Quenching of Singlet Oxygen by Pyocyanin and Related Phenazines†

Pseudomonas aeruginosa is a human pathogen, which causes infections of various organs, including lung, skin and eye, particularly in individuals who are immunocompromised. Pyocyanin (1-hydroxy-5-methylphenazine), a cytotoxic pigment secreted by the bacterium, is among the factors that contribute to virulence of this pathogen. We have previously shown that rose bengal and riboflavin photosensitize oxidation of pyocyanin to a product(s) with diminished reactivity and toxicity. Singlet oxygen was suggested as the major oxidant, based on the inhibitory effect of sodium azide. In the present study, we used the time resolved technique to investigate direct interaction of pyocyanin and related phenazines (1-hydroxyphenazine [1-OH-Phen], 1-methoxy-5-methylphenazine [1-MeO-PCN] and phenazine methosulfate [PMS]) with ¹O₂. The rate constants for the ¹O₂ quenching (physical + chemical) by pyocyanin and 1-OH-Phen in D₂O buffer (pD ∼7.2) have been determined to be 4.8 × 10⁸ and 6.8 × 10⁸ M⁻¹ s⁻¹, respectively. 1-MeO-PCN and PMS were markedly less efficient ¹O₂ quenchers. Among the phenazines studied only phenazine methosulfate photogenerated ¹O₂ (Φ(¹O₂) = 0.56 in acetonitrile). Interaction of ¹O₂ with pyocyanin and other related phenazines produced by the bacteria may be important in determining the potential utility of photochemical/pharmacological approaches to eradicate P. aeruginosa from infected tissues.     

Parametric Euler sum identities

We consider some parametrized classes of multiple sums first studied by Euler. Identities between meromorphic functions of one or more variables in many cases account for reduction formulae for these sums.     

On the Distribution of the Sum of n Non-Identically Distributed Uniform Random Variables

The distribution of the sum of independent identically distributed uniform random variables is well-known. However, it is sometimes necessary to analyze data which have been drawn from different uniform distributions. By inverting the characteristic function, we derive explicit formulae for the distribution of the sum of n non-identically distributed uniform random variables in both the continuous and the discrete case. The results, though involved, have a certain elegance. As examples, we derive from our general formulae some special cases which have appeared in the literature.     

Detection of incipient gear failures using statistical techniques

Gears are important components in most power transmission mechanisms.Failures of gears can cause heavy losses in industry. Conditionmonitoring and fault diagnosis of gears is therefore importantto improve safety and reliability of gearbox operations andreduce losses caused by gear failures. This research proposesa new diagnostic approach based on the statistical analysisof data. It investigates the use of Principal Components Analysis(PCA) to detect growing local faults in a two-stage industrialhelical gearbox. In this research, the vibration signal is usedto monitor fault conditions and a broken tooth is simulatedas a local fault. Since the early detection of faults is a challenge,small fault conditions were tested first as well as severe faultconditions. In order to examine the ability of the PCA to detectfault conditions, first the PCA-based model was created fornormal operating conditions. Any unexpected event such as afault condition causes a significant deviation from the PCAmodel, which is obtained from the normal condition data of thegearbox. The Square Prediction Error (SPE) was calculated todetect the fault conditions. When the vibration signal fromthe gearbox is representative of normal operation, the valueof the SPE shows very little fluctuation and remains under acertain threshold value. However, in the presence of the faultthe SPE fluctuates considerably beyond the threshold value.It is shown that the PCA-based statistical approach cannot onlybe used to detect severe fault conditions, but that it alsoreveals small growing fault conditions at very early stage.The technique also provides information about the state of thefault such as the location of the fault as well as its severity. Received 5 March 2001. Revised 12 December 2001. Accepted 17 January 2002.     

