A PCR-independent approach for mtDNA enrichment and next-generation sequencing: comprehensive evaluation and clinical application.

BACKGROUND: Sequencing the mitochondrial genome has been increasingly important for the investigation of primary mitochondrial diseases (PMD) and mitochondrial genetics. To overcome the limitations originating from PCR-based mtDNA enrichment, we set out to develop and evaluate a PCR-independent approach in this study, named Pime-Seq (PCR-independent mtDNA enrichment and next generation Sequencing). RESULTS: By using the optimized mtDNA enrichment procedure, the mtDNA reads ratio reached 88.0 ± 7.9% in the sequencing library when applied on human PBMC samples. We found the variants called by Pime-Seq were highly consistent among technical repeats. To evaluate the accuracy and reliability of this method, we compared Pime-Seq with lrPCR based NGS by performing both methods simultaneously on 45 samples, yielding 1677 concordant variants, as well as 146 discordant variants with low-level heteroplasmic fraction, in which Pime-Seq showed higher reliability. Furthermore, we applied Pime-Seq on 4 samples of PMD patients retrospectively, and successfully detected all the pathogenic mtDNA variants. In addition, we performed a prospective study on 192 apparently healthy pregnant women during prenatal screening, in which Pime-Seq identified pathogenic mtDNA variants in 4 samples, providing extra information for better health monitoring in these cases. CONCLUSIONS: Pime-Seq can obtain highly enriched mtDNA in a PCR-independent manner for high quality and reliable mtDNA deep-sequencing, which provides us an effective and promising tool for detecting mtDNA variants for both clinical and research purposes.

Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety.

Even though differences in methodology (e.g., sample volume and detection method) have been shown to affect observed microbial water quality, multiple sampling and laboratory protocols continue to be used for water quality monitoring. Research is needed to determine how these differences impact the comparability of findings to generate best management practices and the ability to perform meta-analyses. This study addresses this knowledge gap by compiling and analyzing a data set representing 2,429,990 unique data points on at least one microbial water quality target (e.g., Salmonella presence and Escherichia coli concentration). Variance partitioning analysis was used to quantify the variance in likelihood of detecting each pathogenic target that was uniquely and jointly attributable to non-methodological versus methodological factors. The strength of the association between microbial water quality and select methodological and non-methodological factors was quantified using conditional forest and regression analysis. Fecal indicator bacteria concentrations were more strongly associated with non-methodological factors than methodological factors based on conditional forest analysis. Variance partitioning analysis could not disentangle non-methodological and methodological signals for pathogenic Escherichia coli, Salmonella, and Listeria. This suggests our current perceptions of foodborne pathogen ecology in water systems are confounded by methodological differences between studies. For example, 31% of total variance in likelihood of Salmonella detection was explained by methodological and/or non-methodological factors, 18% was jointly attributable to both methodological and non-methodological factors. Only 13% of total variance was uniquely attributable to non-methodological factors for Salmonella, highlighting the need for standardization of methods for microbiological water quality testing for comparison across studies.IMPORTANCEThe microbial ecology of water is already complex, without the added complications of methodological differences between studies. This study highlights the difficulty in comparing water quality data from projects that used different sampling or laboratory methods. These findings have direct implications for end users as there is no clear way to generalize findings in order to characterize broad-scale ecological phenomenon and develop science-based guidance. To best support development of risk assessments and guidance for monitoring and managing waters, data collection and methods need to be standardized across studies. A minimum set of data attributes that all studies should collect and report in a standardized way is needed. Given the diversity of methods used within applied and environmental microbiology, similar studies are needed for other microbiology subfields to ensure that guidance and policy are based on a robust interpretation of the literature.

A platform for comparing subgroup identification methodologies.

