Assessment of measurement precision in single-voxel spectroscopy at 7 T: Toward minimal detectable changes of metabolite concentrations in the human brain in vivo.

PURPOSE: To introduce a study design and statistical analysis framework to assess the repeatability, reproducibility, and minimal detectable changes (MDCs) of metabolite concentrations determined by in vivo MRS. METHODS: An unbalanced nested study design was chosen to acquire in vivo MRS data within different repeatability and reproducibility scenarios. A spin-echo, full-intensity acquired localized (SPECIAL) sequence was employed at 7 T utlizing three different inversion pulses: a hyperbolic secant (HS), a gradient offset independent adiabaticity (GOIA), and a wideband, uniform rate, smooth truncation (WURST) pulse. Metabolite concentrations, Cramér-Rao lower bounds (CRLBs) and coefficients of variation (CVs) were calculated. Both Bland-Altman analysis and a restricted maximum-likelihood estimation (REML) analysis were performed to estimate the different variance contributions of the repeatability and reproducibility of the measured concentration. A Bland-Altmann analysis of the spectral shape was performed to assess the variance of the spectral shape, independent of quantification model influences. RESULTS: For the used setup, minimal detectable changes of brain metabolite concentrations were found to be between 0.40 µmol/g and 2.23 µmol/g. CRLBs account for only 16 % to 74 % of the total variance of the metabolite concentrations. The application of gradient-modulated inversion pulses in SPECIAL led to slightly improved repeatability, but overall reproducibility appeared to be limited by differences in positioning, calibration, and other day-to-day variations throughout different sessions. CONCLUSION: A framework is introduced to estimate the precision of metabolite concentrations obtained by MRS in vivo, and the minimal detectable changes for 13 metabolite concentrations measured at 7 T using SPECIAL are obtained.

IL-19 Halts Progression of Atherosclerotic Plaque, Polarizes, and Increases Cholesterol Uptake and Efflux in Macrophages.

Atherosclerosis regression is an important clinical goal, and treatments that can reverse atherosclerotic plaque formation are actively being sought. Our aim was to determine whether administration of exogenous IL-19, a Th2 cytokine, could attenuate progression of preformed atherosclerotic plaque and to identify molecular mechanisms. LDLR(-/-) mice were fed a Western diet for 12 weeks, then administered rIL-19 or phosphate-buffered saline concomitant with Western diet for an additional 8 weeks. Analysis of atherosclerosis burden showed that IL-19-treated mice were similar to baseline, in contrast to control mice which showed a 54% increase in plaque, suggesting that IL-19 halted the progression of atherosclerosis. Plaque characterization showed that IL-19-treated mice had key features of atherosclerosis regression, including a reduction in macrophage content and an enrichment in markers of M2 macrophages. Mechanistic studies revealed that IL-19 promotes the activation of key pathways leading to M2 macrophage polarization, including STAT3, STAT6, Kruppel-like factor 4, and peroxisome proliferator-activated receptor γ, and can reduce cytokine-induced inflammation in vivo. We identified a novel role for IL-19 in regulating macrophage lipid metabolism through peroxisome proliferator-activated receptor γ-dependent regulation of scavenger receptor-mediated cholesterol uptake and ABCA1-mediated cholesterol efflux. These data show that IL-19 can halt progression of preformed atherosclerotic plaques by regulating both macrophage inflammation and cholesterol homeostasis and implicate IL-19 as a link between inflammation and macrophage cholesterol metabolism.

Extending digital PCR analysis by modelling quantification cycle data.

