Excess Variance Research Articles

Pilot study on peptide purity - glycated hexapeptide of HbA1c

Main textUnder the auspices of the Protein Analysis Working Group (PAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a pilot study, CCQM-P55.2.c, was coordinated by the Bureau International des Poids et Mesures (BIPM), the Health Sciences Authority (HSA) of Singapore and the Chinese National Institute of Metrology (NIM). Three Metrology Institutes or Designated Institutes and the BIPM participated. Participants were required to assign the mass fraction of glycated hexapeptide of HbA1c (GE) present as the main component in the comparison sample for CCQM-P55.2.c. The comparison samples were prepared by HSA/BIPM from synthetic GE purchased from a commercial supplier and used as provided without further treatment or purification.GE was selected to be representative of the performance of a laboratory's measurement capability for the purity assignment of chemically synthesized peptides of known sequence, without cross-links, up to 5 kDa and modification (mono-glycation). It was anticipated to provide an analytical measurement challenge representative for the value-assignment of compounds of broadly similar structural characteristics.The majority of participants used amino acid analysis (PICAA) or quantitative nuclear magnetic resonance (PICqNMR) spectroscopy with a correction for structurally-related peptide impurities. It was decided to assign reference values (RVs) based on the KCRVs of CCQM-K115.c for both the GE mass fraction and the mass fraction of the peptide related impurities as indispensable contributor regardless of the use of PICAA, mass balance or any other approach to determine the GE purity. This allowed participants to demonstrate the efficacy of their implementation of the approaches used to determine the GE mass fraction. In particular, it allows participants to demonstrate the efficacy of their implementation of peptide related impurity identification and quantification.More detailed studies on the identification/quantification of peptide related impurities revealed that the integrity of the impurity profile of the related peptide impurities obtained by the participant is crucial for the impact on accuracy of the GE mass fraction assignment.The assessment of the mass fraction of peptide impurities is based on the assumption that all results are directly taken for the calculation of the RVPepImp by use of random-effects meta-analysis (DerSimonian-Laird (DSL) variance-weighted mean). The RVPepImp of 45.4 mg/g is associated with a corresponding expanded uncertainty of 9.5 mg/g (k =2.26) providing a more realistic basis of evaluation for the capabilities of the participants to identify/quantify peptide related impurities. Inspection of the degree of equivalence plots for the mass fraction of peptide impurities and additional information obtained from the peptide related impurity profile indicates that in all cases the major related peptide impurities have been identified and quantified.The approach selected to obtain a RVGE for the mass fraction of GE is based on the DerSimonian-Laird (DSL) variance-weighted mean. The DSL mean takes into account the uncertainties of the results while introducing sufficient excess variance to allow for their observed dispersion resulting in a larger expanded uncertainty U(RVGE). The RVGE based on CCQM-K115.c is 628 mg/g with a corresponding expanded uncertainty of the RVGE of 27 mg/g (k =2.26). All GE mass fraction results are in agreement with the RVGE.To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Observations of Nutrient Supply by Mesoscale Eddy Stirring and Small‐Scale Turbulence in the Oligotrophic North Atlantic

AbstractSustaining biological export over the open ocean requires a physical supply of nutrients to the mixed layer and thermocline. The relative importance of diapycnal mixing, diapycnal advection, and isopycnal stirring by mesoscale eddies in providing this nutrient supply is explored using a field campaign in oligotrophic waters in the subtropical North Atlantic, consisting of transects over and off the mid‐Atlantic ridge. Eddy stirring rates are estimated from the excess temperature variance dissipation relative to the turbulent kinetic energy dissipation, and using eddy statistics from satellite observations combined with 9‐month‐long mooring data. The vertical nutrient fluxes by diapycnal mixing, diapycnal advection, and isopycnal mesoscale eddy stirring are assessed using nitrate measurements from observations or a climatology. Diapycnal mixing and advection provide a nutrient supply within the euphotic zone, but a loss of nutrients within the upper thermocline. Eddy stirring augments, and is comparable to, the diapycnal transfer of nutrients within the summertime upper thermocline, while also acting to replenish nutrients within the deeper parts of the thermocline. The eddy supply of nitrate is relatively small in the center of the subtropical gyre, reaching up to 0.06 mol N m−2yr−1, but is likely to be enhanced on the flanks of the gyre due to larger isopycnal slopes and lateral nitrate gradients. The nutrient supply to the euphotic zone is achieved via a multistage mechanism: a diapycnal transfer of nutrients by small‐scale turbulence to the euphotic zone, and an isopycnal stirring of nutrients by mesoscale eddies replenishing nutrients in the upper thermocline.

