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

SVD Audio Watermarking: A Tool to Enhance the Security of Image Transmission over ZigBee Networks, Journal of Telecommunications and Information Technology, 2011, nr 4

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

An Efficient Chaotic Interleaver for Image Transmission over IEEE 802.15.4 Zigbee Network, Journal of Telecommunications and Information Technology, 2011, nr 2

This paper studies a vital issue in wireless communications, which is the transmission of images over wireless networks. IEEE ZigBee 802.15.4 is a short-range communication standard that could be used for small distance multimedia transmissions. In fact, the ZigBee network is a wireless personal area network (WPAN), which needs a strong interleaving mechanism for protection against error bursts. This paper presents a novel chaotic interleaving scheme for this purpose. This scheme depends on the chaotic Baker map. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for image transmission over a correlated fading channel is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes

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

Phytochemical Investigation of <i>Cordia africana</i> Lam. Stem Bark: Molecular Simulation Approach

Background: The current work planned to evaluate Cordia africana Lam. stem bark, a traditionally used herb in curing of different ailments in Africa such as gastritis and wound infections, based on phytochemical and antibacterial studies of two pathogenic microorganisms: methicillin-resistant Staphylococcus aureus (MRSA) and Helicobacter pylori. Methods: High performance liquid chromatography (HPLC) profiling was used for qualitative and quantitative investigation of the ethanol extract. The minimum inhibitory concentration (MIC) of the ethanolic extract and isolated compounds was estimated using the broth microdilution method and evidenced by molecular dynamics simulations. Results: Four compounds were isolated and identified for the first time: α-amyrin, β-sitosterol, rosmarinic acid (RA) and methyl rosmarinate (MR). HPLC analysis illustrated that MR was the dominant phenolic acid. MR showed the best bacterial inhibitory activity against MRSA and H. pylori with MIC 7.81 ± 1.7 μg/mL and 31.25 ± 0.6, respectively, when compared to clarithromycin and vancomycin, respectively. Conclusion: The antibacterial activity of the stem bark of Cordia africana Lam. was evidenced against MRSA and H. pylori. Computational modeling of the studied enzyme-ligands systems reveals that RA and MR can potentially inhibit both MRSA peptidoglycan transpeptidases and H. pylori urease, thereby creating a pathway via the use of a double target approach in antibacterial treatment

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

Juvenile and juvenile-onset systemic lupus erythematosus patients: Clinical characteristics, disease activity and damage

Background: The diagnosis of systemic lupus erythematosus (SLE) in children is challenging. The heterogeneous manifestations and disease impact on the child’s growth highlight the importance of timely diagnosis and management. Objective: The aim of the work was to assess and compare the clinical characteristics, disease activity and damage between children with juvenile SLE (JSLE) and adult patients with juvenile-onset (JO-SLE). Patients and methods: 78 SLE patients; 26 children (JSLE) and 52 JO-SLE adults were included in this study. Disease activity was assessed using the SLE Disease Activity Index (SLEDAI) and organ damage using the Systemic Lupus International Collaborating Clinics (SLICC) index. Results: The mean age of the JSLE children was 13.25 ± 2.09 years and 23.17 ± 4.26 years for JO-SLE cases. Age at disease-onset and female gender tended to be higher in JO-SLE cases than in children with JSLE. There was a significantly higher frequency of serositis, nephritis and hematological involvement in the JO-SLE (57.7%, 76.9%, 73.1%, respectively) compared to the JSLE cases (15.4%, 30.8%, 30.8%, respectively) (p < 0.001 for all). The erythrocyte sedimentation rate, creatinine and proteinuria were significantly increased in JO-SLE while alkaline phosphatase was higher in JSLE cases. In JO-SLE cases, SLEDAI significantly increased (5.96 ± 6.18 vs 3.12 ± 1.97; p = 0.003) and the SLICC tended to increase compared to the JSLE children. More JO-SLE cases received hydroxychloroquine and azathioprine. Conclusion: The existence of differences in clinical phenotype has been confirmed, between JSLE and JO-SLE especially as regards serositis, nephritis and heamatological affection. The disease damage was comparable which denotes that the maximum organ involvement occurs in childhood with an almost stationary course

Low Energy Lossless Image Compression Algorithm for Wireless Sensor Network (LE-LICA)

The energy consumption restricts the design of image compression algorithms in Wireless Sensor Network (WSN). The tradeoff between the decompressed image quality and energy consumption should be considered in the design. The field of image processing introduced many image compression algorithms for WSN. Joint Photographic Experts Group 2000 (JPEG2000) and Absolute Moment Block Truncation Coding (AMBTC) are examples of these algorithms. This tradeoff is considered in the design of the proposed algorithm to get Lossless image compression algorithm with a high compression rate. LE-LICA is compared with the traditional algorithms using popular metrics such as: Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), and energy consumption. The proposed algorithm enhances both the image quality and the energy consumption. A great challenge to reconstruct an image at the sink without lossless (the best quality) and low energy consumption at the sensor node. The results show the preference of the proposed algorithm to the others