Since the advent of the phrase "subgroup identification," there has been an explosion of methodologies that seek to identify meaningful subgroups of patients with exceptional response in order to further the realization of personalized medicine. However, to perform fair comparison and understand what methods work best under different clinical trials situations, a common platform is needed for comparative effectiveness of these various approaches. In this paper, we describe a comprehensive project that created an extensive platform for evaluating subgroup identification methods as well as a publicly posted challenge that was used to elicit new approaches. We proposed a common data-generating model for creating virtual clinical trial datasets that contain subgroups of exceptional responders encompassing the many dimensions of the problem or null scenarios in which there are no such subgroups. Furthermore, we created a common scoring system for evaluating performance of purported methods for identifying subgroups. This makes it possible to benchmark methodologies in order to understand what methods work best under different clinical trial situations. The findings from this project produced considerable insights and allow us to make recommendations for how the statistical community can better compare and contrast old and new subgroup identification methodologies.

Comparison of the ELISA method with the nephelometric method for determination of serum amyloid A in patients with COVID 19.

This study aimed to examine the agreement of the serum amyloid A (SAA) values determined using the ELISA test and the nephelometric automated method. This study included 80 serum samples obtained from patients with COVID-19. Samples were determined using ELISA and the nephelometric method. Wilcoxon signed ranks test showed a statistically significant difference in the calculated median values (Z = -2.432, p = 0.015). The correlation between methods was statistically significant (r = 0.603, p < 0.0001). Bland Altman analysis showed a bias of 56.6 mg/L and a relative bias of 7.4% between the methods. The results of this study indicate that further studies are needed that will examine the compliance between the ELISA and the nephelometric method for determining SAA, and the results must be carefully interpreted based on the method used.

Comparison of five different methodologies for evaluating ankle-foot orthosis stiffness.

BACKGROUND: The mechanical properties of an ankle-foot orthosis (AFO) play an important role in the gait mechanics of the end user. However, testing methodologies for evaluating these mechanical properties are not standardized. The purpose of this study was to compare five different evaluation frameworks to assess AFO stiffness. METHOD: The same 13 carbon composite AFOs were tested with five different methods. Four previously reported custom test fixtures (the BRUCE, KST, SMApp, and EMPIRE) rotated an AFO into dorsiflexion about a defined axis in the sagittal plane. The fifth method involved quasi-static deflection of AFOs into dorsiflexion by hanging weights (HW) from the footplate. AFO rotational stiffness was calculated as the linear fit of the AFO resistive torque and angular deflection. Differences between methods were assessed using descriptive statistics and a repeated measures Friedman with post-hoc Bonferroni-Holm adjusted Wilcoxon signed-rank tests. RESULTS: There were significant differences in measured AFO stiffnesses between test methods. Specifically, the BRUCE and HW methods measured lower stiffness than both the EMPIRE and the KST. Stiffnesses measured by the SMApp were not significantly different than any test method. Stiffnesses were lowest in the HW method, where motion was not constrained to a single plane. The median difference in absolute AFO stiffness across methods was 1.03 Nm/deg with a range of [0.40 to 2.35] Nm/deg. The median relative percent difference, measured as the range of measured stiffness from the five methods over the average measured stiffness was 62% [range 13% to 156%]. When the HW method was excluded, the four previously reported test fixtures produced a median difference in absolute AFO stiffness of 0.52 [range 0.38 to 2.17] Nm/deg with a relative percent difference between the methods of 27% [range 13% to 89%]. CONCLUSIONS: This study demonstrates the importance of developing mechanical testing standards, similar to those that exist for lower limb prosthetics. Lacking standardization, differences in methodology can result in large differences in measured stiffness, particularly for different constraints on motion. Non-uniform measurement practices may limit the clinical utility of AFO stiffness as a metric in AFO prescription and future research.

A comparison of intracranial volume estimation methods and their cross-sectional and longitudinal associations with age.

Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI) studies, both as a covariate and as a variable of interest. Findings of associations between ICV and age have varied, potentially due to differences in ICV estimation methods. Here, we compared five commonly used ICV estimation methods and their associations with age. T1-weighted cross-sectional MRI data was included for 651 healthy individuals recruited through the NORMENT Centre (mean age = 46.1 years, range = 12.0-85.8 years) and 2410 healthy individuals recruited through the UK Biobank study (UKB, mean age = 63.2 years, range = 47.0-80.3 years), where longitudinal data was also available. ICV was estimated with FreeSurfer (eTIV and sbTIV), SPM12, CAT12, and FSL. We found overall high correlations across ICV estimation method, with the lowest observed correlations between FSL and eTIV (r = .87) and between FSL and CAT12 (r = .89). Widespread proportional bias was found, indicating that the agreement between methods varied as a function of head size. Body weight, age, sex, and mean ICV across methods explained the most variance in the differences between ICV estimation methods, indicating possible confounding for some estimation methods. We found both positive and negative cross-sectional associations with age, depending on dataset and ICV estimation method. Longitudinal ICV reductions were found for all ICV estimation methods, with annual percentage change ranging from -0.293% to -0.416%. This convergence of longitudinal results across ICV estimation methods offers strong evidence for age-related ICV reductions in mid- to late adulthood.

Comparative evaluation of molecular methods for the quantitative measure of torquetenovirus viremia, the new surrogate marker of immune competence.

BACKGROUND: Torquetenovirus (TTV) viremia is emerging as a promising tool to assess functional immune competence, to predict posttransplant immune-related complications, and eventually to customize immunosuppression. METHODS: In this study, 327 blood samples were tested using two real-time PCR (rtPCR) assays both targeted to the untranslated region of the TTV genome. The first assay was an in-house rtPCR developed by our group, the second one was the recently marketed TTV R-GENE assay. RESULTS: In the validation study, the TTV R-GENE showed good performances in precision and reproducibility, and sensitivity as low as 12 TTV DNA copies/mL, like previously reported for the in-house rtPCR. The Bland-Altman analysis showed that the mean difference between the two methods was -0.3 log copies/mL. In the comparison study, 69% and 72% of samples were detected positive by rtPCR and TTV R-GENE, respectively (94% concordance, κ = 0.88). Performances did not differ between the two rtPCRs by type of TTV group examined. When a newly-developed in-house digital droplet PCR was applied for TTV quantification and used as an alternative method of comparison on 94 samples, the results strongly correlated with those obtained by the two rtPCR methods (99% concordance). CONCLUSION: In summary, all the molecular methods assayed are highly sensitive and accurate in quantitation of TTV DNA in blood samples.

Capillary blood tests may overestimate ketosis: triangulation between three different measures of ß-hydroxybutyrate.

The ketone body ß-hydroxybutyrate (BHB), assessed by a point-of-care meter in venous whole blood (BHBv), was used as the main outcome in a study on nutritional ketosis in healthy older adults. Two other BHB measures were also used in the study for validation and exploratory purposes, and here we report findings on correlation and agreement between those three methods. Ketosis in the range of 0-1.5 mmol/L was induced in 15 healthy volunteers by intake of medium-chain fatty acids after a 12-h fast. BHBv was assessed at 12 time points for 4 h. The same point-of-care meter was also used to test capillary blood (BHBc) at three time points, and a laboratory test determined total ketones (TK) in plasma (BHBp + acetoacetate) at four time points. A total of 180 cases included simultaneous data on BHBv, BHBc, BHBp, and TK. TK correlated with BHBp (Pearson's r = 0.99), BHBv (r = 0.91), and BHBc (r = 0.91), all P < 0.0001. BHBv and BHBp had good agreement in absolute values. However, the slope between BHBc and BHBv, measured with the same device, was in the range of 0.64-0.78 in different regression models, indicating substantially higher BHB concentrations in capillary versus venous blood. We conclude that all three methods are valid to detect relative changes in ketosis, but our results highlight the importance of method considerations and the possible need to adjust cutoffs, e.g., in the management of ketoacidosis and in the evaluation and comparison of dietary interventions.

Sequential rank agreement methods for comparison of ranked lists.