A numerical study of 21-cm signal suppression and noise increase in direction-dependent calibration of LOFAR data

ABSTRACT We investigate systematic effects in direction-dependent gain calibration in the context of the Low-Frequency Array (LOFAR) 21-cm Epoch of Reionization (EoR) experiment. The LOFAR EoR Key Science Project aims to detect the 21-cm signal of neutral hydrogen on interferometric baselines of 50–250 λ. We show that suppression of faint signals can effectively be avoided by calibrating these short baselines using only the longer baselines. However, this approach causes an excess variance on the short baselines due to small gain errors induced by overfitting during calibration. We apply a regularized expectation–maximization algorithm with consensus optimization (sagecal-co) to real data with simulated signals to show that overfitting can be largely mitigated by penalising spectrally non-smooth gain solutions during calibration. This reduces the excess power with about a factor of 4 in the simulations. Our results agree with earlier theoretical analysis of this bias-variance trade off and support the gain-calibration approach to the LOFAR 21-cm signal data.

Poisson regression for linguists: A tutorial introduction to modelling count data with brms

AbstractCount data is prevalent in many different areas of linguistics, such as when counting words, syntactic constructions, discourse particles, case markers, or speech errors. The Poisson distribution is the canonical distribution for characterising count data with no or unknown upper bound. Given the prevalence of count data in linguistics, Poisson regression has wide utility no matter what subfield of linguistics is considered. However, in contrast to logistic regression, Poisson regression is surprisingly little known. Here, we make a case for why linguists need to consider Poisson regression, and give recommendations for when Poisson regression is more appropriate compared to logistic regression. This tutorial introduces readers to foundational concepts needed to understand the basics of Poisson regression, followed by a hands‐on tutorial using the R package brms. We discuss a dataset where Catalan and Korean speakers change the frequency of their co‐speech gestures as a function of politeness contexts. This dataset also involves exposure variables (the incorporation of time to deal with unequal intervals) and overdispersion (excess variance). Altogether, we hope that more linguists will consider Poisson regression for the analysis of count data.

Exploring black hole scaling relations via the ensemble variability of active galactic nuclei

ABSTRACT An empirical model is presented that links, for the first time, the demographics of active galactic nuclei (AGN) to their ensemble X-ray variability properties. Observations on the incidence of AGN in galaxies are combined with (i) models of the power spectrum density (PSD) of the flux variations of AGN and (ii) parametrizations of the black hole mass versus stellar mass scaling relation to predict the mean excess variance of active black hole populations in cosmological volumes. We show that the comparison of the model with observational measurements of the ensemble excess variance as a function of X-ray luminosity provides a handle on both the PSD models and the black hole mass versus stellar mass relation. We find strong evidence against a PSD model that is described by a broken power law and a constant overall normalization. Instead, our analysis indicates that the amplitude of the PSD depends on the physical properties of the accretion events, such as the Eddington ratio and/or the black hole mass. We also find that current observational measurements of the ensemble excess variance are consistent with the black hole mass versus stellar mass relation of local spheroids based on dynamically determined black hole masses. We also discuss future prospects of the proposed approach to jointly constrain the PSD of AGN and the black hole mass versus stellar mass relation as a function of redshift.

The nature of the extreme X-ray variability in the NLS1 1H 0707-495

ABSTRACT We examine archival XMM-Newton data on the extremely variable narrow-line Seyfert 1 active galactic nucleus (AGN) 1H 0707-495. We construct fractional excess variance (Fvar) spectra for each epoch, including the recent 2019 observation taken simultaneously with eROSITA. We explore both intrinsic and environmental absorption origins for the variability in different epochs, and examine the effect of the photoionized emission lines from outflowing gas. In particular, we show that the unusual soft variability first detected by eROSITA in 2019 is due to a combination of an obscuration event and strong suppression of the variance at 1 keV by photoionized emission, which makes the variance below 1 keV appear more extreme. We also examine the variability on long time-scales, between observations, and find that it is well described by a combination of intrinsic variability and absorption variability. We suggest that the typical extreme high frequency variability, which 1H 0707-495 is known for, is intrinsic to the source, but the large amplitude, low frequency variability that causes prolonged low-flux intervals is likely dominated by variable low-ionization, low-velocity absorption.

