Анализ рисков для здоровья населения питьевой воды, обеззараженной диоксидом хлора (обзор литературы и собственных исследований)

Проаналізовано данні літератури і особистих досліджень щодо безпечності питної води, знезараженої диоксидом хлору. Показана відсутність самостійних досліджень щодо вивчення впливу диоксиду хлору і хлориту на біохімічні константи сироватки крові і активність ферментів. Вказано, що ці показники є у більшій мірі інформативними, ніж традиційні (число еритроцитів, рівень гемоглобіну) як тест-реакції на можливу окислювальну деструкцію під впливом диоксиду хлору і хлорит-аніону.The given literatures and own researches about safety of the potable water disinfected of chlorine dioxide are analyzed. Absence of independent researches of chlorine dioxide and chlorite influence on biochemical constants of blood whey and levels of enzymes activity ascertained. It is specified, that these parameters are in the greater degree informative, rather than traditional (erythrocyte number, level of hemoglobin) as tests - reactions on possible oxidizing destruction under influence of chlorine dioxide and chlorite anion

The effect of iron catalyzed graphitization on the textural properties of carbonized cellulose: Magnetically separable graphitic carbon bodies for catalysis and remediation

Whereas pyrolysis of pristine microcrystalline cellulose spheres yields nonporous amorphous carbon bodies, pyrolysis of microcrystalline cellulose spheres loaded with iron salts leads to the formation of magnetically separable mesoporous graphitic carbon bodies. The microcrystalline cellulose spheres loaded with either iron(III) nitrate, ammonium iron(III) citrate or iron(III) chloride were pyrolyzed up to 800 °C. Temperature dependent X-ray diffraction analysis shows that the iron salts are transformed into iron oxide nanoparticles; their size and distribution are influenced by the anion of the iron salt. The iron oxide nanoparticles are subsequently carbothermally reduced by the amorphous carbon that is obtained from the pyrolysis of the microcrystalline cellulose. Next, the iron nanoparticles catalyze the conversion of the amorphous carbon to graphitic carbon nanostructures as shown with XRD, electron microscopy and Raman spectroscopy. The extent of graphitization depends on the iron nanoparticle size. Nitrogen physisorption measurements show that this graphitization process introduces mesopores into the carbon bodies. The benefits of the properties of the resulting carbon bodies (ferromagnetic character, graphitic content, mesoporosity) are discussed in connection with applications in liquid-phase catalysis and remediation

Passiflora incarnata attenuation of neuropathic allodynia and vulvodynia apropos GABA-ergic and opioidergic antinociceptive and behavioural mechanisms

Background: Passiflora incarnata is widely used as an anxiolytic and sedative due to its putative GABAergic properties. Passiflora incarnata L. methanolic extract (PI-ME) was evaluated in an animal model of streptozotocininduced diabetic neuropathic allodynia and vulvodynia in rats along with antinociceptive, anxiolytic and sedative activities in mice in order to examine possible underlying mechanisms. Methods: PI-ME was tested preliminary for qualitative phytochemical analysis and then quantitatively by proximate and GC-MS analysis. The antinociceptive property was evaluated using the abdominal constriction assay and hot plate test. The anxiolytic activity was performed in a stair case model and sedative activity in an open field test. The antagonistic activities were evaluated using naloxone and/or pentylenetetrazole (PTZ). PI-ME was evaluated for prospective anti-allodynic and anti-vulvodynic properties in a rat model of streptozotocin induced neuropathic pain using the static and dynamic testing paradigms of mechanical allodynia and vulvodynia. Results: GC-MS analysis revealed that PI-ME contained predominant quantities of oleamide (9-octadecenamide), palmitic acid (hexadecanoic acid) and 3-hydroxy-dodecanoic acid, among other active constituents. In the abdominal constriction assay and hot plate test, PI-ME produced dose dependant, naloxone and pentylenetetrazole reversible antinociception suggesting an involvement of opioidergic and GABAergic mechanisms. In the stair case test, PI-ME at 200 mg/kg increased the number of steps climbed while at 600 mg/kg a significant decrease was observed. The rearing incidence was diminished by PI-ME at all tested doses and in the open field test, PI-ME decreased locomotor activity to an extent that was analagous to diazepam. The effects of PI-ME were antagonized by PTZ in both the staircase and open field tests implicating GABAergic mechanisms in its anxiolytic and sedative activities. In the streptozotocin-induced neuropathic nociceptive model, PI-ME (200 and 300 mg/kg) exhibited static and dynamic anti-allodynic effects exemplified by an increase in paw withdrawal threshold and paw withdrawal latency. PI-ME relieved only the dynamic component of vulvodynia by increasing flinching response latency. Conclusions: These findings suggest that Passiflora incarnata might be useful for treating neuropathic pain. The antinociceptive and behavioural findings inferring that its activity may stem from underlying opioidergic and GABAergic mechanisms though a potential oleamide-sourced cannabimimetic involvement is also discussed

Scaffolded amino acids as a close structural mimic of type-3 copper binding sites

We report the use of triazacyclophane (TAC)-scaffolded amino acids as a structural mimic for 3-histidine metal-binding sites in metalloproteins, especially for the mimicry of type-3 copper binding sites as are present in hemocyanin, tyrosinase and catechol oxidase

