Interlaboratory Data Research Articles

Review of techniques, challenges, and new developments for calcium isotope ratio measurements

Calcium isotope meaurements apply to problems spanning the ‘cosmos to benthos.’ Fractionation, source mixing, radioactive decay, and nucleosynthetic processes cause variations in Ca isotope ratios, which can be measured using different types of mass spectrometers. Early measurements employed thermal ionization mass spectrometry (TIMS), which continues to be the most common and precise reference technique. An increasing number of studies use multi-collector inductively coupled plasma mass spectrometry (MC-ICPMS). Both TIMS and MC-ICPMS can yield high-quality data for δ44/40Ca and δ44/42Ca, respectively, but wide ranges in precision exist. Sample size requirements are lower for TIMS, but MC-ICPMS offers faster throughput. Both techniques require purifying Ca by ion-exchange chromatography when analyzing samples with complex matrices. In-situ techniques, like laser ablation MC-ICPMS (LA-MC-ICPMS) and secondary ion mass spectrometry (SIMS), do not require purification. In-situ techniques provide high spatial resolution, but LA-MC-ICPMS and (nano)-SIMS suffer from relatively poor precision compared to TIMS and MC-ICPMS, and the methods lack well-characterized standards, which are essential for comparing datasets.The past few years have seen advances in Ca purification techniques, including automated methods that accelerate sample throughput. The next generation of Ca purification techniques should focus on complete purification and quantitative separation of low-Ca samples. Application of collision-cell technology for suppressing Ar-related molecular isobaric interferences will improve quantification of 40Ca using certain MC-ICPMS models. Similarly, development of new amplifier technology will foster high-precision Faraday cup measurements of low abundance Ca isotopes. Adopting common reference materials, including newly developed standards with complex matrices, would signficantly aid inter-laboratory comparisons, method development, and data compilation efforts. In general, at least two widely-used standards should be measured along with unknown samples to confirm data quality, as well as improve utilization of published Ca isotope datasets by a broader community.

GlycanGUI: Automated Glycan Annotation and Quantification Using Glucose Unit Index.

The retention time provides critical information for glycan annotation and quantification from the Liquid Chromatography Mass Spectrometry (LC-MS) data. However, the variation of the precise retention time of glycans is highly dependent on the experimental conditions such as the specific separating columns, MS instruments and/or the buffer used. This variation hampers the exploitation of retention time for the glycan annotation from LC-MS data, especially when inter-laboratory data are compared. To incorporate the retention time of glycan across experiments, Glucose Unit Index (GUI) can be computed using the dextrin ladder as internal standard. The retention time of glycans are then calibrated with respect to glucose units derived from dextrin ladders. Despite the successful application of the GUI approach, the manual calibration process is quite tedious and often error prone. In this work, we present a standalone software tool GlycanGUI, with a graphic user interface to automatically carry out the GUI-based glycan annotation/quantification and subsequent data analysis. When tested on experimental data, GlycanGUI reported accurate GUI values compared with manual calibration, and thus is ready to be used for automated glycan annotation and quantification using GUI.

ScDetect: a rank-based ensemble learning algorithm for cell type identification of single-cell RNA sequencing in cancer.

Single-cell RNA sequencing (scRNA-seq) has enabled the characterization of different cell types in many tissues and tumor samples. Cell type identification is essential for single-cell RNA profiling, currently transforming the life sciences. Often, this is achieved by searching for combinations of genes that have previously been implicated as being cell-type specific, an approach that is not quantitative and does not explicitly take advantage of other scRNA-seq studies. Batch effects and different data platforms greatly decrease the predictive performance in inter-laboratory and different data type validation. Here, we present a new ensemble learning method named as 'scDetect' that combines gene expression rank-based analysis and a majority vote ensemble machine-learning probability-based prediction method capable of highly accurate classification of cells based on scRNA-seq data by different sequencing platforms. Because of tumor heterogeneity, in order to accurately predict tumor cells in the single-cell RNA-seq data, we have also incorporated cell copy number variation consensus clustering and epithelial score in the classification. We applied scDetect to scRNA-seq data from pancreatic tissue, mononuclear cells and tumor biopsies cells and show that scDetect classified individual cells with high accuracy and better than other publicly available tools. scDetect is an open source software. Source code and test data is freely available from Github (https://github.com/IVDgenomicslab/scDetect/) and Zenodo (https://zenodo.org/record/4764132#.YKCOlrH5AYN). The examples and tutorial page is at https://ivdgenomicslab.github.io/scDetect-Introduction/. And scDetect will be available from Bioconductor. Supplementary data are available at Bioinformatics online.

