DETERMINATION OF BIOACTIVE CONSTITUENTS OF LEAVES OF CORCHORUS AESTUANS (L.) BY GC - MS ANALYSIS

Objective: To investigate the bioactive constituents of ethanol extract of Corchorus aestuans (L.) using GC-MS technique. Methods: The ethanol extract of leaves were subjected to GC- MS analysis using GC Clarus 500 (Perkin Elmer) with Elite- 5MS (5%Diphenyl / 95% Dimethyl poly siloxane, 30 mm x 0.25 mm x0.25μm df). The 2 μl extract sample injected and the components were separated using Helium (1 mL/min) as the carrier gas. Bioactive constituents were detected by the Turbo mass gold detector (Perkin Elmer) with the aid of the Turbomass 5.2 software. Results: The analysis revealed the presence of fourteen different bioactive constituents namely 3, 7,11,15-tetramethyl-2-hexadecen-1-ol (5.6%), Trans-2-undecen-1-ol (1.26%), E-7-Tetradecenol (1.97%), n-Hexadecanoic acid (25.82%), Phytol (22.34%), 9,12,15-octadecatrienoic acid, methyl ester, (Z,Z,Z)- (20.23%), Docosanoic acid, ethyl ester (1.99%), 1-Eicosanol (2.11 %), 9,9-dimethoxybicyclo[3.3.1] nona-2,4-dione (0.60%), Heptadecanoic acid, heptadecyl ester (0.95%), Pentadecanoicacid,2,6,10,14-tetramethyl-,methylester(0.91%), 3-Hexadecycloxycarbonyl-5-(2-hydroxyethyl)-4-methylimidazolium ion (0.90%), Squalene (8.03%), Vitamin E (7.24%). Conclusion: The presence of various bioactive compounds confirms the application of Corchorus aestuans in various disorders. However, isolation of individual phytochemical constituents may proceed to find a lead for herbal therapy

PREPARATION AND CHARACTERIZATION OF CEFTRIAXONE SODIUM ENCAPSULATED CHITOSAN NANOPARTICLES

Objective: The objective of this study was to prepare ceftriaxone sodium chitosan nanoparticles (CS-NP) from different drug and polymer ratios and analyze their physicochemical characteristics.Methods: Ceftriaxone sodium loaded chitosan nanoparticles were prepared using chitosan as a polymer and tri sodium polyphosphate (TPP) as cross linking agent by ionic cross linking and coacervation with the aid of sonication. Various trials have been carried out for the confirmation of nanoformulation. Parameters such as the zeta potential, polydispersity, particle size, entrapment efficiency, in vitro drug release Thermo gravimetric analysis and scanning electron microscope of the nanoparticles were assessed for confirmation of nanoformulation.Results: The formulated nanoparticles showed mean particle size, polydispersity index and zeta potential to be 183.1±8.42 nm, 0.212±0.05, +38.5±1.6 mV respectively and the drug loading was found to be 46.42±10 %. In vitro drug release was showed a biphasic release pattern with initial burst release followed by sustained release of formulated nanoparticles. The cumulative percentage of drug release was about 83.08 %.Conclusion: Formulation F2 was found to be the best formulation with a higher cumulative percentage of drug release. Modified ionic gelation method can be utilized for the development of chitosan nanoparticles of ceftriaxone sodium. Polymer and crosslinking agent concentrations and sonication time are rate-limiting factors for the development of the optimized formulation. The chitosan nanoparticles developed would be capable of sustained delivery of ceftriaxone sodium

Cancer chemopreventive property of Bidens pilosa methanolic extract on two stage in vivo skin carcinogenesis model

The effect of the methanolic extract of whole plant of B. pilosa on drug metabolizing phase I and II enzymes, antioxidant enzymes, lactate dehydrogenase and lipid peroxidase, anticarcinogenic potential in dimethylbenzathracene induced forestomach and tetradecanoyl acetate promoted skin papillomagenesis was studied in mice. The hepatic glutathione S-transferase and DT-diaphorase specific activities were elevated above basal level. Bidens pilosa methanolic extract was effective in elevating antioxidant enzyme response by increasing significantly the hepatic glutathione peroxidase, gluatathione reductase, catalase and superoxide dismutase. Reduced glutathione measured as non protein sulphydryl was found to be significantly increased in liver while in extrahepatic organs it was decreased. In the forestomach, kidney and lung, glutathione S-transferase and DT-diaphorase levels were significantly reduced. Chemopreventive response was calculated by the mean number of papillomas /mouse and percentage of tumorbearing mice. There was a significant inhibition of tumor burden in both the tumor model systems studied.Keywords: Bidens pilosa, chemopreventive, DT-diaphorase, glutathione S-transferase, lactate dehydrogenaseEast and Central African Journal of Pharmaceutical Sciences Vol.14 (2011) 43-5

