The varied clinical and radiological manifestations of contrast-induced encephalopathy following coronary angiography.

Contrast-induced encephalopathy (CIE) is a rare complication of imaging using ionidated contrast media. Its pathogenesis remains unknown, and its clinical presentation is variable. We present two cases of CIE following coronary angiography (CAG) that underscore the multitude of clinical manifestations and imaging findings associated with the disorder. In patients 1, CIE manifested during the CAG with agitation and decreased consciousness, followed by left hemiparesis and visual neglect. Native computed tomography (CT) of the head was unremarkable but CT perfusion (CTP) showed extensive hypoperfusion of the right hemisphere with corresponding slow-wave activity in the electroencephalogram (EEG). These findings were more pronounced the next day. Magnetic Resonance Imaging (MRI) revealed multiple small dot-like ischemic lesions across the brain. By day six she had fully recovered. Patient 2 developed transient expressive aphasia during the CAG followed by migraineous symptoms. Native head CT showed a large area of parenchymal edema, sulcal effacement and variable subarachnoid hyperdensity in the right hemisphere. He developed mild left side hemiparesis, spontaneous gaze deviation and inattention. Brain MRI showed small dot-like acute ischemic lesions across the brain. The next morning, he had a generalized tonic-clonic seizure (GTCS) after which native head CT was normal, but the EEG showed a post-ictal finding covering the right hemisphere. His hemiparesis resolved within two months. The diversity in clinical and radiographic presentations suggest that CIE involve many pathophysiological processes.

Effects of a catalytic converter on PCDD/F, chlorophenol and PAH emissions in residential wood combustion.

Catalytic converters can be used to decrease carbon monoxide, organic compounds and soot from small-scale wood-fired appliances. The reduction is based on the oxidation of gaseous and particulate pollutants promoted by catalytic transition metal surfaces. However, many transition metals have also strong catalytic effect on PCDD/F formation. In this study birch logs were burned in a wood-fired stove (18 kW) with and without a catalytic converter with palladium and platinum as catalysts. PCDD/F, chlorophenol and PAH concentrations were analyzed from three phases of combustion (ignition, pyrolysis and burnout) and from the whole combustion cycle. PCDD/F emissions without the catalytic converter were at a level previously measured for wood combustion (0.15-0.74 ng N m(-3)). PAH emissions without the catalytic converter were high (47-85 mg N m(-3)) which is typical for batch combustion of wood logs. Total PAH concentrations were lower (on average 0.8-fold), and chlorophenol and PCDD/F levels were substantially higher (4.3-fold and 8.7-fold, respectively) when the catalytic converter was used. Increase in the chlorophenol and PCDD/F concentrations was most likely due to the catalytic effect of the platinum and palladium. Platinum and palladium may catalyze chlorination of PCDD/Fs via the Deacon reaction or an oxidation process. The influence of emissions from wood combustion to human health and the environment is a sum of effects caused by different compounds formed in the combustion. Therefore, the usage of platinum and palladium based catalytic converters to reduce emissions from residential wood combustion should be critically evaluated before wide-range utilization of the technology.

Involvement of the first transmembrane segment of human α(2) -adrenoceptors in the subtype-selective binding of chlorpromazine, spiperone and spiroxatrine.

