Characterization of the extracellular polymeric substances and microbial community of aerobic granulation sludge exposed to cefalexin

This study characterizes the extracellular polymeric substances and bacterial community composition of aerobic granules exposed to cefalexin (CLX). The presence of CLX potentially decreases granular stabilities, resulting in a lowered granule diameter. Chemical oxygen demand and NH4+-N removal efficiencies were slightly decreased and the denitrification process was inhibited with CLX addition. Extracellular polymeric substance contents were significantly increased in aerobic granules exposed to CLX. The shifts of fluorescence intensities and peak locations in 3D-EEM fluorescence spectra indicated changes of EPS components. High-throughput sequencing analysis showed aerobic granules with CLX addition in synthetic wastewater had superior diversity of microbial species, and this was the reason that the level and components of EPS changed. The species richness for bacteria was increased from 341 to 352, which was revealed by Chao1. The Shannon index of diversity rose slightly from 3.59 to 3.73 with CLX addition. The abundance of Proteobacteria significantly decreased, while the abundance of Bacteroidetes and Chloroflexi underwent a highly significant increase in aerobic granules exposed to CLX.

Predicting protein function using multiple kernels

High-throughput experimental techniques provide a wide variety of heterogeneous proteomic data sources. To exploit the information spread across multiple sources for protein function prediction, these data sources are transformed into kernels and then integrated into a composite kernel. Several methods first optimize the weights on these kernels to produce a composite kernel, and then train a classifier on the composite kernel. As such, these approaches result in an optimal composite kernel, but not necessarily in an optimal classifier. On the other hand, some approaches optimize the loss of binary classifiers and learn weights for the different kernels iteratively. For multi-class or multi-label data, these methods have to solve the problem of optimizing weights on these kernels for each of the labels, which are computationally expensive and ignore the correlation among labels. In this paper, we propose a method called Predicting Protein Function using Multiple K ernels (ProMK). ProMK iteratively optimizes the phases of learning optimal weights and reduces the empirical loss of multi-label classifier for each of the labels simultaneously. ProMK can integrate kernels selectively and downgrade the weights on noisy kernels. We investigate the performance of ProMK on several publicly available protein function prediction benchmarks and synthetic datasets. We show that the proposed approach performs better than previously proposed protein function prediction approaches that integrate multiple data sources and multi-label multiple kernel learning methods. The codes of our proposed method are available at https://sites.google.com/site/guoxian85/promk.

Quantitative secondary electron imaging for work function extraction at atomic level and layer identification of graphene

Two-dimensional (2D) materials usually have a layer-dependent work function, which require fast and accurate detection for the evaluation of their device performance. A detection technique with high throughput and high spatial resolution has not yet been explored. Using a scanning electron microscope, we have developed and implemented a quantitative analytical technique which allows effective extraction of the work function of graphene. This technique uses the secondary electron contrast and has nanometre-resolved layer information. The measurement of few-layer graphene flakes shows the variation of work function between graphene layers with a precision of less than 10 meV. It is expected that this technique will prove extremely useful for researchers in a broad range of fields due to its revolutionary throughput and accuracy.

Allergic asthma exhaled breath metabolome: a challenge for comprehensive two-dimensional gas chromatography

Allergic asthma represents an important public health issue, most common in the paediatric population, characterized by airway inflammation that may lead to changes in volatiles secreted via the lungs. Thus, exhaled breath has potential to be a matrix with relevant metabolomic information to characterize this disease. Progress in biochemistry, health sciences and related areas depends on instrumental advances, and a high throughput and sensitive equipment such as comprehensive two-dimensional gas chromatography–time of flight mass spectrometry (GC × GC–ToFMS) was considered. GC × GC–ToFMS application in the analysis of the exhaled breath of 32 children with allergic asthma, from which 10 had also allergic rhinitis, and 27 control children allowed the identification of several hundreds of compounds belonging to different chemical families. Multivariate analysis, using Partial Least Squares-Discriminant Analysis in tandem with Monte Carlo Cross Validation was performed to assess the predictive power and to help the interpretation of recovered compounds possibly linked to oxidative stress, inflammation processes or other cellular processes that may characterize asthma. The results suggest that the model is robust, considering the high classification rate, sensitivity, and specificity. A pattern of six compounds belonging to the alkanes characterized the asthmatic population: nonane, 2,2,4,6,6-pentamethylheptane, decane, 3,6-dimethyldecane, dodecane, and tetradecane. To explore future clinical applications, and considering the future role of molecular-based methodologies, a compound set was established to rapid access of information from exhaled breath, reducing the time of data processing, and thus, becoming more expedite method for the clinical purposes.

