RAId_aPS: MS/MS analysis with multiple scoring functions and spectrum-specific statistics

Statistically meaningful comparison/combination of peptide identification results from various search methods is impeded by the lack of a universal statistical standard. Providing an E-value calibration protocol, we demonstrated earlier the feasibility of translating either the score or heuristic E-value reported by any method into the textbook-defined E-value, which may serve as the universal statistical standard. This protocol, although robust, may lose spectrum-specific statistics and might require a new calibration when changes in experimental setup occur. To mitigate these issues, we developed a new MS/MS search tool, RAId_aPS, that is able to provide spectrum-specific E-values for additive scoring functions. Given a selection of scoring functions out of RAId score, K-score, Hyperscore and XCorr, RAId_aPS generates the corresponding score histograms of all possible peptides using dynamic programming. Using these score histograms to assign E-values enables a calibration-free protocol for accurate significance assignment for each scoring function. RAId_aPS features four different modes: (i) compute the total number of possible peptides for a given molecular mass range, (ii) generate the score histogram given a MS/MS spectrum and a scoring function, (iii) reassign E-values for a list of candidate peptides given a MS/MS spectrum and the scoring functions chosen, and (iv) perform database searches using selected scoring functions. In modes (iii) and (iv), RAId_aPS is also capable of combining results from different scoring functions using spectrum-specific statistics. The web link is http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/raid_aps/index.html. Relevant binaries for Linux, Windows, and Mac OS X are available from the same page.Comment: 34 pages, 10 figures, 1 supplementary information file (RAId_aPS_support.pdf). To view the supplementary file, please download and extract the gzipped tar source file listed under "Other formats

Influence of dental metallic artifact from multislice CT in the assessment of simulated mandibular lesions

OBJECTIVE: This study evaluated the influence of metallic dental artifacts on the accuracy of simulated mandibular lesion detection by using multislice technology. MATERIAL AND METHODS: Fifteen macerated mandibles were used. Perforations were done simulating bone lesions and the mandibles were subjected to axial 16 rows multislice CT images using 0.5 mm of slice thickness with 0.3 mm interval of reconstruction. Metallic dental restorations were done and the mandibles were subjected again to CT in the same protocol. The images were analyzed to detect simulated lesions in the mandibles, verifying the loci number and if there was any cortical perforation exposing medullar bone. The analysis was performed by two independent examiners using e-film software. RESULTS: The samples without artifacts presented better results compared to the gold standard (dried mandible with perforations). In the samples without artifacts, all cortical perforation were identified and 46 loci were detected (of 51) in loci number analysis. Among the samples with artifacts, 12 lesions out of 14 were recognized regarding medullar invasion, and 40 out of 51 concerning loci number. The sensitivity in samples without artifacts was 90% and 100% regarding loci number and medullar invasion, respectively. In samples with artifacts, these values dropped to 78% and 86%, respectively. The presence of metallic restorations affected the sensitivity values of the method, but the difference was not significant (p>0.05). CONCLUSIONS: Although there were differences in the results of samples with and without artifacts, the presence of metallic restoration did not lead to misinterpretation of the final diagnosis. However, the validity of multislice CT imaging in this study was established for detection of simulated mandibular bone lesions.CNPqFAPESPCoordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES

Modified Alvarado Scoring System as a diagnostic tool for Acute Appendicitis at Bugando Medical Centre, Mwanza, Tanzania

<p>Abstract</p> <p>Background</p> <p>Decision-making in patients with acute appendicitis poses a diagnostic challenge worldwide, despite much advancement in abdominal surgery. The Modified Alvarado Scoring System (MASS) has been reported to be a cheap and quick diagnostic tool in patients with acute appendicitis. However, differences in diagnostic accuracy have been observed if the scores were applied to various populations and clinical settings. The purpose of this study was to evaluate the diagnostic value of Modified Alvarado Scoring System in patients with acute appendicitis in our setting.</p> <p>Methods</p> <p>A cross-sectional study involving all patients suspected to have acute appendicitis at Bugando Medical Centre over a six-month period between November 2008 and April 2009 was conducted. All patients who met the inclusion criteria were consecutively enrolled in the study. They were evaluated on admission using the MASS to determine whether they had acute appendicitis or not. All patients underwent appendicectomy according to the hospital protocol. The decision to operate was the prerogative of the surgeon or surgical resident based on overall clinical judgment and not the MASS. The diagnosis was confirmed by histopathological examination. Data was collected using a pre-tested coded questionnaire and analyzed using SPSS statistical computer software.</p> <p>Results</p> <p>A total number of 127 patients were studied. Their ages ranged from eight to 76 years (mean 29.64 ± 12.97). There were 37 (29.1%) males and 90 (70.9%) females (M: F = 1:2.4). All patients in this study underwent appendicectomy. The perforation rate was 9.4%. Histopathological examination confirmed appendicitis in 85 patients (66.9%) and the remaining 42 patients had normal appendix giving a negative appendicectomy rate of 33.1% (26.8% for males and 38.3% for females). The sensitivity and specificity of MASS in this study were 94.1% (males 95.8% and females 88.3%) and 90.4% (males 92.9% and females 89.7%) respectively. The Positive Predictive Value and Negative Predictive Value were 95.2% (males 95.5% and females 90.6%) and 88.4% (males 89.3% and females 80.1%) respectively. The accuracy of MASS was 92.9% (males 91.5% and females 87.6%).</p> <p>Conclusion</p> <p>The study shows that use of MASS in patients suspected to have acute appendicitis provides a high degree of diagnostic accuracy and can be employed at Bugando Medical Centre to improve the diagnostic accuracy of acute appendicitis and subsequently reduces negative appendicectomy and complication rates. However, additional investigations may be required to confirm the diagnosis in case of atypical presentation.</p