Co‐development of Crystalline and Mesoscopic Order in Mesostructured Zeolite Nanosheets

Mesoporous zeolites are a new and technologically important class of materials that exhibit improved diffusion and catalytic reaction properties compared to conventional zeolites with sub‐nanometer pore dimensions. During their syntheses, the transient developments of crystalline and mesoscopic order are closely coupled and challenging to control. Correlated solid‐state NMR, X‐ray, and electron microscopy analyses yield new molecular‐level insights on the interactions and distributions of complicated organic structure‐directing agents with respect to crystallizing zeolite frameworks. The analyses reveal the formation of an intermediate layered silicate phase, which subsequently transforms into zeolite nanosheets with uniform nano‐ and mesoscale porosities. Such materials result from coupled surfactant self‐assembly and inorganic crystallization processes, the interplay between which governs the onset and development of framework structural order on different length and time scales.     

Gold‐Catalyzed Intermolecular Anti‐Markovnikov Hydroamination of Alkylidenecyclopropanes

The cationic gold phosphine complex [{PCy₂(o‐biphenyl)}Au(NCMe)]⁺SbF₆^? (Cy=cyclohexyl) catalyzes the intermolecular, anti‐Markovnikov hydroamination reaction of monosubstituted and cis‐ and trans‐disubstituted alkylidenecyclopropanes (ACPs) with imidazolidin‐2‐ones and other nucleophiles. This reaction forms 1‐cyclopropyl alkylamine derivatives in high yield and with high regio‐ and diastereoselectivity. NMR spectroscopic analysis of gold π‐ACP complexes and control experiments point to the sp hybridization of the ACP internal alkene carbon atom as controlling the regiochemistry of the ACP hydroamination reaction.     

Total synthesis and biochemical characterization of mirror image barnase

In this study we synthesized and characterized mirror image barnase (B. amyloliquefaciens ribonuclease). d-Barnase was identical to l-barnase, when analyzed by liquid chromatography and mass-spectrometry. Proteolysis of the mirror image enzyme revealed that in contrast to its native counterpart, d-barnase was completely stable to digestive proteases. In enzymatic assays, d-barnase had the reciprocal chiral specificity and was fully active towards mirror image substrates. Interestingly, d-barnase also hydrolyzed the substrate of the native chirality, albeit 4000 times less efficiently. This effect was further confirmed by digesting a native 112-mer RNA with the enzyme. Additional studies revealed that barnase accommodates a range of substrates with various chiralities, but the prime requirement for guanosine remains. These studies point toward using mirror image enzymes as modern agents in biotechnology.     

On the Nature of Mass Spectrometer Analyzer Contamination

Sample throughput in electrospray ionization mass spectrometry (ESI-MS) is limited by the need for frequent ion path cleaning to remove accumulated debris that can lead to charging and general performance degradation. Contamination of ion optics within the vacuum system is particularly problematic as routine cleaning requires additional time for cycling the vacuum pumps. Differential mobility spectrometry (DMS) can select targeted ion species for transmission, thereby reducing the total number of charged particles entering the vacuum system. In this work, we characterize the nature of instrument contamination, describe efforts to improve mass spectrometer robustness by applying DMS prefiltering to reduce contamination of the vacuum ion optics, and demonstrate the capability of DMS to extend the interval between mass spectrometer cleaning. In addition, we introduce a new approach to effectively detect large charged particles formed during the electrospray ionization (ESI) process.

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Maximizing Ion Transmission in Differential Mobility Spectrometry

We provide modeling and experimental data describing the dominant ion-loss mechanisms for differential mobility spectrometry (DMS). Ion motion is considered from the inlet region of the mobility analyzer to the DMS exit, and losses resulting from diffusion to electrode surfaces, insufficient effective gap, ion fragmentation, and fringing field effects are considered for a commercial DMS system with 1-mm gap height. It is shown that losses due to diffusion and radial oscillations can be minimized with careful consideration of residence time, electrode spacing, gas flow rate, and waveform frequency. Fragmentation effects can be minimized by limitation of the separation field. When these parameters were optimized, fringing field effects at the DMS inlet contributed the most to signal reduction. We also describe a new DMS cell configuration that improves the gas dynamics at the mobility cell inlet. The new cell provides a gas jet that decreases the residence time for ions within the fringing field region, resulting in at least twofold increase in ion signal as determined by experimental data and simulations.

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