CEQAT-DGHS interlaboratory tests for chemical safety: Validation of laboratory test methods by determining the measurement uncertainty and probability of incorrect classification including so-called “Shark profiles”

Laboratory test results are of vital importance for correctly classifying and labelling chemicals as “hazardous” as defined in the UN Globally Harmonized System (GHS)/EC CLP Regulation or as “dangerous goods” as defined in the UN Recommendations on the Transport of Dangerous Goods. Interlaboratory tests play a decisive role in assessing the reliability of laboratory test results. Interlaboratory tests performed over the last 10 years have examined different laboratory test methods. After analysing the results of these interlaboratory tests, the following conclusions can be drawn: 1There is a need for improvement and validation for all laboratory test methods examined. 2To avoid any discrepancy concerning the classification and labelling of chemicals, the use of validated laboratory test methods should be state of the art, with the results accompanied by the measurement uncertainty and (if applicable) the probability of incorrect classification.This paper addresses the probability of correct/incorrect classification (for example, as dangerous goods) on the basis of the measurement deviation obtained from interlaboratory tests performed by the Centre for quality assurance for testing of dangerous goods and hazardous substances (CEQAT-DGHS) to validate laboratory test methods. This paper outlines typical results (e.g. so-called “Shark profiles” – the probability of incorrect classification as a function of the true value estimated from interlaboratory test data) as well as general conclusions and steps to be taken to guarantee that laboratory test results are fit for purpose and of high quality.

Accurate confidence intervals for inter-laboratory calibration and common mean estimation

For a calibration problem that arises in analytical chemistry, the Rocke-Lorenzato model and some generalizations are considered, so as to capture the near constant variability at very low levels of the analyte, and the increasing measurement variation with increased concentration of the analyte. For the common mean problem, a heteroscedastic one-way random effects model is often used to model the data and will be considered herein. Existing interval estimation procedures for these problems are likelihood based large sample procedures, and are not satisfactory, especially for small samples. A modified likelihood methodology, which can be numerically implemented, is shown to perform very well for the above problems. The analysis of inter-laboratory data is reported in order to illustrate the application of the proposed methods.

Multidimensional Ground Reaction Forces and Moments From Wearable Sensor Accelerations via Deep Learning.

Monitoring athlete internal workload exposure, including prevention of catastrophic non-contact knee injuries, relies on the existence of a custom early-warning detection system. This system must be able to estimate accurate, reliable, and valid musculoskeletal joint loads, for sporting maneuvers in near real-time and during match play. However, current methods are constrained to laboratory instrumentation, are labor and cost intensive, and require highly trained specialist knowledge, thereby limiting their ecological validity and wider deployment. An informative next step towards this goal would be a new method to obtain ground kinetics in the field. Here we show that kinematic data obtained from wearable sensor accelerometers, in lieu of embedded force platforms, can leverage recent supervised learning techniques to predict near real-time multidimensional ground reaction forces and moments (GRF/M). Competing convolutional neural network (CNN) deep learning models were trained using laboratory-derived stance phase GRF/M data and simulated sensor accelerations for running and sidestepping maneuvers derived from nearly half a million legacy motion trials. Then, predictions were made from each model driven by five sensor accelerations recorded during independent inter-laboratory data capture sessions. The proposed deep learning workbench achieved correlations to ground truth, by maximum discrete GRF component, of vertical Fz 0.97, anterior Fy 0.96 (both running), and lateral Fx 0.87 (sidestepping), with the strongest mean recorded across GRF components 0.89, and for GRM 0.65 (both sidestepping). These best-case correlations indicate the plausibility of the approach although the range of results was disappointing. The goal to accurately estimate near real-time on-field GRF/M will be improved by the lessons learned in this study. Coaching, medical, and allied health staff could ultimately use this technology to monitor a range of joint loading indicators during game play, with the aim to minimize the occurrence of non-contact injuries in elite and community-level sports.