Prediction of long and short residue properties of crude oils from their infrared and near-infrared spectra

Research has been carried out to determine the feasibility of chemometric modeling of infrared (IR) and near-infrared (NIR) spectra of crude oils to predict the long residue (LR) and short residue (SR) properties of these samples. A novel method is described to predict short residue properties at different flashing temperatures based on the IR spectrum of a crude oil measured at room temperature. The resulting method is the subject of European patent application number 07251853.3 filed by Shell Internationale Research Maatschappij B.V. The study has been carried out on 47 crude oils and 4 blends, representing a large variety of physical and chemical properties. From this set, 28 representative samples were selected by principle component analysis (PCA) and used for calibration. The remaining 23 samples were used as a test set to validate the obtained partial least squares (PLS) regression models. The results demonstrate that this integrated approach offers a fast and viable alternative for the currently applied elaborate ASTM (American Society for Testing and Materials) and IP (Institute of Petroleum) methods. IR spectra, in particular, were found to be a useful input for the prediction of different LR properties. Root mean square error of prediction values of the same order of magnitude as the reproducibility values of the ASTM methods were obtained for yield long on crude (YLC), density (DLR), viscosity (VLR), and pour point (PP) , while the ability to predict the sulfur contents (S) and the carbon residue (CR) was found to be useful for indicative purposes. The prediction of SR properties is also promising. Modeling of the IR spectra, and to a lesser extent, the NIR spectra as a function of the average flash temperature (AFT) was particularly successful for the prediction of the short residue properties density (DSR) and viscosity (VSR). Similar results were obtained from the models to predict SR properties as a function of the yield short on crude (YSC) values. Finally, it was concluded that the applied protocol including sample pretreatment and instrumental measurement is highly reproducible and instrument and accessory independent

Prediction of long-residue properties of potential blends from mathematically mixed infrared spectra of pure crude oils by partial least-squares regression models

Research has been carried out to determine the feasibility of partial least-squares (PLS) regression models to predict the long-residue (LR) properties of potential blends from infrared (IR) spectra that have been created by linearly co-adding the IR spectra of crude oils. The study is the follow-up of a recently developed method to predict LR and short-residue properties from IR spectra and which is currently the subject of PCT patent application WO 2008/135411 filed by Shell International Research Maatschappij B.V. It is found that the PLS prediction models for seven different LR properties [i.e., yield long on crude (YLC), density (DLR), viscosity (VLR), sulfur content (S), pour point (PP), asphaltenes (Asph), and carbon residue (CR)] enabled us to predict the LR properties of 16 blends in two ways. The first predictions were carried out on the IR spectra recorded from the physically prepared blend samples. Next, IR spectra were submitted to the PLS models that were created mathematically by linearly co-adding the IR spectra of the corresponding crude oils in the appropriate weight ratio. Minor differences in the real and artificial blend spectra have been observed, which have been assigned to nonlinear effects. However, preprocessing of the spectra, by subsequently taking the first derivative, multiplicative scatter correction (MSC), and mean centering (MC), resulted in predicted LR property values of the two parallel sets that are largely the same. It implies that mimicking blend spectra by mathematically mixing the IR spectra of crude oils is a valuable, fast, clean, and cheap alternative for the “dirty” and elaborate preparation and testing methods of real blends currently used in the laboratory. Besides, the method can be used as a rapid screening tool for a large series of potential blends

Pore curvature and support composition effects on the electronic properties of supported Pt catalysts: an infrared spectroscopy study with CO as probe molecule

Supported 1 wt% Pt-based catalyst materials have been used as model systems to study pore curvature and support composition effects on the electronic properties of supported Pt nanoparticles. For this purpose, Pt nanoparticles have been loaded onto microporous (ITQ-1), mesoporous (Si- MCM-41, Si-MCM-48 and Si-SBA-15), macroporous (SiO2) all-silica supports, as well as onto a macroporous SiO2 support, impregnated with monovalent (Na+, Cs+) and divalent (Mg2+, Ba2+) cations. Time- and temperature-dependent infrared spectroscopy with CO as probe molecule has been used to investigate the adsorption and desorption properties of CO from these supported Pt nanoparticles. At 350 K, a narrow and smooth linear Pt-coordinated CBBO vibration band at 2070 cm 1 was observed for the all-silica catalysts. The IR-CO-TPD results revealed a slightly higher desorption rate for the micro- and mesoporous supports, probably due to larger non-bonding electrostatic interactions between CO and the pore walls. A systematic shift from linear (L) to bridge (B) bonded CBBO upon a decrease of the radius of curvature, which would indicate an increasing electron charge on the supported Pt nanoparticles, is however not observed. In contrast, a relationship between the L:B band intensity ratio and the Lewis acidity of the monovalent and divalent cations, as expressed by the Kamlet-Taft parameter a, was observed for the Pt/SiO2 catalysts. This effect is less pronounced than for zeolite-supported Pt nanoparticles (J. Phys. Chem. B 2005, 109, 3822–3831), but the results demonstrate that the correlation can be easily transferred from one support type to another, thus providing further guidelines for the design of improved automotive catalysts