Quantitative multiplexed strategies for human Lyme disease serological testing

Lyme disease, which is primarily caused by infection with the bacterium Borrelia burgdorferi in the United States or other Borrelia species internationally, presents an ongoing challenge for diagnostics. Serological testing is the primary means of diagnosis but testing approaches differ widely, with varying degrees of sensitivity and specificity. Moreover, there is currently no reliable test to determine disease resolution following treatment. A distinct challenge in Lyme disease diagnostics is the variable patterns of human immune response to a plurality of antigens presented by Borrelia spp. during the infection. Thus, multiplexed testing approaches that capture these patterns and detect serological response against multiple antigens may be the key to prompt, accurate Lyme disease diagnosis. In this review, current state-of-the-art multiplexed diagnostic approaches are presented and compared with respect to their diagnostic accuracy and their potential for monitoring response to treatment.     

Molecular taxonomic identification in the absence of a ‘barcoding gap’: a test with the endemic flora of the Canarian oceanic hotspot

We use a comprehensive subset of Canarian angiosperms corresponding to 23 families, 35 genera and 60 Canarian endemic taxa to test whether this flora is suitable to taxonomic identification with the two proposed plant DNA barcode sequences and whether these sequences may reveal the existence of cryptic species overlooked by morphology. The rate of discrimination success between the insular congeneric samples using the rbcL+matK combination and a ‘character‐based’ approach (where we use only the combination of nucleotide positions in an alignment that allows unambiguous species identification) is higher (82.29%) than that obtained with the ‘distance‐based’ approach (80.20%) used by the CBOL Plant Working Group in 2009 and also when compared with tests conducted in other floras. This suggests that the molecular identification of the Canarian endemic flora can be achieved as successfully as in other floras where the incidence of radiation is not as relevant. The facts that (i) a distance‐based criterion was unable to discriminate between congeneric and conspecific comparisons and (ii) only the character‐based discrimination criterion resolved cases that the distance‐based criterion did not, further support the use of a character discrimination approach for a more efficient DNA barcoding of floras from oceanic islands like the Canaries. Thus, a barcoding gap seems not to be necessary for the correct molecular characterization of the Canarian flora. DNA barcodes also suggest the possible existence of cryptic taxa to be further investigated by morphology and that the current taxonomic status of some of the taxa analysed may need revision.     

Evaluation of accuracy of fine needle aspiration cytology in BI‐RADS3 category breast lesions: cytohistological correlation in 337 cases

C. Engohan‐Aloghe, N. Hottat, J. Cosaert, R. Boutemy, I. Fayt and J.‐C. Noël
Evaluation of accuracy of fine needle aspiration cytology in BI‐RADS3 category breast lesions: cytohistological correlation in 337 cases Objective: To evaluate the accuracy of fine needle aspiration cytology (FNAC) in BI‐RADS3 breast lesions. Methods: Between January 2004 and December 2007, 337 cases from BI‐RADS3 lesions underwent FNAC. Three to six needle passes were made on each patient. In 67 cases (20%) a histological biopsy was performed. Cytological and histological interpretations were performed by the same pathologist. Results: The histological diagnosis showed that 88% (59/67) of BI‐RADS3 breast lesions were benign. Only 6% (4/67) were malignant, consisting of ductal carcinoma in situ and infiltrating ductal carcinoma. Conclusion: BI‐RADS3 lesions remain disruptive in their management. However, the correlation between cytology and histology showed that most of these lesions were benign and that finally FNAC remains a useful and accurate test in the management of these lesions.     

A Bayesian Chi‐Squared Goodness‐of‐Fit Test for Censored Data Models

Summary We propose a Bayesian chi‐squared model diagnostic for analysis of data subject to censoring. The test statistic has the form of Pearson's chi‐squared test statistic and is easy to calculate from standard output of Markov chain Monte Carlo algorithms. The key innovation of this diagnostic is that it is based only on observed failure times. Because it does not rely on the imputation of failure times for observations that have been censored, we show that under heavy censoring it can have higher power for detecting model departures than a comparable test based on the complete data. In a simulation study, we show that tests based on this diagnostic exhibit comparable power and better nominal Type I error rates than a commonly used alternative test proposed by Akritas (1988, Journal of the American Statistical Association 83, 222–230). An important advantage of the proposed diagnostic is that it can be applied to a broad class of censored data models, including generalized linear models and other models with nonidentically distributed and nonadditive error structures. We illustrate the proposed model diagnostic for testing the adequacy of two parametric survival models for Space Shuttle main engine failures.     

