Sensory, physicochemical and microbiological quality of irradiated minimally processed cauliflower

Minimally processed cauliflower samples were irradiated, stored at 5 °C for 2 weeks and analyzed for sensory, physicochemical and microbiological qualities at 0th, 7th and 14th days. The data showed highest mean values of 7.93 and 7.57 for appearance and flavor, respectively, for 1.0 kGy treated samples. The D₁₀ values of contaminating microorganisms on cauliflower were 0.20 (Escherischia coli) and 0.24 kGy (Salmonella paratyphae A.) and the resulting 5D₁₀ value was 1.2 kGy. The study revealed that a dose of 1.5 kGy is enough for retention of quality and reduction of microbial load to 5D₁₀ values in cauliflower during 2 weeks storage at refrigerated temperature.     

Direct preparation and structure determination of tertiary and secondary amine boranes from primary or secondary amine boranes

New secondary and tertiary amine borane derivatives were prepared in a one-pot reaction starting from primary amine boranes. The reaction involves treatment of an amine borane with 2 equivalents of s-BuLi at −78 °C. In general, mixtures of mono and di metallated products were obtained. Alkyl iodides and benzyl chloride reacted with the lithiated amine, but aldehydes and ketones were reduced. Conversion was high as determined by NMR, but moderate to low yields were obtained after chromatography, possibly due to decomposition on silica. Crystal structures were obtained for the compounds 3a, 3b and 3c.     

Addition of hydrogen halides to alkylidenecyclopropanes: a highly efficient and stereoselective method for the preparation of homoallylic halides

The reaction of alkylidenecyclopropanes with HCl or with HBr proceeds very smoothly at 120°C to produce the corresponding homoallylic halides stereoselectively in good to excellent yields. For example, the reaction of (1-phenylbenzylidene)cyclopropane, (1-butylpentylidene)cyclopropane and octylidenecyclopropane with hydrochloric acid produced the corresponding homoallylic chlorides, 4-chloro-1,1-diphenyl-1-butene, 4-butyl-1-chloro-3-octene and (E)-1-chloro-3-undecene in 99, 96, and 87% yields, respectively. The reaction of (1-butylpentylidene)cyclopropane with hydrobromic acid yielded 1-bromo-4-butyl-3-octene in 95% yield.     

Scattering Behavior of Restructured Aggregates: A Simulation Study

Simulations of diffusion-limited cluster-cluster aggregation (DLCA) with no restructuring, full restructuring, and partial restructuring have been performed. The scattering patterns produced from these aggregates have been simulated using the Rayleigh-Gans-Debye approximation. Pure DLCA aggregates produced a scattering pattern with the slope of the fractal region being about -1.8. In contrast, the slope of the fractal region of the scattering pattern for fully restructured aggregates was about -2.1, indicating an increase in fractal dimension. Partial restructuring at large length scales produced an upward turn in the scattering pattern at low qr(o), while at high qr(o) the fractal section of the pure DLCA aggregate was retained. This last result was expected and is consistent with the results and postulations of several other workers. This simulation shows that the type of scattering pattern often obtained from orthokinetic or sheared aggregation can be produced by restructuring of aggregates at large length scales. Copyright 2001 Academic Press.     

Brownian motion in magnetic field: A model for a semi-quantum stochastic process

The Brownian motion of an ensemble of charged particles in a quantizing magnetic field is considered in a simple quasi-classical model. The model describes random jumps between the Landau levels—corresponding to the quantized motion perpendicular to the magnetic field, and markovian fluctuations in momentum space—corresponding to the classical motion parallel to the field. A random walk dynamics is adopted for the former while an Ornstein-Uhlenbeck process is considered for the latter. The resulting Fokker-Planck equations constitute a semi-quantum stochastic process. The equations are solved and several physical aspects of the underlying system are discussed.     

Synthesis and electronic characterization of bipyridine dithiolate rhodium(III) complexes

Five new mixed diimine 1,1'-dithiolate or dithiocarbamate ligand complexes of the form [Rh(bpy)2(SS)][PF6]n, where bpy = 2,2'-bipyridine and SS = various substituted dialkyldithiocarbamates or 1,1'-dithiolates, were synthesized from cis-[Rh(bpy)2(OTf)2][OTf]. The triflate ligands are easily displaced by other ligands and allow these syntheses to proceed in high yields (80-90% overall) under relatively mild reaction conditions and to give high purity products. Electrochemistry shows irreversible two-electron reduction of Rh(III) to Rh(I) and a concomitant loss of one bipyridine ligand; this is followed by reversible one-electron reduction of the remaining 2,2'-bipyridine ligand. The electronic characterizations of these complexes are consistent with significant delocalization of the sulfur electron density onto the empty metal d orbitals. The 1,1'-dithiolate ligands induce larger red shifts in the absorption and emission spectra than the dithiocarbamates as the 1,1'-dithiolates have a more extensive conjugation system.     

Evidence of Shear Rate Dependence on Restructuring and Breakup of Latex Aggregates

Small-angle static light scattering has been used to probe the evolution of aggregate size and structure in the shear-induced aggregation of latex particles. The size of aggregates obtained from the particle-sizing instrument (Coulter LS230) was compared with the size of those obtained with another approach utilizing the Guinier equation on the scattering data. Comparison of the two methods for studying the effects of mixing on the evolution of the aggregate size with time revealed similar trends. The aggregate structures were quantified in terms of their fractal dimensions on the grounds of the validity of Rayleigh-Gans-Debye scattering theory for the fractal aggregates. Analysis of the scattering patterns of aggregates verified that restructuring of the aggregates occurred as the aggregates were exposed to certain shear environments, resulting in a scale-dependent structure that could not be quantified by a fractal dimension. The effect of restructuring on aggregate size was particularly noticeable when the aggregates were exposed to average shear rates of 40 to 80 s(-1), whereas no significant restructuring occurred at lower shear rates. At 100 s(-1), the fragmentation of aggregates appeared to be more significant than aggregate compac-tion. Copyright 2001 Academic Press.     