Bayesian uncertainty analysis of inversion models applied to the inference of thermal properties of walls

In this work, we propose a fully Bayesian uncertainty analysis of the indirect measurement of thermal properties of walls from in situ temperature and flux measurements, obtained with an active method, using a one dimensional transient thermal model. We show that this approach is able to take into account the uncertainty of the inputs of the thermal model and the uncertainty of the output observations, for a more reliable uncertainty estimation of the calibration parameters and any derived quantity. For this problem, we improve the classical Bayesian inversion model by taking into account underestimated uncertainty on reported output observations, which is a frequently encountered issue in practice. We provide some recommendations for a wider applicability of the method. We illustrate the principles of uncertainty evaluation of the Guide to the Expression of Uncertainty in Measurement in terms of a real case study to evaluate the thermal resistance of a multilayer wall placed in a climatic chamber. For this application, we compare results of the Bayesian inversion with classical steady-state results in comparable experimental conditions. We perform a sensitivity analysis to study the effect of duration, input uncertainties and excess variance prior, and we make recommendations. R code is made available that enables a Bayesian uncertainty evaluation of inversion models for related applications.

L2-Penalized temporal logit-mixed models for the estimation of regional obesity prevalence over time.

Obesity is considered to be one of the primary health risks in modern industrialized societies. Estimating the evolution of its prevalence over time is an essential element of public health reporting. This requires the application of suitable statistical methods on epidemiologic data with substantial local detail. Generalized linear-mixed models with medical treatment records as covariates mark a powerful combination for this purpose. However, the task is methodologically challenging. Disease frequencies are subject to both regional and temporal heterogeneity. Medical treatment records often show strong internal correlation due to diagnosis-related grouping. This frequently causes excessive variance in model parameter estimation due to rank-deficiency problems. Further, generalized linear-mixed models are often estimated via approximate inference methods as their likelihood functions do not have closed forms. These problems combined lead to unacceptable uncertainty in prevalence estimates over time. We propose an l2-penalized temporal logit-mixed model to solve these issues. We derive empirical best predictors and present a parametric bootstrap to estimate their mean-squared errors. A novel penalized maximum approximate likelihood algorithm for model parameter estimation is stated. With this new methodology, the regional obesity prevalence in Germany from 2009 to 2012 is estimated. We find that the national prevalence ranges between 15 and 16%, with significant regional clustering in eastern Germany.

Using a machine learning proxy for localization in ensemble data assimilation

Ensemble data assimilation methods, particularly iterative forms of ensemble smoother, are very useful assisted history matching techniques. One of the main challenges in the application of these methods is the excessive variance loss due to sampling errors occasioned by the limited size ensembles used in practical cases. The standard procedure to mitigate this problem is called distance-based localization. However, in this case, the data assimilation performance becomes highly dependent on the choice of the localization region. Moreover, there are several relevant examples of non-local model parameters and data types, in which cases, distance-based localization does not apply. This paper proposes a distance-free localization procedure that combines a least-squares support vector (LS-SVR) proxy with a non-isotropic tapering function proposed in the literature. We tested the proposed method in two versions of the PUNQ-S3 problem. In the first version, we tested the method to localize scalar (non-local) parameters. The results show relevant improvements, especially in terms of preserving the posterior variance of the ensemble compared to methods investigated in Lacerda et al. (J. Pet. Sci. Eng. 172,690–706, 2019). The second version considered the problem of localization of grid parameters. In this case, the proposed method outperformed a distance-based localization approach proposed in the literature.

No support for the hereditarian hypothesis of the Black-White achievement gap using polygenic scores and tests for divergent selection.

Debate about the cause of IQ score gaps between Black and White populations has persisted within genetics, anthropology, and psychology. Recently, authors claimed polygenic scores provide evidence that a significant portion of differences in cognitive performance between Black and White populations are caused by genetic differences due to natural selection, the "hereditarian hypothesis." This study aims to show conceptual and methodological flaws of past studies supporting the hereditarian hypothesis. Polygenic scores for educational attainment were constructed for African and European samples of the 1000 Genomes Project. Evidence for selection was evaluated using an excess variance test. Education associated variants were further evaluated for signals of selection by testing for excess genetic differentiation (Fst ). Expected mean difference in IQ for populations was calculated under a neutral evolutionary scenario and contrasted to hereditarian claims. Tests for selection using polygenic scores failed to find evidence of natural selection when the less biased within-family GWAS effect sizes were used. Tests for selection using Fst values did not find evidence of natural selection. Expected mean difference in IQ was substantially smaller than postulated by hereditarians, even under unrealistic assumptions that overestimate genetic contribution. Given these results, hereditarian claims are not supported in the least. Cognitive performance does not appear to have been under diversifying selection in Europeans and Africans. In the absence of diversifying selection, the best case estimate for genetic contributions to group differences in cognitive performance is substantially smaller than hereditarians claim and is consistent with genetic differences contributing little to the Black-White gap.