Potential exposure assessment errors associated with body-worn RF dosimeters

Personal exposure meters for assessing exposure to RF electric or magnetic fields are subject to errors associated with perturbations of the fields by the presence of the human body. Although these alterations are complex they are not completely unpredictable. This article concludes that this error in a common worst-case scenario could reach up to 30 dB and therefore is of concern for exposure assessment. We present several guidelines to address this issue and a useful insight into the overall problem based on finite-difference time-domain simulations and experimental verification.     

Roles of the negatively charged N-terminal extension of Saccharomyces cerevisiae ribosomal protein S5 revealed by characterization of a yeast strain containing human ribosomal protein S5

Ribosomal protein (rp) S5 belongs to a family of ribosomal proteins that includes bacterial rpS7. rpS5 forms part of the exit (E) site on the 40S ribosomal subunit and is essential for yeast viability. Human rpS5 is 67% identical and 79% similar to Saccharomyces cerevisiae rpS5 but lacks a negatively charged (pI approximately 3.27) 21 amino acid long N-terminal extension that is present in fungi. Here we report that replacement of yeast rpS5 with its human homolog yielded a viable yeast strain with a 20%-25% decrease in growth rate. This replacement also resulted in a moderate increase in the heavy polyribosomal components in the mutant strain, suggesting either translation elongation or termination defects, and in a reduction in the polyribosomal association of the elongation factors eEF3 and eEF1A. In addition, the mutant strain was characterized by moderate increases in +1 and -1 programmed frameshifting and hyperaccurate recognition of the UAA stop codon. The activities of the cricket paralysis virus (CrPV) IRES and two mammalian cellular IRESs (CAT-1 and SNAT-2) were also increased in the mutant strain. Consistently, the rpS5 replacement led to enhanced direct interaction between the CrPV IRES and the mutant yeast ribosomes. Taken together, these data indicate that rpS5 plays an important role in maintaining the accuracy of translation in eukaryotes and suggest that the negatively charged N-terminal extension of yeast rpS5 might affect the ribosomal recruitment of specific mRNAs.     

Comparative analysis of genetic relationship and diagnostic markers of several taxa of Guizotia Cass. (Asteraceae) as revealed by AFLPs and RAPDs

Amplified fragment length polymorphism (AFLP) and random amplified polymorphic DNA (RAPD) were employed to examine the genetic relationship between Guizotia taxa, to suggest the taxonomic status of some of these taxa, and to identify their diagnostic markers. Results from AFLPs and RAPDs share some features in common, both revealing G. scabra ssp. schimperi as the most closely related taxon to G. abyssinica, and indicating that G. arborescens and G. zavattarii are the most divergent taxa. Most of the diagnostic markers revealed in this study were specific to G. arborescens and G. zavattarii. Our analysis suggests that G. scabra ssp. scabra, G. scabra ssp. schimperi, Chelelu and Ketcha are separate species. In this study, AFLP was found to be superior to RAPD in detecting genetic variation, in internal consistency of the data and in the fitness of its clusters to genetic similarity data. AFLPs revealed genetic relationship between Guizotia taxa that is more inline with the cytogenetic and hybridization studies than that revealed by RAPDs.     

What is the Value of a Good Map? An Example Using High Spatial Resolution Imagery to Aid Riparian Restoration

Riparian areas contain structurally diverse habitats that are challenging to monitor routinely and accurately over broad areas. As the structural variability within riparian areas is often indiscernible using moderate-scale satellite imagery, new mapping techniques are needed. We used high spatial resolution satellite imagery from the QuickBird satellite to map harvested and intact forests in coastal British Columbia, Canada. We distinguished forest structural classes used in riparian restoration planning, each with different restoration costs. To assess the accuracy of high spatial resolution imagery relative to coarser imagery, we coarsened the pixel resolution of the image, repeated the classifications, and compared results. Accuracy assessments produced individual class accuracies ranging from 70 to 90% for most classes; whilst accuracies obtained using coarser scale imagery were lower. We also examined the implications of map error on riparian restoration budgets derived from our classified maps. To do so, we modified the confusion matrix to create a cost error matrix quantifying costs associated with misclassification. High spatial resolution satellite imagery can be useful for riparian mapping; however, errors in restoration budgets attributable to misclassification error can be significant, even when using highly accurate maps. As the spatial resolution of imagery increases, it will be used more routinely in ecosystem ecology. Thus, our ability to evaluate map accuracy in practical, meaningful ways must develop further. The cost error matrix is one method that can be adapted for conservation and planning decisions in many ecosystems.