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Record W2278699880

A Polyclonal Antibody-based Immunoassay for Determination of Growth Stimulant Ractopamine: Comparative Study with Recent Advances in Immunoassay Methods

2013· article· en· W2278699880 on OpenAlexaboutno aff
Yi-Chih Lei, Yung-Te Tai, Kuan-Huei Hsieh, Chiao-Po Lin, Tong‐Hsuan Chang, Wen‐Ren Li, Shi‐Yuan Sheu, Chu-Hsu Yao, Tzong‐Fu Kuo

Bibliographic record

Venue臺灣獸醫學雜誌 · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPharmacological Effects and Assays
Canadian institutionsnot available
Fundersnot available
KeywordsRactopaminePolyclonal antibodiesImmunoassayChromatographyChemistryEuropean unionDetection limitAntibodyImmunologyBiology
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.371
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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