Modelling X-ray RMS spectra II: the ultrafast outflow of PDS 456

ABSTRACT We present an improved model for excess variance spectra describing ultrafast outflows and successfully apply it to the luminous ($L_{\rm bol}\sim 10^{47}\mathrm{erg}\, \mathrm{s}^{-1}$) low-redshift (z = 0.184) quasar Pico del Dias Survey (PDS) 456. The model is able to account well for the broadening of the spike-like features of these outflows in the excess variance spectrum of PDS 456, by considering two effects: a correlation between the outflow velocity and the logarithmic X-ray flux and intrinsic Doppler broadening with $v_\mathrm{int} = 10^4\, \mathrm{km}\, \mathrm{s}^{-1}$. The models were generated by calculating the fractional excess variance of count spectra from a Monte Carlo simulation. We find evidence that the outflow in PDS 456 is structured, i.e. there exist two or more layers with outflow velocities $0.27\!-\!0.30\, c$, $0.41\!-\!0.49\, c$, and $0.15\!-\!0.20\, c$ for a possible third layer, which agrees well with the literature. We discuss the prospects of generally applicable models for excess variance spectra for detecting ultrafast outflows and investigating their structure. We provide an estimate for the strength of the correlation between the outflow velocity and the logarithmic X-ray flux and investigate its validity.

Individual and Area-level Factors Contributing to the Geographic Variation in Ambulatory Care Sensitive Conditions in Finland: A Register-based Study.

Measuring primary health care (PHC) performance through hospitalizations for ambulatory care sensitive conditions (ACSCs) remains controversial-recent cross-sectional research claims that its geographic variation associates more with individual socioeconomic position (SEP) and health status than PHC supply. To clarify the usage of ACSCs as a PHC performance indicator by quantifying how disease burden, both PHC and hospital supply and spatial access contribute over time to geographic variation in Finland when individual SEP and comorbidities were adjusted for. The Finnish Care Register for Health Care provided hospitalizations for ACSCs (divided further into subgroups of acute, chronic, and vaccine-preventable causes) in 2011-2017. With 3-level nested multilevel Poisson models-individuals, PHC authorities, and hospital authorities-we estimated the proportion of the variance in ACSCs explained by selected factors at 3 time periods. In age-adjusted and sex-adjusted analysis of total ACSCs the variances between hospital authorities was nearly twice that between PHC authorities. Individual SEP and comorbidities explained 19%-30% of the variance between PHC authorities and 25%-36% between hospital authorities; and area-level disease burden and arrangement and usage of hospital care a further 14%-16% and 32%-33%-evening out the unexplained variances between PHC and hospital authorities. Alongside individual factors, areas' disease burden and factors related to hospital care explained the excess variances in ACSCs captured by hospital authorities. Our consistent findings over time suggest that the local strain on health care and the regional arrangement of hospital services affect ACSCs-necessitating caution when comparing areas' PHC performance through ACSCs.

Composite-asset-risk approach to solving the equity premium puzzle

We demonstrate that the equity premium puzzle can be explained by a combination of modern portfolio theory (MPT) and a consumption capital asset pricing model (CAPM). We assume that an investor maximizes her/his utility as determined by the expected return and risk for a composite asset portfolio including purchasing an equity and selling a riskless asset jointly. If the variance of the composite asset is greater than that expected by the CAPM, then the equity premium puzzle can be resolved according to the MPT. The intrinsic bubbles may explain the observed excessive expectation and variance of equity return premium.

