Separating the wheat from the chaff: unbiased filtering of background tandem mass spectra improves protein identification

Only a small fraction of spectra acquired in LC-MS/MS runs matches peptides from target proteins upon database searches. The remaining, operationally termed background, spectra originate from a variety of poorly controlled sources and affect the throughput and confidence of database searches. Here, we report an algorithm and its software implementation that rapidly removes background spectra, regardless of their precise origin. The method estimates the dissimilarity distance between screened MS/MS spectra and unannotated spectra from a partially redundant background library compiled from several control and blank runs. Filtering MS/MS queries enhanced the protein identification capacity when searches lacked spectrum to sequence matching specificity. In sequence-similarity searches it reduced by, on average, 30-fold the number of orphan hits, which were not explicitly related to background protein contaminants and required manual validation. Removing high quality background MS/MS spectra, while preserving in the data set the genuine spectra from target proteins, decreased the false positive rate of stringent database searches and improved the identification of low-abundance proteins.

Identification of the nuclear factor kappa-beta (NF-kB) in cortical of mice Wistar using Technovit 7200 VCR (R)

Objective: this study aimed to develop a nondecalcified bone sample processing technique enabling immunohistochemical labeling of proteins by kappa-beta nuclear factor (NF-kB) utilizing the Technovit 7200 VCR (R) in adult male Wistar rats. Study Method: A 1.8 mm diameter defect was performed 0.5mm from the femur proximal joint by means of a round bur. Experimental groups were divided according to fixing solution prior to histologic processing: Group 1- ethanol 70%; Group 2-10% buffered formalin; and Group 3- Glycerol diluted in 70% ethanol at a 70/30 ratio + 10% buffered formalin. The post-surgical periods ranged from 01 to 24 hours. Control groups included a nonsurgical procedure group (NSPG) and surgical procedures where bone exposure was performed (SPBE) without drilling. Prostate carcinoma was the positive control (PC) and samples subjected to incomplete immunohistochemistry protocol were the negative control (NC). Following euthanization, all samples were kept at 4 degrees C for 7 days, and were dehydrated in a series of alcohols at -20 degrees C. The polymer embedding procedure was performed at ethanol/polymer ratios of 70%-30%, 50%-50%, 30%-70%, 100%, and 100% for 72 hours at -20 degrees C. Polymerization followed the manufacturer`s recommendation. The samples were grounded and polished to 10-15 mu m thickness, and were deacrylated. The sections were rehydrated and were submitted to the primary polyclonal antibody anti-NF-kB on a 1:75 dilution for 12 hours at room temperature. Results: Microscopy showed that the Group 2 presented positive reaction to NF-kB, diffuse reactions for NSPG and SPBE, and no reaction for the NC group. Conclusion: The results obtained support the feasibility of the developed immunohistochemistry technique.

Identification of enteropathogenic and enterohaemorrhagic Escherichia coli strains by immunoserological detection of intimin

Aims: To evaluate the sensitivity and specificity of polyclonal and monoclonal antibodies (Mabs) against intimin in the detection of enteropathogenic and enterohaemorrhagic Escherichia coli isolates using immunoblotting. Methods and Results: Polyclonal and Mabs against the intimin-conserved region were raised, and their reactivities were compared in enteropathogenic E. coli (EPEC) and enterohaemorrhagic E. coli (EHEC) isolates using immunoblotting analysis. In comparison with rat antiserum, rabbit anti-intimin IgG-enriched fraction had a stronger recognition pattern to a wide spectrum of intimin types in different EPEC and EHEC serotypes. On the other hand, murine monoclonal IgG2b specific to intimin, with dissociation constant of 1 center dot 3 x 10-8 mol l-1, failed in the detection of some of these isolates. Conclusion: All employed antibodies showed 100% specificity, not reacting with any of the eae-negative isolates. The sensitivity range was according to the employed antisera, and 97% for rabbit anti-intimin IgG-enriched fraction, followed by 92% and 78% sensitivity with rat antisera and Mab. Significance and Impact of the Study: The rabbit anti-intimin IgG-enriched fraction in immunoblotting analysis is a useful tool for EPEC and EHEC diagnoses.

