Metabolism of norethisterone in the greyhound
Bibliographic record
Abstract
RATIONALE: Norethisterone has been used as a successful oral contraceptive in humans for many years. It was recently permitted for use as an oestrus suppressant in racing greyhounds. To monitor the use of norethisterone as part of a routine drug surveillance programme, knowledge of its metabolism was required to enable detection. METHODS: Gas chromatography/mass spectrometry and selective derivatisation techniques have been used to identify urinary metabolites of norethisterone following oral administration to the greyhound. Metabolites were extracted using solid-phase and liquid-liquid extraction techniques. RESULTS: Several metabolites were identified, including reduced, mono-, di- and trihydroxylated steroids. The major metabolites observed were 17α-ethynyl-5β-estrane-3α,17β-diol, 17α-ethynyl-5α-estrane-3β,17β-diol, three 17α-ethynylestranetriol stereoisomers and two 17α-ethynylestranetetrol stereoisomers. The major metabolites were predominantly excreted as glucuronic acid conjugates and detection of the administration of norethisterone was possible for up to 8 days post-dose using the methods described. The nandrolone metabolites, 19-norepiandrosterone, estranediol and 19-noretiocholanolone, were also identified in the post-administration samples collected up to 8 h after dosing the treated animals. CONCLUSIONS: The urinary metabolites identified in this study have further increased the knowledge of steroid metabolism in the greyhound, providing information to support routine drug testing programmes for greyhound racing.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".