The development of an expedient method for the synthesis of a diverse series of cyclopropane [alpha]-amino acids

Thèse diffusée initialement dans le cadre d'un projet pilote des Presses de l'Université de Montréal/Centre d'édition numérique UdeM (1997-2008) avec l'autorisation de l'auteur.

Analysis of plasma tocopherols alpha, gamma, and 5-nitro-gamma in rats with inflammation by HPLC coulometric detection

Reactive nitrogen oxide species (RNOS) have been implicated as effector molecules in inflammatory diseases. There is emerging evidence that gamma-tocopherol (gammaT), the major form of vitamin E in the North American diet, may play an important role in these diseases. GammaT scavenges RNOS such as peroxynitrite by forming a stable adduct, 5-nitro-gammaT (NGT). Here we describe a convenient HPLC method for the simultaneous determination of NGT, alphaT, and gammaT in blood plasma and other tissues. Coulometric detection of NGT separated on a deactivated reversed-phase column was linear over a wide range of concentrations and highly sensitive (approximately 10 fmol detection limit). NGT extracted from blood plasma of 15-week-old Fischer 344 rats was in the low nM range, representing approximately 4% of gammaT. Twenty-four h after intraperitoneal injection of zymosan, plasma NGT levels were 2-fold higher compared to fasted control animals when adjusted to gammaT or corrected for total neutral lipids, while alpha- and gammaT levels remained unchanged. These results demonstrate that nitration of gammaT is increased under inflammatory conditions and highlight the importance of RNOS reactions in the lipid phase. The present HPLC method should be helpful in clarifying the precise physiological role of gammaT.

Ueber o-Nitro-Phenyl-[alpha]-Picolyl-Alkin und einige seiner Derivate : Ueber Phenyl-[alpha]-Picolyl-Alkin /

Thesis (doctoral)--Konigl. Universitat Breslau, 1900.

Complete assignment of (1)H and (13)C NMR spectra of alpha-phenylsulfinyl-N-methoxy-N-methylpropionamide and some p-substituted derivatives

The complete assignment of the (1)H and (13)C NMR spectra of the diastereomeric pairs of some alpha-arylsulfinyl-substituted N-methoxy-N-methylpropionamides with the substituents methoxy, methyl, chloro, nitro is reported. Copyright (C) 2008 John Wiley & Sons, Ltd.

Biotransformation of alpha-Bromoacetophenones by the Marine Fungus Aspergillus sydowii

The biotransformation reactions of alpha-bromoacetophenone (1), p-bromo-alpha-bromoacetophenone (2), and p-nitro-alpha-bromoacetophenone (3) by whole cells of the marine fungus Aspergillus sydowii Ce19 have been investigated. Fungal cells that had been grown in artificial sea water medium containing a high concentration of chloride ions (1.20 M) catalysed the biotransformation of 1 to 2-bromo-1-phenylethanol 4 (56%), together with the alpha-chlorohydrin 7 (9%), 1-phenylethan-1,2-diol 9 (26%), acetophenone 10 (4%) and phenylethanol 11 (5%) identified by GC-MS analysis. In addition, it was observed that the enzymatic reaction was accompanied by the spontaneous debromination of 1 to yield alpha-chloroacetophenone 5 (9%) and alpha-hydroxyacetophenone 6 (18%) identified by GC-FID analysis. When 2 and 3 were employed as substrates, various biotransformation products were detected but the formation of halohydrins was not observed. It is concluded that marine fungus A. sydowii Ce19 presents potential for the biotransformations of bromoacetophenone derivatives.

The semi-synthetic kaurane ent-16 alpha-methoxykauran-19-oic acid induces vascular relaxation and hypotension in rats

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mechanism of attenuation of muscle protein degradation induced by tumor necrosis factor-alpha and angiotensin II by beta-hydroxy-beta-methylbutyrate

Both tumor necrosis factor-alpha (TNF-alpha)/interferon-gamma (IFN-gamma) and angiotensin II (ANG II) induced an increase in total protein degradation in murine myotubes, which was completely attenuated by treatment with beta-hydroxy-beta-methylbutyrate (HMB; 50 microM). There was an increase in formation of reactive oxygen species (ROS) within 30 min, as well as an increase in the activity of both caspase-3 and -8, and both effects were attenuated by HMB. Moreover, inhibitors of caspase-3 and -8 completely attenuated both ROS formation and total protein degradation induced by TNF-alpha/IFN-gamma and ANG II. There was an increased autophosphorylation of double-stranded RNA-dependent protein kinase (PKR), which was attenuated by the specific caspase-3 and -8 inhibitors. Neither ROS formation or protein degradation occurred in myotubes expressing a catalytically inactive PKR variant, PKRDelta6, in response to TNF-alpha/IFN-gamma, compared with myotubes expressing wild-type PKR, although there was still activation of caspase-3 and -8. HMB also attenuated activation of PKR, suggesting that it was important in protein degradation. Formation of ROS was attenuated by rotenone, an inhibitor of the mitochondrial electron transport chain, nitro-l-arginine methyl ester, an inhibitor of nitric oxide synthase, and SB 203580, a specific inhibitor of p38 mitogen-activated protein kinase (p38 MAPK), which also attenuated total protein degradation. Activation of p38 MAPK by PKR provides the link to ROS formation. These results suggest that TNF-alpha/IFN-gamma and ANG II induce muscle protein degradation by a common signaling pathway, which is attenuated by HMB, and that this involves the initial activation of caspase-3 and -8, followed by autophosphorylation and activation of PKR, which then leads to increased ROS formation via activation of p38 MAPK. Increased ROS formation is known to induce protein degradation through the ubiquitin-proteasome pathway.

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.