BACKGROUND AND PURPOSE: Some large antagonist ligands (ARC239, chlorpromazine, prazosin, spiperone, spiroxatrine) bind to the human α(2A) -adrenoceptor with 10- to 100-fold lower affinity than to the α(2B)- and α(2C)-adrenoceptor subtypes. Previous mutagenesis studies have not explained this subtype selectivity. EXPERIMENTAL APPROACH: The possible involvement of the extracellular amino terminus and transmembrane domain 1 (TM1) in subtype selectivity was elucidated with eight chimaeric receptors: six where TM1 and the N-terminus were exchanged between the α(2)-adrenoceptor subtypes and two where only TM1 was exchanged. Receptors were expressed in CHO cells and tested for ligand binding with nine chemically diverse antagonist ligands. For purposes of interpretation, molecular models of the three human α(2)-adrenoceptors were constructed based on the ß(2)-adrenoceptor crystal structure. KEY RESULTS: The affinities of three antagonists (spiperone, spiroxatrine and chlorpromazine) were significantly improved by TM1 substitutions of the α(2A)-adrenoceptor, but reciprocal effects were not seen for chimaeric receptors based on α(2B)- and α(2C)-adrenoceptors. Molecular docking of these ligands suggested that binding occurs in the orthosteric ligand binding pocket. CONCLUSIONS AND IMPLICATIONS: TM1 is involved in determining the low affinity of some antagonist ligands at the human α(2A)-adrenoceptor. The exact mechanism is not known, but the position of TM1 at a large distance from the binding pocket indicates that TM1 does not participate in specific side-chain interactions with amino acids within the binding pocket of the receptor or with ligands bound therein. Instead, molecular models suggest that TM1 has indirect conformational effects related to the charge distribution or overall shape of the binding pocket.

The second extracellular loop of alpha2A-adrenoceptors contributes to the binding of yohimbine analogues.

BACKGROUND AND PURPOSE: Rodent alpha(2A)-adrenoceptors bind the classical alpha(2)-antagonists yohimbine and rauwolscine with lower affinity than the human alpha(2A)-adrenoceptor. A serine-cysteine difference in the fifth transmembrane helix (TM; position 5.43) partially explains this, but all determinants of the interspecies binding selectivity are not known. Molecular models of alpha(2A)-adrenoceptors suggest that the second extracellular loop (XL2) folds above the binding cavity and may participate in antagonist binding. EXPERIMENTAL APPROACH: Amino acids facing the binding cavity were identified using molecular models: side chains of residues 5.43 in TM5 and xl2.49 and xl2.51 in XL2 differ between the mouse and human receptors. Reciprocal mutations were made in mouse and human alpha(2A)-adrenoceptors at positions 5.43, xl2.49 and xl2.51, and tested with a set of thirteen chemically diverse ligands in competition binding assays. KEY RESULTS: Reciprocal effects on the binding of yohimbine and rauwolscine in human and mouse alpha(2A)-adrenoceptors were observed for mutations at 5.43, xl2.49 and xl2.51. The binding profile of RS-79948-197 was reversed only by the XL2 substitutions. CONCLUSIONS AND IMPLICATIONS: Positions 5.43, xl2.49 and xl2.51 are major determinants of the species preference for yohimbine and rauwolscine of the human versus mouse alpha(2A)-adrenoceptors. Residues at positions xl2.49 and xl2.51 determine the binding preference of RS-79948-197 for the human alpha(2A)-adrenoceptor. Thus, XL2 is involved in determining the species preferences of alpha(2A)-adrenoceptors of human and mouse for some antagonists.

Performance of multicomponent self-organizing regression (MCSOR) in QSAR, QSPR, and multivariate calibration: comparison with partial least-squares (PLS) and validation with large external data sets.

A novel method for underdetermined regression problems, multicomponent self-organizing regression (MCSOR), has been recently introduced. Here, its performance is compared with partial least-squares (PLS), which is perhaps the most widely adopted multivariate method in chemometrics. A potpourri of models is presented, and MCSOR appears to provide highly predictive models that are comparable with or better than the corresponding PLS models in large internal (leave-one-out, LOO) and pseudo-external (leave-many-out, LMO) validation tests. The "blind" external predictive ability of MCSOR and PLS is demonstrated employing large melting point, factor Xa, log P and log S data sets. In a nutshell, MCSOR is fast, conceptually simple (employing multiple linear regression, MLR, as a statistical tool), and applicable to all kinds of multivariate problems with single Y-variable.

Quantum nature of the sign preference in ion-induced nucleation.