Classificação Automática de Modulação Digital com uso de Correntropia para Ambientes de Rádio Cognitivo

Modern wireless systems employ adaptive techniques to provide high throughput while observing desired coverage, Quality of Service (QoS) and capacity. An alternative to further enhance data rate is to apply cognitive radio concepts, where a system is able to exploit unused spectrum on existing licensed bands by sensing the spectrum and opportunistically access unused portions. Techniques like Automatic Modulation Classification (AMC) could help or be vital for such scenarios. Usually, AMC implementations rely on some form of signal pre-processing, which may introduce a high computational cost or make assumptions about the received signal which may not hold (e.g. Gaussianity of noise). This work proposes a new method to perform AMC which uses a similarity measure from the Information Theoretic Learning (ITL) framework, known as correntropy coefficient. It is capable of extracting similarity measurements over a pair of random processes using higher order statistics, yielding in better similarity estimations than by using e.g. correlation coefficient. Experiments carried out by means of computer simulation show that the technique proposed in this paper presents a high rate success in classification of digital modulation, even in the presence of additive white gaussian noise (AWGN)

Estudo da hidrodinâmica de um novo separador líquido-líquido: aplicação ao sistema óleo-bruto/água produzida

This work aims to use a different hydrodynamic condition applied to a new design of mixer-settler on treating wastewater produced by petroleum industry, called MDIF (Misturador-Decantador à Inversão de Fases/ Mixer-Settler based on Phase Inversion MSPI). The use of this different hydrodynamic behaviour is possible due to vertical disposition of the device and the principle of Phase Inversion that controls the MDIF, providing the generation (creation) of a cascade of drops, into an organic layer, that works as micro-decanters, thus making possible the formation of a bed of non-coalesced drops, called Bed Formation . The use of this new hydrodynamics condition allows to increase the residence time of the oil carrier drops, into an organic layer, and the device can treat a greater volume of wastewater. In view of to get this condition it is necessary to operate at high throughput (58,6 m3.m-2.h-1). By results, the condition of Bed Formation is the best one to be used when MSPI operates with throughput up to 58,6 m3.m-2.h-1. The results using the condition of Bed Formation show that increasing the height of the bed of non-coalesced drops and/or decreasing the volumetric ratio (O/A) an increase of the separation efficiency is detected

Interspecific fish hybrids in Brazil: management of genetic resources for sustainable use

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Synchrotron X-ray powder diffraction data of atorvastatin

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimation of outcrossing rate in a breeding population of Eucalyptus urophylla with dominant RAPD and AFLP markers

Eucalyptus breeding is typically conducted by selection in open-pollinated progenies. As mating is controlled only on the female side of the cross, knowledge of outcrossing versus selling rates is essential for maintaining adequate levels of genetic variability for continuous gains. Outcrossing rate in an open-pollinated breeding population of Eucalyptus urophylla was estimated by two PCR-based dominant marker technologies, RAPD and AFLP, using 11 open-pollinated progeny arrays of 24 individuals. Estimated outcrossing rates indicate predominant outcrossing and suggest maintenance of adequate genetic variability within families. The multilcous outcrossing rate (t(m)) estimated from RAPD markers (0.93 +/- 0.027), although in the same range, was higher (alpha > 0.01) than the estimate based on AFLP (0.89 +/- 0.033). Both estimates were of similar magnitude to those estimated for natural populations using isozymes. The estimated Wright's fixation index was lower than expected based on t, possibly resulting from selection against selfed seedlings when sampling plants for the study. An empirical analysis suggests that 18 is the minimum number of dominant marker loci necessary to achieve robust estimates of t,. This study demonstrates the usefulness of dominant markers, both RAPD and AFLP, for estimating the outcrossing rate in breeding and natural populations of forest trees. We anticipate an increasing use of such PCR-based technologies in mating-system studies, in view of their high throughput and universality of the reagents, particularly for species where isozyme systems have not yet been optimized.

Combinatorial synthesis and directed evolution applied to the production of alpha-helix forming antimicrobial peptides analogues

Antimicrobial peptides (AMPs) are effector molecules of innate immune systems found in different groups of organisms, including microorganisms, plants, insects, amphibians and humans. These peptides exhibit several structural motifs but the most abundant AMPs assume an amphipathic alpha-helical structure. The alpha-helix forming antimicrobial peptides are excellent candidates for protein engineering leading to an optimization of their biological activity and target specificity. Nowadays several approaches are available and this review deals with the use of combinatorial synthesis and directed evolution in order to provide a high-throughput source of antimicrobial peptides analogues with enhanced lytic activity and specificity.

