Single-Laboratory Validation of a Modified Liquid Chromatographic Method with UV Detection for Determination of Trenbolone Residues in Bovine Liver and Muscle
Bibliographic record
Abstract
Trenbolone acetate is a synthetic testosterone analog registered for use in a number of countries as a growth-promoting hormone, applied as an implant in the ears of feedlot cattle. The method is intended for the detection and quantitation of trace amounts of alpha- and beta-trenbolone in bovine tissues (muscle, liver) by liquid chromatography (LC) with UV detection and eliminates the use of the structural analog, 19-nortestosterone, as an internal standard. Trenbolone residues are extracted from tissues that have been homogenized in sodium acetate with a 3-phase liquid-liquid extraction by adding a mixture of water-acetonitrile-dichloromethanehexane, with trenbolone residues preferentially partitioned into the middle acetonitrile layer. The extract is passed through solid-phase extraction cartridges (both C18 and silica gel) using, respectively, methanol-water and acetone-toluene as eluents. Reversed-phase high-performance LC separation is performed, an octadecyl-bonded column with methanol-acetonitrile-water used as mobile phase for sample analysis. The limit of detection is 0.2 ng/g in muscle tissue and 0.6 ng/g in liver tissue, with coefficients of variation of 3.5-12.1% for alpha- and beta-trenbolone at concentrations from 0.2 to 4.0 ng/g fortified in muscle and 3.3-26.0% from liver fortified at 0.6-10.0 ng/g. Absolute recoveries of 40-130% were observed, but the use of fortified matrix curves eliminated recovery correction. Critical control points were identified in a pH adjustment step and an evaporation step during method validation, which included ruggedness testing. Analysis of incurred tissues (bovine liver and muscle) stored at -20 degrees C for over 25 weeks did not identify any significant loss of residues.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".