Development of a confirmatory method for detecting recombinant bovine somatotropin in plasma by immunomagnetic precipitation followed by ultra-high performance liquid chromatography coupled to tandem mass spectrometry Part A Chemistry, analysis, control, exposure & risk assessment
Bibliographic record
Abstract
Recombinant bovine somatotropin (rbST), a synthetic growth hormone, is used to stimulate growth and enhance milk production in dairy cows. Both its use and the sale of dairy products from treated animals are prohibited in the European Union, as well as in Australia, Canada, Japan, and New Zealand, but authorised in several countries (e.g. Brazil, USA). Screening methods involve detecting anti-rbST antibodies (biomarkers) in treated cows. Confirmatory methods are required to prove rbST abuse. The major challenges in determining rbST are its potentially low levels, its high similarity to native bST, and matrix interferences. To overcome these obstacles, we have developed a method involving immunomagnetic precipitation followed by UHPLC-MS/MS for rbST detection. Briefly, protein G magnetic beads pre-coated with an in-house produced monoclonal antibody were added to plasma. Incubation at room temperature allowed rbST present in the sample to bind to the magnetic beads. After that, magnetic beads were isolated by centrifugation and thoroughly washed (PBS, PBS + 0.2% Tween 20). Finally, rbST was released by alkalinisation and the samples were trypsin digested prior to UHPLC-MS/MS analysis in the MRM mode. Validation was done in accordance with European Commission Decision 2002/657/CE. Matrix-matched calibration with internal standards was used. The decision limit (CCα) reached with this approach was 0.11 µg l⁻¹.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".