BBN constraints on dark radiation isocurvature

The existence of dark radiation that is completely decoupled from the standard model in the early Universe leaves open the possibility of an associated dark radiation isocurvature mode. We show that the presence of dark radiation isocurvature leads to spatial variation in the primordial abundances of helium and deuterium due to spatial variation in Neff during Big Bang nucleosynthesis. We use the result to constrain the existence of such an isocurvature mode on scales down to ∼ 1 Mpc scales. By measuring the excess variance in the primordial helium to hydrogen and deuterium to hydrogen ratio in different galaxies, we constrain the variance in average isocurvature in a galaxy to be less than 0.13/Δ N̄eff at 95% confidence. Here Δ N̄eff is the spatially averaged increase in Neff due to the additional dark radiation component.

The soft excess of the NLS1 galaxy Mrk 359 studied with an XMM-Newton-NuSTAR monitoring campaign

Context. Joint XMM-Newton and NuSTAR multiple exposures allow us to disentangle the different emission components of active galactic nuclei (AGNs) and to study the evolution of their different spectral features. In this work, we present the timing and spectral properties of five simultaneous XMM-NewtonandNuSTAR observations of the Narrow Line Seyfert 1 galaxy Mrk 359. Aims. We aim to provide the first broadband spectral modeling of Mrk 359 describing its emission spectrum from the UV up to the hard X-rays. Methods. We performed temporal and spectral data analysis, characterising the amplitude and spectral changes of the Mrk 359 time series and computing the 2–10 keV normalised excess variance. The spectral broadband modelling assumes the standard hot Comptonising corona and reflection component, while for the soft excess we tested two different models: a warm, optically thick Comptonising corona (the two-corona model) and a reflection model in which the soft-excess is the result of a blurred reflected continuum and line emission (the reflection model). Results. High and low flux states were observed during the campaign. The former state has a softer spectral shape, while the latter shows a harder one. The photon index is in the 1.75–1.89 range, and only a lower limit to the hot-corona electron temperature can be found. A constant reflection component, likely associated with distant matter, is observed. Regarding the soft excess, we found that among the reflection models we tested, the one providing the better fit (reduced χ2 = 1.14) is the high-density one. However, a significantly better fit (reduced χ2 = 1.08) is found by modelling the soft excess with a warm Comptonisation model. Conclusions. The present analysis suggests the two-corona model as the best scenario for the optical-UV to X-ray emission spectrum of Mrk 359.

Evaluating the reliability of U–Pb laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) carbonate geochronology: matrix issues and a potential calcite validation reference material

Abstract. We document that the reliability of carbonate U–Pb dating by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is improved by matching the aspect ratio of the LA single-hole drilling craters and propagating long-term excess variance and systematic uncertainties. We investigated the impact of different matrices and ablation crater geometries using U–Pb isotope analyses of one primary (WC-1) and two secondary reference materials (RMs). Validation RMs (VRMs) include a previously characterised one (ASH-15D) and a new candidate (JT), characterised by ID-TIMS (intercept age: 13.797±0.031 Ma) with excellent agreement to pooled LA-ICP-MS measurements (13.75±0.11 | 0.36 Ma), a U concentration of approx. 1 µg g−1 and 238U∕206Pb ratios from 5 to 460, defining the isochron well. Differences in ablation crater depth to diameter ratios (aspect ratio) introduce an offset due to downhole fractionation and/or matrix effects. This effect can be observed either when the crater size between U–Pb RM and the sample changes or when the ablation rate for the sample is different than for the RM. Observed deviations are up to 20 % of the final intercept age depending on the degree of crater geometry mismatch. The long-term excess uncertainty was calculated to be in the range of 2 % (ASH-15D) to 2.5 % (JT), and we recommend propagating this uncertainty into the uncertainty of the final results. Additionally, a systematic offset to the ID-TIMS age of 2 %–3 % was observed for ASH-15D but not for JT. This offset might be due to different ablation rates of ASH-15D compared to the primary RM or remaining matrix effects, even when the aspect ratios chosen are similar.