BACKGROUND: Digital PCR (dPCR) is a technique for estimating the concentration of a target nucleic acid by loading a sample into a large number of partitions, amplifying the target and using a fluorescent marker to identify which partitions contain the target. The standard analysis uses only the proportion of partitions containing target to estimate the concentration and depends on the assumption that the initial distribution of molecules in partitions is Poisson. In this paper we describe a way to extend such analysis using the quantification cycle (Cq) data that may also be available, but rather than assuming the Poisson distribution the more general Conway-Maxwell-Poisson distribution is used instead. RESULTS: A software package for the open source language R has been created for performing the analysis. This was used to validate the method by analysing Cq data from dPCR experiments involving 3 types of DNA (attenuated, virulent and plasmid) at 3 concentrations. Results indicate some deviation from the Poisson distribution, which is strongest for the virulent DNA sample. Theoretical calculations indicate that the deviation from the Poisson distribution results in a bias of around 5 % for the analysed data if the standard analysis is used, but that it could be larger for higher concentrations. Compared to the estimates of subsequent efficiency, the estimates of 1st cycle efficiency are much lower for the virulent DNA, moderately lower for the attenuated DNA and close for the plasmid DNA. Further method validation using simulated data gave results closer to the true values and with lower standard deviations than the standard method, for concentrations up to approximately 2.5 copies/partition. CONCLUSIONS: The Cq-based method is effective at estimating DNA concentration and is not seriously affected by data issues such as outliers and moderately non-linear trends. The data analysis suggests that the Poisson assumption of the standard approach does lead to a bias that is fairly small, though more research is needed. Estimates of the 1st cycle efficiency being lower than estimates of the subsequent efficiency may indicate samples that are mixtures of single-stranded and double-stranded DNA. The model can reduce or eliminate the resulting bias.

IL-19 reduces ligation-mediated neointimal hyperplasia by reducing vascular smooth muscle cell activation.

We tested the hypothesis that IL-19, a putative member of the type 2 helper T-cell family of anti-inflammatory interleukins, can attenuate intimal hyperplasia and modulate the vascular smooth muscle cell (VSMC) response to injury. Ligated carotid artery of IL-19 knockout (KO) mice demonstrated a significantly higher neointima/intima ratio compared with wild-type (WT) mice (P = 0.04). More important, the increased neointima/intima ratio in the KO could be reversed by injection of 10 ng/g per day recombinant IL-19 into the KO mouse (P = 0.04). VSMCs explanted from IL-19 KO mice proliferated significantly more rapidly than WT. This could be inhibited by addition of IL-19 to KO VSMCs (P = 0.04 and P < 0.01). IL-19 KO VSMCs migrated more rapidly compared with WT (P < 0.01). Interestingly, there was no type 1 helper T-cell polarization in the KO mouse, but there was significantly greater leukocyte infiltrate in the ligated artery in these mice compared with WT. IL-19 KO VSMCs expressed significantly greater levels of inflammatory mRNA, including IL-1ß, tumor necrosis factor α, and monocyte chemoattractant protein-1 in response to tumor necrosis factor α stimulation (P < 0.01 for all). KO VSMCs expressed greater adhesion molecule expression and adherence to monocytes. Together, these data indicate that IL-19 is a previously unrecognized counterregulatory factor for VSMCs, and its expression is an important protective mechanism in regulation of vascular restenosis.

Temporal patterns in adult salmon migration timing across southeast Alaska.

Pacific salmon migration timing can drive population productivity, ecosystem dynamics, and human harvest. Nevertheless, little is known about long-term variation in salmon migration timing for multiple species across broad regions. We used long-term data for five Pacific salmon species throughout rapidly warming southeast Alaska to describe long-term changes in salmon migration timing, interannual phenological synchrony, relationships between climatic variation and migratory timing, and to test whether long-term changes in migration timing are related to glaciation in headwater streams. Temporal changes in the median date of salmon migration timing varied widely across species. Most sockeye populations are migrating later over time (11 of 14), but pink, chum, and especially coho populations are migrating earlier than they did historically (16 of 19 combined). Temporal trends in duration and interannual variation in migration timing were highly variable across species and populations. The greatest temporal shifts in the median date of migration timing were correlated with decreases in the duration of migration timing, suggestive of a loss of phenotypic variation due to natural selection. Pairwise interannual correlations in migration timing varied widely but were generally positive, providing evidence for weak region-wide phenological synchrony. This synchrony is likely a function of climatic variation, as interannual variation in migration timing was related to climatic phenomenon operating at large- (Pacific decadal oscillation), moderate- (sea surface temperature), and local-scales (precipitation). Surprisingly, the presence or the absence of glaciers within a watershed was unrelated to long-term shifts in phenology. Overall, there was extensive heterogeneity in long-term patterns of migration timing throughout this climatically and geographically complex region, highlighting that future climatic change will likely have widely divergent impacts on salmon migration timing. Although salmon phenological diversity will complicate future predictions of migration timing, this variation likely acts as a major contributor to population and ecosystem resiliency in southeast Alaska.

