Concerted HO2 elimination from alpha-Aminoalkylperoxyl free radicals : Experimental and theoretical evidence from the gas phase NH2 center dot CHCO2- + O-2 reaction

We have investigated the gas-phase reaction of the alpha-aminoacetate (glycyl) radical anion (NH2(sic)CHCO2-) with O-2 using ion trap mass spectrometry, quantum chemistry, and statistical reaction rate theory. This radical is found to undergo a remarkably rapid reaction with O-2 to form the hydroperoxyl radical (HO2(sic)) and an even-electron imine (NHCHCO2-), with experiments and master equation simulations revealing that reaction proceeds at the ion molecule collision rate. This reaction is facilitated by a low-energy concerted HO2(sic) elimination mechanism in the NH2CH(OO(sic))CO2- peroxyl radical. These findings can explain the widely observed free-radical-mediated oxidation of simple amino acids to amides plus alpha-keto acids (their imine hydrolysis products). This work also suggests that imines will be the main intermediates in the atmospheric oxidation of primary and secondary amines, including amine carbon capture solvents such as 2-aminoethanol (commonly known as monoethanolamine, or MEA), in a process that avoids the ozone-promoting conversion of (sic)NO to (sic)NO2 commonly encountered in peroxyl radical chemistry.

Reactions of simple and peptidic alpha-carboxylate radical anions with dioxygen in the gas phase

alpha-Carboxylate radical anions are potential reactive intermediates in the free radical oxidation of biological molecules (e. g., fatty acids, peptides and proteins). We have synthesised well-defined alpha-carboxylate radical anions in the gas phase by UV laser photolysis of halogenated precursors in an ion-trap mass spectrometer. Reactions of isolated acetate ((center dot)CH(2)CO(2)) and 1-carboxylatobutyl (CH(3)CH(2)CH(2)(center dot)CHCO(2)(-)) radical anions with dioxygen yield carbonate (CO(3)(center dot-)) radical anions and this chemistry is shown to be a hallmark of oxidation in simple and alkyl-substituted cross-conjugated species. Previous solution phase studies have shown that C(alpha)-radicals in peptides, formed from free radical damage, combine with dioxygen to form peroxyl radicals that subsequently decompose into imine and keto acid products. Here, we demonstrate that a novel alternative pathway exists for two alpha-carboxylate C(alpha)-radical anions: the acetylglycinate radical anion (CH(3)C(O)NH(center dot)CHCO(2)(-)) and the model peptide radical anion, YGGFG(center dot-). Reaction of these radical anions with dioxygen results in concerted loss of carbon dioxide and hydroxyl radical. The reaction of the acetylglycinate radical anion with dioxygen reveals a two-stage process involving a slow, followed by a fast kinetic regime. Computational modelling suggests the reversible formation of the C(alpha) peroxyl radical facilitates proton transfer from the amide to the carboxylate group, a process reminiscent of, but distinctive from, classical proton-transfer catalysis. Interestingly, inclusion of this isomerization step in the RRKM/ME modelling of a G3SX level potential energy surface enables recapitulation of the experimentally observed two-stage kinetics.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Partial agonists of the [alpha]3[beta]4[ast] neuronal nicotinic acetylcholine receptor reduce ethanol consumption and seeking in rats

Alcohol use disorders (AUDs) impact millions of individuals and there remain few effective treatment strategies. Despite evidence that neuronal nicotinic acetylcholine receptors (nAChRs) have a role in AUDs, it has not been established which subtypes of the nAChR are involved. Recent human genetic association studies have implicated the gene cluster CHRNA3-CHRNA5-CHRNB4 encoding the α3, α5, and β4 subunits of the nAChR in susceptibility to develop nicotine and alcohol dependence; however, their role in ethanol-mediated behaviors is unknown due to the lack of suitable and selective research tools. To determine the role of the α3, and β4 subunits of the nAChR in ethanol self-administration, we developed and characterized high-affinity partial agonists at α3β4 nAChRs, CP-601932, and PF-4575180. Both CP-601932 and PF-4575180 selectively decrease ethanol but not sucrose consumption and operant self-administration following long-term exposure. We show that the functional potencies of CP-601932 and PF-4575180 at α3β4 nAChRs correlate with their unbound rat brain concentrations, suggesting that the effects on ethanol self-administration are mediated via interaction with α3β4 nAChRs. Also varenicline, an approved smoking cessation aid previously shown to decrease ethanol consumption and seeking in rats and mice, reduces ethanol intake at unbound brain concentrations that allow functional interactions with α3β4 nAChRs. Furthermore, the selective α4β2(*) nAChR antagonist, DHβE, did not reduce ethanol intake. Together, these data provide further support for the human genetic association studies, implicating CHRNA3 and CHRNB4 genes in ethanol-mediated behaviors. CP-601932 has been shown to be safe in humans and may represent a potential novel treatment for AUDs.

Estrogen receptor-Beta activated apoptosis in benign hyperplasia and cancer of the prostate is androgen independent and TNF-alpha mediated

Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are androgen-dependent diseases commonly treated by inhibiting androgen action. However, androgen ablation or castration fail to target androgen-independent cells implicated in disease etiology and recurrence. Mechanistically different to castration, this study shows beneficial proapoptotic actions of estrogen receptor–β (ERβ) in BPH and PCa. ERβ agonist induces apoptosis in prostatic stromal, luminal and castrate-resistant basal epithelial cells of estrogen-deficient aromatase knock-out mice. This occurs via extrinsic (caspase-8) pathways, without reducing serum hormones, and perturbs the regenerative capacity of the epithelium. TNFα knock-out mice fail to respond to ERβ agonist, demonstrating the requirement for TNFα signaling. In human tissues, ERβ agonist induces apoptosis in stroma and epithelium of xenografted BPH specimens, including in the CD133+ enriched putative stem/progenitor cells isolated from BPH-1 cells in vitro. In PCa, ERβ causes apoptosis in Gleason Grade 7 xenografted tissues and androgen-independent cells lines (PC3 and DU145) via caspase-8. These data provide evidence of the beneficial effects of ERβ agonist on epithelium and stroma of BPH, as well as androgen-independent tumor cells implicated in recurrent disease. Our data are indicative of the therapeutic potential of ERβ agonist for treatment of PCa and/or BPH with or without androgen withdrawal.