Long term γ-ray variability of blazars

We used the data from the Fermi Gamma-ray Space Telescope to characterise the γ-ray flux variability of blazars on month-like time scales. Our sample consists of 1120 blazars of which 481 are flat spectrum radio quasars (FSRQs) and 639 are BL Lac objects (BL Lacs). We generated monthly binned light curves of our sample for a period of approximately nine years from 2008 August to 2017 December and quantified variability by using excess variance (Fvar). On month-like time scales, 371/481 FSRQs are variable (80%), while only about 50% (304/639) of BL Lacs are variable. This suggests that FSRQs are more variable than BL Lac objects. We find a mean Fvar of 0.55 ± 0.33 and 0.47 ± 0.29 for FSRQs and BL Lacs respectively. Large Fvar in FSRQs is also confirmed from the analysis of the ensemble structure function. By Dividing our sample of blazars based on the position of the synchrotron peak in their broad-band spectral energy distribution, we find that the low synchrotron peaked (LSP) sources have the largest mean Fvar value of 0.54 ± 0.32 while the intermediate synchrotron peaked (ISP) and high synchrotron peaked sources have mean Fvar values of 0.45 ± 0.25 and 0.47 ± 0.33 respectively. On month-like time scales, we find FSRQs to show a high duty cycle (DC) of variability of 66% relative to BL Lacs that show a DC of 36%. We find that both the Fvar and time scale of variability (τ) do not correlate with MBH. We note that Fvar is found to be weakly correlated with Doppler factor (δ) and τ is also weakly correlated with δ. Most of the sources in our sample have τ of the order of days, which might be related to processes in the jet. We find marginal difference in the distribution of τ between FSRQs and BL Lacs.

Searching for ultra-fast outflows in AGN using variability spectra

ABSTRACT We present a qualitative search for ultra-fast outflows (UFOs) in excess variance spectra of radio-quiet active galactic nuclei (AGNs). We analyse 42 sources from the spectroscopic UFO detection sample, and an additional 22 different sources from the variability sample. A total of 58 sources have sufficient observational data from XMM–Newton EPIC-pn and variability for an excess variance spectrum to be calculated. We examine these spectra for peaks corresponding to variable blue-shifted H- and He-like ion absorption lines from UFOs. We find good evidence for such outflows in 28 per cent of the AGN sample and weak evidence in a further 31 per cent, meaning that ∼30–60 per cent of the AGN sample hosts such UFOs. The mean and median blue-shifted velocity is found to be ∼0.14c and 0.12c, respectively. Current variability methods allow for a fast, model-independent determination of UFOs; however, further work needs to be undertaken to better characterize the statistical significance of the peaks in these spectra by more rigorous modelling. Detecting good evidence for variable UFO lines in a large number of sources also lays the groundwork for detailed analysis of the variability time-scales of the absorbers. This will allow us to probe their densities and hence distances from the central supermassive black hole.

Key comparison study on peptide purity - synthetic oxytocin

Under the auspices of the Protein Analysis Working Group (PAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a key comparison, CCQM-K115.b, was coordinated by the Bureau International des Poids et Mesures (BIPM) and the Chinese National Institute of Metrology (NIM). Seven Metrology Institutes or Designated Institutes and the BIPM participated. Participants were required to assign the mass fraction of oxytocin (OXT) present as the main component in the comparison sample for CCQM-K115.b. The comparison samples were prepared from synthetic OXT purchased from a commercial supplier and used as provided without further treatment or purification.OXT was selected to be representative of the performance of a laboratory's measurement capability for the purity assignment of chemically synthesized peptides of known sequence, with one cross-link and up to 5 kDa. It was anticipated to provide an analytical measurement challenge representative for the value-assignment of compounds of broadly similar structural characteristics.The majority of participants used amino acid analysis (PICAA) or quantitative nuclear magnetic resonance (PICqNMR) spectroscopy with a correction for structurally-related peptide impurities approach as the amount of material that has been provided to each participant (25 mg) is insufficient to perform a full mass balance based characterization of the material by a participating laboratory. The coordinators, both the BIPM and the NIM, were the laboratories to use the mass balance approach as they had more material available.It was decided to propose KCRVs for both the OXT mass fraction and the mass fraction of the peptide related impurities as indispensable contributor regardless of the use of PICAA, PICqNMR or mass balance to determine the OXT purity. This allowed participants to demonstrate the efficacy of their implementation of the approaches used to determine the OXT mass fraction. In particular, it allows participants to demonstrate the efficacy of their implementation of peptide related impurity identification and quantification.More detailed studies on the identification/quantification of peptide related impurities and the hydrolysis efficiency revealed that the integrity of the impurity profile of the related peptide impurities obtained by the participant is crucial for the impact on accuracy of the OXT mass fraction assignment.The assessment of the mass fraction of peptide impurities is based on the assumption that only the Largest Consistent Subset (LCS) of results is taken for the calculation of the KCRVPepImp by use of the weighted mean. The KCRVPepImp of 31.6 mg/g is associated with a small corresponding expanded uncertainty of ±1.4 mg/g (k =2) providing a more realistic basis of evaluation for the capabilities of the participants to identify/quantify peptide related impurities. Inspection of the degree of equivalence plots for the mass fraction of peptide impurities and additional information obtained from the peptide related impurity profile indicates that in many cases the major related peptide impurities have been identified and quantified.The approach selected to obtain a KCRVOXT for the mass fraction of OXT is based on random-effects meta-analysis (DerSimonian-Laird (DSL) variance-weighted mean). The DSLmean takes into account the uncertainties of the results while introducing sufficient excess variance to allow for their observed dispersion resulting in a larger expanded uncertainty U(KCRVOXT). The KCRVOXT for CCQM-K115.b is 787.2 mg/g with a corresponding expanded uncertainty of the KCRVOXT of ±12.9 mg/g. All OXT mass fraction results except the result of NMIM are in agreement with the KCRVOXT. It should be pointed out that the mass balance approaches show smaller uncertainties than PICAA or PICqNMR approaches. Mass balance approaches seem to produce slightly higher OXT mass fractions while PICAA approaches deliver slightly lower OXT mass fractions.Main textTo reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Pilot study on peptide purity—synthetic oxytocin