Attenuation of experimental atherosclerosis by interleukin-19.

OBJECTIVE: Interleukin-19 (IL-19) is a putative Th2, anti-inflammatory interleukin. Its expression and potential role in atherogenesis are unknown. IL-19 is not detected in normal artery and is expressed to a greater degree in plaque from symptomatic versus asymptomatic patients, suggesting a compensatory counter-regulatory function. We tested whether IL-19 could reduce atherosclerosis in susceptible mice and identified plausible mechanisms. APPROACH AND RESULTS: LDLR(-/-) mice fed an atherogenic diet and injected with either 1.0 or 10.0 ng/g per day recombinant mouse IL-19 had significantly less plaque area in the aortic arch compared with controls (P<0.0001). Weight gain, cholesterol, and triglyceride levels were not significantly different. Gene expression in splenocytes from IL-19-treated mice demonstrated immune cell Th2 polarization, with decreased expression of T-bet, interferon-γ, interleukin-1ß, and interleukin-12ß and increased expression of GATA3 and FoxP3 mRNA. A greater percentage of lymphocytes were Th2 polarized in IL-19-treated mice. Cellular characterization of plaque by immunohistochemistry demonstrated that IL-19-treated mice have significantly less macrophage infiltrate compared with controls (P<0.001). Intravital microscopy revealed significantly less leukocyte adhesion in wild-type mice injected with IL-19 and fed an atherogenic diet compared with controls. Treatment of cultured endothelial cells, vascular smooth muscle cells, and bone marrow-derived macrophages with IL-19 resulted in a significant decrease in chemokine mRNA and mRNA stability protein human antigen R. CONCLUSIONS: These data suggest that IL-19 is a potent inhibitor of experimental atherosclerosis, with diverse mechanisms including immune cell polarization, decrease in macrophage adhesion, and decrease in gene expression. This may identify IL-19 as a novel therapeutic to limit vascular inflammation.

Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation.

One of the benefits of Digital PCR (dPCR) is the potential for unparalleled precision enabling smaller fold change measurements. An example of an assessment that could benefit from such improved precision is the measurement of tumour-associated copy number variation (CNV) in the cell free DNA (cfDNA) fraction of patient blood plasma. To investigate the potential precision of dPCR and compare it with the established technique of quantitative PCR (qPCR), we used breast cancer cell lines to investigate HER2 gene amplification and modelled a range of different CNVs. We showed that, with equal experimental replication, dPCR could measure a smaller CNV than qPCR. As dPCR precision is directly dependent upon both the number of replicate measurements and the template concentration, we also developed a method to assist the design of dPCR experiments for measuring CNV. Using an existing model (based on Poisson and binomial distributions) to derive an expression for the variance inherent in dPCR, we produced a power calculation to define the experimental size required to reliably detect a given fold change at a given template concentration. This work will facilitate any future translation of dPCR to key diagnostic applications, such as cancer diagnostics and analysis of cfDNA.

Clinically and industrially relevant incurred reference materials to improve analysis of food allergens, milk, egg, almond, hazelnut and walnut.

Measurement of food allergen protein concentrations against thresholds can improve allergen risk management and precautionary allergen labelling. Such measurement suffers well known problems which could be ameliorated by well characterised reference materials (RMs) providing meaningful information for risk assessors. We investigated the preparation and characterisation of the first consensus informed industrially and clinically relevant multi-allergen matrix RM kit for five priority allergens. It is a medium analytical difficulty processed food chocolate paste matrix (a) devoid of allergens, and (b) incurred with five allergens at the clinically relevant concentration of 10 mg kg-1 expressed as protein. The allergen raw materials: hens' egg white powder, skimmed cows' milk powder, almond powder (full fat), hazelnut powder (partially defatted), and walnut powder (partially defatted), are also available as RMs. The preparation, gravimetric traceability to the SI, homogeneity, and stability were found to be fit-for-purpose and the RMs are now available to the analytical community.

