Byrsonima fagifolia Niedenzu Apolar Compounds with Antitubercular Activity

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

Antioxidant Activity and Total Phenols from the Methanolic Extract of Miconia albicans (Sw.) Triana Leaves

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

Studies on anti-allergic constituents in the leaves and stems of Anchietia salutaris var. martiana (Violaceae)

The anti-allergic active fractionation of hexane extracts of the leaves and stems of Anchietia salutaris,ar. martiana (family Violaceae) nas performed by monitoring their activities with an in vitro bioassay system measuring the inhibitory effects on induced histamine release from guinea pig lung cells. Three known pentacyclic triterpenes (friedelin, alpha-amyrin, beta-amyrin) were isolated, but these compounds were inactive. Aliphatic hydrocarbons and methyl esters of fatty acids (palmitic, oleic, linoleic, linolenic acids) were detected in active fractions. All compounds isolated were detected for the first time in this medicinal plant.

Ésteres triterpênicos de Himatanthus sucuuba (Spruce) Woodson

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Coumarins and terpenoids from Dorstenia asaroides Gardn. in Hook

Phytochemical investigation of rhizomes and leaves of Dorstenia asaroides Gardn. in Hook. (Moraceae) afforded the furocoumarins psoralen and bergapten, the triterpenes α-amyrin, α-amyrin acetate, β-amyrin acetate, lupeyl acetate and simiarenol and saccharose.

Flavonoids from Chiococca braquiata (Rubiaceae)

A new flavonol 4′-methoxykaempferol-7-(acetyloxy)-3,5-O-α-L- rhamnoside (1), was isolated from the leaves of Chiococca braquiata, along with three known flavonoids apigenin, 7-O-methoxyquercetrin and quercetrin and four triterpenes α-amirin, β-amirin, ursolic and oleanolic acids . Their structures were established on the basis of spectroscopic methods.

Atividade anti-micobacteriana de extratos de folhas de Byrsonima crassa Nied

In this study, the antimycobacterial activity of chloroformic and methanolic extracts obtained from Byrsonima crassa leaves was evaluated. Antimycobacterial activity was assessed through the microtechnique named Microplate Alamar Blue Assay (MABA) and the promising active principles were identified by spectrophotometric analysis. The chloroformic extract presenting 62.5 μg mL-1 minimum inhibitory concentration (MIC) showed to be active against tuberculosis bacillus. The MIC value of the methanolic extract was 1000 μg mL-1. For the chloroformic one , phytochemical analysis indicated that antimycobacterial activity might be related to the presence of triterpenes.

A new tropane alkaloid and other constituents of Erythroxylum rimosum (Erythroxylaceae)

A new tropane alkaloid, named the 7β-acetoxy-3β,6β- dibenzoyloxytropane (1), was isolated from a methanol extract of Erythroxylum rimosum O.E. Schulz leaves. Other known compounds were detected, including quercetin, kaempferol-3-O-α-l-arabinofuranoside, (+)-catechin, epicatechin, quercetin-3-O-α-arabinofuranoside, quercetin-3-O-α- arabinopyranoside, quercetin-3-O-β-arabinopyranoside, quercetin-3-β- glucopyranoside, kaempferol, quercetin-3-O-β-galactopyranoside, β-sitosterol, α-amyrin, β-amyrin, and the ester derivatives of these two amyrins. Compound 1 exhibited weak inhibition of acetylcholinesterase. Structural identification was performed using IR, ESIHRMS and one- and two-dimensional NMR data analyses and confirmed by comparison with literature data. © 2013 Phytochemical Society of Europe.

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.