Gene discovery in Boophilus microplus, the cattle tick - the transcriptomes of ovaries, salivary glands, and hemocytes

The quest for new control strategies for ticks can profit from high throughput genomics. In order to identify genes that are involved in oogenesis and development, in defense, and in hematophagy, the transcriptomes of ovaries, hemocytes, and salivary glands from rapidly ingurgitating females, and of salivary glands from males of Boophilus microplus were PCR amplified, and the expressed sequence tags (EST) of random clones were mass sequenced. So far, more than 1,344 EST have been generated for these tissues, with approximately 30% novelty, depending on the the tissue studied. To date approximately 760 nucleotide sequences from B. microplus are deposited in the NCBI database. Mass sequencing of partial cDNAs of parasite genes can build up this scant database and rapidly generate a large quantity of useful information about potential targets for immunobiological or chemical control.

A Simple Method Based on ICP-MS for Estimation of Background Levels of Arsenic, Cadmium, Copper, Manganese, Nickel, Lead, and Selenium in Blood of the Brazilian Population

Throughout the world, biomonitoring has become the standard for assessing exposure of individuals to toxic elements as well as for responding to serious environmental public health problems. However, extensive biomonitoring surveys require rapid and simple analytical methods. Thus, a simple and high-throughput method is proposed for the determination of arsenic (As), cadmium (Cd), copper (Cu), manganese (Mn), nickel (Ni), lead (Pb), and selenium (Se) in blood samples by using inductively coupled plasma-mass spectrometry (ICP-MS). Prior to analysis, 200 l of blood samples was mixed with 500 l of 10% v/v tetramethylammonium hydroxide (TMAH) solution, incubated for 10 min, and subsequently diluted to 10 ml with a solution containing 0.05% w/v ethylenediamine tetraacetic acid (EDTA) + 0.005% v/v Triton X-100. After that, samples were directly analyzed by ICP-MS (ELAN DRC II). Rhodium was selected as an internal standard with matrix-matching calibration. Method detection limits were 0.08, 0.04, 0.5, 0.09, 0.12, 0.04, and 0.1 g//L for As, Cd, Cu, Mn, Ni, Pb, and Se, respectively. Validation data are provided based on the analysis of blood samples from the trace elements inter-\comparison program operated by the Institut National de Sante Publique du Quebec, Canada. Additional validation was provided by the analysis of human blood samples by the proposed method and by using electrothermal atomic absorption spectrometry (ETAAS). The method was subsequently applied for the estimation of background metal blood values in the Brazilian population. In general, the mean concentrations of As, Cd, Cu, Mn, Ni, Pb, and Se in blood were 1.1, 0.4, 890, 9.6, 2.1, 65.4, and 89.3 g/L, respectively, and are in agreement with other global populations. Influences of age, gender, smoking habits, alcohol consumption, and geographical variation on the values were also considered. Smoking habits influenced the levels of Cd in blood. The levels of Cu, Mn, and Pb were significantly correlated with gender, whereas Cu and Pb were significantly correlated with age. There were also interesting differences in Mn and Se levels in the population living in the north of Brazil compared to the south.

PrimerSNP: a web tool for whole-genome selection of allele-specific and common primers of phylogenetically-related bacterial genomic sequences

Background: The increasing number of genomic sequences of bacteria makes it possible to select unique SNPs of a particular strain/species at the whole genome level and thus design specific primers based on the SNPs. The high similarity of genomic sequences among phylogenetically-related bacteria requires the identification of the few loci in the genome that can serve as unique markers for strain differentiation. PrimerSNP attempts to identify reliable strain-specific markers, on which specific primers are designed for pathogen detection purpose.Results: PrimerSNP is an online tool to design primers based on strain specific SNPs for multiple strains/species of microorganisms at the whole genome level. The allele-specific primers could distinguish query sequences of one strain from other homologous sequences by standard PCR reaction. Additionally, PrimerSNP provides a feature for designing common primers that can amplify all the homologous sequences of multiple strains/species of microorganisms. PrimerSNP is freely available at http://cropdisease.ars.usda.gov/similar to primer.Conclusion: PrimerSNP is a high-throughput specific primer generation tool for the differentiation of phylogenetically-related strains/species. Experimental validation showed that this software had a successful prediction rate of 80.4 - 100% for strain specific primer design.

Utilização do alcohol use disorders identification test (Audit) para identificação do consumo de álcool entre estudantes do ensino médio

Alcohol is one of the drugs most widely used among teenagers. Just recently, studies have been developed regarding the screening of use of alcohol by this population. This work aimed to investigate the use of AUDIT as a method for screening and evaluation of alcohol consumption among High School students. The sample was composed by 1227 students from two public schools, who answered to the Alcohol Use Disorders Identification Test (AUDIT) and informed their socioeconomic level, religion, and occurrence of relationship problems caused by drunkenness of family members. Using an 8 cut-off point, AUDIT has identified 17.8% of students with risk drinking. These results have revealed that AUDIT is easy to be applied and well accepted by the students. It was also evident the importance of this instrument in the follow-up programs of prevention and intervention of alcoholic beverages use.