Effects of Bacillus thuringiensis toxin on hepatic lipid peroxidation and free-radical scavengers in rats given alpha-tocopherol or acetylsalicylate

The effect of Dipel (D), a Bacillus thuringiensis-based bioinsecticide, on hepatic antioxidant enzyme activities and lipid peroxidation in rat liver was investigated. Administration of D in a dose of 1 mg/100 g body mass for 4 successive days increased the activities of glutathione peroxidase (GPx), glutathione reductase (GR) and the level of malondialdehyde (MDA) in rat hepatocytes. The activity of superoxide dismutase (SOD) and glutathione (GSH) level were decreased. Administration of D in rats pretreated with alpha-tocopherol (alphaT) or acetylsalicylic acid (ASA) decreased the activities of GPx, GR and MDA levels, while the GSH level was increased compared with rats treated with D alone. The SOD activity was increased in rats pretreated with alphaT before D, but decreased on pretreatment with ASA, compared with rats treated with D alone. The results indicated that D induced oxidative stress in rat liver that has been protected by prior administration of alphaT or ASA.     

A novel spectrofluorimetric method for determination of lomefloxacin adopting on zinc(II) chelation strategy: Application in human plasma

A new sensitive and instantaneous spectrofluorimetric method for efficient determination of lomefloxacin (LMX) in its pure, dosage form and human plasma was designed. The developed method depends on formation of a metal-chelation compound of LMX as a ligand with zinc(II) in a buffer of acetate (pH 5.5). The following parameters; type of metal, concentration of metal, pH, type of buffer and diluting solvent were optimized. After carefully investigation; 0.2 mM zinc, 2.0 ml acetate buffer (pH 5.5) and water as diluting solvent were set as optimum reaction conditions. Under these conditions, a large increase in the intensity of the fluorescence of LMX was attained at 450 after excitation at 284 nm. The limits of detection and quantification were 5.8 and 1.9 ng ml⁻¹, respectively, with linearity range of 10.0 to 500.0 ng ml⁻¹. The binding mode of LMX and zinc(II) ion (Zn²⁺) was found to be 2:1, respectively, and confirmed by Job's plot method. Furthermore, it extended to the analysis of LMX in the spiked plasma of humans with percentage recovery (98.70 ± 0.97 to 100.30 ± 1.69%, n = 3).     

A new traffic congestion prediction strategy (TCPS) based on edge computing

Real-time accurate traffic congestion prediction can enable Intelligent traffic management systems (ITMSs) that replace traditional systems to improve the efficiency of traffic and reduce traffic congestion. The ITMS consists of three main layers, which are: Internet of Things (IoT), edge, and cloud layers. Edge can collect real-time data from different routes through IoT devices such as wireless sensors, and then it can compute and store this collected data before transmitting them to the cloud for further processing. Thus, an edge is an intermediate layer between IoT and cloud layers that can receive the transmitted data through IoT to overcome cloud challenges such as high latency. In this paper, a novel real-time traffic congestion prediction strategy (TCPS) is proposed based on the collected data in the edge’s cache server at the edge layer. The proposed TCPS contains three stages, which are: (i) real-time congestion prediction (RCP) stage, (ii) congestion direction detection (CD²) stage, and (iii) width change decision (WCD) stage. The RCP aims to predict traffic congestion based on the causes of congestion in the hotspot using a fuzzy inference system. If there is congestion, the CD² stage is used to detect the congestion direction based on the predictions from the RCP by using the Optimal Weighted Naïve Bayes (OWNB) method. The WCD stage aims to prevent the congestion occurrence in which it is used to change the width of changeable routes (CR) after detecting the direction of congestion in CD². The experimental results have shown that the proposed TCPS outperforms other recent methodologies. TCPS provides the highest accuracy, precision, and recall. Besides, it provides the lowest error, with values equal to 95%, 74%, 75%, and 5% respectively.

     

High cooperativity of the SV40 major capsid protein VP1 in virus assembly

SV40 is a small, non enveloped DNA virus with an icosahedral capsid of 45 nm. The outer shell is composed of pentamers of the major capsid protein, VP1, linked via their flexible carboxy-terminal arms. Its morphogenesis occurs by assembly of capsomers around the viral minichromosome. However the steps leading to the formation of mature virus are poorly understood. Intermediates of the assembly reaction could not be isolated from cells infected with wt SV40. Here we have used recombinant VP1 produced in insect cells for in vitro assembly studies around supercoiled heterologous plasmid DNA carrying a reporter gene. This strategy yields infective nanoparticles, affording a simple quantitative transduction assay. We show that VP1 assembles under physiological conditions into uniform nanoparticles of the same shape, size and CsCl density as the wild type virus. The stoichiometry is one DNA molecule per capsid. VP1 deleted in the C-arm, which is unable to assemble but can bind DNA, was inactive indicating genuine assembly rather than non-specific DNA-binding. The reaction requires host enzymatic activities, consistent with the participation of chaperones, as recently shown. Our results demonstrate dramatic cooperativity of VP1, with a Hill coefficient of approximately 6. These findings suggest that assembly may be a concerted reaction. We propose that concerted assembly is facilitated by simultaneous binding of multiple capsomers to a single DNA molecule, as we have recently reported, thus increasing their local concentration. Emerging principles of SV40 assembly may help understanding assembly of other complex systems. In addition, the SV40-based nanoparticles described here are potential gene therapy vectors that combine efficient gene delivery with safety and flexibility.     

