Direct detection of chlorosilylene and time resolved study of some of its reactions in the gas-phase using a new photochemical precursor

Chlorosilylene, ClSiH, was prepared by 193 nm laser flash photolysis of 1-chloro-1-silacyclopent-3-ene in the gas phase. ClSiH was monitored in real time at 457.9 nm using a CW argon ion laser. The kinetics of reactions of ClSiH with C2H4, CH2 = CHCMe3, C2H2, Me2O, SO2, HCl, MeSiH3, Me2SiH2, Me3SiH, MeGeH3, MeGeH3 and precursor have been studied at ambient temperatures for the first time. Addition reactions of ClSiH and reactions with lone pair donors are faster than insertion reactions. Surprisingly ClSiH inserts faster into Si-H than Ge-H bonds. ClSiH is intermediate in reactivity between SiH2 and SiCI2. Relative reactivities of CISiH and SiH2 vary considerably. (c) 2005 Elsevier B.V. All rights reserved.

Direct detection of dimethylstannylene and tetramethyldistannene in solution and the gas phase by laser flash photolysis of 1,1-dimethylstannacyclopent-3-enes

The photochemistry of 1,1-dimethyl- and 1,1,3,4-tetramethylstannacyclopent-3-ene (4a and 4b,respectively) has been studied in the gas phase and in hexane solution by steady-state and 193-nm laser flash photolysis methods. Photolysis of the two compounds results in the formation of 1,3-butadiene (from 4a) and 2,3-dimethyl-1,3-butadiene (from 4b) as the major products, suggesting that cycloreversion to yield dimethylstannylene (SnMe2) is the main photodecomposition pathway of these molecules. Indeed, the stannylene has been trapped as the Sn-H insertion product upon photolysis of 4a in hexane containing trimethylstannane. Flash photolysis of 4a in the gas phase affords a transient absorbing in the 450-520nm range that is assigned to SnMe2 by comparison of its spectrum and reactivity to those previously reported from other precursors. Flash photolysis of 4b in hexane solution affords results consistent with the initial formation of SnMe2 (lambda(max) approximate to 500 nm), which decays over similar to 10 mu s to form tetramethyldistannene (5b; lambda(max) approximate to 470 nm). The distannene decays over the next ca. 50 mu s to form at least two other longer-lived species, which are assigned to higher SnMe2 oligomers. Time-dependent DFT calculations support the spectral assignments for SnMe2 and Sn2Me4, and calculations examining the variation in bond dissociation energy with substituent (H, Me, and Ph) in disilenes, digermenes, and distannenes rule out the possibility that dimerization of SnMe2 proceeds reversibly. Addition of methanol leads to reversible reaction with SnMe2 to form a transient absorbing at lambda(max) approximate to 360 nm, which is assigned to the Lewis acid-base complex between SnMe2 and the alcohol.

First detection of methylgermylene in the gas phase and time-resolved study of some of its reactions

A new transient species has been produced and detected by the gas-phase, 193 nm laser flash photolysis of 1,3,4-trimethylgermacyclopent-3-ene, TMGCP. The species has strong visible absorptions in the wavelength region 450−520 nm (maximum at 485 nm) and is attributed to the germylene, MeGeH. Time-resolved kinetic studies have led to the first rate constants for its reactions with GeH4, Me2GeH2, C2H2, C2H4, C3H6, i-C4H8, TMGCP, MeOH, HCl, and SO2. The reactivity of MeGeH is compared to those of GeH2 and GeMe2. The Me-for-H substituent effect varies according to reaction type and is not constant from GeH2 to MeGeH to GeMe2.

Ag dopedWO(3)-based powder sensor for the detection of NO gas in air

WO3-based materials as sensors for the monitor of environmental gases such as NO2 (NO + NO2) have been rapidly developed for various potential applications (stationary and mobile uses). It has been reported that these materials are highly sensitive to NOx with the sensitivity further enhanced by adding precious group metals (PGM such as Pt, Pd, Au, etc.). However, there has been limited work in revealing the sensing mechanism for these gases over the WO3-based sensors. In particular, the role of promoter is not yet clear though speculations on their catalytic, electronic and structural effects have been made in the past. In parallel to these PGM promoters here we report,for the first time, that Ag promotion can also enhance WO3 sensitivity significantly. In addition, this promotion decreases the optimum sensor temperature of 300 degreesC for Most WO3-based sensors, to below 200 degreesC. Characterizations (XRD, TEM, and impedance measurement) reveal that there is no significant bulk structure change nor particle size alteration in the WO3 phases during the NO exposure. However, it is found that the Ag doping creates a high concentration of oxygen vacancies in form of coordinated crystallographic shear (CS) planes onto the underneath WO3. It is thus proposed that the Ag particle facilitates the oxidative conversion of NO to NO2 followed by a subsequent NO2 adsorption on the defective WO, sites created at the Ag-WO3 interface; hence, accounting for the high molecular sensitivity. (C) 2002 Elsevier Science B.V. All rights reserved.