Observed first in Wilson's pioneering experiments in the cloud chamber, the sign preference has remained a mystery for more than a century. We investigate the sign preference using a quantum approach and show that this puzzling phenomenon is essentially quantum in nature. It is shown that the effect of the chemical identity of the core ion is controlled by the electronic structure of the core ion through the influence on the intermolecular bonding energies during the initial steps of cluster formation. Our results demonstrate the superiority of the quantum approach and indicate fundamental problems of conventional ion-induced nucleation theories, in which the electronic structure of the core ion is either ignored or not treated rigorously.

Sources and elemental composition of ambient PM(2.5) in three European cities.

Source apportionment of urban fine particle mass (PM(2.5)) was performed from data collected during 1998-1999 in Amsterdam (The Netherlands), Erfurt (Germany) and Helsinki (Finland), using principal component analysis (PCA) and multiple linear regression. Six source categories of PM(2.5) were identified in Amsterdam. They were traffic-related particles (30% of the average PM(2.5)), secondary particles (34%), crustal material (7%), oil combustion (11%), industrial and incineration processes (9%), and sea salt (2%). The unidentified PM(2.5) fraction was 7% on the average. In Erfurt, four source categories were extracted with some difficulties in interpretation of source profiles. They were combustion emissions related to traffic (32%), secondary PM (32%), crustal material (21%) and industrial processes (8%). In Erfurt, 3% of PM(2.5) remained unidentified. Air pollution data and source apportionment results from the two Central European cities were compared to previously published results from Helsinki, where about 80% of average PM(2.5) was attributed to transboundary air pollution and particles from traffic and other regional combustion sources. Our results indicate that secondary particles and local combustion processes (mainly traffic) were the most important source categories in all cities; their impact on the average PM(2.5) was almost equal in Amsterdam and Erfurt whereas, in Helsinki, secondary particles made up for as much as half of the total average PM(2.5).

Alternative QSAR models for selected estradiol and cytochrome P450 ligands: comparison between classical, spectroscopic, CoMFA and GRID/GOLPE methods.

The performance of the spectroscopic EVA (eigenvalue) and EEVA (electronic eigenvalue) methods was tested with data sets applying coumarin 7-hydroxylation inhibitors (28 compounds) for cytochrome P450 mouse CYP2A5 and human CYP2A6 enzymes and 11ss-, 16a-, and 17a-substituted estradiol derivatives (30 compounds) for the lamb uterine estrogen receptor, and compared with the performance of the classical Hansch-type, CoMFA and GRID/GOLPE methods. Besides the internal predictability, the external predictability of the models was tested with several randomized training and test sets to ensure the validity and reliability of the models. Partial least squares (PLS) regression was employed as a general statistical tool with the EVA and EEVA methods. Some supplementary models were also built using only one PLS component with McGowan's volumes (MgVol and MgVol(2)) as additional descriptors and employing multiple linear regression (MLR) as the modelling tool. In general, both the internal and external performance of the EVA model, and more especially the EEVA model, with one PLS component and MgVol parameters was satisfactory, being either as good as or clearly better than that of the Hansch-type, CoMFA and GRID/GOLPE models.

Performance of (consensus) kNN QSAR for predicting estrogenic activity in a large diverse set of organic compounds.

A novel method (in the context of quantitative structure-activity relationship (QSAR)) based on the k nearest neighbour (kNN) principle, has recently been introduced for the derivation of predictive structure-activity relationships. Its performance has been tested for estimating the estrogen binding affinity of a diverse set of 142 organic molecules. Highly predictive models have been obtained. Moreover, it has been demonstrated that consensus-type kNN QSAR models, derived from the arithmetic mean of individual QSAR models were statistically robust and provided more accurate predictions than the great majority of the individual QSAR models. Finally, the consensus QSAR method was tested with 3D QSAR and log P data from a widely used steroid benchmark data set.

Ultrafine particles in urban air and respiratory health among adult asthmatics.