Interleukin-19 (IL-19) induces heme oxygenase-1 (HO-1) expression and decreases reactive oxygen species in human vascular smooth muscle cells.

Heme oxygenase-1 (HO-1) has potent anti-inflammatory activity and recognized vascular protective effects. We have recently described the expression and vascular protective effects of an anti-inflammatory interleukin (IL-19), in vascular smooth muscle cells (VSMC) and injured arteries. The objective of this study was to link the anti-inflammatory effects of IL-19 with HO-1 expression in resident vascular cells. IL-19 induced HO-1 mRNA and protein in cultured human VSMC, as assayed by quantitative RT-PCR, immunoblot, and ELISA. IL-19 does not induce HO-1 mRNA or protein in human endothelial cells. IL-19 activates STAT3 in VSMC, and IL-19-induced HO-1 expression is significantly reduced by transfection of VSMC with STAT3 siRNA or mutation of the consensus STAT binding site in the HO-1 promoter. IL-19 treatment can significantly reduce ROS-induced apoptosis, as assayed by Annexin V flow cytometry. IL-19 significantly reduced ROS concentrations in cultured VSMC. The IL-19-induced reduction in ROS concentration is attenuated when HO-1 is reduced by siRNA, indicating that the IL-19-driven decrease in ROS is mediated by HO-1 expression. IL-19 reduces vascular ROS in vivo in mice treated with TNFα. This points to IL-19 as a potential therapeutic for vascular inflammatory diseases and a link for two previously unassociated protective processes: Th2 cytokine-induced anti-inflammation and ROS reduction.

Optimisation of data acquisition towards continuous cardiac Magnetic Resonance Fingerprinting applications.

PURPOSE: Assess and optimise acquisition parameters for continuous cardiac Magnetic Resonance Fingerprinting (MRF). METHODS: Different acquisition schemes (flip angle amplitude, lobe size, T2-preparation pulses) for cardiac MRF were assessed in simulations and phantom and demonstrated in one healthy volunteer. Three different experimental designs were evaluated using central composite and fractional factorial designs. Relative errors for T1 and T2 were calculated for a wide range of realistic T1 and T2 value combinations. The effect of different designs on the accuracy of T1 and T2 was assessed using response surface modelling and Cohen's f calculations. RESULTS: Larger flip angle amplitudes lead to an improvement of T2 accuracy and precision for simulations and phantom experiments. Similar effects could also be shown qualitatively in in-vivo scans. Accuracy and precision of T1 were robust to different design parameters with improved values for faster flip angle variation. Cohen's f showed that T2-preparation pulses influence the accuracy of T2. The number of pulses used is the most important parameter. Without T2-preparation pulses, RMSE were 3.0 ± 8.09 % for T1 and 16.24 ± 14.47 % for T2. Using those pulses reduced the RMSE to 2.3 ± 8.4 % for T1 and 14.11 ± 13.46 % for T2. Nonetheless, even if the improvement is significant, RMSE are still too high for reliable quantification. CONCLUSION: In contrast to previous study using triggered MRF sequences using < 30° flip angles, large flip angle amplitudes led to better results for continuous cardiac MRF sequences. T2-preparation pulse can improve the accuracy of T2 estimation but lead to longer scan times.

Macromolecule modelling for improved metabolite quantification using short echo time brain 1 H MRS at 3 T and 7 T: The PRaMM Model.

Purpose: To improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain 1 H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints. Methods: Full- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities. These ratios were then used as soft constraints in the proposed PRaMM model for quantification of full spectra. The PRaMM model was validated by comparison with a single component macromolecule model and a macromolecule subtraction technique. Moreover, the influence of the PRaMM model on the repeatability and reproducibility compared to those other methods was investigated. Results: The developed PRaMM model performed better than the two other approaches in all three investigated brain regions. Several estimates of metabolite concentration and their Cramér-Rao lower bounds were affected by the PRaMM model reproducibility, and repeatability of the achieved concentrations were tested by evaluating the method on a second repeated acquisitions dataset. While the observed effects on both metrics were not significant, the fit quality metrics were improved for the PRaMM method (p≤0.0001). Minimally detectable changes are in the range 0.5 - 1.9 mM and percent coefficients of variations are lower than 10% for almost all the clinically relevant metabolites. Furthermore, potential overparameterization was ruled out. Conclusion: Here, the PRaMM model, a method for an improved quantification of metabolites was developed, and a method to investigate the role of the MM background and its individual components from a clinical perspective is proposed.