Serum proteomic abnormality predating screen detection of ovarian cancer

Ovarian cancer is characterized by vague, non-specific symptoms, advanced stage at diagnosis and poor overall survival. A nested case control study was undertaken on stored serial serum samples from women who developed ovarian cancer and healthy controls (matched for serum processing and storage conditions as well as attributes such as age) in a pilot randomized controlled trial of ovarian cancer screening. The unique feature of this study is that the women were screened for up to 7 years. The serum samples underwent prefractionation using a reversed-phase batch extraction protocol prior to MALDI-TOF MS data acquisition. Our exploratory analysis shows that combining a single MS peak with CA125 allows statistically significant discrimination at the 5% level between cases and controls up to 12 months in advance of the original diagnosis of ovarian cancer. Such combinations work much better than a single peak or CA125 alone. This paper demonstrates that mass spectra from the low molecular weight serum proteome carry information useful for early detection of ovarian cancer. The next step is to identify the specific biomarkers that make early detection possible.

Detection of polycyclic aromatic hydrocarbons using quartz crystal microbalances

A chemically coated piezoelectric sensor has been developed for the determination of PAHs in the liquid phase. An organic monolayer attached to the surface of a gold electrode of a quartz crystal microbalance (QCM) via a covalent thiol-gold link complete with an ionically bound recognition element has been produced. This study has employed the PAH derivative 9-anthracene carboxylic acid which, once bound to the alkane thiol, functions as the recognition element. Binding of anthracene via pi-pi interaction has been observed as a frequency shift in the QCM with a detectability of the target analyte of 2 ppb and a response range of 0-50 ppb. The relative response of the sensor altered for different PAHs despite pi-pi interaction being the sole communication between recognition element and analyte. It is envisaged that such a sensor could be employed in the identification of key marker compounds and, as such, give an indication of total PAH flux in the environment.

Enantioselective detection of L-serine

An acoustic wave sensor coated with an artificial biomimetic recognition element has been developed to selectively detect the amino acid L-serine. A highly specific non-covalently imprinted polymer was cast on one electrode of a quartz crystal microbalance (QCM) as a thin permeable film. Selective rebinding of the L-serine was observed as a frequency shift in the QCM with a detection limit of 2 ppb and for concentrations up to 0.4 ppm. The sensor binding is shown to be capable of discrimination between L- and D-stereoisomers of serine as a result of the enantioselectivity of the imprinted binding sites. (C) 2002 Elsevier Science B.V. All rights reserved.

Detection of pressed hazelnut oil in virgin olive oil by analysis of polar components: improvement and validation of the method

An improved method for the detection of pressed hazelnut oil in admixtures with virgin olive oil by analysis of polar components is described. The method. which is based on the SPE-based isolation of the polar fraction followed by RP-HPLC analysis with UV detection. is able to detect virgin olive oil adulterated with pressed hazelnut oil at levels as low as 5% with accuracy (90.0 +/- 4.2% recovery of internal standard), good reproducibility (4.7% RSD) and linearity (R-2: 0.9982 over the 5-40% adulteration range). An international ring-test of the developed method highlighted its capability as 80% of the samples were, on average, correctly identified despite the fact that no training samples were provided to the participating laboratories. However, the large variability in marker components among the pressed hazelnut oils examined prevents the use of the method for quantification of the level of adulteration. (C) 2003 Elsevier Ltd. All rights reserved.

Identification of Bartonella species in rodents, shrews and cats in Denmark: detection of two B-henselae variants, one in cats and the other in the long-tailed field mouse

Small mammals and stray cats were trapped in two areas of North Zealand, Denmark, and their blood cultured for hemotrophic bacteria. Bacterial isolates were recovered in pure culture and subjected to 16S rDNA gene sequencing. Bartonella species were isolated from five mammalian species: B. grahamii from Microtus agrestis (field vole) and Apodemus flavicollis (yellow-necked field mouse); B. taylorii from M. agrestis, A. flavicollis and A. sylvaticus (long-tailed field mouse); B. tribocorum from A. flavicollis; R vinsonii subsp. vinsonii from M. agrestis and A. sylvaticus; and B. birtlesii from Sorex vulgaris (common shrew). In addition, two variant types of B. henselae were identified: variant I was recovered from three specimens of A. sylvaticus, and B. henselae variant 11 from I I cats; in each case this was the only B. henselae variant found. No Bartonella species was isolated from Clethrionomys glareolus (bank vole) or Micromys minutus (harvest mouse). These results suggest that B. henselae occurs in two animal reservoirs in this region, one of variant I in A. sylvaticus, which may be transmitted between mice by the tick Ixodes ricinus, and another of variant 11 in cats, which may be transmitted by the cat flea (Ctenocephalides felis). To our knowledge, this is the first report of the occurrence of B. henselae and B. tribocorum in Apodemus mice.