Airborne particles are associated with adverse health effects and contribute to excess mortality in epidemiological studies. A recent hypothesis proposes that the high numbers of ultrafine (<0.1 microm diameter) particles in ambient air might provoke alveolar inflammation and subsequently cause exacerbations in pre-existing cardiopulmonary diseases. To test the hypothesis adult asthmatics were followed with daily peak expiratory flow (PEF) measurements and symptom and medication diaries for six months, while simultaneously monitoring particulate pollution in ambient air. The associations between daily health endpoints of 57 asthmatics and indicators of air pollution were examined by multivariate regression models. Daily mean number concentration of particles, but not particle mass (PM10 (particle mass <10 microm), PM2.5-10, PM2.5, PM1), was negatively associated with daily PEF deviations. The strongest effects were seen for particles in the ultrafine range. However, the effect of ultrafine particles could not definitely be separated from other traffic generated pollutants, namely nitric oxide, nitrogen dioxide and carbon monoxide. No associations were observed with respiratory symptoms or medication use. Particle mass measurements can be strongly influenced by mechanically produced, soil-derived particles, which may not be associated with adverse health effects. Therefore, air quality monitoring should include particle number concentrations, which mainly reflect ultrafine particles.

Number concentration and size of particles in urban air: effects on spirometric lung function in adult asthmatic subjects.

Daily variations in ambient particulate air pollution are associated with variations in respiratory lung function. It has been suggested that the effects of particulate matter may be due to particles in the ultrafine (0.01-0.1 microm) size range. Because previous studies on ultrafine particles only used self-monitored peak expiratory flow rate (PEFR), we assessed the associations between particle mass and number concentrations in several size ranges measured at a central site and measured (biweekly) spirometric lung function among a group of 54 adult asthmatics (n = 495 measurements). We also compared results to daily morning, afternoon, and evening PEFR measurements done at home (n = 7,672-8,110 measurements). The median (maximum) 24 hr number concentrations were 14,500/cm(3) (46,500/cm(3)) ultrafine particles and 800/cm(3) (2,800/cm(3)) accumulation mode (0.1-1 microm) particles. The median (maximum) mass concentration of PM(2.5) (particulate matter < 2.5 microm) and PM(10) (particulate matter < 10 microm in aerodynamic diameter) were 8.4 microg/m(3) (38.3 microg/m(3)) and 13.5 microg/m(3) (73.7 microg/m(3)), respectively. The number of accumulation mode particles was consistently inversely associated with PEFR in spirometry. Inverse, but nonsignificant, associations were observed with ultrafine particles, and no associations were observed with large particles (PM(10)). Compared to the effect estimates for self-monitored PEFR, the effect estimates for spirometric PEFR tended to be larger. The standard errors were also larger, probably due to the lower number of spirometric measurements. The present results support the need to monitor the particle number and size distributions in urban air in addition to mass.

Effect of urea on fly ash PCDD/F concentrations in different particle sizes.

The effect of urea as an inhibitor for reducing polychlorinated dibenzo-p-dioxin and dibenzofuran (PCDD/F) concentrations in flue gases was studied in a pilot scale plant, together with the effect on the particle size distribution of these compounds. Total PCDD/F concentrations decreased by a maximum of 74%, the decrease being greatest for the most highly (octa-) chlorinated isomers. The PCDD/F reduction affected all the particle size classes when an adequate amount of urea was used (1% of the fuel input), which indicates that inhibition, unlike formation, is independent of the fly ash particle size distribution.

PCDD/F reduction in incinerator flue gas by adding urea to RDF feedstock.

The effect of urea on PCDD/F formation in a pilot incinerator was studied by incinerating urea with refuse-derived fuel (RDF) at three concentrations (0.1%, 0.5% and 1.0%, of the fuel feed). A distinct reduction in both PCDD/F and chlorophenol concentrations could be noticed when urea was introduced into the system. Partial-least-square (PLS) analysis of the data showed the importance of certain chlorophenol isomers as PCDD/F precursors, pointing to the possibility that the impact point of the urea inhibitor could be before the precursor molecules, i.e. chlorophenols, have been formed.

