Key comparison study on peptide purity - synthetic oxytocin
Bibliographic record
Abstract
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 KCRV PepImp by use of the weighted mean. The KCRV PepImp 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 KCRV OXT 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(KCRV OXT ). The KCRV OXT for CCQM-K115.b is 787.2 mg/g with a corresponding expanded uncertainty of the KCRV OXT of ±12.9 mg/g. All OXT mass fraction results except the result of NMIM are in agreement with the KCRV OXT . 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 text 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 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).
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".