Key comparison study on peptide purity - hexapeptide of HbA0
Bibliographic record
Abstract
Main text Under the auspices of the Protein Analysis Working Group (PAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a key comparison, CCQM-K115.2018, 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). Ten Metrology Institutes or Designated Institutes and the BIPM participated. Participants were required to assign the mass fraction of the hexapeptide of HbA0 (VE) present as the main component in the comparison sample for CCQM-K115.2018. The comparison samples were prepared by HSA/BIPM from synthetic VE purchased from a commercial supplier and used as provided without further treatment or purification. VE 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 without modification. 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) with a correction for structurally-related peptide impurities approach as the amount of material that had been provided to each participant (25 mg) was insufficient to perform a full mass balance based characterization of the material by a participating laboratory. The coordinators, the BIPM, the HSA 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 VE 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 VE purity. This allowed participants to demonstrate the efficacy of their implementation of the approaches used to determine the VE mass fraction. In particular, it allowed 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 VE mass fraction assignment. The assessment of the mass fraction of peptide impurities is based on the assumption that only the most consistent set of results is taken for the calculation of the KCRVPepImp. The sum of the combined cis/trans VE depsipeptide impurities (only identified/quantified by NRC and confirmed by BIPM and HSA) and mass fractions of peptide related impurities that have been identified by at least two participants have been used to establish the KCRVPepImp. The KCRVPepImp of 53.0 mg/g is associated with a corresponding expanded uncertainty of 17.3 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 all cases the major related peptide impurity, VE depsipeptide, has not been identified. The VE depsipeptide impurity was initially and uniquely identified and quantified by the NRC by the use of 1H-NMR. The related peptide impurity mass fraction results of only four participants (NRC, LGC, LNE and HSA) are in agreement with the KCRVPepImp. The NRC has identified and quantified the VE depsipeptide whereas the LGC, LNE and HSA have not identified the VE depsipeptide but accounted for that contribution. The approach selected to obtain a KCRVVE for the mass fraction of VE is based on a mass balance calculation that takes into account the most consistent set of results for the peptide related impurities KCRVPepImp, TFA mass fraction and the water mass fraction. The KCRVVE for CCQM-K115.2018 is 613 mg/g with a corresponding expanded uncertainty of the KCRVVE of 20 mg/g (k = 2). 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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".