Ion mobility spectrometric monitoring of phosdrin from foliage in greenhouse.

The monitoring of Phosdrin (mevinphos; insecticide) from foliage and foliage extracts was achieved by an aspiration-type ion mobility spectrometer. This technique is based on ion mobility, which is proportional to the molecular weight, shape, and charge. The operation principle of the ion mobility spectrometer is to measure mobility distribution changes of product and reactant ions. This technique can measure positive and negative ion clusters at the same time in six different measuring electrodes. Each measuring electrode detects a different portion of the ion mobility distribution formed within the cell's radioactive source. The pattern recognition used is based on differences in the gas profiles for different compounds. This study shows that an ion mobility spectrometer can be used to monitor Phosdrin from foliage without the need for any time-consuming extraction procedure. The responses for Phosdrin-containing and background (control) samples were easily separated from each other. The responses declined as a function of time in the positive and sum response channels. In addition, the sum of the absolute values of signals at six measuring channels (sum response) were linearly proportional to the concentration of Phosdrin. Just before application (i.e., in background), this value was 41 bits, whereas these values were 10-fold, 11-fold, 8-fold, 6-fold, 5-fold, and 3.5-fold at the time points 4, 8, 11, 24, 50, and 72 hours after the spraying of Phosdrin.

Carbon disulfide and hydrogen sulfide removal with a peat biofilter.

Simultaneous removal of H2S and CS2 was studied with a peat biofilter inoculated with a Thiobacillus strain that oxidizes both compounds in an acidic environment. Both sulfurous gases at concentrations below 600 mg S/m3 were efficiently removed, and the removal efficiencies were similar, 99%, with an empty bed retention time (EBRT) of more than 60 sec. Concentrations greater than 1300-5000 mg S/m3 caused overloading of the filter material, resulting in high H2SO4 production, accumulation of elemental sulfur, and reduced removal efficiency. The highest sulfur removal rate achieved was 4500 g-S/day/m3 filter material. These results indicate that peat is suitable as a biofilter material for the removal of a mixture of H2S and CS2 when concentrations of gases to be purified are low (less than 600 mg/m3), but it is still odorous and toxic to the environment and humans.

Urea as a PCDD/F inhibitor in municipal waste incineration.

Emissions of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) from municipal waste incineration have been widely studied because of their extensive toxicity, and many efforts have been made to restrict their emissions. Although a number of chemical compounds have been shown in laboratory-scale tests to inhibit the formation of PCDD/Fs, few have been tested in pilot- or full-scale plants. This work evaluates the effect of urea as a PCDD/F inhibitor in a pilot-scale incinerator that uses refuse-derived fuel (RDF). The decomposition of urea under the test conditions was also studied using detailed kinetic modeling. An aqueous solution of urea was injected into the flue gas stream after the furnace at approximately 730 degrees C, with varied urea concentrations and flue gas residence times used between the furnace and the sampling point. The results demonstrate that urea can successfully inhibit PCDD/F formation in waste incineration if concentrations and injection points are properly adjusted. The kinetic model showed that urea can be rapidly decomposed under appropriate flue gas conditions, indicating that in addition to the urea molecule itself, decomposition products of urea can also be responsible for the reduction of PCDD/F production during incineration.

Oxidation of gas mixtures containing dimethyl sulfide, hydrogen sulfide, and methanethiol using a two-stage biotrickling filter.