Anti-Quorum Sensing and Anti-Biofilm Activity of Pelargonium × hortorum Root Extract against Pseudomonas aeruginosa: Combinatorial Effect of Catechin and Gallic Acid

HPLC-UV was used to compare the major constituents of two Pelargonium × hortorum cultivars and Pelargonium sidoides root extract. It revealed the presence of catechin and gallic acid in high concentrations and the absence of umckalin in P. × hortorum root extracts. The antibacterial activity of these extracts was screened against 19 Pseudomonas aeruginosa clinical isolates. P. × hortorum root extracts showed the lowest MIC values (512–1024 µg/mL). This activity was concluded to be attributable to the high concentrations of catechin and gallic acid. The anti-biofilm activity of catechin, gallic acid, and their combination was examined by a crystal violet assay. The combination reduced the percentage of strong and moderate biofilm-forming isolates from 52.63% to 5.26%. The impact on lasI and lasR genes expression using qRT-PCR and simultaneous docking against LasR protein was explored. The combination downregulated lasI and lasR gene expression in eight and six P. aeruginosa isolates, respectively, and showed the greatest docking score. Additionally, the in vivo protection capability of this combination in infected mice showed enhancement in the survival rate. Our study revealed the potential biofilm and quorum-sensing-inhibitory activity of the catechin and gallic acid combination as a novel alternative to inhibit bacterial pathogenicity.     

Cerium Oxide Nanorods Synthesized by Dalbergia sissoo Extract for Antioxidant,Cytotoxicity, and Photocatalytic Applications

In this study, cerium oxide nanorods (CeO₂-NRs) were synthesized by using the phytochemicals present in the Dalbergia sissoo extract. The physiochemical characteristics of the as-prepared CeO₂-NRs were investigated by using ultraviolet-visible spectroscopy (UV-VIS), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction analysis (XRD). The SEM and UV-VIS analyses revealed that the acquired nanomaterials possessed a rod-like morphology while the XRD results further confirmed that the synthesized NRs exhibited a cubic crystal lattice system. The antioxidant capacity of the synthesized CeO₂-NRs was investigated by using several in vitro biochemical assays. It was observed that the synthesized NRs exhibited better antioxidant potential in comparison to the industrial antioxidant of the butylated hydroxyanisole (BHA) in 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay. The biochemical assays, including lipid peroxidation (LPO), total antioxidant capacity (TAC), and catalase activity (CAT), were also performed in the human lymphocytes incubated with the CeO₂-NRs to investigate the impact of the NRs on these oxidative biomarkers. Enhanced reductive capabilities were observed in all the assays, revealing that the NRs possess excellent antioxidant properties. Moreover, the cytotoxic potential of the CeO₂-NRs was also investigated with the MTT assay. The CeO₂-NRs were found to effectively kill off the cancerous cells (MCF-7 human breast cancer cell line), further indicating that the synthesized NRs exhibit anticancer potential as well. One of the major applications studied for the prepared CeO₂-NRs was performing the statistical optimization of the photocatalytic degradation reaction of the methyl orange (MO) dye. The reaction was optimized by using the technique of response surface methodology (RSM). This advanced approach facilitates the development of the predictive model on the basis of central composite design (CCD) for this degradation reaction. The maximum degradation of 99.31% was achieved at the experimental optimized conditions, which corresponded rather well with the predicted percentage degradation values of 99.58%. These results indicate that the developed predictive model can effectively explain the performed experimental reaction. To conclude, the CeO₂-NRs exhibited excellent results for multiple applications.     

Solubility Optimization of Loxoprofen as a Nonsteroidal Anti-Inflammatory Drug: Statistical Modeling and Optimization

Industrial-based application of supercritical CO₂ (SCCO₂) has emerged as a promising technology in numerous scientific fields due to offering brilliant advantages, such as simplicity of application, eco-friendliness, and high performance. Loxoprofen sodium (chemical formula C₁₅H₁₈O₃) is known as an efficient nonsteroidal anti-inflammatory drug (NSAID), which has been long propounded as an effective alleviator for various painful disorders like musculoskeletal conditions. Although experimental research plays an important role in obtaining drug solubility in SCCO₂, the emergence of operational disadvantages such as high cost and long-time process duration has motivated the researchers to develop mathematical models based on artificial intelligence (AI) to predict this important parameter. Three distinct models have been used on the data in this work, all of which were based on decision trees: K-nearest neighbors (KNN), NU support vector machine (NU-SVR), and Gaussian process regression (GPR). The data set has two input characteristics, P (pressure) and T (temperature), and a single output, Y = solubility. After implementing and fine-tuning to the hyperparameters of these ensemble models, their performance has been evaluated using a variety of measures. The R-squared scores of all three models are greater than 0.9, however, the RMSE error rates are 1.879 × 10⁻⁴, 7.814 × 10⁻⁵, and 1.664 × 10⁻⁴ for the KNN, NU-SVR, and GPR models, respectively. MAE metrics of 1.116 × 10⁻⁴, 6.197 × 10⁻⁵, and 8.777 × 10⁻⁵errors were also discovered for the KNN, NU-SVR, and GPR models, respectively. A study was also carried out to determine the best quantity of solubility, which can be referred to as the (x₁ = 40.0, x₂ = 338.0, Y = 1.27 × 10⁻³) vector.