Dissolution testing of modified release products with biorelevant media: An OrBiTo ring study using the USP apparatus III and IV

During the OrBiTo project, our knowledge on the gastrointestinal environment has improved substantially and biorelevant media composition have been refined. The aim of this study was to propose optimized biorelevant testing conditions for modified release products, to evaluate the reproducibility of the optimized compendial apparatus III (USP apparatus III) and compendial apparatus IV (USP apparatus IV, open-loop mode) dissolution methods and to evaluate the usefulness of these methods to forecast the direction of food effects, if any, based on the results of two «ring» studies and by using two model modified release (MR) products, Ciproxin / Cipro XR and COREG CR. Six OrBiTo partners participated in each of the ring studies. All laboratories were provided with standard protocols, pure drug substance, and dose units.For the USP apparatus III, the dissolution methods applied to Ciproxin / Cipro XR, a monolithic MR product of an active pharmaceutical ingredient (API) with moderate aqueous solubility, were robust with low intra- and inter-laboratory data variability. Data from all partners were in line on a qualitative basis with food effect data in humans. For the USP apparatus IV, the dissolution methods applied to COREG CR, a multiparticulate, pH dependent, MR product of an API with low and pH dependent solubility led to high intra- and inter- laboratory data variability. Data from all partners were in line, on a qualitative basis, with the previously observed food effects in humans.

Evaluation of the Solus One Salmonella Assay in Select Foods: Collaborative Study: First Action 2020.03.

The Solus One Salmonella immunoassay utilizes Salmonella specific selective media and automated liquid handling, for the rapid and specific detection of Salmonella species in select food types. The candidate method was evaluated using 375 g test portions in an unpaired study design for a single matrix, instant non-fat dry milk (NFDM) powder. The matrix was compared to the United States Food and Drug Administration/Bacteriological Analytical Manual (FDA/BAM) Chapter 5 Salmonella reference method. Eleven participants from 10 laboratories within academia and industry, located within the United States, Mexico, South Africa, Germany, and the United Kingdom, contributed data for the collaborative study. Three levels of contamination were evaluated for each matrix: an uninoculated control level [0 colony forming units (CFU)/test portion], a low inoculum level (0.2-2 CFU/test portion) and a high inoculum level (2-5 CFU/test portion). Statistical analysis was conducted according to the Probability of Detection (POD) statistical model. Results obtained for the low inoculum level test portions produced a dLPOD value with a 95% confidence interval between the candidate method confirmed (both alternative and conventional confirmation procedures) and the reference method of 0.07 (-0.02, 0.15). The dLPOD results indicate equivalence between the candidate method and the reference method for the matrix evaluated and the method demonstrated acceptable inter-laboratory reproducibility as determined in the collaborative evaluation. False positive and false negative rates were determined for the matrix and produce values of <2%. Based on the data generated, the method demonstrated acceptable inter-laboratory reproducibility data and statistical analysis.

International cooperation in age-dating uranium standards for nuclear forensics using the 231Pa/235U radiochronometer

During 2017–2018 Los Alamos National Laboratory, Lawrence Livermore National Laboratory and the China Institute of Atomic Energy collaborated in an interlaboratory 231Pa/235U radiochronometry exercise. The laboratories used different analytical methods to obtain a consensus model purification date for CRM U010 of December 28, 1958 ± 198 days and for CRM U850 of May 20, 1958 ± 363 days. These results agree with previously reported model dates using the 230Th/234U radiochronometer as well as the production histories of these materials. The concordance of interlaboratory data confirms the ability of laboratories to make reproducible radiochronometry measurements using distinct analytical approaches.

Effects of different constants and standards on the reproducibility of carbonate clumped isotope (Δ47 ) measurements: Insights from a long-term dataset.

