of potentiometric sensors to generate the signal, and an artificial neural network (ANN) correctly trained to obtain the calibration model. As a great amount of information is required for the proper modelling, we proposed its automated generation by using the sequential injection analysis (SIA) technique. First signals used were steady-state: the equilibrium signal after a step-change in concentration. We have now adapted our procedures to record the transient response corresponding to a sample step. The novelty in this approach is therefore the use of the dynamic components of the signal in order to better discriminate or differentiate a sample. In the developed electronic tongue systems, detection is carried out by using a sensor array formed by five potentiometric sensors based on PVC membranes. For the developed application we employed two different chloride-selective sensors, two nitrate-selective sensors and one generic response sensor. As the amount of raw data (fivefold recordings corresponding to the five sensors) is excessive for an ANN, some feature extraction step prior to the modelling was needed. In order to attain substantial data reduction and noise filtering, the data obtained were fitted with orthonormal Legendre polynomials. In this case, a third-degree Legendre polynomial was shown to be sufficient to fit the data. The coefficients of these polynomials were the input information fed into the ANN used to model the concentrations of the determined species (Cl⁻, and ). Best results were obtained by using a backpropagation neural network trained with the Bayesian regularisation algorithm; the net had a single hidden layer containing three neurons with the tansig transfer function. The results obtained from the time-dependent response were compared with those obtained from steady-state conditions, showing the former superior performance. Finally, the method was applied for determining anions in synthetic samples and real water samples, where a satisfactory comparison was also achieved.      

Oxygen uptake rate in production of xylitol by Candida guilliermondii with different aeration rates and initial xylose concentrations

The global oxygen uptake rate (OUR) and specific oxygen uptake rates (SOUR) were determined for different values of the volumetric oxygen mass transfer coefficient (15, 43, and 108 h⁻¹), and for varying initial xylose concentrations (50, 100, 150, and 200 g/L) in shaking flasks. The initial cell concentration was 4.0 g/L, and there was only significant growth in the fermentation with the highest oxygen availability. In this condition, OUR increased proportionally to cell growth, reaching maximum values from 2.1 to 2.5 g of O₂/(L·h) in the stationary phase when the initial substrate concentration was raised from 50 to 200 g/L, respectively. SOUR showed different behavior, growing to a maximum value coinciding with the beginning of the exponential growth phase, after which point it decreased. The maximum SOUR values varied from 265 to 370 mg of O₂/(g of cell·h), indicating the interdependence of this parameter and the substrate concentration. Although the volumetric productivity dropped slightly from 1.55 to 1.18 g of xylitol/(L·h), the strain producing capacity (γ _P/X ) rose from 9 to 20.6 g/g when the initial substrate concentration was increased from 50 to 200 g/L. As for the xylitol yield over xylose consumed (γ _P/S ), there was no significant variation, resulting in a mean value of 0.76 g/g. The results are of interest in establishing a strategy for controlling the dynamic oxygen supply to maximize volumetric productivity.     

EQUILIBRIUM HEAT OF FUSION OF POLYTETRAFLUOROETHYLENE

The reliability of the values of equilibrium heat of fusion, △H_m, of polytetrafluoroethylene (PTFE)reported in the literature and the inadequacy of the generally accepted value of 13 .7 or 14.6 cal/gwere discussed. Through extrapolating linear plot of △H_m vs. V_(sp) of the thermally aged PTFE virginas-polymerized samples prepared in accord with ASTM D 1457-81a, △H_m~o=79.6J/g (19.0 cal/g)and V_(sp) (specific volume of amorphous PTFE at 23℃)=0.480 cm~3/g (or ρ_a=2 .08g/cm~3) were ob-tained. The heats of fusion, △H_m, of the thermally aged and γ-irradiated samples are different irrespec-tive of the same V_(sp) value for both samples. A qualitative explanation of this phenomenon was givenbased on the H_v patterns of SALS and Kawai's model.     

RSM analysis of the effects of the oxygen transfer coefficient and inoculum size on the xylitol production by Candida guilliermondii

Biotechnology production of xylitol is an excellent alternative to the industrial chemical process for the production of this polyalcohol. In this work the behavior of Candida guilliermondii yeast was studied when crucial process variables were modified. The K _La (between 18 and 40/h) and the initial cell mass (between 4 and 10 g) were considered as control variables. A response surface methodology was applied to the experimental design to study the resulting effect when the control variables were modified. A regression model was developed and used to determine an optimal value that was further validated experimentally. The optimal values determined for K _La and X ₀ were 32.85/h and 9.86 g, respectively, leading to maximum values for productivity (1.628 g/h) and xylitol yield (0.708 g/g).     

Optimization of critical medium components for the maximal production of gentamicin by Micromonospora echinospora ATCC 15838 using response surface methodology

Optimization of the fermentation medium components for maximum gentamicin production by Micromonospora echinospora ATCC 15838 was carried out. Response surface methodology was applied to optimize the medium constituents. A 2⁴full-factorial central composite design was chosen to explain the combined effects of the four medium constituents, viz. starch, soyabean meal, K₂HPO₄, and CoCl₂ and to design a minimum number of experiments. A second order model was developed and fitted using least square method. The R ² value of the model was 0.9723, which shows that model is best fit for the present studies. The results of analysis of variance and regression of a second order model showed that the linear effects of starch (p<0.001697) and CoCl₂(p<7.99E-13), and cross product effects of starch and soyabean meal (p<0.029876) and soyabean meal and CoCl₂ (p<0.008909) were more significant, suggesting that these were critical variables having the greatest effect on the production of gentamicin in the production medium. The optimized medium consisting of 9 g/L starch, 3 g/L soyabean meal, 0.9 g/L K₂HPO₄, and 0.01 g/L CoCL₂ predicted 850 mg/L of gentamicin which was almost 110% higher than that of the unoptimized medium. The amounts of starch, soyabean meal, and K₂HPO₄ required were also reduced with RSM.     

2-(α-Pyridyl)-thioquinaldinamide (PTQA)-A novel fluorimetric reagent in inorganic trace analysis. I: The nonextractive,nonquenching fluorescent method for the determination of chromium(VI)

A direct fluorimetric method for determining Cr(VI) in aqueous solutions is described. The nonfluorescent reagent 2-(-pyridyl)-thioquinaldinamide (PTQA) and Cr(VI) interact to produce an intensely fluorescent species [_ex(max) 360 nm; _em(max) 500 nm] showing constant and maximum fluorescence intensity in slightly acidic media (0.18N–1.08N H₂SO₄). The fluorescence attains its maximum value within 5 min and remains unchanged for 24 h. The system obeys Beer's law from 2 ng/ml to 0.8 g/ml of Cr(VI). Over sixty cations, anions and complexing agents are without any effect on the fluorimetric determination of 0.1 g/ml of Cr(VI). The method has been tested with synthetic mixtures, steels, solutions containing both Cr(III) and Cr(VI), and environmental samples.