Identification and lineage genotyping of South American trypanosomes using fluorescent fragment length barcoding

Trypanosoma cruzi and Trypanosoma rangeli are human-infective blood parasites, largely restricted to Central and South America. They also infect a wide range of wild and domestic mammals and are transmitted by a numerous species of triatomine bugs. There are significant overlaps in the host and geographical ranges of both species. The two species consist of a number of distinct phylogenetic lineages. A range of PCR-based techniques have been developed to differentiate between these species and to assign their isolates into lineages. However, the existence of at least six and five lineages within T. cruzi and T. rangeli, respectively, makes identification of the full range of isolates difficult and time consuming. Here we have applied fluorescent fragment length barcoding (FFLB) to the problem of identifying and genotyping T. cruzi, T. rangeli and other South American trypanosomes. This technique discriminates species on the basis of length polymorphism of regions of the rDNA locus. FFLB was able to differentiate many trypanosome species known from South American mammals: T. cruzi cruzi. T. cruzi marinkellei, T. dionisii-like, T. evansi, T. lewisi, T. rangeli, T. theileri and T. vivax. Furthermore, all five T. rangeli lineages and many T. cruzi lineages could be identified, except the hybrid lineages TcV and TcVI that could not be distinguished from lineages III and II respectively. This method also allowed identification of mixed infections of T. cruzi and T. rangeli lineages in naturally infected triatomine bugs. The ability of FFLB to genotype multiple lineages of T. cruzi and T. rangeli together with other trypanosome species, using the same primer sets is an advantage over other currently available techniques. Overall, these results demonstrate that FFLB is a useful method for species diagnosis, genotyping and understanding the epidemiology of American trypanosomes. (C) 2010 Elsevier B.V. All rights reserved.

Development of molecular assays for the identification of the 11 Eimeria species of the domestic rabbit (Oryctolagus cuniculus)

Coccidiosis are the major parasitic diseases in poultry and other domestic animals including the domestic rabbit (Oryctolagus cuniculus). Eleven distinct Eimeria species have been identified in this host, but no PCR-based method has been developed so far for unequivocal species differentiation. In this work, we describe the development of molecular diagnostic assays that allow for the detection and discrimination of the 11 Eimeria species that infect rabbits. We determined the nucleotide sequences of the ITS1 ribosomal DNAs and designed species-specific primers for each species. We performed specificity tests of the assays using heterologous sets of primers and DNA samples, and no cross-specific bands were observed. We obtained a detection limit varying from 500 fg to 1 pg, which corresponds approximately to 0.8-1.7 sporulated oocysts, respectively. The test reported here showed good reproducibility and presented a consistent sensitivity with three different brands of amplification enzymes. These novel diagnostic assays will permit population surveys to be performed with high sensitivity and specificity, thus contributing to a better understanding of the epidemiology of this important group of coccidian parasites. (C) 2010 Elsevier B.V. All rights reserved.

Interactive Vector Field Feature Identification

We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features within the vector field may be spatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation of attributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enable interactive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field points within the distances computed between their associated attribute points. The proposed method is performed at interactive rates for enhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.

Experimental identification of chaotic fibers

In a 2D parameter space, by using nine experimental time series of a Clitia`s circuit, we characterized three codimension-1 chaotic fibers parallel to a period-3 window. To show the local preservation of the properties of the chaotic attractors in each fiber, we applied the closed return technique and two distinct topological methods. With the first topological method we calculated the linking, numbers in the sets of unstable periodic orbits, and with the second one we obtained the symbolic planes and the topological entropies by applying symbolic dynamic analysis. (C) 2007 Elsevier Ltd. All rights reserved.

PLANT LEAF IDENTIFICATION BASED ON VOLUMETRIC FRACTAL DIMENSION

Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.

Plant Leaf Identification Using Gabor Wavelets

This article presents a novel method of plant classification using Gabor wavelet filters to extract texture filters in a foliar surface. The aim of this promising method is to add to the results obtained by other leaf attributes (such as shape, contour, color, among others), increasing, therefore, the percentage of classification of plant species. To corroborate the efficiency of the technique, an experiment using 20 species from Brazilian flora was done and discussed. The results are also compared with texture Fourier descriptors and cooccurrence matrices. (C) 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 236-243, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20201

A powder X-ray diffraction method for detection of polyprenylated benzophenones in plant extracts associated with HPLC for quantitative analysis

