Liquid-phase microextraction of polycyclic aromatic hydrocarbons: A review

Polycyclic aromatic hydrocarbons (PAHs) are a large group of organic compounds comprised of two or more fused benzene rings, which arise from the incomplete combustion of organic materials. These compounds have been of concern as carcinogens and mutagens for the past 50-60 years. Lately, they are also receiving attention as endocrine-disrupting chemicals. Therefore, proper analytical methods are required for sampling and analyzing these compounds. In response to problems associated with the conventional methods like solid-phase extraction (SPE) and liquid-liquid extraction (LLE), many studies have focused on the miniaturization of different sample preparation techniques. In this regard, the use of different types of liquid phase microextraction (LPME) techniques has increased significantly during the recent few decades. LPME techniques are advantageous because they use single-step sample preparation and have shown a greater sensitivity, selectivity, and efficiency than the conventional methods. In addition, these techniques have good potential for automation, to reduce the time and cost of analysis. This review focuses on the most important configurations of LPME including single‐drop microextraction (SDME), hollow-fiber liquid-phase microextraction (HF-LPME), and dispersive liquid-liquid microextraction (DLLME) techniques used for the sampling and determination of PAHs in different samples, along with their cons and pros, as well as their prospects

Descriptive osteology of Squalius orientalis from Urmia Lake basin of Iran

Osteological features are important to study the taxonomy and phylogenetic relationship of fishes. Since there is no information is available about osteological features of Squalius orientalis, therefore this study was aimed to provide a detailed description of the osteological features of this species from the Urmia lake basin of Iran and comparing it with population of S. orientalis from the Caspian Sea basin. For this purpose, the specimens were collected from Zarineh River of the Urmia lake basin and cleared and stained with alizarin red S and alcian blue for osteological examinations. Finally, a detailed osteological features of this species was provided and compared with those of the Caspian Sea basin. Based on the results, having a longer pre-vomer, dorsally oriented parasphenoid alar, longer ventral blade-shaped process of the orbitosphenoid, concaved masticatory plate, pointed ascending process of the palatine, concaved posterior margin of the opercle, and a small posterior process of the cleithrum can differentiate S. orientalis of the Urmia Lake basin from those of the Caspian Sea basin. In addition, the observed osteological difference suggest that both studied populations belong to same taxon

A new look at the modified Coulomb potential in a strong magnetic field

The static Coulomb potential of Quantum Electrodynamics (QED) is calculated in the presence of a strong magnetic field in the lowest Landau level (LLL) approximation using two different methods. First, the vacuum expectation value of the corresponding Wilson loop is calculated perturbatively in two different regimes of dynamical mass $m_{dyn.}$, {\it i.e.}, $|{\mathbf{q}}_{\|}^{2}|\ll m_{dyn.}^{2}\ll |eB|$ and $m_{dyn.}^{2}\ll |\mathbf{q}_{\|}^{2}|\ll|eB|$, where $\mathbf{q}_{\|}$ is the longitudinal components of the momentum relative to the external magnetic field $B$. The result is then compared with the static potential arising from Born approximation. Both results coincide. Although the arising potentials show different behavior in the aforementioned regimes, a novel dependence on the angle $\theta$ between the particle-antiparticle's axis and the direction of the magnetic field is observed. In the regime $|{\mathbf{q}}_{\|}^{2}|\ll m_{dyn.}^{2}\ll |eB|$, for strong enough magnetic field and depending on the angle $\theta$, a qualitative change occurs in the Coulomb-like potential; Whereas for $\theta=0,\pi$ the potential is repulsive, it exhibits a minimum for angles $\theta\in]0,\pi[$.Comment: V1: 26 pages, 8 figures, latex format, V2: Accepted for publication in PRD (2007

GenoMetric Query Language: A novel approach to large-scale genomic data management