A biofiltration technique was developed for removing a mixture of hydrogen sulfide (H2S), methanethiol (MeSH), and dimethyl sulfide (Me2S) from waste gases. Since H2S, especially at high concentrations, disturbs the removal of Me2S, two biotrickling filters with different microbes and operating pH levels were connected in series to create a two-stage system. Different loads of these gases were studied in order to determine their impact on the removal capacity of the system. The microbial consortia for these filters were enriched from the sludge of a Finnish refinery with bubbling H2S or Me2S. Acclimation for Me2S took 2 weeks, though no acclimation time was needed for the other gases. The first filter, at a pH of 2, removed most of the H2S and some of the MeSH and Me2S. The second filter, at a pH of approximately 6.5, removed the rest of the MeSH and most of the Me2S. The total maximum loads of the whole two-stage biotrickling filter were 1150 g/m3/day for H2S-S (suffix S indicates the results are counted as sulfur amounts), 879 g/m3/day for Me2S-S, and 66 g/m3/day for MeSH-S treated in a gas mixture. The average removal efficiencies for all gases tested were 99% or higher.

Monitoring odorous sulfur emissions using self-organizing maps for handling ion mobility spectrometry data.

Possibilities for monitoring emissions of reduced sulfur compounds in pulp and paper mills were investigated using ion mobility spectrometry (IMS) and a self-organizing map (SOM) algorithm. The reduced sulfur compounds measured were hydrogen sulfide (H2S), dimethyl sulfide (DMS), and methyl mercaptan (MM). Attention was paid to momentary concentrations because there is no monitoring device able to measure peak concentrations of reduced sulfur compounds under field conditions. These methods were evaluated by measuring the reduced sulfur compounds first in the laboratory and then at a process monitoring site at a pulp factory. The aim was to find out whether it would be possible to use the laboratory measurements to recognize the same reduced sulfur compounds at the monitoring site. Data collection was followed by analysis using the SOM algorithm and Sammon's mapping. The results showed that the IMS spectra of reduced sulfur compounds and their mixtures can be distinguished from each other by computationally intelligent methods and that the spectra from the process monitoring site corresponded with the laboratory measurements to a certain extent.

Physiology and taxonomy of thiobacillus strain TJ330, which oxidizes carbon disulphide (CS2).

A bacterium (strain TJ330) capable of using carbon disulphide (CS2) as its sole energy source in an acidic environment was isolated from a peat biofilter used in experiments to remove CS2 and hydrogen sulphide (H2S) from air. Its physiology and taxonomy are described here. The strain oxidized CS2, H2S and elemental sulphur to sulphate chemolithotrophically. The rate of sulphate production was highest at pH 2. The maximum growth rate constant (micromax) using CS2 as a substrate was 3.9 x 10(-2) h(-1) (generation time 18 h) and the Monod constant (Ks) was 0.97-2.6 micromol l(-1) CS2 (74-198 microg l(-1)), corresponding to an equilibrium with 15-40 ppm CS2 in the headspace. The optimum growth temperature using elemental sulphur as a substrate was 28 degrees C. The strain bears morphological and physiological similarities to Thiobacillus thiooxidans, but the latter is incapable of oxidizing CS2. The strain TJ330 (DSM 8985) showed only 44.2 + 11.8% DNA homology with the type strain T. thiooxidans ATCC 19377, while its homology with T. ferrooxidans ATCC 23270 was 17.1 + 3.4%. The strain TJ 330 represents a high-affinity bacterium which can effectively remove low CS2 concentrations in an acid environment. These properties can be utilized in biotechnological purification applications.

Toxic chlorinated and polyaromatic hydrocarbons in simulated house fires.

Toxic chlorinated hydrocarbons (polychlorinated biphenyls, benzenes and dioxins and furans) and polyaromatic hydrocarbons were examined in combustion gas and deposited soot wipe samples from simulated house fires. Concentrations of these substances were high during the fires, the amounts of polychlorinated dioxins and furans (PCDD/Fs) in the combustion gas varying from 1.0 to >7.2 ng/m3 (I-TEQ) and those of polyaromatic hydrocarbons from 6.4 to 470 mg/m3. Thus large amounts of organic compounds may be released in house fires. As a result, there is a need for careful personal protection of fire-fighters and remediation workers against combustion gases during a fire and on contaminated surfaces after it.