Investigation of support vector machine for the detection of architectural distortion in mammographic images

This paper investigates detection of architectural distortion in mammographic images using support vector machine. Hausdorff dimension is used to characterise the texture feature of mammographic images. Support vector machine, a learning machine based on statistical learning theory, is trained through supervised learning to detect architectural distortion. Compared to the Radial Basis Function neural networks, SVM produced more accurate classification results in distinguishing architectural distortion abnormality from normal breast parenchyma.

Towards the automatic reconstruction of dendritic trees using particle filters

The 3D reconstruction of a Golgi-stained dendritic tree from a serial stack of images captured with a transmitted light bright-field microscope is investigated. Modifications to the bootstrap filter are discussed such that the tree structure may be estimated recursively as a series of connected segments. The tracking performance of the bootstrap particle filter is compared against Differential Evolution, an evolutionary global optimisation method, both in terms of robustness and accuracy. It is found that the particle filtering approach is significantly more robust and accurate for the data considered.

Empirical mode decomposition: a novel technique for the study of tremor time series

Tremor is a clinical feature characterized by oscillations of a part of the body. The detection and study of tremor is an important step in investigations seeking to explain underlying control strategies of the central nervous system under natural (or physiological) and pathological conditions. It is well established that tremorous activity is composed of deterministic and stochastic components. For this reason, the use of digital signal processing techniques (DSP) which take into account the nonlinearity and nonstationarity of such signals may bring new information into the signal analysis which is often obscured by traditional linear techniques (e.g. Fourier analysis). In this context, this paper introduces the application of the empirical mode decomposition (EMD) and Hilbert spectrum (HS), which are relatively new DSP techniques for the analysis of nonlinear and nonstationary time-series, for the study of tremor. Our results, obtained from the analysis of experimental signals collected from 31 patients with different neurological conditions, showed that the EMD could automatically decompose acquired signals into basic components, called intrinsic mode functions (IMFs), representing tremorous and voluntary activity. The identification of a physical meaning for IMFs in the context of tremor analysis suggests an alternative and new way of detecting tremorous activity. These results may be relevant for those applications requiring automatic detection of tremor. Furthermore, the energy of IMFs was visualized as a function of time and frequency by means of the HS. This analysis showed that the variation of energy of tremorous and voluntary activity could be distinguished and characterized on the HS. Such results may be relevant for those applications aiming to identify neurological disorders. In general, both the HS and EMD demonstrated to be very useful to perform objective analysis of any kind of tremor and can therefore be potentially used to perform functional assessment.

A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition

Transient neural assemblies mediated by synchrony in particular frequency ranges are thought to underlie cognition. We propose a new approach to their detection, using empirical mode decomposition (EMD), a data-driven approach removing the need for arbitrary bandpass filter cut-offs. Phase locking is sought between modes. We explore the features of EMD, including making a quantitative assessment of its ability to preserve phase content of signals, and proceed to develop a statistical framework with which to assess synchrony episodes. Furthermore, we propose a new approach to ensure signal decomposition using EMD. We adapt the Hilbert spectrum to a time-frequency representation of phase locking and are able to locate synchrony successfully in time and frequency between synthetic signals reminiscent of EEG. We compare our approach, which we call EMD phase locking analysis (EMDPL) with existing methods and show it to offer improved time-frequency localisation of synchrony.

Detection of neural correlates of self-paced motor activity using empirical mode decomposition phase locking analysis

Transient episodes of synchronisation of neuronal activity in particular frequency ranges are thought to underlie cognition. Empirical mode decomposition phase locking (EMDPL) analysis is a method for determining the frequency and timing of phase synchrony that is adaptive to intrinsic oscillations within data, alleviating the need for arbitrary bandpass filter cut-off selection. It is extended here to address the choice of reference electrode and removal of spurious synchrony resulting from volume conduction. Spline Laplacian transformation and independent component analysis (ICA) are performed as pre-processing steps, and preservation of phase synchrony between synthetic signals. combined using a simple forward model, is demonstrated. The method is contrasted with use of bandpass filtering following the same preprocessing steps, and filter cut-offs are shown to influence synchrony detection markedly. Furthermore, an approach to the assessment of multiple EEG trials using the method is introduced, and the assessment of statistical significance of phase locking episodes is extended to render it adaptive to local phase synchrony levels. EMDPL is validated in the analysis of real EEG data, during finger tapping. The time course of event-related (de)synchronisation (ERD/ERS) is shown to differ from that of longer range phase locking episodes, implying different roles for these different types of synchronisation. It is suggested that the increase in phase locking which occurs just prior to movement, coinciding with a reduction in power (or ERD) may result from selection of the neural assembly relevant to the particular movement. (C) 2009 Elsevier B.V. All rights reserved.