Carbonate clumped isotope (Δ47 ) thermometry examines the temperature-dependent excess abundance of the 13 C-18 O bond in the carbonate lattice. Inconsistent temperature calibrations and standard values have been reported among laboratories, which has led to the use of equilibrated gases and carbonate standards for standardization. Furthermore, different acid fractionation factors and isotopic parameter sets have been proposed for improving inter-laboratory data comparability. However, few long-term datasets have been generated to explore the effects of these factors on the long-term reproducibility of Δ47 data within a laboratory. Four standards (ISTB-1, NBS-19, GBWO4416, and GB04417) were analyzed as unknowns by isotope ratio mass spectrometry from 2015 to 2019. The values of Δ47 were calibrated using the ETH standards. We investigated the Assonov, Brand, and Gonfiantini isotope parameter sets for carbon and oxygen isotopes, as well as two correction schemes of equilibrated gas and carbonate standardization, using the same sample measurements to determine which procedures enhanced reproducibility. ISTB-1 (calcite) and ZK312-346W (dolomite) were measured to determine the 90°C acid fractionation factor. The corrected 90°C acid fractionation factors are 0.076 ± 0.008‰ for ISTB-1 and 0.077 ± 0.009‰ for ZK312-346W. The choice of isotope parameter set had no significant influence on final Δ47 values in this study. However, using the Assonov parameters to calculate Δ47 values improved the reproducibility of the results. The use of carbonate standards improved reproducibility through time compared with the use of equilibrated gases for standardization. At 90°C, the acid fractionation factors of calcite and dolomite are statistically indistinguishable. We find an insignificant effect from changing the isotope parameter set, suggesting that the choice of isotope parameter set among laboratories is not a major factor affecting inter-laboratory reproducibility. We find that using carbonate standards improved the reproducibility of results, suggesting that the use of carbonate standards may help to achieve inter-laboratory comparability of results in future studies.

Rapid extraction method of polycyclic aromatic compounds in soil using basic silica selective pressurized liquid extraction

Complex chemical mixtures found in soils at contaminated sites typically includes polycyclic aromatic compounds (PACs), thus posing potential environmental and human health risks. Pressurized liquid extraction (PLE) followed by silica clean-up is one of the most often used extraction methods for PACs in soil. While silica clean-up provide satisfactory recovery of oxygenated polycyclic aromatic hydrocarbons (OPAHs), this technique provides limited recovery of azaarenes. In this work, we used PLE and in-cell clean up with basic silica to increase the recovery of OPAHs and azaarenes. The optimized selective pressurized liquid extraction (SPLE) method used 4 g basic silica, dichloromethane, 100% flush volume, 100 and 120 °C extraction temperatures, with two static cycles for each temperature, no rinse in between the two extractions, and 20 and 120 s purge for the first and second extraction temperature, respectively. The method was validated for a wide range of PAC groups, including OPAHs, azaarenes, alkylated PAHs, and sulfur heterocycles (SPACs), in total 87 PACs, using certified reference material and in comparison to the results from previous inter-laboratory data. Our SPLE method yielded results that are in agreement with certified values and inter-laboratory data from prior analysis. The SPLE method also yielded lower variation than the results from the inter-laboratory data for analysis of OPAH and azaarenes, suggesting better precision than previous methods. More importantly, the SPLE method increases sample analysis throughput as extra clean-up step is not necessary anymore. The SPLE method was then successfully applied to rapidly screen PACs in three soil samples.

Microplastic in soil–current status in Europe with special focus on method tests with Austrian samples

Within the last decade the production of plastic steadily increased and so did the amount of plastic waste. When bigger plastic pieces enter the environment, they are fragmented over time due to mechanical and environmental forces. The occurring and the directly released microplastic cause severe problems on soil organisms, due to alteration of physical properties and chemical interactions in the habitat. Main emissions sources of microplastic are different kinds of abrasions (road traffic, packaging, fibers of textiles during washing), waste disposal and drifts. Remains of mulching foils and protection nets spoil agricultural soil as well as the application of compost, sewage sludge and digestate, which may contain microplastic. Once released, microplastic accumulates much stronger in terrestrial than in aquatic systems. Spectroscopic, microscopic and thermo-analytical methods are commonly used to analyze microplastic in soil. The main challenges are to differentiate between soil matrix and plastic particles and to get rid of disturbing organic compounds. Unfortunately, there is no soil without plastic, no environmental blind sample to allow the finding of method limits. Inter-laboratory cooperation and data collection should allow estimation and comparison of emissions not only on European but on global scale. Investigations of Austrian samples provided a first orientation for regulations and measures to avoid further environmental pollution.