Motivation: Improvement of sequencing technologies and data processing pipelines is rapidly providing sequencing data, with associated high-level features, of many individual genomes in multiple biological and clinical conditions. They allow for data-driven genomic, transcriptomic and epigenomic characterizations, but require state-of-the-art ‘big data’ computing strategies, with abstraction levels beyond available tool capabilities. Results: We propose a high-level, declarative GenoMetric Query Language (GMQL) and a toolkit for its use. GMQL operates downstream of raw data preprocessing pipelines and supports queries over thousands of heterogeneous datasets and samples; as such it is key to genomic ‘big data’ analysis. GMQL leverages a simple data model that provides both abstractions of genomic region data and associated experimental, biological and clinical metadata and interoperability between many data formats. Based on Hadoop framework and Apache Pig platform, GMQL ensures high scalability, expressivity, flexibility and simplicity of use, as demonstrated by several biological query examples on ENCODE and TCGA datasets. Availability and implementation: The GMQL toolkit is freely available for non-commercial use at http://www.bioinformatics.deib.polimi.it/GMQL/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Enhancing synchronizability of weighted dynamical networks using betweenness centrality

By considering the eigenratio of the Laplacian of the connection graph as synchronizability measure, we propose a procedure for weighting dynamical networks to enhance theirsynchronizability. The method is based on node and edge betweenness centrality measures and is tested on artificially const ructed scale-free, Watts-Strogatz and random networks as well as on some real-world graphs. It is also numerically shown that the same procedure could be used to enhance the phase synchronizability of networks of nonidentical oscillators

Explorative visual analytics on interval-based genomic data and their metadata

Background: With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. Results: This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. Conclusions: GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSEunder GPLv3 open-source license

EEG-Based Functional Brain Networks: Does the Network Size Matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks – whose nodes can vary from tens to hundreds – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies

A new Raman metric for the characterisation of graphene oxide and its derivatives

Raman spectroscopy is among the primary techniques for the characterisation of graphene materials, as it provides insights into the quality of measured graphenes including their structure and conductivity as well as the presence of dopants. However, our ability to draw conclusions based on such spectra is limited by a lack of understanding regarding the origins of the peaks. Consequently, traditional characterisation techniques, which estimate the quality of the graphene material using the intensity ratio between the D and the G peaks, are unreliable for both GO and rGO. Herein we reanalyse the Raman spectra of graphenes and show that traditional methods rely upon an apparent G peak which is in fact a superposition of the G and D’ peaks. We use this understanding to develop a new Raman characterisation method for graphenes that considers the D’ peak by using its overtone the 2D’. We demonstrate the superiority and consistency of this method for calculating the oxygen content of graphenes, and use the relationship between the D’ peak and graphene quality to define three regimes. This has important implications for purification techniques because, once GO is reduced beyond a critical threshold, further reduction offers limited gain in conductivity

Characterization of aluminum, aluminum oxide and titanium dioxide nanomaterials using a combination of methods for particle surface and size analysis

International audienceThe application of appropriate analytical techniques is essential for nanomaterial (NM) characterization. In this study, we compared different analytical techniques for NM analysis. Regarding possible adverse health effects, ionic and particulate NM effects have to be taken into account. As NMs behave quite differently in physiological media, special attention was paid to techniques which are able to determine the biosolubility and complexation behavior of NMs. Representative NMs of similar size were selected: aluminum (Al 0) and aluminum oxide (Al 2 O 3), to compare the behavior of metal and metal oxides. In addition, titanium dioxide (TiO 2) was investigated. Characterization techniques such as dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) were evaluated with respect to their suitability for fast characterization of nanoparticle dispersions regarding a particle's hydrodynamic diameter and size distribution. By application of inductively coupled plasma mass spectrometry in the single particle mode (SP-ICP-MS), individual nanoparticles were quantified and characterized regarding their size. SP-ICP-MS measurements were correlated with the information gained using other characterization techniques, i.e. transmission electron microscopy (TEM) and small angle X-ray scattering (SAXS). The particle surface as an important descriptor of NMs was analyzed by X-ray diffraction (XRD). NM impurities and their co-localization with biomolecules were determined by ion beam microscopy (IBM) and confocal Raman microscopy (CRM). We conclude advantages and disadvantages of the different techniques applied and suggest options for their complementation. Thus, this paper may serve as a practical guide to particle characterization techniques