The comparison of alternative rankings of a set of items is a general and common task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according to the personalized risk of an event, and genetic studies rank genes according to their difference in gene expression levels. We propose a sequential rank agreement measure to quantify the rank agreement among two or more ordered lists. This measure has an intuitive interpretation, it can be applied to any number of lists even if some are partially incomplete, and it provides information about the agreement along the lists. The sequential rank agreement can be evaluated analytically or be compared graphically to a permutation based reference set in order to identify changes in the list agreements. The usefulness of this measure is illustrated using gene rankings, and using data from two Danish ovarian cancer studies where we assess the within and between agreement of different statistical classification methods.

Comparison of Trotting Stance Detection Methods from an Inertial Measurement Unit Mounted on the Horse's Limb.

The development of on-board sensors, such as inertial measurement units (IMU), has made it possible to develop new methods for analyzing horse locomotion to detect lameness. The detection of spatiotemporal events is one of the keystones in the analysis of horse locomotion. This study assesses the performance of four methods for detecting Foot on and Foot off events. They were developed from an IMU positioned on the canon bone of eight horses during trotting recording on a treadmill and compared to a standard gold method based on motion capture. These methods are based on accelerometer and gyroscope data and use either thresholding or wavelets to detect stride events. The two methods developed from gyroscopic data showed more precision than those developed from accelerometric data with a bias less than 0.6% of stride duration for Foot on and 0.1% of stride duration for Foot off. The gyroscope is less impacted by the different patterns of strides, specific to each horse. To conclude, methods using the gyroscope present the potential of further developments to investigate the effects of different gait paces and ground types in the analysis of horse locomotion.

Comparison of nine heart rate-based models to predict work metabolism of Forest workers.

Predicted work metabolism (WM) from 9 heart rate (HR)-based models were compared to measured WM obtained during work in 39 forest workers. Using measured (i.e. raw) HR in these models can overestimate actual WM since the HR increase associated with body heat accumulation is non-metabolic. Hence, accuracy of WM prediction was assessed on all possible combinations of models using raw HR and corrected HR (thermal component removed) and with five different estimates of maximum work capacity (MWC) for the models that require it as an input. The 50 model combinations produced a wide range of WM estimates. Three models using individual calibration produced the lowest RMSE and narrowest LoA with corrected HR (rRMSE ≤13%; LoA [rBias <5% ± 25%]). One of the models that requires neither determination of the thermal component nor individual calibration performed very well (rRMSE = 18%; LoA [rBias = 1% ± 36%]). Practitioner Summary: These results provide a better understanding of the accuracy of various HR-based work metabolism (WM) estimation models. This information should prove particularly useful to ergonomics professionals wishing to select a method that provides accurate estimation of WM from HR measurements during work in varied thermal environments. Abbreviations: BMI: body mass index; HR: heart rate (beats per min); HR99: HR value exceeded during 99% of the duration of the HR recording period; HRcorr: heart rate without thermal pulses; HRraw: measured heart rate; HRres: heart rate reserve; HRrest: heart rate at rest; LoA: limits of agreement; Mrest: resting metabolism; MWC: maximum work capacity; RMSE: root mean square error; VO2: oxygen consumption; VO2 max: maximum oxygen consumption; WM: work metabolism.

Comparative Analysis of Energy and Exergy Performance of Hydrogen Production Methods.

The study of the viability of hydrogen production as a sustainable energy source is a current challenge, to satisfy the great world energy demand. There are several techniques to produce hydrogen, either mature or under development. The election of the hydrogen production method will have a high impact on practical sustainability of the hydrogen economy. An important profile for the viability of a process is the calculation of energy and exergy efficiencies, as well as their overall integration into the circular economy. To carry out theoretical energy and exergy analyses we have estimated proposed hydrogen production using different software (DWSIM and MATLAB) and reference conditions. The analysis consolidates methane reforming or auto-thermal reforming as the viable technologies at the present state of the art, with reasonable energy and exergy efficiencies, but pending on the impact of environmental constraints as CO2 emission countermeasures. However, natural gas or electrolysis show very promising results, and should be advanced in their technological and maturity scaling. Electrolysis shows a very good exergy efficiency due to the fact that electricity itself is a high exergy source. Pyrolysis exergy loses are mostly in the form of solid carbon material, which has a very high integration potential into the hydrogen economy.

Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison.

BACKGROUND: Because of its non-destructive nature, label-free imaging is an important strategy for studying biological processes. However, routine microscopic techniques like phase contrast or DIC suffer from shadow-cast artifacts making automatic segmentation challenging. The aim of this study was to compare the segmentation efficacy of published steps of segmentation work-flow (image reconstruction, foreground segmentation, cell detection (seed-point extraction) and cell (instance) segmentation) on a dataset of the same cells from multiple contrast microscopic modalities. RESULTS: We built a collection of routines aimed at image segmentation of viable adherent cells grown on the culture dish acquired by phase contrast, differential interference contrast, Hoffman modulation contrast and quantitative phase imaging, and we performed a comprehensive comparison of available segmentation methods applicable for label-free data. We demonstrated that it is crucial to perform the image reconstruction step, enabling the use of segmentation methods originally not applicable on label-free images. Further we compared foreground segmentation methods (thresholding, feature-extraction, level-set, graph-cut, learning-based), seed-point extraction methods (Laplacian of Gaussians, radial symmetry and distance transform, iterative radial voting, maximally stable extremal region and learning-based) and single cell segmentation methods. We validated suitable set of methods for each microscopy modality and published them online. CONCLUSIONS: We demonstrate that image reconstruction step allows the use of segmentation methods not originally intended for label-free imaging. In addition to the comprehensive comparison of methods, raw and reconstructed annotated data and Matlab codes are provided.

Combining bulk and amino acid stable isotope analyses to quantify trophic level and basal resources of detritivores: a case study on earthworms.

Quantification of the bacterial, fungal, and plant energy channels to the nutrition of detritivores is methodologically challenging. This is especially true for earthworms that ingest large amounts of litter and soil mixed with microorganisms. Novel methods such as compound-specific stable isotope analysis (CSIA) of C and N of individual amino acids promise major progress in this field in comparison with bulk stable isotope analysis (bulk SIA). Here, we combine CSIA and bulk SIA of carbon and nitrogen to quantify the linkage of epigeic and endogeic earthworm species to different energy channels across boreal and temperate forest ecosystems. The results showed pronounced flux of energy directly from plants to earthworms (33-50% of essential amino acids, EAA) refining the position of earthworms in soil food webs as both competitors and consumers of microorganisms. Epigeic earthworm species primarily relied on plant litter and endogeic species primarily relied on bacteria and soil organic matter. The linkage of both groups to plant or microbial energy channel was likely driven by the quality of detritus. Both bulk 15N and 13C enrichments were related to the trophic level of earthworms. Furthermore, 15N enrichment was related to the proportions of bacterial and plant EAA in the diet. Strong negative correlation between trophic level (CSIA of nitrogen) and the proportion of plant EAA (CSIA of carbon) suggests that both novel methods can indicate the degree of microbivory in detritivores. CSIA of amino acids provide detailed and baseline-independent information on basal resources and trophic levels of detritivores.

Evaluation of analytical performance of a new high-sensitivity immunoassay for cardiac troponin I.

BACKGROUND: The study aim was to evaluate and compare the analytical performance of the new chemiluminescent immunoassay for cardiac troponin I (cTnI), called Access hs-TnI using DxI platform, with those of Access AccuTnI+3 method, and high-sensitivity (hs) cTnI method for ARCHITECT platform. METHODS: The limits of blank (LoB), detection (LoD) and quantitation (LoQ) at 10% and 20% CV were evaluated according to international standardized protocols. For the evaluation of analytical performance and comparison of cTnI results, both heparinized plasma samples, collected from healthy subjects and patients with cardiac diseases, and quality control samples distributed in external quality assessment programs were used. RESULTS: LoB, LoD and LoQ at 20% and 10% CV values of the Access hs-cTnI method were 0.6, 1.3, 2.1 and 5.3 ng/L, respectively. Access hs-cTnI method showed analytical performance significantly better than that of Access AccuTnI+3 method and similar results to those of hs ARCHITECT cTnI method. Moreover, the cTnI concentrations measured with Access hs-cTnI method showed close linear regressions with both Access AccuTnI+3 and ARCHITECT hs-cTnI methods, although there were systematic differences between these methods. There was no difference between cTnI values measured by Access hs-cTnI in heparinized plasma and serum samples, whereas there was a significant difference between cTnI values, respectively measured in EDTA and heparin plasma samples. CONCLUSIONS: Access hs-cTnI has analytical sensitivity parameters significantly improved compared to Access AccuTnI+3 method and is similar to those of the high-sensitivity method using ARCHITECT platform.