Barium Isotopic Compositions in Thirty‐Four Geological Reference Materials Analysed by MC‐ICP‐MS

Measurement of Ba isotope ratios of widely available reference materials is required for interlaboratory comparison of data. Here, we present new Ba isotope data for thirty‐four geological reference materials, including silicates, carbonates, river/marine sediments and soils. These reference materials (RMs) cover a wide range of compositions, with Ba mass fractions ranging from 6.4 to 1900 µg g−1, SiO2 from 0.62% to 90.36% m/m and MgO from 0.08% to 41.03% m/m. Accuracy and precision of our data were assessed by the analyses of duplicate samples and USGS rock RMs. Barium isotopic compositions for all RMs were in agreement with each other within uncertainty. The variation of δ138/134Ba in these RMs was up to 0.7‰. The shale reference sample, affected by a high degree of chemical weathering, had the highest δ138/134Ba (0.37 ± 0.03‰), while the stream sediment obtained from a tributary draining carbonate rocks was characterised by the lowest δ138/134Ba (−0.30 ± 0.05‰). Geochemical RMs play a fundamental role in the high‐precision and accurate determination of Ba isotopic compositions for natural samples with similar matrices. Analyses of these RMs could provide universal comparability for Ba isotope data and enable assessment of accuracy for interlaboratory data.

Re-Os geochronology for the NIST RM 8505 crude oil: The importance of analytical protocol and uncertainty

The National Institute of Science and Technology (NIST) research material (RM) 8505 is a Venezuelan crude oil certified for its vanadium concentration. It has recently been proposed as a matrix-matched standard for interlaboratory comparison of Re-Os isotopic analyses while serving as a benchmark for petroleum-based Re-Os method development. Here, the NIST RM 8505 oil is characterized using a multi-solvent asphaltene precipitation, permitting interlaboratory Re-Os data comparison and evaluation of techniques used to derive Re-Os isochron ages. We present a detailed discussion of analytical blank sources, critical evaluation of analytical uncertainties, method improvements and data corrections. Additionally, we provide a comprehensive discussion on the effect of data population size and analytical uncertainty on isochron statistics and the robustness of isochron ages. In addition to NIST RM 8505 (2.43 ± 0.15 ng/g Re, 30.0 ± 0.7 pg/g Os), we provide the first Re-Os data for NIST SRM 1634c (1.73 ± 0.01 ng/g Re, 32.5 ± 0.8 pg/g Os) and EnviroMAT SCP Science (39 ± 1 pg/g Re, 1.01 ± 0.02 pg/g Os), two other commercially available hydrocarbon trace metal standards.The application of several asphaltene (ASPH) precipitations using different n-alkane solvents (pentane, heptane and decane) for the NIST RM 8505 significantly improved the spread of data in the 187Re/188Os-187Os/188Os space. Multi-solvent asphaltene precipitations yield an asphaltene-only Model 1 isochron (75 ± 24 Ma) and the maltene-crude oil-asphaltene triplets yield a more precise Model 1 isochron age of 78.5 ± 2.3 Ma with a 187Os/188Osinitial of 0.877 ± 0.021. Our age is considerably older compared to a previously reported Model 1 age of 62.7 ± 5.7 Ma based on C7 ASPH-crude oil-MALT triplets (Liu and Selby, 2017) and considerably younger than the Model 1 age of 98.4 ± 9.5 Ma based on ASPH separates (Liu et al., 2019). The analytical reasons leading to these age differences are discussed in this paper.The geological context for the NIST 8505 oil is unknown, therefore we use trace metal data (Ni, V, Fe, Mo, etc.) to derive plausible constraints for the origin of this oil. The NIST 8505 oil shows trace metal data similar to published data for oils from the Urdaneta district, the La Paz, Mara and Lagunillas oil fields and source rocks of the La Luna Formation in the Maracaibo Basin, Venezuela. In this geological context, our ~79 Ma age for the NIST 8505 oil implies a Late Cretaceous early hydrocarbon generation event from older Upper Cretaceous source rocks and overlaps with the youngest age of potential source rocks in the Maracaibo Basin. However, the age of large-scale oil generation in the Maracaibo Basin is significantly younger, lasting from the Oligocene to the Pliocene.

Analytical Quality Requirements in Human Biomonitoring Programs: Trace Elements in Human Blood.

