A Polyclonal Antibody-based Immunoassay for Determination of Growth Stimulant Ractopamine: Comparative Study with Recent Advances in Immunoassay Methods
Bibliographic record
Abstract
Ractopamine is a β-adrenergic agonist approved for use as a growth promoter in swine and cattle in the USA, Canada and Australia etc. but not in the European Union, China, or Taiwan. Here, we report the development of a polyclonal antibody-based enzyme-linked immunosorbent assay (ELISA) for ractopamine. Rabbits immunized with ractopamine-succinate-ovalbumin were utilized for polyclonal antibody generation. The calibration graphs of ractopamine showed linearity over the concentration ranges 0.3-24.3 μg/kg, whereas IC50 was 3.2 μg/kg, allowing the analysis of urine and serum samples without the need for sample clean-up. This paper also deals with the extraction of hydrochloric acid respect to meat and feed samples. It appears that the limit of determination of this assay for urine, serum and meat matrix was estimated to be 0.3 μg/kg, and for feed samples was 4 μg/kg. The results obtained a rapid, sensitive and specific assay to detect positive samples in routine analysis. Simultaneously, recent advances in immunoassay methods for ractopamine residues are reviewed herein, that can be considered as a basis for further research aimed at identifying the most efficient approaches for the analysis of ractopamine.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".