A robust, direct, rapid and non-destructive X-ray diffraction crystallography method to detect the polyprenylated benzophenones 7-epi-clusianone (1) and guttiferone A (2) in extracts from Garcinia brasiliensis is presented. Powder samples of benzophenones 1 and 2, dried hexane extracts from G. brasiliensis seeds and fruit`s pericarp, and the dried ethanolic extract from G. brasiliensis seeds were unambiguously characterized by powder X-ray diffractometry. The calculated X-ray diffraction peaks from crystal structures of analytes 1 and 2, previously determined by single-crystal X-ray diffraction technique, were overlaid to those of the experimental powder diffractograms, providing a practical identification of these compounds in the analyzed material and confirming the pure contents of the powder samples. Using the X-ray diffraction crystallography method, the studied polyprenylated benzophenones were selectively and simultaneously detected in the extracts which were mounted directly on sample holder. In addition, reference materials of the analytes were not required for analyses since the crystal structures of the compounds are known. High performance liquid chromatography analyses also were comparatively carried out to quantify the analytes in the same plant extracts showing to be in agreement with X-ray diffraction crystallography method. (C) 2010 Elsevier B.V. All rights reserved.

Electroanalytical Method for the Analysis of Methyldopa In Pharmaceutical Tablets Using a Crude Extract of Laccase from Pycnoporus sanguineus as Oxidizing Agent

Several colorimetric and chromatographic methods have been used for the identification and quantification of methyldopa (MA) in pharmaceutical formulations and clinical samples. However, these methods are time- and reagent-consuming, which stimulated our efforts to develop a simple, fast, and low-cost alternative method. We carried out an electroanalytical method for the determination of MA in pharmaceutical formulations using the crude enzymatic extract of laccase from Pycnoporus sanguineus as oxidizing agent. This method is based on the biochemical oxidation of MA by laccase (LAC), both in solution, followed by electrochemical reduction on glassy carbon electrode surface. This method was employed for the determination of MA in pure and pharmaceutical formulations and compared with the results obtained using the official method. A wide linear curve from 23 x 10(-5) to 1 x 10(-4) mol L(-1) was found with a detection limit calculated from 43 x 10(-6) mol L(-1).

Identification of cause of impairment in spiral drawings, using non-stationary feature extraction approach

Parkinson’s disease is a clinical syndrome manifesting with slowness and instability. As it is a progressive disease with varying symptoms, repeated assessments are necessary to determine the outcome of treatment changes in the patient. In the recent past, a computer-based method was developed to rate impairment in spiral drawings. The downside of this method is that it cannot separate the bradykinetic and dyskinetic spiral drawings. This work intends to construct the computer method which can overcome this weakness by using the Hilbert-Huang Transform (HHT) of tangential velocity. The work is done under supervised learning, so a target class is used which is acquired from a neurologist using a web interface. After reducing the dimension of HHT features by using PCA, classification is performed. C4.5 classifier is used to perform the classification. Results of the classification are close to random guessing which shows that the computer method is unsuccessful in assessing the cause of drawing impairment in spirals when evaluated against human ratings. One promising reason is that there is no difference between the two classes of spiral drawings. Displaying patients self ratings along with the spirals in the web application is another possible reason for this, as the neurologist may have relied too much on this in his own ratings.

LiLEDDA – a six step forum-based netnographic research method for nursing and caring sciences

Internet research methods in nursing science are less developed than in other sciences. We choose to present an approach to conducting nursing research on an internet-based forum. This paper presents LiLEDDA, a six-step forum-based netnographic research method for nursing science. The steps consist of: 1. Literature review and identification of the research question(s); 2. Locating the field(s) online; 3. Ethical considerations; 4. Data gathering; 5. Data analysis and interpretation; and 6. Abstractions and trustworthiness. Traditional research approaches are limiting when studying non-normative and non-mainstream life-worlds and their cultures. We argue that it is timely to develop more up-to-date research methods and study designs applicable to nursing science that reflect social developments and human living conditions that tend to be increasingly online-based.

An Agent-Based Approach to Real-Time Patient Identification for Clinical Trials

Patient recruitment for clinical trials is expensive and has been a significant challenge, with many trials not achieving their recruitment goals. One method that shows promise for improving recruitment is the use of interactive prompts that inform practitioners of patient eligibility for clinical trials during consultation. This paper presents the ePCRN-IDEA recruitment system, which utilises an agent-based infrastructure to enable real-time recruitment of patients. In essence, whenever patients enter a clinic, the system compares their details against eligibility criteria, which define the requirements of active clinical trials. If a patient is found to be eligible, a prompt is raised to notify the user. In this way, it becomes possible for recruitment to take place quickly in a cost effective manner, whilst maintaining patient trust through the involvement of their own health care practitioner.

A Gradient-Type Method For Real-Time State Estimation Of Water Distribution Networks

Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.