Antioxidant, Hypoglycemic, Antilipidemic, and Protective Effect of Polyherbal Emulsion (F6-SMONSECCE) on Alloxan-Induced Diabetic Rats.

The current study focused on the antioxidant potential, α-amylase inhibitory activity, and hypoglycemic, hypolipidemic, and histoprotective (pancreas and kidney) effects of polyherbal emulsion on the alloxan-induced diabetic rats. Polyherbal formulations were prepared from extracts and oils of Nigella sativa (N. sativa), Citrullus colocynthis (C. colocynthis), and Silybum marianum (S. marianum). Out of nine stable formulations, one formulation named F6-SMONSECCE was found to be the best after its evaluation using antioxidant and in vitro α-amylase inhibition assay. The prepared herbal formulations showed significant (p < 0.05) antioxidant activity in terms of radical scavenging as 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric-reducing antioxidant power (FRAP) assays and also revealed the presence of a significant amount of total phenolic and flavonoid contents. "F6- SMONSECCE" (prepared with composition; Silybum marianum oil (SMO) + Nigella sativa extract (NSE) + Citrullus colocynthis extract CCE) was selected for an in vivo trial to ascertain its antidiabetic potential. The treatment dose was determined by using an acute toxicity trial on rats. Administration of alloxan (150 mg/kg b.w., i.p.) significantly (P < 0.05) augmented the blood glucose levels and lipid contents as total cholesterol (TC), triglycerides (TG), low-density lipoproteins (LDL-c), and very-low-density lipoproteins (VLDL-c). However, the levels of insulin and high-density lipoproteins (HDL-c) were found to be decreased, and the histopathological alterations were also found in the pancreas and kidney. The administration of the polyherbal formulation (F6-SMONSECCE) significantly attenuated the blood glucose levels (22.94%), TC (29.10%), TG (38.15%), LDL-c (27.58%), and VLDL-c (71.52%), whereas on the other side, the insulin (-149.15%) and HDL-c levels (-22.22%) were significantly increased. A significant histopathological normalization was observed in the pancreas and kidney tissues of the F6-SMONSECCE-treated rats. The current findings proposed that the prepared polyherbal formulation "F6-SMONSECCE" exhibited significant antioxidant, antilipidemic, and hypoglycemic potential and hence might be suggested as a remedy against diabetes or as a coadjuvant to synthetic medicines to maintain normal physiology.

Fractional lower order moment based adaptive algorithms for active noise control of impulsive noise sources.

This letter deals with active noise control (ANC) for impulsive noise sources being modeled using non-Gaussian stable process. The filtered-x least mean square algorithm is based on minimization of the variance of the error signal and becomes unstable for impulsive noise. The filtered-x least mean p-power algorithm-based on minimizing the fractional lower order moment-gives a robust performance for impulsive ANC; however, its convergence speed is very slow. This letter proposes modifying and employing a generalized normalized LMP algorithm for impulsive ANC. Extensive simulations are carried out which demonstrate the effectiveness of the proposed algorithm.

Biological and Hypoglycemic Effects of a Polyherbal Extract on Alloxanized Diabetic Rats.

The current study investigates the antioxidant, antidiabetic, hepatoprotective, and nephroprotective potentials of a polyherbal mixture containing the methanolic extracts of seeds from Nigella sativa, Cicer arietinum, Silybum marianum, and Citrullus colocynthis and the rhizome of Zingiber officinale. The polyherbal extract (PHE) showed significant total phenolic contents (187.17 GAE/g), ferric reducing power (28%), and radical-scavenging activity (86.16%). The PHE also showed a substantial hypoglycemic effect in alloxan-induced diabetic rats by reducing the blood glucose level of the PHE-treated rats (-48.64%) and increasing the insulin level (107.5%) as compared with the diabetic control group. Likewise, an increase in high-density lipoprotein (HDL) contents (22.95%) with an associated decrease in low-density lipoprotein (LDL) levels (-43.93%) was also noted. A significant decrease in serum levels of liver marker enzymes, e.g., SGPT (-36%), SGOT (-31%), and serum ALP (-12%), was also observed as compared with the standard drug-treated group. Based on the findings of the study, it may be suggested that PHE helps ameliorate the severity of diabetes as a herbal remedy and might be employed in nutra-pharmaceuticals, replacing synthetic antidiabetic compounds.

Focal artifact removal from ongoing EEG--a hybrid approach based on spatially-constrained ICA and wavelet de-noising.

Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks and electrical noise, etc., is an important problem in EEG signal processing research. These artifacts must be corrected before further analysis because it renders subsequent analysis very error-prone. One solution is to reject the data segment if artifact is present during the observation interval, however, the rejected data segment could contain important information masked by the artifact. It has already been demonstrated that independent component analysis (ICA) can be an effective and applicable method for EEG de-noising. The goal of this paper is to propose a framework, based on ICA and wavelet denoising (WD), to improve the pre-processing of EEG signals. In particular we employ the concept of spatially-constrained ICA (SCICA) to extract artifact-only independent components (ICs) from the given EEG data, use WD to remove any brain activity from extracted artifacts, and finally project back the artifacts to be subtracted from EEG signals to get clean EEG data. The main advantage of the proposed approach is faster computation, as all ICs are not identified in the usual manner due to the square mixing assumption. Simulation results demonstrate the effectiveness of the proposed approach in removing focal artifacts that can be well separated by SCICA.