The Changes in the Lipid Composition of Mung Bean Seeds as Affected by Processing Methods

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.This study was conducted to assess in detail the possible effects of some technological processes such as soaking, germination, cooking, soaking + cooking, and germination + cooking on the lipid composition of mung bean seeds of Giza 1 variety. TLC analysis of mung bean lipids showed that the phospholipids and triglycerides recorded the highest percentage among lipid fractions (32.26 and 30.10%), while the 1,3 diglycerides constituted the least percentage (2.80%) in mung bean seeds. The soaking, germination and cooking processes caused a decrease in the phospholipids, triglycerides and hydrocarbons accompanied with an increase in monoglycerides, 1,2-(2,3)-diglycerides, sterols and free fatty acids. Eleven fractions were separated from phospholipids class of the studied samples; seven of these fractions were identified. The major component of phospholipids was phosphatidyl choline, amounting to 21.30, 17.84, 16.21, 13.87, 13.20 and 11.47% of the total phospholipids in raw, soaked, germinated, raw-cooked, soaked-cooked and germinated-cooked mung bean seeds, respectively. Gas liquid chromatography of the total lipids of mung bean seeds showed that the unsaturated fatty acids represented 69.58, 64.35, 63.3, 63.16, 61.84 and 61.12%, while the levels of saturated fatty acids were low being 30.37, 34.05, 35.66, 34.64, 37.93 and 38.75% of the total fatty acids in raw, soaked, germinated, raw-cooked, soaked-cooked and germinated-cooked, respectively. The total essential fatty acids (linoleic and linolenic) represented the highest proportion of fatty acids (50.10% of the total fatty acids)

The metabolomic analysis of five Mentha species: cytotoxicity, anti-Helicobacter assessment, and the development of polymeric micelles for enhancing the anti-Helicobacter activity

Mentha species are medicinally used worldwide and remain attractive for research due to the diversity of their phytoconstituents and large therapeutic indices for various ailments. This study used the metabolomics examination of five Mentha species (M. suaveolens, M. sylvestris, M. piperita, M. longifolia, and M. viridis) to justify their cytotoxicity and their anti-Helicobacter effects. The activities of species were correlated with their phytochemical profiles by orthogonal partial least square discriminant analysis (OPLS-DA). Tentatively characterized phytoconstituents using liquid chromatography high-resolution electrospray ionization mass spectrometry (LC-HR-ESI-MS) included 49 compounds: 14 flavonoids, 10 caffeic acid esters, 7 phenolic acids, and other constituents. M. piperita showed the highest cytotoxicity to HepG2 (human hepatoma), MCF-7 (human breast adenocarcinoma), and CACO2 (human colon adenocarcinoma) cells using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays. OPLS-DA and dereplication studies predicted that the cytotoxic activity was related to benzyl glucopyranoside-sulfate, a lignin glycoside. Furthermore, M. viridis was effective in suppressing the growth of Helicobacter pylori at a concentration of 50 mg mL−1. OPLS-DA predicted that this activity was related to a dihydroxytrimethoxyflavone. M. viridis extract was formulated with Pluronic® F127 to develop polymeric micelles as a nanocarrier that enhanced the anti-Helicobacter activity of the extract and provided minimum inhibitory concentrations and minimum bactericidal concentrations of 6.5 and 50 mg mL−1, respectively. This activity was also correlated to tentatively identified constituents, including rosmarinic acid, catechins, carvone, and piperitone oxide

A Brain Region-Specific Predictive Gene Map for Autism Derived by Profiling a Reference Gene Set

Molecular underpinnings of complex psychiatric disorders such as autism spectrum disorders (ASD) remain largely unresolved. Increasingly, structural variations in discrete chromosomal loci are implicated in ASD, expanding the search space for its disease etiology. We exploited the high genetic heterogeneity of ASD to derive a predictive map of candidate genes by an integrated bioinformatics approach. Using a reference set of 84 Rare and Syndromic candidate ASD genes (AutRef84), we built a composite reference profile based on both functional and expression analyses. First, we created a functional profile of AutRef84 by performing Gene Ontology (GO) enrichment analysis which encompassed three main areas: 1) neurogenesis/projection, 2) cell adhesion, and 3) ion channel activity. Second, we constructed an expression profile of AutRef84 by conducting DAVID analysis which found enrichment in brain regions critical for sensory information processing (olfactory bulb, occipital lobe), executive function (prefrontal cortex), and hormone secretion (pituitary). Disease specificity of this dual AutRef84 profile was demonstrated by comparative analysis with control, diabetes, and non-specific gene sets. We then screened the human genome with the dual AutRef84 profile to derive a set of 460 potential ASD candidate genes. Importantly, the power of our predictive gene map was demonstrated by capturing 18 existing ASD-associated genes which were not part of the AutRef84 input dataset. The remaining 442 genes are entirely novel putative ASD risk genes. Together, we used a composite ASD reference profile to generate a predictive map of novel ASD candidate genes which should be prioritized for future research

SVD Audio Watermarking: A Tool to Enhance the Security of Image Transmission over ZigBee Networks

The security is important issue in wireless networks. This paper discusses audio watermarking as a tool to improve the security of image communication over the IEEE 802.15.4 ZigBee network. The adopted watermarking method implements the Singular-Value Decomposition (SVD) mathematical technique. This method is based on embedding a chaotic encrypted image in the Singular Values (SVs) of the audio signal after transforming it into a 2-D format. The objective of chaotic encryption is to enhance the level of security and resist different attacks. Experimental results show that the SVD audio watermarking method maintains the high quality of the audio signals and that the watermark extraction and decryption are possible even in the presence of attacks over the ZigBee network