Human biomonitoring (HBM) programs consist of several interrelated and equally important steps. Of these steps, the study design must answer a specific question: How many individuals must be recruited in order to define the spatial or temporal trends of exposure to environmental pollutants in a given HBM study? Two components must be considered at this stage: the population variability of the expected exposure and the performance characteristics of the analytical methods used. The objective of the present study was to quantify the contribution to the required sample size arising from (i) measurement uncertainty and (ii) inter-laboratory measurement variability. For this purpose, the sample size was calculated using the measurement uncertainty of one laboratory, inter-laboratory comparison exercise data, and population variability for commonly studied metals (mercury, cadmium, and lead) in blood. Measurement uncertainty within one laboratory proved to have little influence on the sample size requirements, while the inter-laboratory variability of the three metals increased the requirements considerably, particularly in cases of low population variability. The multiple laboratories approach requires that laboratory variability be considered as early as the planning stage; a single-laboratory approach is thus a cost-effective compromise in HBM to reduce variability due to the participation of different laboratories.

Proposal for a chemically consistent way to annotate ions arising from the analysis of reference compounds under ESI conditions: A prerequisite to proper mass spectral database constitution in metabolomics.

Nowadays, high-resolution mass spectrometry is widely used for metabolomic studies. Thanks to its high sensitivity, it enables the detection of a large range of metabolites. In metabolomics, the continuous quest for a metabolite identification as complete and accurate as possible has led during the last decade to an ever increasing development of public MS databases (including LC-MS data) concomitantly with bioinformatic tool expansion. To facilitate the annotation process of MS profiles obtained from biological samples, but also to ease data sharing, exchange, and exploitation, the standardization and harmonization of the way to describe and annotate mass spectra seemed crucial to us. Indeed, under electrospray (ESI) conditions, a single metabolite does not produce a unique ion corresponding to its protonated or deprotonated form but could lead to a complex mixture of signals. These MS signals result from the existence of different natural isotopologues of the same compound and also to the potential formation of adduct ions, homomultimeric and heteromultimeric ions, fragment ions resulting from "prompt" in-source dissociations. As a joint reflection process within the French Infrastructure for Metabolomics and Fluxomics (MetaboHUB) and with the purpose of developing a robust and exchangeable annotated MS database made from pure reference compounds (chemical standards) analysis, it appeared to us that giving the metabolomics community some clues to standardize and unambiguously annotate each MS feature was a prerequisite to data entry and further efficient querying of the mass spectral database. The use of a harmonized notation is also mandatory for interlaboratory MS data exchange. Additionally, thorough description of the variety of MS signals arising from the analysis of a unique metabolite might provide greater confidence on its annotation.

Discrimination of Camellia japonica cultivars and chemometric models: An interlaboratory study

Camellia japonica is a valued plant since ancient times throughout the world mostly due to their ornamental flowers. It has a high number of cultivars, with very similar phenotypic and genotypic characteristics which are difficult to discriminate, being some of them often rare and with a high price at the market. Their discrimination is mostly done through visual inspection of the morphologic characteristics which is a hard and inefficient task. Spectroscopic techniques had already been used for taxonomic purposes at species and sub-species level with success and could be an alternative for accurate C. japonica cultivars discrimination. Despite the already recognized success of such techniques, most of the studies arises from a single laboratory and little is known about the robustness of these techniques regarding interlaboratory data transferability. In this context, the work developed herein presents a double aim: (I) to explore the ability of near infrared (NIR) spectroscopy and partial least square – discriminant analysis (PLS-DA) to discriminate C. japonica cultivars and (II) to evaluate data transferability between two independent laboratories (Lab A and Lab B). Air-dried leaves NIR spectra of 43 C. japonica plants (15 distinct cultivars) were acquired in both laboratories using two similar NIR instruments (same manufacturer and model). Spectra were further modelled by PLS-DA after exploratory analysis using principal component analysis (PCA): (I) individually for Lab A and Lab B; (II) using Lab A as calibration and Lab B as validation set and vice-versa and (III) with using Lab A and Lab B data together. The percentage of C. japonica cultivars discrimination for both laboratories was nearly the same (around 83%) indicating no significant differences between Lab A and Lab B analysis. However, the results were quite poor when spectra were modelled with data from a single laboratory and validated with the other (65.5 and 63.8%). When data were merged, 85.9% of correct cultivars assignments were obtained. The results herein obtained could benefit of including additional cultivars and plants; but demonstrated the ability of NIR spectroscopy for C. japonica cultivars discrimination. Regarding data transferability, even when dealing with a similar instrument, some issues arisen preventing easy and efficient spectral library transfers.

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.