Fast and reliable determination of Escherichia coli susceptibility to antibiotics: Infrared microscopy in tandem with machine learning algorithms

Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, the increasing resistance of bacteria to antibiotics has become a global health care problem. Rapid determination of antimicrobial susceptibility of clinical isolates is often crucial for the optimal antimicrobial therapy. The conventional methods used in medical centers for susceptibility testing are time‐consuming (>2 days). Two bacterial culture steps are needed, the first is used to grow the bacteria from urine on agar plates to determine the species of the bacteria (~24 hours). The second culture is used to determine the susceptibility by growing colonies from the first culture for another 24 hours. Here, the main goal is to examine the potential of infrared microscopy combined with multivariate analysis, to reduce the time it takes to identify Escherichia coli susceptibility to antibiotics and to determine the optimum choice of antibiotic to which the bacteria will respond. E coli colonies of the first culture from patients with urinary tract infections (UTI) were examined for the bacterial susceptibility using Fourier‐transform infrared (FTIR). Our results show that it is possible to determine the optimum choice of antibiotic with better than 89% sensitivity, in the time span of few minutes, following the first culture.      

An overview on the correlation of neurological disorders with cardiovascular disease

Neurological disorders (NDs) are one of the leading causes of death especially in the developed countries. Among those NDs, Alzheimer’s disease (AD) and Parkinson disease (PD) are heading the table. There have been several reports in the scientific literatures which suggest the linkage between cardiovascular disorders (CVDs) and NDs. In the present communication, we have tried to compile NDs (AD and PD) association with CVDs reported in the literature. Based on the available scientific literature, we believe that further comprehensive study needs to be done to elucidate the molecular linking points associated with the above mentioned disorders.Abbreviations: AD, Alzheimer’s disease, Aβ, β amyloid, PD, Parkinson disease, l-DOPA, l-dihydroxyphenylalanine, LBs, Lewy bodies, DA, dopamine, APP, amyloid precursor protein, CVD, cardiovascular disease     

Assessing structural variation in a personal genome—towards a human reference diploid genome

Background

Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods.

Results

We demonstrate Parliament’s efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus.

Conclusions

HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1479-3) contains supplementary material, which is available to authorized users.     

A new insight on serum microRNA expression as novel biomarkers in breast cancer patients

Breast cancer (BC) is one of the widespread lethal diseases affecting a large number of women worldwide. As such, employing and identifying significant markers for detecting BC in different stages can assist in better diagnosis and management of the disease. Several diverse markers have been introduced for diagnosis, but their limitations, including low specificity and sensitivity, reduce their application. microRNAs (miRNAs), as short noncoding RNAs, have been shown to significantly influence gene expression in different disease pathologies, especially BC. Clearly, among different samples used for detecting miRNA expressions, circulating miRNAs present as promising and useful biomarkers. Among different body fluid samples, serum serves as one of the most reliable samples, thanks to its high stability under various severe conditions and some unique features. Extensive research has suggested that BC-related miRNAs can remain stable in the serum. The objective of this review is to describe different samples used for detecting miRNAs in BC subjects with emphasis on serum miRNAs. So, this study highlights serum miRNAs with the potential of acting as biomarkers for different stages of BC. We reviewed the possible correlation between potential miRNAs and the risk of early breast cancer, metastatic breast cancer, response to chemotherapy, and relapse.     

Tumor-derived exosomal microRNAs and proteins as modulators of macrophage function

Tumor cells are able to modify their surrounding microenvironment by transmitting bioactive molecules via exosomes. In exosomes, proteins and nucleic acids that can be taken up by surrounding cells have been identified and modulate their functions. Tumor microenvironment consists of different cells such as macrophages. Tumors-associated macrophages (TAMs) express M2 phenotype and affect many processes including tumor initiation, angiogenesis, and metastasis. It has been demonstrated that a high number of TAMs is associated with poor prognosis of cancers. The contents of tumor-derived exosomes such as microRNAs and proteins induce macrophages to M2-like polarization to support tumor growth. Herein, we review the most recent studies on the effect of tumor-derived exosomes on macrophage polarization and function in different types of cancers.