The interlaboratory performance of microbiological methods for food analysis.

Repeatability and reproducibility data for microbiological methods in food analysis were collated and assessed with a view to identifying useful or important trends. Generalized additive modeling for location, shape, and scale was used to model the distribution of variances. It was found that mean reproducibility for log10(CFU) data is largely independent of concentration, while repeatability SD of log10(CFU) data shows a strongly significant decrease in repeatability SD with increasing enumeration. The model for reproducibility SD gave a mean of 0.44, with an upper 95th percentile of approximately 0.76. Repeatability variance could be described reasonably well by a simple dichotomous model; at enumerations below 10(5)/g, the model for repeatability SD gave a mean of approximately 0.35 and upper 95th percentile of 0.63. Above 10(5)/g, the model gave a mean of 0.2 and upper 95th percentile of 0.36. A Horwitz-like function showed no appreciable advantage in describing the data set and gave apparently worse fit. The relationship between repeatability and reproducibility of log10(CFU) is not constant across the concentration range studied. Both repeatability and reproducibility were found to depend on matrix class and organism.

A standard additions method reduces inhibitor-induced bias in quantitative real-time PCR.

A method of calibration for real-time quantitative polymerase chain reaction (qPCR) experiments based on the method of standard additions combined with non-linear curve fitting is described. The method is tested by comparing the results of a traditionally calibrated qPCR experiment with the standard additions experiment in the presence of 2 mM EDTA, a known inhibitor chosen to provide an unambiguous test of the principle by inducing an approximately twofold bias in apparent copy number calculated using traditional calibration. The standard additions method is shown to substantially reduce inhibitor-induced bias in quantitative real-time qPCR.

Novel plasma biomarkers improve discrimination of metabolic health independent of weight.

We sought to determine if novel plasma biomarkers improve traditionally defined metabolic health (MH) in predicting risk of cardiovascular disease (CVD) events irrespective of weight. Poor MH was defined in CATHGEN biorepository participants (n > 9300), a follow-up cohort (> 5600 days) comprising participants undergoing evaluation for possible ischemic heart disease. Lipoprotein subparticles, lipoprotein-insulin resistance (LP-IR), and GlycA were measured using NMR spectroscopy (n = 8385), while acylcarnitines and amino acids were measured using flow-injection, tandem mass spectrometry (n = 3592). Multivariable Cox proportional hazards models determined association of poor MH and plasma biomarkers with time-to-all-cause mortality or incident myocardial infarction. Low-density lipoprotein particle size and high-density lipoprotein, small and medium particle size (HMSP), GlycA, LP-IR, short-chain dicarboxylacylcarnitines (SCDA), and branched-chain amino acid plasma biomarkers were independently associated with CVD events after adjustment for traditionally defined MH in the overall cohort (p = 3.3 × 10-4-3.6 × 10-123), as well as within most of the individual BMI categories (p = 8.1 × 10-3-1.4 × 10-49). LP-IR, GlycA, HMSP, and SCDA improved metrics of model fit analyses beyond that of traditionally defined MH. We found that LP-IR, GlycA, HMSP, and SCDA improve traditionally defined MH models in prediction of adverse CVD events irrespective of BMI.

Applications of robust estimators of covariance in examination of inter-laboratory study data.

Selected robust estimators of covariance or correlation are presented. Their use in the identification of anomalous laboratory results in inter-laboratory data is illustrated. It is shown that robust estimators can substantially reduce the impact of outlying values on multivariate confidence regions and consequently lead to sharper identification of anomalies, even where traditional outlier detection may fail to locate anomalous results.

Standard additions: myth and reality.

Standard additions is a calibration technique devised to eliminate rotational matrix effects in analytical measurement. Although the technique is presented in almost every textbook of analytical chemistry, its behaviour in practice is not well documented and is prone to attract misleading accounts. The most important limitation is that the method cannot deal with translational matrix effects, which need to be handled separately. In addition, because the method involves extrapolation from known data, the method is often regarded as less precise than external calibration (interpolation) techniques. Here, using a generalised model of an analytical system, we look at the behaviour of the method of standard additions under a range of conditions, and find that, if executed optimally, there is no noteworthy loss of precision.