International Network for Comparison of HIV Neutralization Assays: The NeutNet Report II

BACKGROUND: Neutralizing antibodies provide markers for vaccine-induced protective immunity in many viral infections. By analogy, HIV-1 neutralizing antibodies induced by immunization may well predict vaccine effectiveness. Assessment of neutralizing antibodies is therefore of primary importance, but is hampered by the fact that we do not know which assay(s) can provide measures of protective immunity. An international collaboration (NeutNet) involving 18 different laboratories previously compared different assays using monoclonal antibodies (mAbs) and soluble CD4 (Phase I study). METHODS: In the present study (Phase II), polyclonal reagents were evaluated by 13 laboratories. Each laboratory evaluated nine plasmas against an 8 virus panel representing different genetic subtypes and phenotypes. TriMab, a mixture of three mAbs, was used as a positive control allowing comparison of the results with Phase I in a total of nine different assays. The assays used either uncloned virus produced in peripheral blood mononuclear cells (PBMCs) (Virus Infectivity Assays, VIA), or Env (gp160)-pseudotyped viruses (pseudoviruses, PSV) produced in HEK293T cells from molecular clones or from uncloned virus. Target cells included PBMC and genetically engineered cell lines in either single- or multiple-cycle infection format. Infection was quantified by using a range of assay read-outs including extra- or intra-cellular p24 antigen detection, luciferase, beta-galactosidase or green fluorescent protein (GFP) reporter gene expression. FINDINGS: Using TriMab, results of Phase I and Phase II were generally in agreement for six of the eight viruses tested and confirmed that the PSV assay is more sensitive than PBMC (p = 0.014). Comparisons with the polyclonal reagents showed that sensitivities were dependent on both virus and plasma. CONCLUSIONS: Here we further demonstrate clear differences in assay sensitivities that were dependent on both the neutralizing reagent and the virus. Consistent with the Phase I study, we recommend parallel use of PSV and VIA for vaccine evaluation

Modular Mass Spectrometric Tool for Analysis of Composition and Phosphorylation of Protein Complexes

The combination of high accuracy, sensitivity and speed of single and multiple-stage mass spectrometric analyses enables the collection of comprehensive sets of data containing detailed information about complex biological samples. To achieve these properties, we combined two high-performance matrix-assisted laser desorption ionization mass analyzers in one modular mass spectrometric tool, and applied this tool for dissecting the composition and post-translational modifications of protein complexes. As an example of this approach, we here present studies of the Saccharomyces cerevisiae anaphase-promoting complexes (APC) and elucidation of phosphorylation sites on its components. In general, the modular concept we describe could be useful for assembling mass spectrometers operating with both matrix-assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) ion sources into powerful mass spectrometric tools for the comprehensive analysis of complex biological samples

Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage

<p>Abstract</p> <p>Background</p> <p>HIV-1 targets human cells expressing both the CD4 receptor, which binds the viral envelope glycoprotein gp120, as well as either the CCR5 (R5) or CXCR4 (X4) co-receptors, which interact primarily with the third hypervariable loop (V3 loop) of gp120. Determination of HIV-1 affinity for either the R5 or X4 co-receptor on host cells facilitates the inclusion of co-receptor antagonists as a part of patient treatment strategies. A dataset of 1193 distinct gp120 V3 loop peptide sequences (989 R5-utilizing, 204 X4-capable) is utilized to train predictive classifiers based on implementations of random forest, support vector machine, boosted decision tree, and neural network machine learning algorithms. An <it>in silico </it>mutagenesis procedure employing multibody statistical potentials, computational geometry, and threading of variant V3 sequences onto an experimental structure, is used to generate a feature vector representation for each variant whose components measure environmental perturbations at corresponding structural positions.</p> <p>Results</p> <p>Classifier performance is evaluated based on stratified 10-fold cross-validation, stratified dataset splits (2/3 training, 1/3 validation), and leave-one-out cross-validation. Best reported values of sensitivity (85%), specificity (100%), and precision (98%) for predicting X4-capable HIV-1 virus, overall accuracy (97%), Matthew's correlation coefficient (89%), balanced error rate (0.08), and ROC area (0.97) all reach critical thresholds, suggesting that the models outperform six other state-of-the-art methods and come closer to competing with phenotype assays.</p> <p>Conclusions</p> <p>The trained classifiers provide instantaneous and reliable predictions regarding HIV-1 co-receptor usage, requiring only translated V3 loop genotypes as input. Furthermore, the novelty of these computational mutagenesis based predictor attributes distinguishes the models as orthogonal and complementary to previous methods that utilize sequence, structure, and/or evolutionary information. The classifiers are available online at <url>http://proteins.gmu.edu/automute</url>.</p