Comparison of gaseous and particulate emissions from a pilot-scale combustor using three varieties of coal.

Gaseous and particulate emissions generated from the combustion of coal have been associated with adverse effects on human health and the environment, and have therefore been the subject of regulation by federal and state government agencies. Detailed emission characterizations are needed to better understand the impacts of pre- and post-combustion controls on a variety of coals found in the United States (U.S.). While the U.S. Environmental Protection Agency (EPA) requires industry reporting of emissions for criteria and several hazardous air pollutants (HAPs), many of the methods for monitoring and measuring these gaseous and particulate emissions rely on time-integrated sampling techniques. Though these emissions reports provide an overall representation of day-to-day operations, they represent well-controlled operations and do not encompass real combustion events that occur sporadically. The current study not only characterizes emissions from three coals (bituminous, sub-bituminous, and lignite), but also investigates the use of instrumentation for improved measurement and monitoring techniques that provide real-time, continuous emissions data. Testing was completed using the U.S. EPA's Multi-Pollutant Control Research Facility, a pilot-scale coal-fired combustor using industry-standard emission control technologies, in Research Triangle Park, North Carolina. Emissions were calculated based on measurements from the flue gas (pre- and post-electrostatic precipitator), to characterize gaseous species (CO, CO2, O2, NOX, SO2, other acid gases, and several organic HAPs) as well as fine and ultrafine particulate (mass, size distribution, number count, elemental carbon, organic carbon, and black carbon). Comparisons of traditional EPA methods to those made via Fourier Transfer Infrared (FTIR) Spectroscopy for CO, NOX, and SO2 are also reported.

Crohn disease risk prediction-Best practices and pitfalls with exome data.

The Critical Assessment of Genome Interpretation (CAGI) experiment is the first attempt to evaluate the state-of-the-art in genetic data interpretation. Among the proposed challenges, Crohn disease (CD) risk prediction has become the most classic problem spanning three editions. The scientific question is very hard: can anybody assess the risk to develop CD given the exome data alone? This is one of the ultimate goals of genetic analysis, which motivated most CAGI participants to look for powerful new methods. In the 2016 CD challenge, we implemented all the best methods proposed in the past editions. This resulted in 10 algorithms, which were evaluated fairly by CAGI organizers. We also used all the data available from CAGI 11 and 13 to maximize the amount of training samples. The most effective algorithms used known genes associated with CD from the literature. No method could evaluate effectively the importance of unannotated variants by using heuristics. As a downside, all CD datasets were strongly affected by sample stratification. This affected the performance reported by assessors. Therefore, we expect that future datasets will be normalized in order to remove population effects. This will improve methods comparison and promote algorithms focused on causal variants discovery.

Comparison of six methods for the recovery of PCR-compatible microbial DNA from an agricultural biogas plant.