Treatment of uncorrected measurement bias in uncertainty estimation for chemical measurements.

Consistent treatment of measurement bias, including the question of whether or not to correct for bias, is essential for the comparability of measurement results. The case for correcting for bias is discussed, and it is shown that instances in which bias is known or suspected, but in which a specific correction cannot be justified, are comparatively common. The ISO Guide to the Expression of Uncertainty in Measurement does not provide well for this situation. It is concluded that there is a need for guidance on handling cases of uncorrected bias. Several different published approaches to the treatment of uncorrected bias and its uncertainty are critically reviewed with regard to coverage probability and simplicity of execution. On the basis of current studies, and taking into account testing laboratory needs for a simple and consistent approach with a symmetric uncertainty interval, we conclude that for most cases with large degrees of freedom, linear addition of a bias term adjusted for exact coverage ("U(e)") as described by Synek is to be preferred. This approach does, however, become more complex if degrees of freedom are low. For modest bias and low degrees of freedom, summation of bias, bias uncertainty and observed value uncertainty in quadrature ("RSSu") provides a similar interval and is simpler to adapt to reduced degrees of freedom, at the cost of a more restricted range of application if accurate coverage is desired.

Routes to improving the reliability of low level DNA analysis using real-time PCR.

BACKGROUND: Accurate quantification of DNA using quantitative real-time PCR at low levels is increasingly important for clinical, environmental and forensic applications. At low concentration levels (here referring to under 100 target copies) DNA quantification is sensitive to losses during preparation, and suffers from appreciable valid non-detection rates for sampling reasons. This paper reports studies on a real-time quantitative PCR assay targeting a region of the human SRY gene over a concentration range of 0.5 to 1000 target copies. The effects of different sample preparation and calibration methods on quantitative accuracy were investigated. RESULTS: At very low target concentrations of 0.5-10 genome equivalents (g.e.) eliminating any replicates within each DNA standard concentration with no measurable signal (non-detects) compromised calibration. Improved calibration could be achieved by eliminating all calibration replicates for any calibration standard concentration with non-detects ('elimination by sample'). Test samples also showed positive bias if non-detects were removed prior to averaging; less biased results were obtained by converting to concentration, including non-detects as zero concentration, and averaging all values. Tube plastic proved to have a strongly significant effect on DNA quantitation at low levels (p = 1.8 x 10(-4)). At low concentrations (under 10 g.e.), results for assays prepared in standard plastic were reduced by about 50% compared to the low-retention plastic. Preparation solution (carrier DNA or stabiliser) was not found to have a significant effect in this study.Detection probabilities were calculated using logistic regression. Logistic regression over large concentration ranges proved sensitive to non-detected replicate reactions due to amplification failure at high concentrations; the effect could be reduced by regression against log (concentration) or, better, by eliminating invalid responses. CONCLUSION: Use of low-retention plastic tubes is advised for quantification of DNA solutions at levels below 100 g.e. For low-level calibration using linear least squares, it is better to eliminate the entire replicate group for any standard that shows non-detects reasonably attributable to sampling effects than to either eliminate non-detects or to assign arbitrary high Ct values. In calculating concentrations for low-level test samples with non-detects, concentrations should be calculated for each replicate, zero concentration assigned to non-detects, and all resulting concentration values averaged. Logistic regression is a useful method of estimating detection probability at low DNA concentrations.

Scoring in genetically modified organism proficiency tests based on log-transformed results.

The study considers data from 2 UK-based proficiency schemes and includes data from a total of 29 rounds and 43 test materials over a period of 3 years. The results from the 2 schemes are similar and reinforce each other. The amplification process used in quantitative polymerase chain reaction determinations predicts a mixture of normal, binomial, and lognormal distributions dominated by the latter 2. As predicted, the study results consistently follow a positively skewed distribution. Log-transformation prior to calculating z-scores is effective in establishing near-symmetric distributions that are sufficiently close to normal to justify interpretation on the basis of the normal distribution.