Evaluation of nine USGS reference materials for quality control through Univariate Data Analysis System, UDASys3

Data quality in any science plays a fundamental role to achieve valid inferences from experimental data. Inter-laboratory geochemical data for nine geochemical reference materials (GRMs) issued from the United States Geological Survey (USGS) were compiled from numerous literature sources. These data were processed in the third version of UDASYS (UDASys3; Univariate Data Analysis System), which applies automatically a refined statistical procedure to obtain both central tendency and dispersion parameters for univariate statistical data arrays and generates brief as well as extended reports. We present improved working values for central tendency and dispersion (total uncertainty) parameters for 10 major elements (SiO2 to P2O5), 14 rare earth elements (REE; La to Lu), and 42 (B to Zr; Ac to W) trace elements, along with LOI, CO2, H2O+, Cl, F, and S for these GRMs. Because the total uncertainty values of the mean reported in this work are generally lower than the literature uncertainties, the present statistical values are superior to those reported in all previous compilations. This implies that our statistical information will be more useful for instrumental calibration and quality control. An example is presented of the instrumental X-ray florescence spectrometric calibration, in which both sets of GRM concentrations and their 99% uncertainties (literature as well as those obtained from UDASys3) were used for the calibration of 10 major elements. The results show that UDASys3 provided generally more reliable calibration regression equations (higher linear correlation coefficient and lesser uncertainty in intercept and slope values) than the literature concentration estimates.

Xpert® BCR-ABL Ultra¥ Demonstrated Good Inter-Laboratory Reproducibility in Three Consecutive GBMHM External Quality Assessments

Introduction: Monitoring BCR-ABL transcript levels in peripheral whole blood of patients using real-time quantitative PCR is standard of care in the management of Chronic Myeloid Leukemia. Therefore, it is essential to ensure that variability in testing methodology is tightly controlled and compatible with accurate assessments of treatment response. Xpert® BCR-ABL Ultra¥ (Ultra) is an automated cartridge-based assay developed by Cepheid for sensitive assessment of BCR-ABL p210 transcript levels. Every Ultra assay is standardized onto the WHO International Scale (IS) during production. The GBMHM (Groupe des Biologistes Moléculaires des Hémopathies Malignes) program has previously validated a sample preparation protocol designed for Ultra External Quality Assessment (EQA). We report here results from 3 consecutive EQA rounds for Ultra.Methods: Three Ultra EQA panels have been produced at GBMHM, containing a total of 11 members. Each member was produced from two contrived cell lysates, one BCR-ABL negative and one BCR-ABL e14a2/b3a2 positive, prepared according to the two-step Ultra sample preparation protocol per the package insert, but starting from 4 mL of a cell suspension titrating 2.5x106 cells/mL instead of blood (Table 1). Typically, 30 ml of each panel member was produced and aliquoted into 1mL samples before shipping on dry-ice to the participating laboratories. Upon receipt, individual laboratories further prepared the samples for testing following the 2nd lysis procedures.Results: A total of 209 samples were sent to up to 21 different labs and tested in 15 different Ultra lots. The %BCR-ABL/ABL IS ratios in 207 of 209 samples were returned to the GBMHM EQA program. The calculated average ratios were between 0.0066% and 24% IS with coefficients of variation (CVs) ranging from 16% to 77% (Table 1.). The data showed lower CVs at higher %BCR-ABL/ABL ratios. Nighty-five percent confidence intervals (95% CIs) for distribution of the average ratios ranged from ±4.8 fold for sample UC in EQA Round 19.2 to ±1.4 fold for sample UB in Round 19.2. Inter-lab reproducibility was acceptable, with less than 50% CV in 5 out of 8 panel members. The highest CV was observed in the panel member with an average ratio less than 0.01%IS. There was a trend towards an improvement of the CVs in the last EQA round compatible with an ongoing learning process.Conclusions: Overall, inter-laboratory reproducibility data obtained here are compatible with accurate measurements of BCR-ABL mRNA levels using Ultra, demonstrating equivalent or better results compared with non-automated methods. Since 15 different Ultra lots were used, this study verified that the Ultra standardization process is fully operative. To our knowledge, this is the first assessment of Ultra inter-laboratory reproducibility.¥For Research Use Only. Not for use in diagnostic procedures. Not reviewed by any regulatory body. [Display omitted] DisclosuresDay:Cepheid: Employment. Cayuela:Cepheid: Other: financial sponsor to attend John Goldman Conference 2017.