Six different commercial methods were compared to evaluate their efficiency in recovering high quantity/quality PCR compatible microbial DNA from an agricultural biogas plant. Within the last two decades, biogas plants have been developed to produce energy from organic wastes and from devoted biomass. The complex biotransformations are performed by a diverse consortium of microorganisms that is an important reserve of genes and enzymatic activities with a huge range of applications in various commercial fields. In this respect, the ability to isolate DNA from a complex matrix is of high importance. Important parameters of the recovered DNA are good yield, purity, and quality. The methods examined showed considerable differences about quantity and quality of the recovered DNA and, usually, it was observed that a higher amount was accompanied by more degradation. DNA purity was determined by its PCR amplificability. Only two methods were able to provide DNA pure enough to be directly amplified. For the rest of the methods, a few intermediate steps such as dilution and/or the addition of polyvinylpyrrolidone were necessary to remove the inhibitors present and to amplify the DNA. Real-time PCR analysis evidenced that, as expected, prokaryotic DNA was much more abundant than eukaryotic DNA, but some methods were more suited to recovering prokaryotic or eukaryotic DNA. The digestion analysis of ribosomal DNA amplicons confirmed the influence of the methods on the final output, allowing the recovery of only a fraction of the present species as determined by sequencing a small prokaryotic and eukaryotic ribosomal library.

Assessing coral health and disease from digital photographs and in situ surveys.

Methods for monitoring the status of marine communities are increasingly adopting the use of images captured in the field. However, it is not always clear how data collected from photographic images relate to historic data collected using traditional underwater visual census methods. Here, we compare coral health and disease data collected in situ by scuba divers with photographic images collected simultaneously at 12 coral reef sites. Five globally relevant coral diseases were detected on 194 colonies from in situ surveys and 79 colonies from photos, whilst 698 colonies from in situ surveys and 535 colonies from photos exhibited signs of compromised health other than disease. Comparisons of in situ surveys with photographic analyses indicated that the number of disease cases occurring in the examined coral populations (prevalence) was six times higher (4.5 vs. 0.8% of colonies), whilst compromised health was three times higher (14 vs. 4% of colonies) from in situ surveys. Skeletal eroding band disease, sponge overgrowth and presence of Waminoa flatworms were not detected in photographs, though they were identified in situ. Estimates of black band disease and abnormally pigmented coral tissues were similar between the two methods. Estimates of the bleached and healthy colonies were also similar between methods and photographic analyses were a strong predictor of bleached (r 2 = 0.8) and healthy (r 2 = 0.5) colony prevalence from in situ surveys. Moreover, when data on disease and compromised health states resulting in white or pale coral colony appearance were pooled, the prevalence of 'white' colonies from in situ (14%) and photographic analyses (11%) were statistically similar. Our results indicate that information on coral disease and health collected by in situ surveys and photographic analyses are not directly comparable, with in situ surveys generally providing higher estimates of prevalence and greater ability to identify some diseases and compromised states. Careful sampling of photographs can however identify signs of coral stress, including some coral diseases, which may be used to trigger early-warning management interventions.

Applicability of the cobas 6800 System for Epstein-Barr viral load quantitation using whole-blood specimens.

OBJECTIVES: This study aimed to evaluate the analytical performance of the cobas 6800 System (Roche Diagnostics) and assess the feasibility of using whole-blood specimens instead of plasma. METHODS: The analytical performance of the cobas EBV test (Roche Diagnostics) was evaluated. Thereafter, 120 clinical samples were collected to compare the cobas EBV test and the artus EBV RG PCR Kit (Qiagen). The results of the cobas EBV test conducted using paired plasma as well as 5× and 10× diluted whole-blood specimens were compared with those of the artus EBV RG PCR Kit performed using whole blood. RESULTS: The precision of the cobas EBV test was acceptable, and its linearity was confirmed to be within the range of 2.85 to 6.89 log IU/mL. Cross-reactivity was not observed. The best qualitative agreement (Cohen κ = 0.733) was observed using 5× diluted whole blood; the best quantitative correlation (Spearman correlation coefficient = 0.6865) was observed using 10× diluted whole blood. CONCLUSIONS: A significant discrepancy was observed in the results obtained from the 2 assays because of the different specimens used. We observed, however, that diluting whole blood before conducting the cobas EBV test effectively resolved polymerase chain reaction inhibition and viscosity issues, leading to an acceptable correlation with the results from the artus EBV RG PCR Kit conducted using whole blood.