Antinociceptive, antipyretic and anti-inflammatory effects of Clerodendrum phlomidis in mice and rats

The ethanolic extract of Clerodendrum phlomidis L. belonging to the family of Verbenaceae was evaluated for its antinociceptive, antipyretic and anti-inflammatory activity in mice and rats respectively. Analgesic activity was studied by using acetic acid-induced mouse withering test, hot water tail immersion method and eddy’s hot plate method in mice. The antipyretic activity was evaluated against yeast induced pyroxia in rat and anti-inflammatory activity was evaluated by carrageenan-induced hind paw edema and its probable mechanism evaluated in rats. The preliminary phytochemical screening and acute toxicity studies were carried out. C. phlomidis extract showed a dose dependent significant reduction of the number of writhes (

Development and validation of dissolution test for Metoprolol sustained release capsules

Dissolution test for sustained release capsules of Metoprolol 125 mg was developed and validated according to FDA and ICH guidelines. Metoprolol coated pellets were coated with microcrystalline wax and glyceryl distearate for slow release of drug. The dissolution method which uses USP apparatus I (Basket) with rotating at 100 rpm, 900 ml of different dissolution medium, ultra violet spectroscopy for quantification was demonstrated to be robust, discriminating and transferable. Dissolution tests conditions were selected after it was demonstrated that the Metoprolol rapidly dissolved in the aqueous media over the pH range of 1.2 to 7.

OPTIMUM PARAMETERS SELECTION USING BACTERIAL FORAGING OPTIMIZATION FOR WEIGHTED EXTREME LEARNING MACHINE

Extreme Learning Machine (ELM) is a Single Layer Feed Forward Network (SLFN) model with extremely learning capacity and good generalization capabilities. Generally, the performance of ELM for classification task highly based on three factors such as the input weight matrix, the value of bias and the number of hidden neurons presented. ELM randomly chooses the input weights and biases and determines analytically the weights as output. The random selection of biases and the input weight produce an unforeseen result which causes training error and also produces lesser prediction accuracy. Bacterial Foraging Optimization algorithm (BFOA) was used to find the optimum input weight and hidden bias values for ELM. With the unequal distribution of classes in imbalanced data sets, ELM algorithms tussle to find good accuracy. So, ELM algorithm doesn’t get the necessary information about the minority class to make an accurate classification. To deal the issues associated with ELM, in this paper the hybrid algorithms Weighted ELM and Weighted ELM with BFO are proposed. Weighted ELM is proposed to handle the classification data that has imbalanced nature of class distribution. The main objective of weighted ELM is that the related weight value is computed and assigned for each training sample to increase the classification rate. Bacterial Foraging Optimization method is also integrated with the weighted ELM to find the optimum input weight and bias to maximize the classification accuracy. The comparative analysis has been performed over Hepatitis dataset. Further, the experimental results clearly revealed that one of the proposed methods Weighted ELM with BFO performs quite well when compared to others

DESPECKLEING PROSTATE ULTRASONOGRAMS USING PDE WITH WAVELET

Prostate cancer is the leading cause of death for men, since the cause of the disease is mysterious and its early detection is also monotonous. Ultrasound (US) is the most popular tool to detect the human organ glands and also used to diagnose the prostate cancer. Speckle noise is an inherent nature of ultrasound images, which degrades the image quality. So far, No specific filter is available to suppress the speckle noise in prostate image. In this paper, a novel despeckling method PDE with Wavelet is presented for prostate US images. The enhancement method is evaluated by using standard measures like Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR) and Edge Preservation Index (EPI). Further, the despeckling approaches is also evaluated time and space complexity. From the results, it is observed that the filtering method PDE with Wavelet is superior to PDE in terms of denoising and also preserving the information content