Under the auspices of the Protein Analysis Working Group (PAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a pilot study, CCQM-P55.2.b, was coordinated by the Bureau International des Poids et Mesures (BIPM) and the Chinese National Institute of Metrology (NIM). Three Metrology Institutes or Designated Institutes and the BIPM participated. Participants were required to assign the mass fraction of oxytocin (OXT) present as the main component in the comparison sample for CCQM-P55.2.b. The comparison samples were prepared from synthetic OXT purchased from a commercial supplier and used as provided without further treatment or purification.OXT was selected to be representative of the performance of a laboratory's measurement capability for the purity assignment of chemically synthesized peptides of known sequence, with one cross-link and up to 5 kDa. It was anticipated to provide an analytical measurement challenge representative for the value-assignment of compounds of broadly similar structural characteristics.The majority of participants used quantitative nuclear magnetic resonance (PICqNMR) spectroscopy with a correction for structurally-related peptide impurities. Other participants provided results obtained by peptide impurity corrected amino acid analysis (PICAA) or Inductively coupled plasma mass spectrometry (PICICP). It was decided to assign reference values based on the KCRVs of CCQM-K115.b for both the OXT mass fraction and the mass fraction of the peptide related impurities as indispensable contributor regardless of the use of PICAA, mass balance or any other approach to determine the OXT purity. This allowed participants to demonstrate the efficacy of their implementation of the approaches used to determine the OXT mass fraction. In particular, it allows participants to demonstrate the efficacy of their implementation of peptide related impurity identification and quantification.More detailed studies on the identification/quantification of peptide related impurities and the hydrolysis efficiency revealed that the integrity of the impurity profile of the related peptide impurities obtained by the participant is crucial for the impact on accuracy of the OXT mass fraction assignment.The assessment of the mass fraction of peptide impurities is based on the assumption that only the Largest Consistent Subset (LCS) of results is taken for the calculation of the KCRVPepImp by use of the weighted mean. The KCRVPepImp of 31.6 mg/g is associated with a small corresponding expanded uncertainty of ±1.4 mg/g (k = 2) providing a more realistic basis of evaluation for the capabilities of the participants to identify/quantify peptide related impurities. Inspection of the degree of equivalence plots for the mass fraction of peptide impurities and additional information obtained from the peptide related impurity profile indicates that in many cases the major related peptide impurities have been identified and quantified.The approach selected to obtain a KCRVOXT for the mass fraction of OXT is based on random-effects meta-analysis (DerSimonian-Laird (DSL) variance-weighted mean). The DSLmean takes into account the uncertainties of the results while introducing sufficient excess variance to allow for their observed dispersion resulting in a larger expanded uncertainty U(KCRVOXT). The KCRVOXT for CCQM-K115.b is 787.2 mg/g with a corresponding expanded uncertainty of the KCRVOXT of ±12.9 mg/g. It should be pointed out that the mass balance approaches show smaller uncertainties than PICAA, PICqNMR or PICICP approaches. Inspection of the degree of equivalence plots for CCQM-P55.2.b for the mass fraction of OXT shows that all results, except the UME qNMR result, agree with the reference value.Main textTo reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).